A systems biology pipeline identifies regulatory networks for stem cell engineering

Kinney, Melissa A.; Vo, Linda T.; Frame, Jenna M.; Barragan, Jessica; Conway, Ashlee; Li, Shuai; Wong, Kwok-Kin; Collins, James J.; Cahan, Patrick; North, Trista E.; Lauffenburger, Douglas A.; Daley, George Q.

doi:10.1038/s41587-019-0159-2

Cited by 24 publications

(15 citation statements)

References 71 publications

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“…In support of our findings, Kinney et al provided computational evidence of NMDAR involvement in erythropoiesis (Kinney et al, 2019). The authors analyzed 164 publicly available erythroid microarray datasets using an enhanced CellNet bioinformatics algorithm to delineate key transitional states of erythroid differentiation at high resolution.…”

Section: Nmdar Effects On Megakaryocytic Differentiationsupporting

confidence: 77%

N-Methyl-D-Aspartate Receptors in Hematopoietic Cells: What Have We Learned?

et al. 2020

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Section: Nmdar Effects On Megakaryocytic Differentiationsupporting

confidence: 77%

N-Methyl-D-Aspartate Receptors in Hematopoietic Cells: What Have We Learned?

et al. 2020

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“…Transcriptional regulation does not function in isolation, however. Cell fate decisions are heavily influenced by dynamic communication between the nucleus with multiple biological processes and signaling cascades involving macromolecule interactions at the cell membrane, throughout the cytoplasm, and within or on the surface of organelles ( Shah et al, 1996 ; Zhou et al, 2009 ; Julian et al, 2013 ; Julian and Blais, 2015 ; Singh et al, 2015 ; Chen et al, 2016 ; Young et al, 2016 ; Khacho and Slack, 2017b ; Chang et al, 2018 ; Obernier et al, 2018 ; Bahat and Gross, 2019 ; Jaiswal and Kimmel, 2019 ; Kinney et al, 2019 ; Shlyakhtina et al, 2019 ; Chang, 2020 ). The successful development, long-term homeostasis, and post-injury repair of organs and tissues is dependent on the pliability in cell fate decisions that these integrated biological networks permit.…”

Section: Metabolic Organelle Network Regulate Stem Cell Fatementioning

confidence: 99%

Organelle Cooperation in Stem Cell Fate: Lysosomes as Emerging Regulators of Cell Identity

Julian

Stanford

2020

Front. Cell Dev. Biol.

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Regulation of stem cell fate is best understood at the level of gene and protein regulatory networks, though it is now clear that multiple cellular organelles also have critical impacts. A growing appreciation for the functional interconnectedness of organelles suggests that an orchestration of integrated biological networks functions to drive stem cell fate decisions and regulate metabolism. Metabolic signaling itself has emerged as an integral regulator of cell fate including the determination of identity, activation state, survival, and differentiation potential of many developmental, adult, disease, and cancer-associated stem cell populations and their progeny. As the primary adenosine triphosphate-generating organelles, mitochondria are well-known regulators of stem cell fate decisions, yet it is now becoming apparent that additional organelles such as the lysosome are important players in mediating these dynamic decisions. In this review, we will focus on the emerging role of organelles, in particular lysosomes, in the reprogramming of both metabolic networks and stem cell fate decisions, especially those that impact the determination of cell identity. We will discuss the inter-organelle interactions, cell signaling pathways, and transcriptional regulatory mechanisms with which lysosomes engage and how these activities impact metabolic signaling. We will further review recent data that position lysosomes as critical regulators of cell identity determination programs and discuss the known or putative biological mechanisms. Finally, we will briefly highlight the potential impact of elucidating mechanisms by which lysosomes regulate stem cell identity on our understanding of disease pathogenesis, as well as the development of refined regenerative medicine, biomarker, and therapeutic strategies.

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“…Nor can PluriTest predict whether a cell type is capable of commitment to a specific lineage. The Stemformatics MSC test cannot predict whether the profiled MSCs have any clinical efficacy, and CellNet, KeyGenes, and CellScore are not designed to predict which factors will drive the reprogramming process, although these are the forerunners to curated networks that will more completely identify factors required for differentiated states (Kinney et al., 2019).…”

Section: Main Textmentioning

confidence: 99%

Transcriptional Profiling of Stem Cells: Moving from Descriptive to Predictive Paradigms

Wells

Choi

2019

Stem Cell Reports

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Transcriptional profiling is a powerful tool commonly used to benchmark stem cells and their differentiated progeny. As the wealth of stem cell data builds in public repositories, we highlight common data traps, and review approaches to combine and mine this data for new cell classification and cell prediction tools. We touch on future trends for stem cell profiling, such as single-cell profiling, long-read sequencing, and improved methods for measuring molecular modifications on chromatin and RNA that bring new challenges and opportunities for stem cell analysis.

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A systems biology pipeline identifies regulatory networks for stem cell engineering

Cited by 24 publications

References 71 publications

N-Methyl-D-Aspartate Receptors in Hematopoietic Cells: What Have We Learned?

N-Methyl-D-Aspartate Receptors in Hematopoietic Cells: What Have We Learned?

Organelle Cooperation in Stem Cell Fate: Lysosomes as Emerging Regulators of Cell Identity

Transcriptional Profiling of Stem Cells: Moving from Descriptive to Predictive Paradigms

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