Age-Dependent Pancreatic Gene Regulation Reveals Mechanisms Governing Human beta Cell Function
2016; 23 (5): 909-920
Transcription Factor Activity Mapping of a Tissue-Specific in vivo Gene Regulatory Network.
2015; 1 (2): 152-162
Intensive efforts are focused on identifying regulators of human pancreatic islet cell growth and maturation to accelerate development of therapies for diabetes. After birth, islet cell growth and function are dynamically regulated; however, establishing these age-dependent changes in humans has been challenging. Here, we describe a multimodal strategy for isolating pancreatic endocrine and exocrine cells from children and adults to identify age-dependent gene expression and chromatin changes on a genomic scale. These profiles revealed distinct proliferative and functional states of islet α cells or β cells and histone modifications underlying age-dependent gene expression changes. Expression of SIX2 and SIX3, transcription factors without prior known functions in the pancreas and linked to fasting hyperglycemia risk, increased with age specifically in human islet β cells. SIX2 and SIX3 were sufficient to enhance insulin content or secretion in immature β cells. Our work provides a unique resource to study human-specific regulators of islet cell maturation and function.
View details for DOI 10.1016/j.cmet.2016.04.002
View details for Web of Science ID 000375550700021
View details for PubMedID 27133132
An Integrated Cell Purification and Genomics Strategy Reveals Multiple Regulators of Pancreas Development
2014; 10 (10)
Gene Regulatory Networks Governing Pancreas Development
2013; 25 (1): 5-13
A wealth of physical interaction data between transcription factors (TFs) and DNA has been generated, but these interactions often do not have apparent regulatory consequences. Thus, equating physical interaction data with gene regulatory networks (GRNs) is problematic. Here, we comprehensively assay TF activity, rather than binding, to construct a network of gene regulatory interactions in the C. elegans intestine. By manually observing the in vivo tissue-specific knockdown of 921 TFs on a panel of 19 fluorescent transcriptional reporters, we identified a GRN of 411 interactions between 19 promoters and 177 TFs. This GRN shows only modest overlap with physical interactions, indicating that many regulatory interactions are indirect. We applied nested effects modeling to uncover information flow between TFs in the intestine that converges on a small set of physical TF-promoter interactions. We found numerous cell nonautonomous regulatory interactions, illustrating tissue-to-tissue communication. Altogether, our study illuminates the complexity of gene regulation in the context of a living animal.
View details for DOI 10.1016/j.cels.2015.08.003
View details for PubMedID 26430702
Integration of Metabolic and Gene Regulatory Networks Modulates the C. elegans Dietary Response
2013; 153 (1): 253-266
Elucidation of cellular and gene regulatory networks (GRNs) governing organ development will accelerate progress toward tissue replacement. Here, we have compiled reference GRNs underlying pancreas development from data mining that integrates multiple approaches, including mutant analysis, lineage tracing, cell purification, gene expression and enhancer analysis, and biochemical studies of gene regulation. Using established computational tools, we integrated and represented these networks in frameworks that should enhance understanding of the surging output of genomic-scale genetic and epigenetic studies of pancreas development and diseases such as diabetes and pancreatic cancer. We envision similar approaches would be useful for understanding the development of other organs.
View details for DOI 10.1016/j.devcel.2013.03.016
View details for Web of Science ID 000318058400003
Diet-Induced Developmental Acceleration Independent of TOR and Insulin in C. elegans
2013; 153 (1): 240-252
Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus.
View details for DOI 10.1016/j.cell.2013.02.050
View details for Web of Science ID 000316853700021
View details for PubMedID 23540702
Functional modularity of nuclear hormone receptors in a Caenorhabditis elegans metabolic gene regulatory network
MOLECULAR SYSTEMS BIOLOGY
Dietary composition has major effects on physiology. Here, we show that developmental rate, reproduction, and lifespan are altered in C. elegans fed Comamonas DA1877 relative to those fed a standard E. coli OP50 diet. We identify a set of genes that change in expression in response to this diet and use the promoter of one of these (acdh-1) as a dietary sensor. Remarkably, the effects on transcription and development occur even when Comamonas DA1877 is diluted with another diet, suggesting that Comamonas DA1877 generates a signal that is sensed by the nematode. Surprisingly, the developmental effect is independent from TOR and insulin signaling. Rather, Comamonas DA1877 affects cyclic gene expression during molting, likely through the nuclear hormone receptor NHR-23. Altogether, our findings indicate that different bacteria elicit various responses via distinct mechanisms, which has implications for diseases such as obesity and the interactions between the human microbiome and intestinal cells.
View details for DOI 10.1016/j.cell.2013.02.049
View details for Web of Science ID 000316853700020
View details for PubMedID 23540701
Gene-centered regulatory networks
BRIEFINGS IN FUNCTIONAL GENOMICS
2010; 9 (1): 4-12
Gene regulatory networks (GRNs) provide insights into the mechanisms of differential gene expression at a systems level. GRNs that relate to metazoan development have been studied extensively. However, little is still known about the design principles, organization and functionality of GRNs that control physiological processes such as metabolism, homeostasis and responses to environmental cues. In this study, we report the first experimentally mapped metazoan GRN of Caenorhabditis elegans metabolic genes. This network is enriched for nuclear hormone receptors (NHRs). The NHR family has greatly expanded in nematodes: humans have 48 NHRs, but C. elegans has 284, most of which are uncharacterized. We find that the C. elegans metabolic GRN is highly modular and that two GRN modules predominantly consist of NHRs. Network modularity has been proposed to facilitate a rapid response to different cues. As NHRs are metabolic sensors that are poised to respond to ligands, this suggests that C. elegans GRNs evolved to enable rapid and adaptive responses to different cues by a concurrence of NHR family expansion and modular GRN wiring.
View details for DOI 10.1038/msb.2010.23
View details for Web of Science ID 000278575700006
View details for PubMedID 20461074
The C-elegans Snail homolog CES-1 can activate gene expression in vivo and share targets with bHLH transcription factors
NUCLEIC ACIDS RESEARCH
2009; 37 (11): 3689-3698
Differential gene expression plays a critical role in the development and physiology of multicellular organisms. At a 'systems level' (e.g. at the level of a tissue, organ or whole organism), this process can be studied using gene regulatory network (GRN) models that capture physical and regulatory interactions between genes and their regulators. In the past years, significant progress has been made toward the mapping of GRNs using a variety of experimental and computational approaches. Here, we will discuss gene-centered approaches that we employed to characterize GRNs and describe insights that we have obtained into the global design principles of gene regulation in complex metazoan systems.
View details for DOI 10.1093/bfgp/elp049
View details for Web of Science ID 000276191000002
View details for PubMedID 20008400
Matrix and Steiner-triple-system smart pooling assays for high-performance transcription regulatory network mapping
2007; 4 (8): 659-664
Snail-type transcription factors (TFs) are found in numerous metazoan organisms and function in a plethora of cellular and developmental processes including mesoderm and neuronal development, apoptosis and cancer. So far, Snail-type TFs are exclusively known as transcriptional repressors. They repress gene expression by recruiting transcriptional co-repressors and/or by preventing DNA binding of activators from the basic helix-loop-helix (bHLH) family of TFs to CAGGTG E-box sequences. Here we report that the Caenorhabditis elegans Snail-type TF CES-1 can activate transcription in vivo. Moreover, we provide results that suggest that CES-1 can share its binding site with bHLH TFs, in different tissues, rather than only occluding bHLH DNA binding. Together, our data indicate that there are at least two types of CES-1 target genes and, therefore, that the molecular function of Snail-type TFs is more plastic than previously appreciated.
View details for DOI 10.1093/nar/gkp232
View details for Web of Science ID 000267441800026
View details for PubMedID 19372275
Gateway-compatible yeast one-hybrid screens.
2006; 2006 (5)
Yeast one-hybrid (Y1H) assays provide a gene-centered method for the identification of interactions between gene promoters and regulatory transcription factors (TFs). To date, Y1H assays have involved library screens that are relatively expensive and laborious. We present two Y1H strategies that allow immediate prey identification: matrix assays that use an array of 755 individual Caenorhabditis elegans TFs, and smart-pool assays that use TF multiplexing. Both strategies simplify the Y1H pipeline and reduce the cost of protein-DNA interaction identification. We used a Steiner triple system (STS) to create smart pools of 4-25 TFs. Notably, we uniplexed a small number of highly connected TFs to allow efficient assay deconvolution. Both strategies outperform library screens in terms of coverage, confidence and throughput. These versatile strategies can be adapted both to TFs in other systems and, likely, to other biomolecules and assays as well.
View details for DOI 10.1038/NMETH1063
View details for Web of Science ID 000248443900020
View details for PubMedID 17589517
INTRODUCTIONProtein-DNA interactions (PDIs) between transcription factors (TFs) and their target genes form the backbone of transcription regulatory networks. Such PDIs can be identified with either a TF or a gene as a starting point. The Gateway-compatible yeast one-hybrid (Y1H) system provides a high-throughput, gene-centered method for the identification of interactions between a "DNA bait" (e.g., cis-regulatory DNA elements or gene promoters) and "protein preys" (e.g., TFs). The Y1H system is a genetic system to detect PDIs based on selection of reporter gene expression in yeast. DNA baits are fused by Gateway cloning to two reporter genes, HIS3 and lacZ, and the resulting DNA bait::reporter constructs are subsequently integrated into the genome of the host yeast strain. After integration, baits are examined for self-activation (i.e., their ability to drive reporter gene expression in the absence of an exogenous prey protein). Subsequently, each DNA bait is screened for interacting proteins by transforming a library of preys into the corresponding Y1H DNA bait yeast strain. Preys are hybrid proteins composed of a protein from the organism of interest and a heterologous transcription activation domain. When a prey protein binds to the DNA bait, the heterologous activation domain activates reporter gene expression. Thus, physical interactions between both repressors and activators and their DNA targets can be identified.
View details for DOI 10.1101/pdb.prot4590
View details for PubMedID 22485967