Transgenerational inheritance of acquired epigenetic signatures at CpG islands in mice.

Transgenerational epigenetic inheritance in mammals remains a debated subject. Here, we demonstrate that DNA methylation of promoter-associated CpG islands (CGIs) can be transmitted from parents to their offspring in mice. We generated DNA methylation-edited mouse embryonic stem cells (ESCs), in which CGIs of two metabolism-related genes, the Ankyrin repeat domain 26 and the low-density lipoprotein receptor, were specifically methylated and silenced. DNA methylation-edited mice generated by microinjection of the methylated ESCs exhibited abnormal metabolic phenotypes. Acquired methylation of the targeted CGI and the phenotypic traits were maintained and transmitted across multiple generations. The heritable CGI methylation was subjected to reprogramming in parental PGCs and subsequently reestablished in the next generation at post-implantation stages. These observations provide a concrete step toward demonstrating transgenerational epigenetic inheritance in mammals, which may have implications in our understanding of evolutionary biology as well as the etiology, diagnosis, and prevention of non-genetically inherited human diseases.

Tuft Cells Inhibit Pancreatic Tumorigenesis in Mice by Producing Prostaglandin D2.

BACKGROUND & AIMS: Development of pancreatic ductal adenocarcinoma (PDA) involves acinar to ductal metaplasia and genesis of tuft cells. It has been a challenge to study these rare cells because of the lack of animal models. We investigated the role of tuft cells in pancreatic tumorigenesis. METHODS: We performed studies with LSL-KrasG12D/+;Ptf1aCre/+ mice (KC; develop pancreatic tumors), KC mice crossed with mice with pancreatic disruption of Pou2f3 (KPouC mice; do not develop tuft cells), or mice with pancreatic disruption of the hematopoietic prostaglandin D synthase gene (Hpgds, KHC mice) and wild-type mice. Mice were allowed to age or were given caerulein to induce pancreatitis; pancreata were collected and analyzed by histology, immunohistochemistry, RNA sequencing, ultrastructural microscopy, and metabolic profiling. We performed laser-capture dissection and RNA-sequencing analysis of pancreatic tissues from 26 patients with pancreatic intraepithelial neoplasia (PanIN), 19 patients with intraductal papillary mucinous neoplasms (IPMNs), and 197 patients with PDA. RESULTS: Pancreata from KC mice had increased formation of tuft cells and higher levels of prostaglandin D2 than wild-type mice. Pancreas-specific deletion of POU2F3 in KC mice (KPouC mice) resulted in a loss of tuft cells and accelerated tumorigenesis. KPouC mice had increased fibrosis and activation of immune cells after administration of caerulein. Pancreata from KPouC and KHC mice had significantly lower levels of prostaglandin D2, compared with KC mice, and significantly increased numbers of PanINs and PDAs. KPouC and KHC mice had increased pancreatic injury after administration of caerulein, significantly less normal tissue, more extracellular matrix deposition, and higher PanIN grade than KC mice. Human PanIN and intraductal papillary mucinous neoplasm had gene expression signatures associated with tuft cells and increased expression of Hpgds messenger RNA compared with PDA. CONCLUSIONS: In mice with KRAS-induced pancreatic tumorigenesis, loss of tuft cells accelerates tumorigenesis and increases the severity of caerulein-induced pancreatic injury, via decreased production of prostaglandin D2. These data are consistent with the hypothesis that tuft cells are a metaplasia-induced tumor attenuating cell type.

In vivo reprogramming of wound-resident cells generates skin epithelial tissue.

Large cutaneous ulcers are, in severe cases, life threatening1,2. As the global population ages, non-healing ulcers are becoming increasingly common1,2. Treatment currently requires the transplantation of pre-existing epithelial components, such as skin grafts, or therapy using cultured cells2. Here we develop alternative supplies of epidermal coverage for the treatment of these kinds of wounds. We generated expandable epithelial tissues using in vivo reprogramming of wound-resident mesenchymal cells. Transduction of four transcription factors that specify the skin-cell lineage enabled efficient and rapid de novo epithelialization from the surface of cutaneous ulcers in mice. Our findings may provide a new therapeutic avenue for treating skin wounds and could be extended to other disease situations in which tissue homeostasis and repair are impaired.

The influence of transcript assembly on the proteogenomics discovery of microproteins.

Proteogenomics methods have identified many non-annotated protein-coding genes in the human genome. Many of the newly discovered protein-coding genes encode peptides and small proteins, referred to collectively as microproteins. Microproteins are produced through ribosome translation of small open reading frames (smORFs). The discovery of many smORFs reveals a blind spot in traditional gene-finding algorithms for these genes. Biological studies have found roles for microproteins in cell biology and physiology, and the potential that there exists additional bioactive microproteins drives the interest in detection and discovery of these molecules. A key step in any proteogenomics workflow is the assembly of RNA-Seq data into likely mRNA transcripts that are then used to create a searchable protein database. Here we demonstrate that specific features of the assembled transcriptome impact microprotein detection by shotgun proteomics. By tailoring transcript assembly for downstream mass spectrometry searching, we show that we can detect more than double the number of high-quality microprotein candidates and introduce a novel open-source mRNA assembler for proteogenomics (MAPS) that incorporates all of these features. By integrating our specialized assembler, MAPS, and a popular generalized assembler into our proteogenomics pipeline, we detect 45 novel human microproteins from a high quality proteogenomics dataset of a human cell line. We then characterize the features of the novel microproteins, identifying two classes of microproteins. Our work highlights the importance of specialized transcriptome assembly upstream of proteomics validation when searching for short and potentially rare and poorly conserved proteins.

Deriving Quantitative Cell Biological Information from Dye-Dilution Lymphocyte Proliferation Experiments.

The dye-dilution assay is a powerful tool to study lymphocyte expansion dynamics. By combining time course dye-dilution experiments with computational analysis, quantitative information about cell biological parameters, such as percentage of cells dividing, time of division, and time of death, can be produced. Here, we describe the method to generate quantitative cell biological insights from dye-dilution experiments. We describe experimental methods for generating dye-dilution data with murine lymphocytes and then describe the computational data analysis workflow using a recently developed software package called FlowMax. The aim is to interpret the dye-dilution data quantitatively and objectively, such that cell biological parameters can be reported with an appropriate measure of confidence, which in turn depends on the quality and quantity of available data.

Integration of CpG-free DNA induces de novo methylation of CpG islands in pluripotent stem cells.

CpG islands (CGIs) are primarily promoter-associated genomic regions and are mostly unmethylated within highly methylated mammalian genomes. The mechanisms by which CGIs are protected from de novo methylation remain elusive. Here we show that insertion of CpG-free DNA into targeted CGIs induces de novo methylation of the entire CGI in human pluripotent stem cells (PSCs). The methylation status is stably maintained even after CpG-free DNA removal, extensive passaging, and differentiation. By targeting the DNA mismatch repair gene MLH1 CGI, we could generate a PSC model of a cancer-related epimutation. Furthermore, we successfully corrected aberrant imprinting in induced PSCs derived from an Angelman syndrome patient. Our results provide insights into how CpG-free DNA induces de novo CGI methylation and broaden the application of targeted epigenome editing for a better understanding of human development and disease.

AMPK governs lineage specification through Tfeb-dependent regulation of lysosomes.

Faithful execution of developmental programs relies on the acquisition of unique cell identities from pluripotent progenitors, a process governed by combinatorial inputs from numerous signaling cascades that ultimately dictate lineage-specific transcriptional outputs. Despite growing evidence that metabolism is integrated with many molecular networks, how pathways that control energy homeostasis may affect cell fate decisions is largely unknown. Here, we show that AMP-activated protein kinase (AMPK), a central metabolic regulator, plays critical roles in lineage specification. Although AMPK-deficient embryonic stem cells (ESCs) were normal in the pluripotent state, these cells displayed profound defects upon differentiation, failing to generate chimeric embryos and preferentially adopting an ectodermal fate at the expense of the endoderm during embryoid body (EB) formation. AMPK(-/-) EBs exhibited reduced levels of Tfeb, a master transcriptional regulator of lysosomes, leading to diminished endolysosomal function. Remarkably, genetic loss of Tfeb also yielded endodermal defects, while AMPK-null ESCs overexpressing this transcription factor normalized their differential potential, revealing an intimate connection between Tfeb/lysosomes and germ layer specification. The compromised endolysosomal system resulting from AMPK or Tfeb inactivation blunted Wnt signaling, while up-regulating this pathway restored expression of endodermal markers. Collectively, these results uncover the AMPK pathway as a novel regulator of cell fate determination during differentiation.

Effects of extrinsic mortality on the evolution of aging: a stochastic modeling approach.

The evolutionary theories of aging are useful for gaining insights into the complex mechanisms underlying senescence. Classical theories argue that high levels of extrinsic mortality should select for the evolution of shorter lifespans and earlier peak fertility. Non-classical theories, in contrast, posit that an increase in extrinsic mortality could select for the evolution of longer lifespans. Although numerous studies support the classical paradigm, recent data challenge classical predictions, finding that high extrinsic mortality can select for the evolution of longer lifespans. To further elucidate the role of extrinsic mortality in the evolution of aging, we implemented a stochastic, agent-based, computational model. We used a simulated annealing optimization approach to predict which model parameters predispose populations to evolve longer or shorter lifespans in response to increased levels of predation. We report that longer lifespans evolved in the presence of rising predation if the cost of mating is relatively high and if energy is available in excess. Conversely, we found that dramatically shorter lifespans evolved when mating costs were relatively low and food was relatively scarce. We also analyzed the effects of increased predation on various parameters related to density dependence and energy allocation. Longer and shorter lifespans were accompanied by increased and decreased investments of energy into somatic maintenance, respectively. Similarly, earlier and later maturation ages were accompanied by increased and decreased energetic investments into early fecundity, respectively. Higher predation significantly decreased the total population size, enlarged the shared resource pool, and redistributed energy reserves for mature individuals. These results both corroborate and refine classical predictions, demonstrating a population-level trade-off between longevity and fecundity and identifying conditions that produce both classical and non-classical lifespan effects.

FlowMax: A Computational Tool for Maximum Likelihood Deconvolution of CFSE Time Courses.

The immune response is a concerted dynamic multi-cellular process. Upon infection, the dynamics of lymphocyte populations are an aggregate of molecular processes that determine the activation, division, and longevity of individual cells. The timing of these single-cell processes is remarkably widely distributed with some cells undergoing their third division while others undergo their first. High cell-to-cell variability and technical noise pose challenges for interpreting popular dye-dilution experiments objectively. It remains an unresolved challenge to avoid under- or over-interpretation of such data when phenotyping gene-targeted mouse models or patient samples. Here we develop and characterize a computational methodology to parameterize a cell population model in the context of noisy dye-dilution data. To enable objective interpretation of model fits, our method estimates fit sensitivity and redundancy by stochastically sampling the solution landscape, calculating parameter sensitivities, and clustering to determine the maximum-likelihood solution ranges. Our methodology accounts for both technical and biological variability by using a cell fluorescence model as an adaptor during population model fitting, resulting in improved fit accuracy without the need for ad hoc objective functions. We have incorporated our methodology into an integrated phenotyping tool, FlowMax, and used it to analyze B cells from two NFκB knockout mice with distinct phenotypes; we not only confirm previously published findings at a fraction of the expended effort and cost, but reveal a novel phenotype of nfkb1/p105/50 in limiting the proliferative capacity of B cells following B-cell receptor stimulation. In addition to complementing experimental work, FlowMax is suitable for high throughput analysis of dye dilution studies within clinical and pharmacological screens with objective and quantitative conclusions.