1
|
Przanowska RK, Labban N, Przanowski P, Hawes RB, Atkins KA, Showalter SL, Janes KA. Patient-derived response estimates from zero-passage organoids of luminal breast cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.24.586432. [PMID: 38585922 PMCID: PMC10996455 DOI: 10.1101/2024.03.24.586432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Background Primary luminal breast cancer cells lose their identity rapidly in standard tissue culture, which is problematic for testing hormone interventions and molecular pathways specific to the luminal subtype. Breast cancer organoids are thought to retain tumor characteristics better, but long-term viability of luminal-subtype cases is a persistent challenge. Our goal was to adapt short-term organoids of luminal breast cancer for parallel testing of genetic and pharmacologic perturbations. Methods We freshly isolated patient-derived cells from luminal tumor scrapes, miniaturized the organoid format into 5 μl replicates for increased throughput, and set an endpoint of 14 days to minimize drift. Therapeutic hormone targeting was mimicked in these "zero-passage" organoids by withdrawing β-estradiol and adding 4-hydroxytamoxifen. We also examined sulforaphane as an electrophilic stress and commercial neutraceutical with reported anti-cancer properties. Downstream mechanisms were tested genetically by lentiviral transduction of two complementary sgRNAs and Cas9 stabilization for the first week of organoid culture. Transcriptional changes were measured by RT-qPCR or RNA sequencing, and organoid phenotypes were quantified by serial brightfield imaging, digital image segmentation, and regression modeling of cellular doubling times. Results We achieved >50% success in initiating luminal breast cancer organoids from tumor scrapes and maintaining them to the 14-day zero-passage endpoint. Success was mostly independent of clinical parameters, supporting general applicability of the approach. Abundance of ESR1 and PGR in zero-passage organoids consistently remained within the range of patient variability at the endpoint. However, responsiveness to hormone withdrawal and blockade was highly variable among luminal breast cancer cases tested. Combining sulforaphane with knockout of NQO1 (a phase II antioxidant response gene and downstream effector of sulforaphane) also yielded a breadth of organoid growth phenotypes, including growth inhibition with sulforaphane, growth promotion with NQO1 knockout, and growth antagonism when combined. Conclusions Zero-passage organoids are a rapid and scalable way to interrogate properties of luminal breast cancer cells from patient-derived material. This includes testing drug mechanisms of action in different clinical cohorts. A future goal is to relate inter-patient variability of zero-passage organoids to long-term outcomes.
Collapse
Affiliation(s)
- Róża K Przanowska
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Najwa Labban
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Piotr Przanowski
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Russell B Hawes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Kristen A Atkins
- Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Shayna L Showalter
- Department of Surgery, University of Virginia Health System, Charlottesville, VA 22908, USA
- University of Virginia Comprehensive Cancer Center, University of Virginia, Charlottesville, VA 22908, USA
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
- University of Virginia Comprehensive Cancer Center, University of Virginia, Charlottesville, VA 22908, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| |
Collapse
|
2
|
Ram A, Pargett M, Choi Y, Murphy D, Cabel M, Kosaisawe N, Quon G, Albeck J. Deciphering the History of ERK Activity from Fixed-Cell Immunofluorescence Measurements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.16.580760. [PMID: 38405841 PMCID: PMC10889026 DOI: 10.1101/2024.02.16.580760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The Ras/ERK pathway drives cell proliferation and other oncogenic behaviors, and quantifying its activity in situ is of high interest in cancer diagnosis and therapy. Pathway activation is often assayed by measuring phosphorylated ERK. However, this form of measurement overlooks dynamic aspects of signaling that can only be observed over time. In this study, we combine a live, single-cell ERK biosensor approach with multiplexed immunofluorescence staining of downstream target proteins to ask how well immunostaining captures the dynamic history of ERK activity. Combining linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunostains, in which Fra-1 and pRb levels imply long term activation of ERK signaling, while Egr-1 and c-Myc indicate recent activation. We show that this framework can distinguish different classes of ERK dynamics within a heterogeneous population, providing a tool for annotating ERK dynamics within fixed tissues.
Collapse
Affiliation(s)
- Abhineet Ram
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Yongin Choi
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Devan Murphy
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Markhus Cabel
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, Davis
| | - Gerald Quon
- Department of Molecular and Cellular Biology, University of California, Davis
| | - John Albeck
- Department of Molecular and Cellular Biology, University of California, Davis
| |
Collapse
|
3
|
Sparta B, Kosaisawe N, Pargett M, Patankar M, DeCuzzi N, Albeck JG. Continuous sensing of nutrients and growth factors by the mTORC1-TFEB axis. eLife 2023; 12:e74903. [PMID: 37698461 PMCID: PMC10547473 DOI: 10.7554/elife.74903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 09/11/2023] [Indexed: 09/13/2023] Open
Abstract
mTORC1 senses nutrients and growth factors and phosphorylates downstream targets, including the transcription factor TFEB, to coordinate metabolic supply and demand. These functions position mTORC1 as a central controller of cellular homeostasis, but the behavior of this system in individual cells has not been well characterized. Here, we provide measurements necessary to refine quantitative models for mTORC1 as a metabolic controller. We developed a series of fluorescent protein-TFEB fusions and a multiplexed immunofluorescence approach to investigate how combinations of stimuli jointly regulate mTORC1 signaling at the single-cell level. Live imaging of individual MCF10A cells confirmed that mTORC1-TFEB signaling responds continuously to individual, sequential, or simultaneous treatment with amino acids and the growth factor insulin. Under physiologically relevant concentrations of amino acids, we observe correlated fluctuations in TFEB, AMPK, and AKT signaling that indicate continuous activity adjustments to nutrient availability. Using partial least squares regression modeling, we show that these continuous gradations are connected to protein synthesis rate via a distributed network of mTORC1 effectors, providing quantitative support for the qualitative model of mTORC1 as a homeostatic controller and clarifying its functional behavior within individual cells.
Collapse
Affiliation(s)
- Breanne Sparta
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Madhura Patankar
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - Nicholaus DeCuzzi
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, DavisDavisUnited States
| |
Collapse
|
4
|
Farahani PE, Yang X, Mesev EV, Fomby KA, Brumbaugh-Reed EH, Bashor CJ, Nelson CM, Toettcher JE. pYtags enable spatiotemporal measurements of receptor tyrosine kinase signaling in living cells. eLife 2023; 12:82863. [PMID: 37212240 DOI: 10.7554/elife.82863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 04/24/2023] [Indexed: 05/23/2023] Open
Abstract
Receptor tyrosine kinases (RTKs) are major signaling hubs in metazoans, playing crucial roles in cell proliferation, migration, and differentiation. However, few tools are available to measure the activity of a specific RTK in individual living cells. Here, we present pYtags, a modular approach for monitoring the activity of a user-defined RTK by live-cell microscopy. pYtags consist of an RTK modified with a tyrosine activation motif that, when phosphorylated, recruits a fluorescently labeled tandem SH2 domain with high specificity. We show that pYtags enable the monitoring of a specific RTK on seconds-to-minutes time scales and across subcellular and multicellular length scales. Using a pYtag biosensor for epidermal growth factor receptor (EGFR), we quantitatively characterize how signaling dynamics vary with the identity and dose of activating ligand. We show that orthogonal pYtags can be used to monitor the dynamics of EGFR and ErbB2 activity in the same cell, revealing distinct phases of activation for each RTK. The specificity and modularity of pYtags open the door to robust biosensors of multiple tyrosine kinases and may enable engineering of synthetic receptors with orthogonal response programs.
Collapse
Affiliation(s)
- Payam E Farahani
- Department of Chemical & Biological Engineering, Princeton University, Princeton, United States
| | - Xiaoyu Yang
- Department of Bioengineering, Rice University, Houston, United States
- Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, United States
| | - Emily V Mesev
- Department of Molecular Biology, Princeton University, Princeton, United States
| | - Kaylan A Fomby
- Department of Molecular Biology, Princeton University, Princeton, United States
| | - Ellen H Brumbaugh-Reed
- Department of Molecular Biology, Princeton University, Princeton, United States
- IRCC International Research Collaboration Center, National Institutes of Natural Sciences, Tokyo, Japan
| | - Caleb J Bashor
- Department of Bioengineering, Rice University, Houston, United States
- Department of Biosciences, Rice University, Houston, United States
| | - Celeste M Nelson
- Department of Chemical & Biological Engineering, Princeton University, Princeton, United States
- Department of Molecular Biology, Princeton University, Princeton, United States
| | - Jared E Toettcher
- Department of Molecular Biology, Princeton University, Princeton, United States
| |
Collapse
|
5
|
Wang L, Paudel BB, McKnight RA, Janes KA. Nucleocytoplasmic transport of active HER2 causes fractional escape from the DCIS-like state. Nat Commun 2023; 14:2110. [PMID: 37055441 PMCID: PMC10102026 DOI: 10.1038/s41467-023-37914-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 04/05/2023] [Indexed: 04/15/2023] Open
Abstract
Activation of HER2/ErbB2 coincides with escape from ductal carcinoma in situ (DCIS) premalignancy and disrupts 3D organization of cultured breast-epithelial spheroids. The 3D phenotype is infrequent, however, and mechanisms for its incomplete penetrance have been elusive. Using inducible HER2/ErbB2-EGFR/ErbB1 heterodimers, we match phenotype penetrance to the frequency of co-occurring transcriptomic changes and uncover a reconfiguration in the karyopherin network regulating ErbB nucleocytoplasmic transport. Induction of the exportin CSE1L inhibits nuclear accumulation of ErbBs, whereas nuclear ErbBs silence the importin KPNA1 by inducing miR-205. When these negative feedbacks are incorporated into a validated systems model of nucleocytoplasmic transport, steady-state localization of ErbB cargo becomes ultrasensitive to initial CSE1L abundance. Erbb2-driven carcinomas with Cse1l deficiency outgrow less irregularly from mammary ducts, and NLS-attenuating mutants or variants of HER2 favor escape in 3D culture. We conclude here that adaptive nucleocytoplasmic relocalization of HER2 creates a systems-level molecular switch at the premalignant-to-malignant transition.
Collapse
Affiliation(s)
- Lixin Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - B Bishal Paudel
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - R Anthony McKnight
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- Olympus Veran Technologies, St. Louis, MO, USA
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
- Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, VA, USA.
| |
Collapse
|
6
|
Przanowski P, Przanowska RK, Guertin MJ. ANKLE1 cleaves mitochondrial DNA and contributes to cancer risk by promoting apoptosis resistance and metabolic dysregulation. Commun Biol 2023; 6:231. [PMID: 36859531 PMCID: PMC9977882 DOI: 10.1038/s42003-023-04611-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 02/20/2023] [Indexed: 03/03/2023] Open
Abstract
Alleles within the chr19p13.1 locus are associated with increased risk of both ovarian and breast cancer and increased expression of the ANKLE1 gene. ANKLE1 is molecularly characterized as an endonuclease that efficiently cuts branched DNA and shuttles between the nucleus and cytoplasm. However, the role of ANKLE1 in mammalian development and homeostasis remains unknown. In normal development ANKLE1 expression is limited to the erythroblast lineage and we found that ANKLE1's role is to cleave the mitochondrial genome during erythropoiesis. We show that ectopic expression of ANKLE1 in breast epithelial-derived cells leads to genome instability and mitochondrial DNA (mtDNA) cleavage. mtDNA degradation then leads to mitophagy and causes a shift from oxidative phosphorylation to glycolysis (Warburg effect). Moreover, mtDNA degradation activates STAT1 and expression of epithelial-mesenchymal transition (EMT) genes. Reduction in mitochondrial content contributes to apoptosis resistance, which may allow precancerous cells to avoid apoptotic checkpoints and proliferate. These findings provide evidence that ANKLE1 is the causal cancer susceptibility gene in the chr19p13.1 locus and describe mechanisms by which higher ANKLE1 expression promotes cancer risk.
Collapse
Affiliation(s)
- Piotr Przanowski
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA.
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, VA, USA.
| | - Róża K Przanowska
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Michael J Guertin
- Center for Cell Analysis and Modeling, University of Connecticut, Farmington, CT, USA.
- Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT, USA.
| |
Collapse
|
7
|
Hsu YJ, Yin YJ, Tsai KF, Jian CC, Liang ZW, Hsu CY, Wang CC. TGFBR3 supports anoikis through suppressing ATF4 signaling. J Cell Sci 2022; 135:276173. [PMID: 35912788 DOI: 10.1242/jcs.258396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 07/18/2022] [Indexed: 11/20/2022] Open
Abstract
Epithelial morphogenesis and oncogenic transformation can cause loss of cell adhesion, and detached cells are eliminated by anoikis. Here, we reveal that transforming growth factor beta receptor 3 (TGFBR3) acts as an anoikis mediator through the coordination of activating transcription factor 4 (ATF4). In breast cancer, TGFBR3 is progressively lost, but elevated TGFBR3 is associated with a histologic subtype characterized by cellular adhesion defects. Dissecting the impact of extracellular matrix (ECM) deprivation, we demonstrate that ECM loss promotes TGFBR3 expression, which in turn differentiates cell aggregates to a prosurvival phenotype and drives the intrinsic apoptotic pathway. We demonstrate that inhibition of TGFBR3 impairs epithelial anoikis by activating ATF4 signaling. These preclinical findings provide a rationale for therapeutic inhibition of ATF4 in the subgroup of breast cancer patients with low TGFBR3 expression.
Collapse
Affiliation(s)
- Yu-Jhen Hsu
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | - Yih-Jia Yin
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 30013, Taiwan.,Department of Medical Science, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | - Kai-Feng Tsai
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | - Cian-Chun Jian
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | - Zi-Wen Liang
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | - Chien-Yu Hsu
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 30013, Taiwan
| | - Chun-Chao Wang
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 30013, Taiwan.,Department of Medical Science, National Tsing Hua University, Hsinchu, 30013, Taiwan
| |
Collapse
|
8
|
Substratum stiffness regulates Erk signaling dynamics through receptor-level control. Cell Rep 2021; 37:110181. [PMID: 34965432 PMCID: PMC8756379 DOI: 10.1016/j.celrep.2021.110181] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 08/01/2021] [Accepted: 12/06/2021] [Indexed: 01/02/2023] Open
Abstract
The EGFR/Erk pathway is triggered by extracellular ligand stimulation, leading to stimulus-dependent dynamics of pathway activity. Although mechanical properties of the microenvironment also affect Erk activity, their effects on Erk signaling dynamics are poorly understood. Here, we characterize how the stiffness of the underlying substratum affects Erk signaling dynamics in mammary epithelial cells. We find that soft microenvironments attenuate Erk signaling, both at steady state and in response to epidermal growth factor (EGF) stimulation. Optogenetic manipulation at multiple signaling nodes reveals that intracellular signal transmission is largely unaffected by substratum stiffness. Instead, we find that soft microenvironments decrease EGF receptor (EGFR) expression and alter the amount and spatial distribution of EGF binding at cell membranes. Our data demonstrate that the mechanical microenvironment tunes Erk signaling dynamics via receptor-ligand interactions, underscoring how multiple microenvironmental signals are jointly processed through a highly conserved pathway that regulates tissue development, homeostasis, and disease progression.
Collapse
|
9
|
Wang CC. Metabolic Stress Adaptations Underlie Mammary Gland Morphogenesis and Breast Cancer Progression. Cells 2021; 10:2641. [PMID: 34685621 PMCID: PMC8534177 DOI: 10.3390/cells10102641] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 09/26/2021] [Accepted: 09/28/2021] [Indexed: 11/23/2022] Open
Abstract
Breast cancers display dynamic reprogrammed metabolic activities as cancers develop from premalignant lesions to primary tumors, and then metastasize. Numerous advances focus on how tumors develop pro-proliferative metabolic signaling that differs them from adjacent, non-transformed epithelial tissues. This leads to targetable oncogene-driven liabilities among breast cancer subtypes. Other advances demonstrate how microenvironments trigger stress-response at single-cell resolution. Microenvironmental heterogeneities give rise to cell regulatory states in cancer cell spheroids in three-dimensional cultures and at stratified terminal end buds during mammary gland morphogenesis, where stress and survival signaling juxtapose. The cell-state specificity in stress signaling networks recapture metabolic evolution during cancer progression. Understanding lineage-specific metabolic phenotypes in experimental models is useful for gaining a deeper understanding of subtype-selective breast cancer metabolism.
Collapse
Affiliation(s)
- Chun-Chao Wang
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu 30013, Taiwan; ; Tel.: +886-3-516-2589
- Department of Medical Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| |
Collapse
|
10
|
Liotta LA, Pappalardo PA, Carpino A, Haymond A, Howard M, Espina V, Wulfkuhle J, Petricoin E. Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine. Expert Rev Proteomics 2021; 18:845-861. [PMID: 34607525 PMCID: PMC10720974 DOI: 10.1080/14789450.2021.1984886] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/21/2021] [Indexed: 10/20/2022]
Abstract
INTRODUCTION Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics. AREAS COVERED We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement. EXPERT OPINION LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.
Collapse
Affiliation(s)
- Lance A. Liotta
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Philip A. Pappalardo
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Alan Carpino
- Fluidigm Corporation, South San Francisco, CA, USA
| | - Amanda Haymond
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Marissa Howard
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Virginia Espina
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Julie Wulfkuhle
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Emanuel Petricoin
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| |
Collapse
|
11
|
Schaff DL, Singh S, Kim KB, Sutcliffe MD, Park KS, Janes KA. Fragmentation of Small-Cell Lung Cancer Regulatory States in Heterotypic Microenvironments. Cancer Res 2021; 81:1853-1867. [PMID: 33531375 PMCID: PMC8137564 DOI: 10.1158/0008-5472.can-20-1036] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 12/02/2020] [Accepted: 01/28/2021] [Indexed: 11/16/2022]
Abstract
Small-cell lung cancers derive from pulmonary neuroendocrine cells, which have stem-like properties to reprogram into other cell types upon lung injury. It is difficult to uncouple transcriptional plasticity of these transformed cells from genetic changes that evolve in primary tumors or secondary metastases. Profiling of single cells is also problematic if the required sample dissociation activates injury-like signaling and reprogramming. Here we defined cell-state heterogeneities in situ through laser capture microdissection-based 10-cell transcriptomics coupled with stochastic-profiling fluctuation analysis. In labeled cells from a small-cell lung cancer mouse model initiated by neuroendocrine deletion of Rb1-Trp53, variations in transcript abundance revealed cell-to-cell differences in regulatory state in vitro and in vivo. Fluctuating transcripts in spheroid culture were partly shared among Rb1-Trp53-null models, and heterogeneities increased considerably when cells were delivered intravenously to colonize the liver. Colonization of immunocompromised animals drove a fractional appearance of alveolar type II-like markers and poised cells for paracrine stimulation from immune cells and hepatocytes. Immunocompetency further exaggerated the fragmentation of tumor states in the liver, yielding mixed stromal signatures evident in bulk sequencing from autochthonous tumors and metastases. Dozens of transcript heterogeneities recurred irrespective of biological context; their mapped orthologs brought together observations of murine and human small-cell lung cancer. Candidate heterogeneities recurrent in the liver also stratified primary human tumors into discrete groups not readily explained by molecular subtype but with prognostic relevance. These data suggest that heterotypic interactions in the liver and lung are an accelerant for intratumor heterogeneity in small-cell lung cancer. SIGNIFICANCE: These findings demonstrate that the single-cell regulatory heterogeneity of small-cell lung cancer becomes increasingly elaborate in the liver, a common metastatic site for the disease.See related articles by Singh and colleagues, p. 1840 and Sutcliffe and colleagues, p. 1868.
Collapse
Affiliation(s)
- Dylan L Schaff
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Shambhavi Singh
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Kee-Beom Kim
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, Virginia
| | - Matthew D Sutcliffe
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Kwon-Sik Park
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, Virginia
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.
- Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, Virginia
| |
Collapse
|
12
|
Singh S, Sutcliffe MD, Repich K, Atkins KA, Harvey JA, Janes KA. Pan-Cancer Drivers Are Recurrent Transcriptional Regulatory Heterogeneities in Early-Stage Luminal Breast Cancer. Cancer Res 2021; 81:1840-1852. [PMID: 33531373 PMCID: PMC8137565 DOI: 10.1158/0008-5472.can-20-1034] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 12/02/2020] [Accepted: 01/28/2021] [Indexed: 11/16/2022]
Abstract
The heterogeneous composition of solid tumors is known to impact disease progression and response to therapy. Malignant cells coexist in different regulatory states that can be accessed transcriptomically by single-cell RNA sequencing, but these methods have many caveats related to sensitivity, noise, and sample handling. We revised a statistical fluctuation analysis called stochastic profiling to combine with 10-cell RNA sequencing, which was designed for laser-capture microdissection (LCM) and extended here for immuno-LCM. When applied to a cohort of late-onset, early-stage luminal breast cancers, the integrated approach identified thousands of candidate regulatory heterogeneities. Intersecting the candidates from different tumors yielded a relatively stable set of 710 recurrent heterogeneously expressed genes (RHEG), which were significantly variable in >50% of patients. RHEGs were not strongly confounded by dissociation artifacts, cell-cycle oscillations, or driving mutations for breast cancer. Rather, RHEGs were enriched for epithelial-to-mesenchymal transition genes and, unexpectedly, the latest pan-cancer assembly of driver genes across cancer types other than breast. These findings indicate that heterogeneous transcriptional regulation conceivably provides a faster, reversible mechanism for malignant cells to evaluate the effects of potential oncogenes or tumor suppressors on cancer hallmarks. SIGNIFICANCE: Profiling intratumor heterogeneity of luminal breast carcinoma cells identifies a recurrent set of genes, suggesting sporadic activation of pathways known to drive other types of cancer.See related articles by Schaff and colleagues, p. 1853 and Sutcliffe and colleagues, p. 1868.
Collapse
Affiliation(s)
- Shambhavi Singh
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Matthew D Sutcliffe
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Kathy Repich
- Department of Radiology, University of Virginia, Charlottesville, Virginia
| | - Kristen A Atkins
- Department of Pathology, University of Virginia, Charlottesville, Virginia
| | - Jennifer A Harvey
- Department of Radiology, University of Virginia, Charlottesville, Virginia
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.
- Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, Virginia
| |
Collapse
|
13
|
Sutcliffe MD, Galvao RP, Wang L, Kim J, Rosenfeld LK, Singh S, Zong H, Janes KA. Premalignant Oligodendrocyte Precursor Cells Stall in a Heterogeneous State of Replication Stress Prior to Gliomagenesis. Cancer Res 2021; 81:1868-1882. [PMID: 33531372 PMCID: PMC8137536 DOI: 10.1158/0008-5472.can-20-1037] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 12/02/2020] [Accepted: 01/28/2021] [Indexed: 11/16/2022]
Abstract
Cancer evolves from premalignant clones that adopt unusual cell states to achieve transformation. We previously pinpointed the oligodendrocyte precursor cell (OPC) as a cell of origin for glioma, but the early changes of mutant OPCs during premalignancy remained unknown. Using mice engineered for inducible Nf1-Trp53 loss in OPCs, we acutely isolated labeled mutant OPCs by laser-capture microdissection, determined global gene-expression changes by bulk RNA sequencing, and compared with cell-state fluctuations at the single-cell level by stochastic profiling, which uses RNA-sequencing measurements from random pools of 10 mutant cells. At 12 days after Nf1-Trp53 deletion, bulk differences were mostly limited to mitotic hallmarks and genes for ribosome biosynthesis, and stochastic profiling revealed a spectrum of stem-progenitor (Axl, Aldh1a1), proneural, and mesenchymal states as potential starting points for gliomagenesis. At 90 days, bulk sequencing detected few differentially expressed transcripts, whereas stochastic profiling revealed cell states for neurons and mural cells that do not give rise to glial tumors, suggesting cellular dead-ends for gliomagenesis. Importantly, mutant OPCs that strongly expressed key effectors of nonsense-mediated decay (Upf3b) and homology-dependent DNA repair (Rad51c, Slx1b, Ercc4) were identified along with DNA-damage markers, suggesting transcription-associated replication stress. Analysis of 10-cell transcriptomes at 90 days identified a locus of elevated gene expression containing an additional repair endonuclease (Mus81) and Rin1, a Ras-Raf antagonist and possible counterbalance to Nf1 loss, which was microdeleted or downregulated in gliomas at 150 days. These hidden cell-state variations uncover replication stress as a potential bottleneck that must be resolved for glioma initiation. SIGNIFICANCE: Profiling premalignant cell states in a mouse model of glioma uncovers regulatory heterogeneity in glioma cells-of-origin and defines a state of replication stress that precedes tumor initiation.See related articles by Singh and colleagues, p. 1840 and Schaff and colleagues, p. 1853.
Collapse
Affiliation(s)
- Matthew D Sutcliffe
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Rui P Galvao
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, Virginia
| | - Lixin Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Jungeun Kim
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, Virginia
| | - Lauren K Rosenfeld
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, Virginia
| | - Shambhavi Singh
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Hui Zong
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, Virginia.
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.
- Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, Virginia
| |
Collapse
|
14
|
Amrhein L, Fuchs C. stochprofML: stochastic profiling using maximum likelihood estimation in R. BMC Bioinformatics 2021; 22:123. [PMID: 33722188 PMCID: PMC7958472 DOI: 10.1186/s12859-021-03970-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 01/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue. RESULTS We present the R package stochprofML which uses the maximum likelihood principle to parameterize heterogeneity from the cumulative expression of small random pools of cells. We evaluate the algorithm's performance in simulation studies and present further application opportunities. CONCLUSION Stochastic profiling outweighs the necessary demixing of mixed samples with a saving in experimental cost and effort and less measurement error. It offers possibilities for parameterizing heterogeneity, estimating underlying pool compositions and detecting differences between cell populations between samples.
Collapse
Affiliation(s)
- Lisa Amrhein
- Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany
- Department of Mathematics, Technical University Munich, Boltzmannstrasse 3, 85748 Garching, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany
- Department of Mathematics, Technical University Munich, Boltzmannstrasse 3, 85748 Garching, Germany
- Faculty of Business Administration and Economics, Bielefeld University, Universitätsstrasse 25, 33615 Bielefeld, Germany
| |
Collapse
|
15
|
Kosaisawe N, Sparta B, Pargett M, Teragawa CK, Albeck JG. Transient phases of OXPHOS inhibitor resistance reveal underlying metabolic heterogeneity in single cells. Cell Metab 2021; 33:649-665.e8. [PMID: 33561427 PMCID: PMC8005262 DOI: 10.1016/j.cmet.2021.01.014] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 10/13/2020] [Accepted: 01/13/2021] [Indexed: 12/16/2022]
Abstract
Cell-to-cell heterogeneity in metabolism plays an unknown role in physiology and pharmacology. To functionally characterize cellular variability in metabolism, we treated cells with inhibitors of oxidative phosphorylation (OXPHOS) and monitored their responses with live-cell reporters for ATP, ADP/ATP, or activity of the energy-sensing kinase AMPK. Across multiple OXPHOS inhibitors and cell types, we identified a subpopulation of cells resistant to activation of AMPK and reduction of ADP/ATP ratio. This resistant state persists transiently for at least several hours and can be inherited during cell divisions. OXPHOS inhibition suppresses the mTORC1 and ERK growth signaling pathways in sensitive cells, but not in resistant cells. Resistance is linked to a multi-factorial combination of increased glucose uptake, reduced protein biosynthesis, and G0/G1 cell-cycle status. Our results reveal dynamic fluctuations in cellular energetic balance and provide a basis for measuring and predicting the distribution of cellular responses to OXPHOS inhibition.
Collapse
Affiliation(s)
- Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Breanne Sparta
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Carolyn K Teragawa
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA.
| |
Collapse
|
16
|
Davies AE, Pargett M, Siebert S, Gillies TE, Choi Y, Tobin SJ, Ram AR, Murthy V, Juliano C, Quon G, Bissell MJ, Albeck JG. Systems-Level Properties of EGFR-RAS-ERK Signaling Amplify Local Signals to Generate Dynamic Gene Expression Heterogeneity. Cell Syst 2020; 11:161-175.e5. [PMID: 32726596 PMCID: PMC7856305 DOI: 10.1016/j.cels.2020.07.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 05/06/2020] [Accepted: 07/02/2020] [Indexed: 02/08/2023]
Abstract
Intratumoral heterogeneity is associated with aggressive tumor behavior, therapy resistance, and poor patient outcomes. Such heterogeneity is thought to be dynamic, shifting over periods of minutes to hours in response to signaling inputs from the tumor microenvironment. However, models of this process have been inferred from indirect or post-hoc measurements of cell state, leaving the temporal details of signaling-driven heterogeneity undefined. Here, we developed a live-cell model system in which microenvironment-driven signaling dynamics can be directly observed and linked to variation in gene expression. Our analysis reveals that paracrine signaling between two cell types is sufficient to drive continual diversification of gene expression programs. This diversification emerges from systems-level properties of the EGFR-RAS-ERK signaling cascade, including intracellular amplification of amphiregulin-mediated paracrine signals and differential kinetic filtering by target genes including Fra-1, c-Myc, and Egr1. Our data enable more precise modeling of paracrine-driven transcriptional variation as a generator of gene expression heterogeneity. A record of this paper's transparent peer review process is included in the Supplemental Information.
Collapse
Affiliation(s)
- Alexander E Davies
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA; Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Stefan Siebert
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Taryn E Gillies
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Yongin Choi
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Savannah J Tobin
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA; Department of Veterinary Biosciences, College of Veterinary Medicine, the Ohio State University, Columbus, OH 43210, USA
| | - Abhineet R Ram
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Vaibhav Murthy
- Department of Veterinary Biosciences, College of Veterinary Medicine, the Ohio State University, Columbus, OH 43210, USA
| | - Celina Juliano
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Gerald Quon
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA
| | - Mina J Bissell
- Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, Davis, CA 95616, USA.
| |
Collapse
|
17
|
Pereira EJ, Burns JS, Lee CY, Marohl T, Calderon D, Wang L, Atkins KA, Wang CC, Janes KA. Sporadic activation of an oxidative stress-dependent NRF2-p53 signaling network in breast epithelial spheroids and premalignancies. Sci Signal 2020; 13:13/627/eaba4200. [PMID: 32291314 DOI: 10.1126/scisignal.aba4200] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Breast and mammary epithelial cells experience different local environments during tissue development and tumorigenesis. Microenvironmental heterogeneity gives rise to distinct cell regulatory states whose identity and importance are just beginning to be appreciated. Cellular states diversify when clonal three-dimensional (3D) spheroids are cultured in basement membrane, and one such state is associated with stress tolerance and poor response to anticancer therapeutics. Here, we found that this state was jointly coordinated by the NRF2 and p53 pathways, which were costabilized by spontaneous oxidative stress within 3D cultures. Inhibition of NRF2 or p53 individually disrupted some of the transcripts defining the regulatory state but did not yield a notable phenotype in nontransformed breast epithelial cells. In contrast, combined perturbation prevented 3D growth in an oxidative stress-dependent manner. By integrating systems models of NRF2 and p53 signaling in a single oxidative stress network, we recapitulated these observations and made predictions about oxidative stress profiles during 3D growth. NRF2 and p53 signaling were similarly coordinated in normal breast epithelial tissue and hormone-negative ductal carcinoma in situ lesions but were uncoupled in triple-negative breast cancer (TNBC), a subtype in which p53 is usually mutated. Using the integrated model, we correlated the extent of this uncoupling in TNBC cell lines with the importance of NRF2 in the 3D growth of these cell lines and their predicted handling of oxidative stress. Our results point to an oxidative stress tolerance network that is important for single cells during glandular development and the early stages of breast cancer.
Collapse
Affiliation(s)
- Elizabeth J Pereira
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Joseph S Burns
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Christina Y Lee
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Taylor Marohl
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Delia Calderon
- Biology and Chemistry Programs, California State University Channel Islands, Camarillo, CA 93012, USA
| | - Lixin Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Kristen A Atkins
- Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Chun-Chao Wang
- Institute of Molecular Medicine and Department of Medical Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA. .,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| |
Collapse
|
18
|
Goglia AG, Wilson MZ, Jena SG, Silbert J, Basta LP, Devenport D, Toettcher JE. A Live-Cell Screen for Altered Erk Dynamics Reveals Principles of Proliferative Control. Cell Syst 2020; 10:240-253.e6. [PMID: 32191874 DOI: 10.1016/j.cels.2020.02.005] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 01/08/2020] [Accepted: 02/24/2020] [Indexed: 12/18/2022]
Abstract
Complex, time-varying responses have been observed widely in cell signaling, but how specific dynamics are generated or regulated is largely unknown. One major obstacle has been that high-throughput screens are typically incompatible with the live-cell assays used to monitor dynamics. Here, we address this challenge by screening a library of 429 kinase inhibitors and monitoring extracellular-regulated kinase (Erk) activity over 5 h in more than 80,000 single primary mouse keratinocytes. Our screen reveals both known and uncharacterized modulators of Erk dynamics, including inhibitors of non-epidermal growth factor receptor (EGFR) receptor tyrosine kinases (RTKs) that increase Erk pulse frequency and overall activity. Using drug treatment and direct optogenetic control, we demonstrate that drug-induced changes to Erk dynamics alter the conditions under which cells proliferate. Our work opens the door to high-throughput screens using live-cell biosensors and reveals that cell proliferation integrates information from Erk dynamics as well as additional permissive cues.
Collapse
Affiliation(s)
- Alexander G Goglia
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544
| | - Maxwell Z Wilson
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544
| | - Siddhartha G Jena
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544
| | - Jillian Silbert
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544
| | - Lena P Basta
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544
| | - Danelle Devenport
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544
| | - Jared E Toettcher
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544.
| |
Collapse
|
19
|
Nye DMR, Albertson RM, Weiner AT, Hertzler JI, Shorey M, Goberdhan DCI, Wilson C, Janes KA, Rolls MM. The receptor tyrosine kinase Ror is required for dendrite regeneration in Drosophila neurons. PLoS Biol 2020; 18:e3000657. [PMID: 32163406 PMCID: PMC7067388 DOI: 10.1371/journal.pbio.3000657] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 02/07/2020] [Indexed: 12/13/2022] Open
Abstract
While many regulators of axon regeneration have been identified, very little is known about mechanisms that allow dendrites to regenerate after injury. Using a Drosophila model of dendrite regeneration, we performed a candidate screen of receptor tyrosine kinases (RTKs) and found a requirement for RTK-like orphan receptor (Ror). We confirmed that Ror was required for regeneration in two different neuron types using RNA interference (RNAi) and mutants. Ror was not required for axon regeneration or normal dendrite development, suggesting a specific role in dendrite regeneration. Ror can act as a Wnt coreceptor with frizzleds (fzs) in other contexts, so we tested the involvement of Wnt signaling proteins in dendrite regeneration. We found that knockdown of fz, dishevelled (dsh), Axin, and gilgamesh (gish) also reduced dendrite regeneration. Moreover, Ror was required to position dsh and Axin in dendrites. We recently found that Wnt signaling proteins, including dsh and Axin, localize microtubule nucleation machinery in dendrites. We therefore hypothesized that Ror may act by regulating microtubule nucleation at baseline and during dendrite regeneration. Consistent with this hypothesis, localization of the core nucleation protein γTubulin was reduced in Ror RNAi neurons, and this effect was strongest during dendrite regeneration. In addition, dendrite regeneration was sensitive to partial reduction of γTubulin. We conclude that Ror promotes dendrite regeneration as part of a Wnt signaling pathway that regulates dendritic microtubule nucleation.
Collapse
Affiliation(s)
- Derek M. R. Nye
- Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
- MSTP Program, Milton S. Hershey College of Medicine, Hershey, Pennsylvania, United States of America
| | - Richard M. Albertson
- Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
- MSTP Program, Milton S. Hershey College of Medicine, Hershey, Pennsylvania, United States of America
| | - Alexis T. Weiner
- Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - J. Ian Hertzler
- Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Matthew Shorey
- Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
| | | | - Clive Wilson
- Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Kevin A. Janes
- Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Melissa M. Rolls
- Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
- * E-mail:
| |
Collapse
|
20
|
Wang H, Lian Y, Li C, Ma Y, Yan Z, Dong C. SIN-KNO: A method of gene regulatory network inference using single-cell transcription and gene knockout data. J Bioinform Comput Biol 2020; 17:1950035. [PMID: 32019417 DOI: 10.1142/s0219720019500355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
As a tool of interpreting and analyzing genetic data, gene regulatory network (GRN) could reveal regulatory relationships between genes, proteins, and small molecules, as well as understand physiological activities and functions within biological cells, interact in pathways, and how to make changes in the organism. Traditional GRN research focuses on the analysis of the regulatory relationships through the average of cellular gene expressions. These methods are difficult to identify the cell heterogeneity of gene expression. Existing methods for inferring GRN using single-cell transcriptional data lack expression information when genes reach steady state, and the high dimensionality of single-cell data leads to high temporal and spatial complexity of the algorithm. In order to solve the problem in traditional GRN inference methods, including the lack of cellular heterogeneity information, single-cell data complexity and lack of steady-state information, we propose a method for GRN inference using single-cell transcription and gene knockout data, called SINgle-cell transcription data-KNOckout data (SIN-KNO), which focuses on combining dynamic and steady-state information of regulatory relationship contained in gene expression. Capturing cell heterogeneity information could help understand the gene expression difference in different cells. So, we could observe gene expression changes more accurately. Gene knockout data could observe the gene expression levels at steady-state of all other genes when one gene is knockout. Classifying the genes before analyzing the single-cell data could determine a large number of non-existent regulation, greatly reducing the number of regulation required for inference. In order to show the efficiency, the proposed method has been compared with several typical methods in this area including GENIE3, JUMP3, and SINCERITIES. The results of the evaluation indicate that the proposed method can analyze the diversified information contained in the two types of data, establish a more accurate gene regulation network, and improve the computational efficiency. The method provides a new thinking for dealing with large datasets and high computational complexity of single-cell data in the GRN inference.
Collapse
Affiliation(s)
- Huiqing Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Yuanyuan Lian
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Chun Li
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Yue Ma
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Zhiliang Yan
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, Shanxi, China
| | - Chunlin Dong
- Dryland Agriculture Research Center, Shanxi Academy of Agricultural Sciences, Taiyuan, Shanxi, China
| |
Collapse
|
21
|
Yao M, Ventura PB, Jiang Y, Rodriguez FJ, Wang L, Perry JSA, Yang Y, Wahl K, Crittenden RB, Bennett ML, Qi L, Gong CC, Li XN, Barres BA, Bender TP, Ravichandran KS, Janes KA, Eberhart CG, Zong H. Astrocytic trans-Differentiation Completes a Multicellular Paracrine Feedback Loop Required for Medulloblastoma Tumor Growth. Cell 2020; 180:502-520.e19. [PMID: 31983537 DOI: 10.1016/j.cell.2019.12.024] [Citation(s) in RCA: 93] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 10/16/2019] [Accepted: 12/17/2019] [Indexed: 12/19/2022]
Abstract
The tumor microenvironment (TME) is critical for tumor progression. However, the establishment and function of the TME remain obscure because of its complex cellular composition. Using a mouse genetic system called mosaic analysis with double markers (MADMs), we delineated TME evolution at single-cell resolution in sonic hedgehog (SHH)-activated medulloblastomas that originate from unipotent granule neuron progenitors in the brain. First, we found that astrocytes within the TME (TuAstrocytes) were trans-differentiated from tumor granule neuron precursors (GNPs), which normally never differentiate into astrocytes. Second, we identified that TME-derived IGF1 promotes tumor progression. Third, we uncovered that insulin-like growth factor 1 (IGF1) is produced by tumor-associated microglia in response to interleukin-4 (IL-4) stimulation. Finally, we found that IL-4 is secreted by TuAstrocytes. Collectively, our studies reveal an evolutionary process that produces a multi-lateral network within the TME of medulloblastoma: a fraction of tumor cells trans-differentiate into TuAstrocytes, which, in turn, produce IL-4 that stimulates microglia to produce IGF1 to promote tumor progression.
Collapse
Affiliation(s)
- Maojin Yao
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA
| | - P Britten Ventura
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA
| | - Ying Jiang
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA
| | - Fausto J Rodriguez
- Division of Neuropathology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Lixin Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Justin S A Perry
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA
| | - Yibo Yang
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA
| | - Kelsey Wahl
- Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Rowena B Crittenden
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA; Beirne B. Carter Center for Immunology Research, University of Virginia, Charlottesville, VA 22908, USA
| | - Mariko L Bennett
- Department of Neurobiology, Stanford University, Palo Alto, CA 94305, USA
| | - Lin Qi
- Brain Tumor Program, Texas Children's Cancer Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Cong-Cong Gong
- School of Food Science and Engineering, South China University of Technology, Guangzhou, China
| | - Xiao-Nan Li
- Brain Tumor Program, Texas Children's Cancer Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ben A Barres
- Department of Neurobiology, Stanford University, Palo Alto, CA 94305, USA
| | - Timothy P Bender
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA; Beirne B. Carter Center for Immunology Research, University of Virginia, Charlottesville, VA 22908, USA
| | - Kodi S Ravichandran
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA; Beirne B. Carter Center for Immunology Research, University of Virginia, Charlottesville, VA 22908, USA; VIB-UGent Center for Inflammation Research and Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Charles G Eberhart
- Division of Neuropathology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Hui Zong
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA 22908, USA.
| |
Collapse
|
22
|
Vodiasova EA, Chelebieva ES, Kuleshova ON. The new technologies of high-throughput single-cell RNA sequencing. Vavilovskii Zhurnal Genet Selektsii 2019. [DOI: 10.18699/vj19.520] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
A wealth of genome and transcriptome data obtained using new generation sequencing (NGS) technologies for whole organisms could not answer many questions in oncology, immunology, physiology, neurobiology, zoology and other fields of science and medicine. Since the cell is the basis for the living of all unicellular and multicellular organisms, it is necessary to study the biological processes at its level. This understanding gave impetus to the development of a new direction – the creation of technologies that allow working with individual cells (single-cell technology). The rapid development of not only instruments, but also various advanced protocols for working with single cells is due to the relevance of these studies in many fields of science and medicine. Studying the features of various stages of ontogenesis, identifying patterns of cell differentiation and subsequent tissue development, conducting genomic and transcriptome analyses in various areas of medicine (especially in demand in immunology and oncology), identifying cell types and states, patterns of biochemical and physiological processes using single cell technologies, allows the comprehensive research to be conducted at a new level. The first RNA-sequencing technologies of individual cell transcriptomes (scRNA-seq) captured no more than one hundred cells at a time, which was insufficient due to the detection of high cell heterogeneity, existence of the minor cell types (which were not detected by morphology) and complex regulatory pathways. The unique techniques for isolating, capturing and sequencing transcripts of tens of thousands of cells at a time are evolving now. However, new technologies have certain differences both at the sample preparation stage and during the bioinformatics analysis. In the paper we consider the most effective methods of multiple parallel scRNA-seq using the example of 10XGenomics, as well as the specifics of such an experiment, further bioinformatics analysis of the data, future outlook and applications of new high-performance technologies.
Collapse
Affiliation(s)
- E. A. Vodiasova
- A.O. Kovalevsky Institute of Biology of the Southern Seas, RAS
| | | | - O. N. Kuleshova
- A.O. Kovalevsky Institute of Biology of the Southern Seas, RAS
| |
Collapse
|
23
|
Avila Cobos F, Vandesompele J, Mestdagh P, De Preter K. Computational deconvolution of transcriptomics data from mixed cell populations. Bioinformatics 2019; 34:1969-1979. [PMID: 29351586 DOI: 10.1093/bioinformatics/bty019] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Accepted: 01/10/2018] [Indexed: 12/22/2022] Open
Abstract
Summary Gene expression analyses of bulk tissues often ignore cell type composition as an important confounding factor, resulting in a loss of signal from lowly abundant cell types. In this review, we highlight the importance and value of computational deconvolution methods to infer the abundance of different cell types and/or cell type-specific expression profiles in heterogeneous samples without performing physical cell sorting. We also explain the various deconvolution scenarios, the mathematical approaches used to solve them and the effect of data processing and different confounding factors on the accuracy of the deconvolution results. Contact katleen.depreter@ugent.be. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Francisco Avila Cobos
- Center for Medical Genetics Ghent (CMGG), Ghent University, 9000 Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium.,Bioinformatics Institute Ghent from Nucleotides to Networks (BIG N2N), 9000 Ghent, Belgium
| | - Jo Vandesompele
- Center for Medical Genetics Ghent (CMGG), Ghent University, 9000 Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium.,Bioinformatics Institute Ghent from Nucleotides to Networks (BIG N2N), 9000 Ghent, Belgium
| | - Pieter Mestdagh
- Center for Medical Genetics Ghent (CMGG), Ghent University, 9000 Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium.,Bioinformatics Institute Ghent from Nucleotides to Networks (BIG N2N), 9000 Ghent, Belgium
| | - Katleen De Preter
- Center for Medical Genetics Ghent (CMGG), Ghent University, 9000 Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium.,Bioinformatics Institute Ghent from Nucleotides to Networks (BIG N2N), 9000 Ghent, Belgium
| |
Collapse
|
24
|
Yu L, Li J, Minami I, Qu X, Miyagawa S, Fujimoto N, Hasegawa K, Chen Y, Sawa Y, Kotera H, Liu L. Clonal Isolation of Human Pluripotent Stem Cells on Nanofibrous Substrates Reveals an Advanced Subclone for Cardiomyocyte Differentiation. Adv Healthc Mater 2019; 8:e1900165. [PMID: 31087474 DOI: 10.1002/adhm.201900165] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 04/02/2019] [Indexed: 11/06/2022]
Abstract
Human pluripotent stem cells (hPSCs) have been widely used for various applications including disease modeling and regenerative medicine, among others. Recently, an increasing number of studies has focused on heterogeneity among hPSCs, which could affect cell quality and subsequent applications. In this study, a nanofibrous platform is developed for single human induced pluripotent stem cell isolation and culture. One type of single cell-derived subclone is established and found to have a distinct morphology compared to other subclones. When used for differentiation toward cardiomyocytes, this type of subclone demonstrates higher differentiation efficiency, increased maturation, and stronger beating compared to those derived from the other subclones. The findings provide a convenient method for single-cell isolation and culture, and demonstrate that variations in differentiation tendencies exist among subclones from the same cell line. This substrate adhesion-based selection process could be used to obtain cell lines with improved differentiation efficiency toward cardiomyocytes and other cell types, which would be advantageous for studies in various fields.
Collapse
Affiliation(s)
- Leqian Yu
- Institutes for Integrated Cell‐Material Sciences (WPI‐iCeMS)Kyoto University Kyoto 606‐8501 Japan
- Department of Micro EngineeringKyoto University Kyoto 615‐8540 Japan
| | - Junjun Li
- Institutes for Integrated Cell‐Material Sciences (WPI‐iCeMS)Kyoto University Kyoto 606‐8501 Japan
- Department of Cardiovascular SurgeryOsaka University Graduate School of Medicine Osaka 565‐0871 Japan
| | - Itsunari Minami
- Department of Cell Design for Tissue ConstructionFaculty of MedicineOsaka University Osaka 565‐0871 Japan
| | - Xiang Qu
- Department of Cardiovascular SurgeryOsaka University Graduate School of Medicine Osaka 565‐0871 Japan
| | - Shigeru Miyagawa
- Department of Cardiovascular SurgeryOsaka University Graduate School of Medicine Osaka 565‐0871 Japan
| | - Nanae Fujimoto
- Department of Cardiovascular SurgeryOsaka University Graduate School of Medicine Osaka 565‐0871 Japan
| | - Kouichi Hasegawa
- Institutes for Integrated Cell‐Material Sciences (WPI‐iCeMS)Kyoto University Kyoto 606‐8501 Japan
| | - Yong Chen
- Institutes for Integrated Cell‐Material Sciences (WPI‐iCeMS)Kyoto University Kyoto 606‐8501 Japan
- PASTEURDépartement de chimieécole normale supérieurePSL Research UniversitySorbonne UniversitésUPMC Université Paris 06 CNRS Paris 75005 France
| | - Yoshiki Sawa
- Department of Cardiovascular SurgeryOsaka University Graduate School of Medicine Osaka 565‐0871 Japan
| | - Hidetoshi Kotera
- Institutes for Integrated Cell‐Material Sciences (WPI‐iCeMS)Kyoto University Kyoto 606‐8501 Japan
- Department of Micro EngineeringKyoto University Kyoto 615‐8540 Japan
| | - Li Liu
- Institutes for Integrated Cell‐Material Sciences (WPI‐iCeMS)Kyoto University Kyoto 606‐8501 Japan
- Department of Cardiovascular SurgeryOsaka University Graduate School of Medicine Osaka 565‐0871 Japan
| |
Collapse
|
25
|
McDavid A, Gottardo R, Simon N, Drton M. GRAPHICAL MODELS FOR ZERO-INFLATED SINGLE CELL GENE EXPRESSION. Ann Appl Stat 2019; 13:848-873. [PMID: 31388390 PMCID: PMC6684253 DOI: 10.1214/18-aoas1213] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Bulk gene expression experiments relied on aggregations of thousands of cells to measure the average expression in an organism. Advances in microfluidic and droplet sequencing now permit expression profiling in single cells. This study of cell-to-cell variation reveals that individual cells lack detectable expression of transcripts that appear abundant on a population level, giving rise to zero-inflated expression patterns. To infer gene co-regulatory networks from such data, we propose a multivariate Hurdle model. It is comprised of a mixture of singular Gaussian distributions. We employ neighborhood selection with the pseudo-likelihood and a group lasso penalty to select and fit undirected graphical models that capture conditional independences between genes. The proposed method is more sensitive than existing approaches in simulations, even under departures from our Hurdle model. The method is applied to data for T follicular helper cells, and a high-dimensional profile of mouse dendritic cells. It infers network structure not revealed by other methods; or in bulk data sets. An R implementation is available at https://github.com/amcdavid/HurdleNormal.
Collapse
Affiliation(s)
- Andrew McDavid
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center; Rochester, New York
| | - Raphael Gottardo
- Vaccine and Infectuous Disease Division, Fred Hutchinson Cancer Research Center
- Department of Statistic, University of Washington; Seattle, Washington
| | - Noah Simon
- Department of Biostatistics, University of Washington; Seattle, Washington
| | - Mathias Drton
- Department of Statistic, University of Washington; Seattle, Washington
- Department of Mathematical Sciences, University of Copenhagen; Denmark
| |
Collapse
|
26
|
Singh S, Wang L, Schaff DL, Sutcliffe MD, Koeppel AF, Kim J, Onengut-Gumuscu S, Park KS, Zong H, Janes KA. In situ 10-cell RNA sequencing in tissue and tumor biopsy samples. Sci Rep 2019; 9:4836. [PMID: 30894605 PMCID: PMC6426952 DOI: 10.1038/s41598-019-41235-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 03/04/2019] [Indexed: 12/11/2022] Open
Abstract
Single-cell transcriptomic methods classify new and existing cell types very effectively, but alternative approaches are needed to quantify the individual regulatory states of cells in their native tissue context. We combined the tissue preservation and single-cell resolution of laser capture with an improved preamplification procedure enabling RNA sequencing of 10 microdissected cells. This in situ 10-cell RNA sequencing (10cRNA-seq) can exploit fluorescent reporters of cell type in genetically engineered mice and is compatible with freshly cryoembedded clinical biopsies from patients. Through recombinant RNA spike-ins, we estimate dropout-free technical reliability as low as ~250 copies and a 50% detection sensitivity of ~45 copies per 10-cell reaction. By using small pools of microdissected cells, 10cRNA-seq improves technical per-cell reliability and sensitivity beyond existing approaches for single-cell RNA sequencing (scRNA-seq). Detection of low-abundance transcripts by 10cRNA-seq is comparable to random 10-cell groups of scRNA-seq data, suggesting no loss of gene recovery when cells are isolated in situ. Combined with existing approaches to deconvolve small pools of cells, 10cRNA-seq offers a reliable, unbiased, and sensitive way to measure cell-state heterogeneity in tissues and tumors.
Collapse
Affiliation(s)
- Shambhavi Singh
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA
| | - Lixin Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA
| | - Dylan L Schaff
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA
| | - Matthew D Sutcliffe
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA
| | - Alex F Koeppel
- Bioinformatics Core, University of Virginia, Charlottesville, VA, 22908, USA
| | - Jungeun Kim
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, VA, 22908, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Kwon-Sik Park
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, VA, 22908, USA
| | - Hui Zong
- Department of Microbiology, Immunology & Cancer Biology, University of Virginia, Charlottesville, VA, 22908, USA
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA.
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA.
- Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA.
| |
Collapse
|
27
|
Cai W, Chiu YJ, Ramakrishnan V, Tsai Y, Chen C, Lo YH. A single-cell translocation and secretion assay (TransSeA). LAB ON A CHIP 2018; 18:3154-3162. [PMID: 30179236 PMCID: PMC6177299 DOI: 10.1039/c8lc00821c] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Understanding biological heterogeneity at the single cell level is required for advancing insights into the complexity of human physiology and diseases. While advances in technological and analytical methods have afforded unprecedented glimpses of this heterogeneity, the information captured to date largely represents one-time "snap" shots of single cell physiology. To address the limits of existing methods and to accelerate discoveries from single cell studies, we developed a single-cell translocation and secretion assay (TransSeA) that supports time lapse analysis, enables molecular cargo analysis of secretions such as extracellular vesicles (EVs) from single cells, allows massively parallel single cell transfer according to user-defined cell selection criteria, and supports tracking of phenotypes between parental and progeny cells derived from single cells. To demonstrate the unique capabilities and efficiencies of the assay, we present unprecedented single cell studies related to cell secretions, EV cargos and cell intrinsic properties. Although used as examples to demonstrate the feasibility and versatility of the technology, the studies already provided insights into key unanswered questions such as the microRNAs carried by EVs, the relationships between EV secretion rates and gene expressions, and the spontaneous, trans-generational phenotypic changes in EV secretion between parental and progeny cells.
Collapse
Affiliation(s)
- Wei Cai
- Materials Science and Engineering Program, University of California at San Diego, La Jolla, California, USA.
| | | | | | | | | | | |
Collapse
|
28
|
Pogrebniak KL, Curtis C. Harnessing Tumor Evolution to Circumvent Resistance. Trends Genet 2018; 34:639-651. [PMID: 29903534 DOI: 10.1016/j.tig.2018.05.007] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 05/16/2018] [Accepted: 05/21/2018] [Indexed: 02/08/2023]
Abstract
High-throughput sequencing can be used to measure changes in tumor composition across space and time. Specifically, comparisons of pre- and post-treatment samples can reveal the underlying clonal dynamics and resistance mechanisms. Here, we discuss evidence for distinct modes of tumor evolution and their implications for therapeutic strategies. In addition, we consider the utility of spatial tissue sampling schemes, single-cell analysis, and circulating tumor DNA to track tumor evolution and the emergence of resistance, as well as approaches that seek to forestall resistance by targeting tumor evolution. Ultimately, characterization of the (epi)genomic, transcriptomic, and phenotypic changes that occur during tumor progression coupled with computational and mathematical modeling of tumor evolutionary dynamics may inform personalized treatment strategies.
Collapse
Affiliation(s)
- Katherine L Pogrebniak
- Cancer Biology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; http://med.stanford.edu/curtislab.html
| | - Christina Curtis
- Cancer Biology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; http://med.stanford.edu/curtislab.html.
| |
Collapse
|
29
|
Automated brightfield morphometry of 3D organoid populations by OrganoSeg. Sci Rep 2018; 8:5319. [PMID: 29593296 PMCID: PMC5871765 DOI: 10.1038/s41598-017-18815-8] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 12/18/2017] [Indexed: 02/08/2023] Open
Abstract
Spheroid and organoid cultures are powerful in vitro models for biology, but size and shape diversity within the culture is largely ignored. To streamline morphometric profiling, we developed OrganoSeg, an open-source software that integrates segmentation, filtering, and analysis for archived brightfield images of 3D culture. OrganoSeg is more accurate and flexible than existing platforms, and we illustrate its potential by stratifying 5167 breast-cancer spheroid and 5743 colon and colorectal-cancer organoid morphologies. Organoid transcripts grouped by morphometric signature heterogeneity were enriched for biological processes not prominent in the original RNA sequencing data. OrganoSeg enables complete, objective quantification of brightfield phenotypes, which may give insight into the molecular and multicellular mechanisms of organoid regulation.
Collapse
|
30
|
Bajikar SS, Wang CC, Borten MA, Pereira EJ, Atkins KA, Janes KA. Tumor-Suppressor Inactivation of GDF11 Occurs by Precursor Sequestration in Triple-Negative Breast Cancer. Dev Cell 2017; 43:418-435.e13. [PMID: 29161592 DOI: 10.1016/j.devcel.2017.10.027] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2016] [Revised: 09/18/2017] [Accepted: 10/25/2017] [Indexed: 12/18/2022]
Abstract
Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous carcinoma in which various tumor-suppressor genes are lost by mutation, deletion, or silencing. Here we report a tumor-suppressive mode of action for growth-differentiation factor 11 (GDF11) and an unusual mechanism of its inactivation in TNBC. GDF11 promotes an epithelial, anti-invasive phenotype in 3D triple-negative cultures and intraductal xenografts by sustaining expression of E-cadherin and inhibitor of differentiation 2 (ID2). Surprisingly, clinical TNBCs retain the GDF11 locus and expression of the protein itself. GDF11 bioactivity is instead lost because of deficiencies in its convertase, proprotein convertase subtilisin/kexin type 5 (PCSK5), causing inactive GDF11 precursor to accumulate intracellularly. PCSK5 reconstitution mobilizes the latent TNBC reservoir of GDF11 in vitro and suppresses triple-negative mammary cancer metastasis to the lung of syngeneic hosts. Intracellular GDF11 retention adds to the concept of tumor-suppressor inactivation and reveals a cell-biological vulnerability for TNBCs lacking therapeutically actionable mutations.
Collapse
Affiliation(s)
- Sameer S Bajikar
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Chun-Chao Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Institute of Molecular Medicine & Department of Medical Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Michael A Borten
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Elizabeth J Pereira
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Kristen A Atkins
- Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
| |
Collapse
|
31
|
Hung YP, Teragawa C, Kosaisawe N, Gillies TE, Pargett M, Minguet M, Distor K, Rocha-Gregg BL, Coloff JL, Keibler MA, Stephanopoulos G, Yellen G, Brugge JS, Albeck JG. Akt regulation of glycolysis mediates bioenergetic stability in epithelial cells. eLife 2017; 6:27293. [PMID: 29239720 PMCID: PMC5730373 DOI: 10.7554/elife.27293] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Accepted: 12/05/2017] [Indexed: 12/26/2022] Open
Abstract
Cells use multiple feedback controls to regulate metabolism in response to nutrient and signaling inputs. However, feedback creates the potential for unstable network responses. We examined how concentrations of key metabolites and signaling pathways interact to maintain homeostasis in proliferating human cells, using fluorescent reporters for AMPK activity, Akt activity, and cytosolic NADH/NAD+ redox. Across various conditions, including glycolytic or mitochondrial inhibition or cell proliferation, we observed distinct patterns of AMPK activity, including both stable adaptation and highly dynamic behaviors such as periodic oscillations and irregular fluctuations that indicate a failure to reach a steady state. Fluctuations in AMPK activity, Akt activity, and cytosolic NADH/NAD+ redox state were temporally linked in individual cells adapting to metabolic perturbations. By monitoring single-cell dynamics in each of these contexts, we identified PI3K/Akt regulation of glycolysis as a multifaceted modulator of single-cell metabolic dynamics that is required to maintain metabolic stability in proliferating cells.
Collapse
Affiliation(s)
- Yin P Hung
- Department of Cell Biology, Harvard Medical School, Boston, United States.,Department of Neurobiology, Harvard Medical School, Boston, United States.,Department of Pathology, Brigham and Women's Hospital, Boston, United States
| | - Carolyn Teragawa
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| | - Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| | - Taryn E Gillies
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| | - Marta Minguet
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| | - Kevin Distor
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| | - Briana L Rocha-Gregg
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| | - Jonathan L Coloff
- Department of Cell Biology, Harvard Medical School, Boston, United States
| | - Mark A Keibler
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, United States
| | - Gregory Stephanopoulos
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, United States
| | - Gary Yellen
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Joan S Brugge
- Department of Cell Biology, Harvard Medical School, Boston, United States
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, United States
| |
Collapse
|
32
|
Gillies TE, Pargett M, Minguet M, Davies AE, Albeck JG. Linear Integration of ERK Activity Predominates over Persistence Detection in Fra-1 Regulation. Cell Syst 2017; 5:549-563.e5. [PMID: 29199017 DOI: 10.1016/j.cels.2017.10.019] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Revised: 08/29/2017] [Accepted: 10/27/2017] [Indexed: 12/14/2022]
Abstract
ERK signaling regulates the expression of target genes, but it is unclear how ERK activity dynamics are interpreted. Here, we investigate this question using simultaneous, live, single-cell imaging of two ERK activity reporters and expression of Fra-1, a target gene controlling epithelial cell identity. We find that Fra-1 is expressed in proportion to the amplitude and duration of ERK activity. In contrast to previous "persistence detector" and "selective filter" models in which Fra-1 expression only occurs when ERK activity persists beyond a threshold duration, our observations demonstrate that the network regulating Fra-1 expression integrates total ERK activity and responds to it linearly. However, exploration of a generalized mathematical model of the Fra-1 coherent feedforward loop demonstrates that it can perform either linear integration or persistence detection, depending on the basal mRNA production rate and protein production delays. Our data indicate that significant basal expression and short delays cause Fra-1 to respond linearly to integrated ERK activity.
Collapse
Affiliation(s)
- Taryn E Gillies
- Department of Molecular and Cellular Biology, University of California, Davis, CA 95616, USA
| | - Michael Pargett
- Department of Molecular and Cellular Biology, University of California, Davis, CA 95616, USA
| | - Marta Minguet
- Department of Molecular and Cellular Biology, University of California, Davis, CA 95616, USA
| | - Alex E Davies
- Department of Molecular and Cellular Biology, University of California, Davis, CA 95616, USA; Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - John G Albeck
- Department of Molecular and Cellular Biology, University of California, Davis, CA 95616, USA.
| |
Collapse
|
33
|
Dacheux E, Malys N, Meng X, Ramachandran V, Mendes P, McCarthy JEG. Translation initiation events on structured eukaryotic mRNAs generate gene expression noise. Nucleic Acids Res 2017; 45:6981-6992. [PMID: 28521011 PMCID: PMC5499741 DOI: 10.1093/nar/gkx430] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 05/10/2017] [Indexed: 11/14/2022] Open
Abstract
Gene expression stochasticity plays a major role in biology, creating non-genetic cellular individuality and influencing multiple processes, including differentiation and stress responses. We have addressed the lack of knowledge about posttranscriptional contributions to noise by determining cell-to-cell variations in the abundance of mRNA and reporter protein in yeast. Two types of structural element, a stem–loop and a poly(G) motif, not only inhibit translation initiation when inserted into an mRNA 5΄ untranslated region, but also generate noise. The noise-enhancing effect of the stem–loop structure also remains operational when combined with an upstream open reading frame. This has broad significance, since these elements are known to modulate the expression of a diversity of eukaryotic genes. Our findings suggest a mechanism for posttranscriptional noise generation that will contribute to understanding of the generally poor correlation between protein-level stochasticity and transcriptional bursting. We propose that posttranscriptional stochasticity can be linked to cycles of folding/unfolding of a stem–loop structure, or to interconversion between higher-order structural conformations of a G-rich motif, and have created a correspondingly configured computational model that generates fits to the experimental data. Stochastic events occurring during the ribosomal scanning process can therefore feature alongside transcriptional bursting as a source of noise.
Collapse
Affiliation(s)
- Estelle Dacheux
- Warwick Integrative Synthetic Biology Centre (WISB) and School of Life Sciences, University of Warwick, Gibbet Hill, Coventry CV4 7AL, UK
| | - Naglis Malys
- Warwick Integrative Synthetic Biology Centre (WISB) and School of Life Sciences, University of Warwick, Gibbet Hill, Coventry CV4 7AL, UK
| | - Xiang Meng
- Warwick Integrative Synthetic Biology Centre (WISB) and School of Life Sciences, University of Warwick, Gibbet Hill, Coventry CV4 7AL, UK
| | - Vinoy Ramachandran
- Warwick Integrative Synthetic Biology Centre (WISB) and School of Life Sciences, University of Warwick, Gibbet Hill, Coventry CV4 7AL, UK
| | - Pedro Mendes
- Center for Quantitative Medicine, UConn Health, 263 Farmington Avenue, CT 06030-6033, USA
| | - John E G McCarthy
- Warwick Integrative Synthetic Biology Centre (WISB) and School of Life Sciences, University of Warwick, Gibbet Hill, Coventry CV4 7AL, UK
| |
Collapse
|
34
|
Liu T, Wu H, Wu S, Wang C. Single-Cell Sequencing Technologies for Cardiac Stem Cell Studies. Stem Cells Dev 2017; 26:1540-1551. [PMID: 28859577 DOI: 10.1089/scd.2017.0050] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Today with the rapid advancements in stem cell studies and the promising potential of using stem cells in clinical therapy, there is an increasing demand for in-depth comprehensive analysis on individual cell transcriptome and epigenome, as they play critical roles in a number of cell functions such as cell differentiation, growth, and reprogramming. The development of single-cell sequencing technologies has helped in revealing some exciting new perspectives in stem cells and regenerative medicine research. Among the various potential applications, single-cell analysis for cardiac stem cells (CSCs) holds tremendous promises in understanding the mechanisms of heart development and regeneration, which might light up the path toward cell therapy for cardiovascular diseases. This review briefly highlights the recent progresses in single-cell sequencing analysis technologies and their applications in CSC research.
Collapse
Affiliation(s)
- Tiantian Liu
- 1 Center for Genomics & Department of Basic Sciences, School of Medicine, Loma Linda University , Loma Linda, California
| | - Hongjin Wu
- 1 Center for Genomics & Department of Basic Sciences, School of Medicine, Loma Linda University , Loma Linda, California.,2 Cancer Research Institute, Hangzhou Cancer Hospital , Hangzhou, Zhejiang Province, P.R. China
| | - Shixiu Wu
- 2 Cancer Research Institute, Hangzhou Cancer Hospital , Hangzhou, Zhejiang Province, P.R. China
| | - Charles Wang
- 1 Center for Genomics & Department of Basic Sciences, School of Medicine, Loma Linda University , Loma Linda, California
| |
Collapse
|
35
|
Hannan RT, Peirce SM, Barker TH. Fibroblasts: Diverse Cells Critical to Biomaterials Integration. ACS Biomater Sci Eng 2017; 4:1223-1232. [PMID: 31440581 DOI: 10.1021/acsbiomaterials.7b00244] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Fibroblasts are key participants in wound healing and inflammation, and are capable of driving the progression of tissue repair to fully functional tissue or pathologic scar, or fibrosis, depending on the specific mechanical and biochemical cues with which they are presented. Thus, understanding and modulating the fibroblastic response to implanted materials is paramount to achieving desirable outcomes, such as long-term implant function or tissue regeneration. However, fibroblasts are remarkably heterogeneous and can differ vastly in their contributions to regeneration and fibrosis. This heterogeneity exists between tissues and within tissues, down to the level of individual cells. This review will discuss the role of fibroblasts, the pitfalls of describing them as a collective, the specifics of their function, and potential future directions to better understand and organize their highly variable biology.
Collapse
Affiliation(s)
- Riley T Hannan
- Department of Pathology, University of Virginia, 415 Lane Road, Charlottesville, Virginia 22903, United States.,Department of Biomedical Engineering, University of Virginia, 415 Lane Road, Charlottesville, Virginia 22903, United States
| | - Shayn M Peirce
- Department of Pathology, University of Virginia, 415 Lane Road, Charlottesville, Virginia 22903, United States.,Department of Biomedical Engineering, University of Virginia, 415 Lane Road, Charlottesville, Virginia 22903, United States
| | - Thomas H Barker
- Department of Biomedical Engineering, University of Virginia, 415 Lane Road, Charlottesville, Virginia 22903, United States
| |
Collapse
|
36
|
Inhibition of extracellular matrix mediated TGF-β signalling suppresses endometrial cancer metastasis. Oncotarget 2017; 8:71400-71417. [PMID: 29069715 PMCID: PMC5641058 DOI: 10.18632/oncotarget.18069] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 05/07/2017] [Indexed: 01/06/2023] Open
Abstract
Although aggressive invasion and distant metastases are an important cause of morbidity and mortality in patients with endometrial cancer (EC), the requisite events determining this propensity are currently unknown. Using organotypic three-dimensional culture of endometrial cancer cell lines, we demonstrated anti-correlated TGF-β signalling gene expression patterns that arise among extracellular matrix (ECM)-attached cells. TGF-β pathway seemed to be active in EC cells forming non-glandular colonies in 3D-matrix but weaker in glandular colonies. Functionally we found that out of several ECM proteins, fibronectin relatively promotes Smad phosphorylation suggesting a potential role in regulating TGF-β signalling in non-glandular colonies. Importantly, alteration of TGF-β pathway induced EMT and MET in both type of colonies through slug protein. The results exemplify a crucial role of TGF-β pathway during EC metastasis in human patients and inhibition of the pathway in a murine model impaired tumour cell invasion and metastasis depicting an attractive target for therapeutic intervention of malignant tumour progression. These findings provide key insights into the role of ECM-derived TGF-β signalling to promote endometrial cancer metastasis and offer an avenue for therapeutic targeting of microenvironment derived signals along with tumour cells.
Collapse
|
37
|
Martins AJ, Narayanan M, Prüstel T, Fixsen B, Park K, Gottschalk RA, Lu Y, Andrews-Pfannkoch C, Lau WW, Wendelsdorf KV, Tsang JS. Environment Tunes Propagation of Cell-to-Cell Variation in the Human Macrophage Gene Network. Cell Syst 2017; 4:379-392.e12. [PMID: 28365150 DOI: 10.1016/j.cels.2017.03.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 11/15/2016] [Accepted: 03/01/2017] [Indexed: 01/22/2023]
Abstract
Cell-to-cell variation in gene expression and the propagation of such variation (PoV or "noise propagation") from one gene to another in the gene network, as reflected by gene-gene correlation across single cells, are commonly observed in single-cell transcriptomic studies and can shape the phenotypic diversity of cell populations. While gene network "rewiring" is known to accompany cellular adaptation to different environments, how PoV changes between environments and its underlying regulatory mechanisms are less understood. Here, we systematically explored context-dependent PoV among genes in human macrophages, utilizing different cytokines as natural perturbations of multiple molecular parameters that may influence PoV. Our single-cell, epigenomic, computational, and stochastic simulation analyses reveal that environmental adaptation can tune PoV to potentially shape cellular heterogeneity by changing parameters such as the degree of phosphorylation and transcription factor-chromatin interactions. This quantitative tuning of PoV may be a widespread, yet underexplored, property of cellular adaptation to distinct environments.
Collapse
Affiliation(s)
- Andrew J Martins
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Manikandan Narayanan
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Thorsten Prüstel
- Computational Biology Section, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Bethany Fixsen
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kyemyung Park
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA; Biophysics Program, University of Maryland-NIH Graduate Partnership Program, University of Maryland, College Park, MD 20742, USA
| | - Rachel A Gottschalk
- Lymphocyte Biology Section, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yong Lu
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Cynthia Andrews-Pfannkoch
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - William W Lau
- Office of Intramural Research, Center for Information Technology, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katherine V Wendelsdorf
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA
| | - John S Tsang
- Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA; Trans-NIH Center for Human Immunology (CHI), National Institutes of Health, Bethesda, MD 20892, USA.
| |
Collapse
|
38
|
Shah M, Smolko CM, Kinicki S, Chapman ZD, Brautigan DL, Janes KA. Profiling Subcellular Protein Phosphatase Responses to Coxsackievirus B3 Infection of Cardiomyocytes. Mol Cell Proteomics 2017; 16:S244-S262. [PMID: 28174228 DOI: 10.1074/mcp.o116.063487] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Revised: 01/31/2017] [Indexed: 01/23/2023] Open
Abstract
Cellular responses to stimuli involve dynamic and localized changes in protein kinases and phosphatases. Here, we report a generalized functional assay for high-throughput profiling of multiple protein phosphatases with subcellular resolution and apply it to analyze coxsackievirus B3 (CVB3) infection counteracted by interferon signaling. Using on-plate cell fractionation optimized for adherent cells, we isolate protein extracts containing active endogenous phosphatases from cell membranes, the cytoplasm, and the nucleus. The extracts contain all major classes of protein phosphatases and catalyze dephosphorylation of plate-bound phosphosubstrates in a microtiter format, with cellular activity quantified at the end point by phosphospecific ELISA. The platform is optimized for six phosphosubstrates (ERK2, JNK1, p38α, MK2, CREB, and STAT1) and measures specific activities from extracts of fewer than 50,000 cells. The assay was exploited to examine viral and antiviral signaling in AC16 cardiomyocytes, which we show can be engineered to serve as susceptible and permissive hosts for CVB3. Phosphatase responses were profiled in these cells by completing a full-factorial experiment for CVB3 infection and type I/II interferon signaling. Over 850 functional measurements revealed several independent, subcellular changes in specific phosphatase activities. During CVB3 infection, we found that type I interferon signaling increases subcellular JNK1 phosphatase activity, inhibiting nuclear JNK1 activity that otherwise promotes viral protein synthesis in the infected host cell. Our assay provides a high-throughput way to capture perturbations in important negative regulators of intracellular signal-transduction networks.
Collapse
Affiliation(s)
- Millie Shah
- From the ‡Department of Biomedical Engineering
| | | | | | | | - David L Brautigan
- the ‖Center for Cell Signaling and Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, Virginia 22908
| | | |
Collapse
|
39
|
Chen X, Chakravarty T, Zhang Y, Li X, Zhong JF, Wang C. Single-cell transcriptome and epigenomic reprogramming of cardiomyocyte-derived cardiac progenitor cells. Sci Data 2016; 3:160079. [PMID: 27622691 PMCID: PMC5020870 DOI: 10.1038/sdata.2016.79] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Accepted: 08/11/2016] [Indexed: 12/12/2022] Open
Abstract
The molecular basis underlying the dedifferentiation of mammalian adult cardiomyocytes (ACMs) into myocyte-derived cardiac progenitor cells (mCPCs) during cardiac tissue regeneration is poorly understood. We present data integrating single-cell transcriptome and whole-genome DNA methylome analyses of mouse mCPCs to understand the epigenomic reprogramming governing their intrinsic cellular plasticity. Compared to parental cardiomyocytes, mCPCs display epigenomic reprogramming with many differentially-methylated regions, both hypermethylated and hypomethylated, across the entire genome. Correlating well with the methylome, our single-cell transcriptomic data show that the genes encoding cardiac structure and function proteins are remarkably down-regulated in mCPCs, while those for cell cycle, proliferation, and stemness are significantly up-regulated. In addition, implanting mCPCs into infarcted mouse myocardium improves cardiac function with augmented left ventricular ejection fraction. This dataset suggests that the cellular plasticity of mammalian cardiomyocytes is the result of a well-orchestrated epigenomic reprogramming and a subsequent global transcriptomic alteration. Understanding cardiomyocyte epigenomic reprogramming may enable the design of future clinical therapies that induce cardiac regeneration, and prevent heart failure.
Collapse
Affiliation(s)
- Xin Chen
- Center for Genomics & Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, California 92350, USA
- These authors contributed equally to this work
| | - Tushar Chakravarty
- Center for Genomics & Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, California 92350, USA
- These authors contributed equally to this work
| | - Yiqiang Zhang
- Division of Cardiology, Department of Medicine, and Center for Cardiovascular Biology, and Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington 98109, USA
- These authors contributed equally to this work
| | - Xiaojin Li
- CardioDx, Inc., 600 Saginaw Drive, Redwood City, California 94063, USA
| | - Jiang F. Zhong
- Division of Periodontology, Diagnostic Sciences & Dental Hygiene & Biomedical Sciences, Herman Ostrow School of Dentistry, and Norris Cancer Center, University of Southern California, Los Angeles, Los Angeles, California 90089, USA
| | - Charles Wang
- Center for Genomics & Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, California 92350, USA
| |
Collapse
|
40
|
Derr A, Yang C, Zilionis R, Sergushichev A, Blodgett DM, Redick S, Bortell R, Luban J, Harlan DM, Kadener S, Greiner DL, Klein A, Artyomov MN, Garber M. End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data. Genome Res 2016; 26:1397-1410. [PMID: 27470110 PMCID: PMC5052061 DOI: 10.1101/gr.207902.116] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Accepted: 07/27/2016] [Indexed: 12/27/2022]
Abstract
RNA-seq protocols that focus on transcript termini are well suited for applications in which template quantity is limiting. Here we show that, when applied to end-sequencing data, analytical methods designed for global RNA-seq produce computational artifacts. To remedy this, we created the End Sequence Analysis Toolkit (ESAT). As a test, we first compared end-sequencing and bulk RNA-seq using RNA from dendritic cells stimulated with lipopolysaccharide (LPS). As predicted by the telescripting model for transcriptional bursts, ESAT detected an LPS-stimulated shift to shorter 3′-isoforms that was not evident by conventional computational methods. Then, droplet-based microfluidics was used to generate 1000 cDNA libraries, each from an individual pancreatic islet cell. ESAT identified nine distinct cell types, three distinct β-cell types, and a complex interplay between hormone secretion and vascularization. ESAT, then, offers a much-needed and generally applicable computational pipeline for either bulk or single-cell RNA end-sequencing.
Collapse
Affiliation(s)
- Alan Derr
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - Chaoxing Yang
- Program in Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - Rapolas Zilionis
- Department of System Biology, Harvard Medical School, Boston, Massachusetts 02115, USA; Institute of Biotechnology, Vilnius University, LT 02241 Vilnius, Lithuania
| | - Alexey Sergushichev
- Computer Technologies Department, ITMO University, Saint Petersburg, 197101, Russia; Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, Missouri 63110, USA
| | - David M Blodgett
- Department of Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - Sambra Redick
- Program in Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - Rita Bortell
- Program in Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - Jeremy Luban
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - David M Harlan
- Department of Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - Sebastian Kadener
- Biological Chemistry Department, Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 91904, Israel
| | - Dale L Greiner
- Program in Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA; Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| | - Allon Klein
- Department of System Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Maxim N Artyomov
- Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, Missouri 63110, USA
| | - Manuel Garber
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA; Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA
| |
Collapse
|
41
|
Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling. PLoS Comput Biol 2016; 12:e1005016. [PMID: 27438699 PMCID: PMC4954693 DOI: 10.1371/journal.pcbi.1005016] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2015] [Accepted: 06/07/2016] [Indexed: 12/18/2022] Open
Abstract
Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational “deconvolution” of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of ‘ON’ versus ‘OFF’ cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies. Different cells can make different amounts of biomolecules such as RNA transcripts of genes. New technologies are emerging to measure the transcript level of many genes in single cells. However, accurate quantification of the biological variation from cell to cell can be challenging due to the low transcript level of many genes and the presence of substantial measurement noise. Here we present a flexible, novel computational approach to quantify biological cell-to-cell variation that can use different types of data, namely measurements directly obtained from single cells, and/or those from random pools of k-cells (e.g., k = 10). Assessment of these different inputs using simulated and real data revealed that each data type can offer advantages under different scenarios, but combining both single- and k-cell measurements tend to offer the best of both. Application of our approach to single- and k-cell data obtained from resting and inflammatory macrophages, an important type of immune cells implicated in diverse diseases, revealed interesting changes in cell-to-cell variation in transcript levels upon inflammatory stimulation, thus suggesting that inflammation can shape not only the average expression level of a gene but also the gene’s degree of expression variation among single cells.
Collapse
|
42
|
Chitforoushzadeh Z, Ye Z, Sheng Z, LaRue S, Fry RC, Lauffenburger DA, Janes KA. TNF-insulin crosstalk at the transcription factor GATA6 is revealed by a model that links signaling and transcriptomic data tensors. Sci Signal 2016; 9:ra59. [PMID: 27273097 DOI: 10.1126/scisignal.aad3373] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Signal transduction networks coordinate transcriptional programs activated by diverse extracellular stimuli, such as growth factors and cytokines. Cells receive multiple stimuli simultaneously, and mapping how activation of the integrated signaling network affects gene expression is a challenge. We stimulated colon adenocarcinoma cells with various combinations of the cytokine tumor necrosis factor (TNF) and the growth factors insulin and epidermal growth factor (EGF) to investigate signal integration and transcriptional crosstalk. We quantitatively linked the proteomic and transcriptomic data sets by implementing a structured computational approach called tensor partial least squares regression. This statistical model accurately predicted transcriptional signatures from signaling arising from single and combined stimuli and also predicted time-dependent contributions of signaling events. Specifically, the model predicted that an early-phase, AKT-associated signal downstream of insulin repressed a set of transcripts induced by TNF. Through bioinformatics and cell-based experiments, we identified the AKT-repressed signal as glycogen synthase kinase 3 (GSK3)-catalyzed phosphorylation of Ser(37) on the long form of the transcription factor GATA6. Phosphorylation of GATA6 on Ser(37) promoted its degradation, thereby preventing GATA6 from repressing transcripts that are induced by TNF and attenuated by insulin. Our analysis showed that predictive tensor modeling of proteomic and transcriptomic data sets can uncover pathway crosstalk that produces specific patterns of gene expression in cells receiving multiple stimuli.
Collapse
Affiliation(s)
- Zeinab Chitforoushzadeh
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA. Department of Pharmacology, University of Virginia, Charlottesville, VA 22908, USA
| | - Zi Ye
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Ziran Sheng
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Silvia LaRue
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Rebecca C Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Douglas A Lauffenburger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
| |
Collapse
|
43
|
LoVerso PR, Cui F. Cell type-specific transcriptome profiling in mammalian brains. Front Biosci (Landmark Ed) 2016; 21:973-85. [PMID: 27100485 DOI: 10.2741/4434] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
A mammalian brain contains numerous types of cells. Advances in neuroscience in the past decade allow us to identify and isolate neural cells of interest from mammalian brains. Recent developments in high-throughput technologies, such as microarrays and next-generation sequencing (NGS), provide detailed information on gene expression in pooled cells on a genomic scale. As a result, many novel genes have been found critical in cell type-specific transcriptional regulation. These differentially expressed genes can be used as molecular signatures, unique to a particular class of neural cells. Use of this gene expression-based approach can further differentiate neural cell types into subtypes, potentially linking some of them with neurological diseases. In this article, experimental techniques used to purify neural cells are described, followed by a review on recent microarray- or NGS-based transcriptomic studies of common neural cell types. The future prospects of cell type-specific research are also discussed.
Collapse
Affiliation(s)
- Peter R LoVerso
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, One Lomb Memorial Dr., Rochester, NY 14623
| | - Feng Cui
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, One Lomb Memorial Dr., Rochester, NY 14623,
| |
Collapse
|
44
|
Illendula A, Gilmour J, Grembecka J, Tirumala VSS, Boulton A, Kuntimaddi A, Schmidt C, Wang L, Pulikkan JA, Zong H, Parlak M, Kuscu C, Pickin A, Zhou Y, Gao Y, Mishra L, Adli M, Castilla LH, Rajewski RA, Janes KA, Guzman ML, Bonifer C, Bushweller JH. Small Molecule Inhibitor of CBFβ-RUNX Binding for RUNX Transcription Factor Driven Cancers. EBioMedicine 2016; 8:117-131. [PMID: 27428424 PMCID: PMC4919611 DOI: 10.1016/j.ebiom.2016.04.032] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Revised: 04/12/2016] [Accepted: 04/25/2016] [Indexed: 10/29/2022] Open
Abstract
Transcription factors have traditionally been viewed with skepticism as viable drug targets, but they offer the potential for completely novel mechanisms of action that could more effectively address the stem cell like properties, such as self-renewal and chemo-resistance, that lead to the failure of traditional chemotherapy approaches. Core binding factor is a heterodimeric transcription factor comprised of one of 3 RUNX proteins (RUNX1-3) and a CBFβ binding partner. CBFβ enhances DNA binding of RUNX subunits by relieving auto-inhibition. Both RUNX1 and CBFβ are frequently mutated in human leukemia. More recently, RUNX proteins have been shown to be key players in epithelial cancers, suggesting the targeting of this pathway could have broad utility. In order to test this, we developed small molecules which bind to CBFβ and inhibit its binding to RUNX. Treatment with these inhibitors reduces binding of RUNX1 to target genes, alters the expression of RUNX1 target genes, and impacts cell survival and differentiation. These inhibitors show efficacy against leukemia cells as well as basal-like (triple-negative) breast cancer cells. These inhibitors provide effective tools to probe the utility of targeting RUNX transcription factor function in other cancers.
Collapse
Affiliation(s)
- Anuradha Illendula
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Jane Gilmour
- School of Cancer Sciences, Institute of Biomedical Research, University of Birmingham, Birmingham, UK
| | | | | | - Adam Boulton
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Aravinda Kuntimaddi
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Charles Schmidt
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Lixin Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - John A Pulikkan
- Department of Molecular, Cell and Cancer Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Hongliang Zong
- Division of Hematology/Oncology, Department of Medicine, Weill Medical College of Cornell University, New York, NY, USA
| | - Mahmut Parlak
- Department of Biochemistry, University of Virginia, Charlottesville, VA, USA
| | - Cem Kuscu
- Department of Biochemistry, University of Virginia, Charlottesville, VA, USA
| | - Anna Pickin
- School of Cancer Sciences, Institute of Biomedical Research, University of Birmingham, Birmingham, UK
| | - Yunpeng Zhou
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Yan Gao
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Lauren Mishra
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, USA
| | - Mazhar Adli
- Department of Biochemistry, University of Virginia, Charlottesville, VA, USA
| | - Lucio H Castilla
- Department of Molecular, Cell and Cancer Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Roger A Rajewski
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS, USA
| | - Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Monica L Guzman
- Division of Hematology/Oncology, Department of Medicine, Weill Medical College of Cornell University, New York, NY, USA
| | - Constanze Bonifer
- School of Cancer Sciences, Institute of Biomedical Research, University of Birmingham, Birmingham, UK
| | - John H Bushweller
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| |
Collapse
|
45
|
Lyons J, Herring CA, Banerjee A, Simmons AJ, Lau KS. Multiscale analysis of the murine intestine for modeling human diseases. Integr Biol (Camb) 2016; 7:740-57. [PMID: 26040649 DOI: 10.1039/c5ib00030k] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
When functioning properly, the intestine is one of the key interfaces between the human body and its environment. It is responsible for extracting nutrients from our food and excreting our waste products. It provides an environment for a host of healthful microbes and serves as a first defense against pathogenic ones. These processes require tight homeostatic controls, which are provided by the interactions of a complex mix of epithelial, stromal, neural and immune cells, as well as the resident microflora. This homeostasis can be disrupted by invasive microbes, genetic lesions, and carcinogens, resulting in diseases such Clostridium difficile infection, inflammatory bowel disease (IBD) and cancer. Enormous strides have been made in understanding how this important organ functions in health and disease using everything from cell culture systems to animal models to human tissue samples. This has resulted in better therapies for all of these diseases, but there is still significant room for improvement. In the United States alone, 14,000 people per year die of C. difficile, up to 1.6 million people suffer from IBD, and more than 50,000 people die every year from colon cancer. Because these and other intestinal diseases arise from complex interactions between the different components of the gut ecosystem, we propose that systems approaches that address this complexity in an integrative manner may eventually lead to improved therapeutics that deliver lasting cures. This review will discuss the use of systems biology for studying intestinal diseases in vivo with particular emphasis on mouse models. Additionally, it will focus on established experimental techniques that have been used to drive this systems-level analysis, and emerging techniques that will push this field forward in the future.
Collapse
Affiliation(s)
- Jesse Lyons
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | | | | | | |
Collapse
|
46
|
Janes KA. Single-cell states versus single-cell atlases - two classes of heterogeneity that differ in meaning and method. Curr Opin Biotechnol 2016; 39:120-125. [PMID: 27042975 DOI: 10.1016/j.copbio.2016.03.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2015] [Revised: 03/04/2016] [Accepted: 03/20/2016] [Indexed: 12/30/2022]
Abstract
Recent advances have created new opportunities to dissect cellular heterogeneity at the omics level. The enthusiasm for deep single-cell profiling has obscured a discussion of different types of heterogeneity and the most-appropriate techniques for studying each type. Here, I distinguish heterogeneity in regulation from heterogeneity in lineage. Snapshots of lineage heterogeneity provide a cell atlas that catalogs cellular diversity within complex tissues. Profiles of regulatory heterogeneity seek to interrogate one lineage deeply to capture an ensemble of single-cell states. Single-cell atlases require molecular signatures from many cells at a throughput afforded by mass cytometry-based, microfluidic-based, and microencapsulation-based methods. Single-cell states are more dependent on time, microenvironment, and low-abundance transcripts, emphasizing in situ methods that stress depth of profiling and quantitative accuracy.
Collapse
Affiliation(s)
- Kevin A Janes
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908 USA.
| |
Collapse
|
47
|
Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. Cell Res 2016; 26:304-19. [PMID: 26902283 PMCID: PMC4783472 DOI: 10.1038/cr.2016.23] [Citation(s) in RCA: 403] [Impact Index Per Article: 50.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Revised: 01/05/2016] [Accepted: 01/28/2016] [Indexed: 02/06/2023] Open
Abstract
Single-cell genome, DNA methylome, and transcriptome sequencing methods have been separately developed. However, to accurately analyze the mechanism by which transcriptome, genome and DNA methylome regulate each other, these omic methods need to be performed in the same single cell. Here we demonstrate a single-cell triple omics sequencing technique, scTrio-seq, that can be used to simultaneously analyze the genomic copy-number variations (CNVs), DNA methylome, and transcriptome of an individual mammalian cell. We show that large-scale CNVs cause proportional changes in RNA expression of genes within the gained or lost genomic regions, whereas these CNVs generally do not affect DNA methylation in these regions. Furthermore, we applied scTrio-seq to 25 single cancer cells derived from a human hepatocellular carcinoma tissue sample. We identified two subpopulations within these cells based on CNVs, DNA methylome, or transcriptome of individual cells. Our work offers a new avenue of dissecting the complex contribution of genomic and epigenomic heterogeneities to the transcriptomic heterogeneity within a population of cells.
Collapse
|
48
|
Rao SR, Subbarayan R, Dinesh MG, Arumugam G, Raja STK. Differentiation of human gingival mesenchymal stem cells into neuronal lineages in 3D bioconjugated injectable protein hydrogel construct for the management of neuronal disorder. Exp Mol Med 2016; 48:e209. [PMID: 26869025 PMCID: PMC4892868 DOI: 10.1038/emm.2015.113] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Revised: 09/14/2015] [Accepted: 09/30/2015] [Indexed: 01/05/2023] Open
Abstract
The success of regeneration attempt is based on an ideal combination of stem cells, scaffolding and growth factors. Tissue constructs help to maintain stem cells in a required area for a desired time. There is a need for easily obtainable cells, potentially autologous stem cells and a biologically acceptable scaffold for use in humans in different difficult situations. This study aims to address these issues utilizing a unique combination of stem cells from gingiva and a hydrogel scaffold, based on a natural product for regenerative application. Human gingival mesenchymal stem cells (HGMSCs) were, with due induction, differentiated to neuronal lineages to overcome the problems associated with birth tissue-related stem cells. The differentiation potential of neuronal lineages was confirmed with suitable specific markers. The properties of mesenchymal stem cells in encapsulated form were observed to be similar to free cells. The encapsulated cells (3D) were then subjected to differentiation into neuronal lineages with suitable inducers, and the morphology and gene expression of transient cells were analyzed. HGMSCs was differentiated into neuronal lineages as both free and encapsulated forms without any significant differences. The presence of Nissl bodies and the neurite outgrowth confirm the differentiation. The advantages of this new combination appear to make it a promising tissue construct for translational application.
Collapse
Affiliation(s)
- Suresh Ranga Rao
- Department of Periodontology and Implantology, Faculty of Dental Sciences, Centre for Regenerative Medicine and Stem Cell Research, Sri Ramachandra University, Chennai, India
| | - Rajasekaran Subbarayan
- Centre for Regenerative Medicine and Stem Cell Research, Central Research Facility, Sri Ramachandra University, Chennai, India
| | - Murugan Girija Dinesh
- Centres for Indian Systems of Medicine Quality Assurance and Standardization, Sri Ramachandra University, Chennai, India
| | - Gnanamani Arumugam
- Microbiology Division, Central Leather Research Institute Adyar, Chennai, India
| | | |
Collapse
|
49
|
Epigenomic Reprogramming of Adult Cardiomyocyte-Derived Cardiac Progenitor Cells. Sci Rep 2015; 5:17686. [PMID: 26657817 PMCID: PMC4677315 DOI: 10.1038/srep17686] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Accepted: 10/14/2015] [Indexed: 01/01/2023] Open
Abstract
It has been believed that mammalian adult cardiomyocytes (ACMs) are terminally-differentiated and are unable to proliferate. Recently, using a bi-transgenic ACM fate mapping mouse model and an in vitro culture system, we demonstrated that adult mouse cardiomyocytes were able to dedifferentiate into cardiac progenitor-like cells (CPCs). However, little is known about the molecular basis of their intrinsic cellular plasticity. Here we integrate single-cell transcriptome and whole-genome DNA methylation analyses to unravel the molecular mechanisms underlying the dedifferentiation and cell cycle reentry of mouse ACMs. Compared to parental cardiomyocytes, dedifferentiated mouse cardiomyocyte-derived CPCs (mCPCs) display epigenomic reprogramming with many differentially-methylated regions, both hypermethylated and hypomethylated, across the entire genome. Correlated well with the methylome, our transcriptomic data showed that the genes encoding cardiac structure and function proteins are remarkably down-regulated in mCPCs, while those for cell cycle, proliferation, and stemness are significantly up-regulated. In addition, implantation of mCPCs into infarcted mouse myocardium improves cardiac function with augmented left ventricular ejection fraction. Our study demonstrates that the cellular plasticity of mammalian cardiomyocytes is the result of a well-orchestrated epigenomic reprogramming and a subsequent global transcriptomic alteration.
Collapse
|
50
|
Sparta B, Pargett M, Minguet M, Distor K, Bell G, Albeck JG. Receptor Level Mechanisms Are Required for Epidermal Growth Factor (EGF)-stimulated Extracellular Signal-regulated Kinase (ERK) Activity Pulses. J Biol Chem 2015; 290:24784-92. [PMID: 26304118 DOI: 10.1074/jbc.m115.662247] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2015] [Indexed: 11/06/2022] Open
Abstract
In both physiological and cell culture systems, EGF-stimulated ERK activity occurs in discrete pulses within individual cells. Many feedback loops are present in the EGF receptor (EGFR)-ERK network, but the mechanisms driving pulsatile ERK kinetics are unknown. Here, we find that in cells that respond to EGF with frequency-modulated pulsatile ERK activity, stimulation through a heterologous TrkA receptor system results in non-pulsatile, amplitude-modulated activation of ERK. We further dissect the kinetics of pulse activity using a combination of FRET- and translocation-based reporters and find that EGFR activity is required to maintain ERK activity throughout the 10-20-minute lifetime of pulses. Together, these data indicate that feedbacks operating within the core Ras-Raf-MEK-ERK cascade are insufficient to drive discrete pulses of ERK activity and instead implicate mechanisms acting at the level of EGFR.
Collapse
Affiliation(s)
- Breanne Sparta
- From the Departments of Molecular and Cellular Biology and
| | | | - Marta Minguet
- From the Departments of Molecular and Cellular Biology and
| | - Kevin Distor
- From the Departments of Molecular and Cellular Biology and
| | - George Bell
- Microbiology and Molecular Genetics, University of California, Davis, California 95616
| | - John G Albeck
- From the Departments of Molecular and Cellular Biology and
| |
Collapse
|