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      Rigor and reproducibility in human brain organoid research: Where we are and where we need to go

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          Summary

          Human brain organoid models have emerged as a promising tool for studying human brain development and function. These models preserve human genetics and recapitulate some aspects of human brain development, while facilitating manipulation in an in vitro setting. Despite their potential to transform biology and medicine, concerns persist about their fidelity. To fully harness their potential, it is imperative to establish reliable analytic methods, ensuring rigor and reproducibility. Here, we review current analytical platforms used to characterize human forebrain cortical organoids, highlight challenges, and propose recommendations for future studies to achieve greater precision and uniformity across laboratories.

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          Abstract

          Sandoval et al. reviewed the current quantitative methods used for cellular, molecular, and functional analyses of brain organoid models, with a focus on cortical organoids. The authors identified the challenges posed by this powerful and innovative technology and proposed recommendations to improve the reliability and reproducibility of data generated across laboratories.

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          Most cited references163

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          Understanding the Warburg effect: the metabolic requirements of cell proliferation.

          In contrast to normal differentiated cells, which rely primarily on mitochondrial oxidative phosphorylation to generate the energy needed for cellular processes, most cancer cells instead rely on aerobic glycolysis, a phenomenon termed "the Warburg effect." Aerobic glycolysis is an inefficient way to generate adenosine 5'-triphosphate (ATP), however, and the advantage it confers to cancer cells has been unclear. Here we propose that the metabolism of cancer cells, and indeed all proliferating cells, is adapted to facilitate the uptake and incorporation of nutrients into the biomass (e.g., nucleotides, amino acids, and lipids) needed to produce a new cell. Supporting this idea are recent studies showing that (i) several signaling pathways implicated in cell proliferation also regulate metabolic pathways that incorporate nutrients into biomass; and that (ii) certain cancer-associated mutations enable cancer cells to acquire and metabolize nutrients in a manner conducive to proliferation rather than efficient ATP production. A better understanding of the mechanistic links between cellular metabolism and growth control may ultimately lead to better treatments for human cancer.
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            Reversed graph embedding resolves complex single-cell trajectories

            Single-cell trajectories can unveil how gene regulation governs cell fate decisions. However, learning the structure of complex trajectories with two or more branches remains a challenging computational problem. We present Monocle 2, which uses reversed graph embedding to describe multiple fate decisions in a fully unsupervised manner. Applied to two studies of blood development, Monocle 2 revealed that mutations in key lineage transcription factors diverts cells to alternative fates.
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              Cerebral organoids model human brain development and microcephaly

              The complexity of the human brain has made it difficult to study many brain disorders in model organisms, and highlights the need for an in vitro model of human brain development. We have developed a human pluripotent stem cell-derived 3D organoid culture system, termed cerebral organoid, which develops various discrete though interdependent brain regions. These include cerebral cortex containing progenitor populations that organize and produce mature cortical neuron subtypes. Furthermore, cerebral organoids recapitulate features of human cortical development, namely characteristic progenitor zone organization with abundant outer radial glial stem cells. Finally, we use RNAi and patient-specific iPS cells to model microcephaly, a disorder that has been difficult to recapitulate in mice. We demonstrate premature neuronal differentiation in patient organoids, a defect that could explain the disease phenotype. Our data demonstrate that 3D organoids can recapitulate development and disease of even this most complex human tissue.
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                Author and article information

                Contributors
                Journal
                Stem Cell Reports
                Stem Cell Reports
                Stem Cell Reports
                Elsevier
                2213-6711
                16 May 2024
                11 June 2024
                16 May 2024
                : 19
                : 6
                : 796-816
                Affiliations
                [1 ]Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
                [2 ]Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
                [3 ]Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
                [4 ]Department of Pediatrics–Neurology, Baylor College of Medicine, Houston, TX, USA
                [5 ]Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, USA
                [6 ]Department of Psychiatry, University of Iowa Health Care, Iowa City, IA 52242, USA
                [7 ]Iowa Neuroscience Institute, University of Iowa Health Care, Iowa City, IA 52242, USA
                [8 ]Molecular Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, WI 53705, USA
                [9 ]Department of Neuroscience, Center for Visual Science, Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester NY 14642, USA
                [10 ]Departments of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53705, USA
                [11 ]Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
                [12 ]Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
                [13 ]Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
                [14 ]Center for Cellular and Molecular Therapeutics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
                [15 ]Center for Epilepsy and NeuroDevelopmental Disorders (ENDD), The Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
                [16 ]Human Neuron Core, Rosamund Stone Zander Translational Neuroscience Center, Boston Children’s Hospital, Boston, MA, USA
                [17 ]F.M. Kirby Neurobiology Department, Boston Children’s Hospital, Boston, MA, USA
                [18 ]Center for Drug Discovery, Baylor College of Medicine, Houston, TX, USA
                [19 ]Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
                Author notes
                []Corresponding author aislinn-williams@ 123456uiowa.edu
                [∗∗ ]Corresponding author mirjana.maletic-savatic@ 123456bcm.edu
                [∗∗∗ ]Corresponding author xinyu.zhao@ 123456wisc.edu
                [20]

                These authors contributed equally

                Article
                S2213-6711(24)00114-0
                10.1016/j.stemcr.2024.04.008
                11297560
                38759644
                101ccdc4-445f-402f-845c-baa5202ba8ab
                © 2024 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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