No Time to Age: Uncoupling Aging from Chronological Time

Multicellular life evolved from simple unicellular organisms that could replicate indefinitely, being essentially ageless. At this point, life split into two fundamentally different cell types: the immortal germline representing an unbroken lineage of cell division with no intrinsic endpoint and the mortal soma, which ages and dies. In this review, we describe the germline as clock-free and the soma as clock-bound and discuss aging with respect to three DNA-based cellular clocks (telomeric, DNA methylation, and transposable element). The ticking of these clocks corresponds to the stepwise progressive limitation of growth and regeneration of somatic cells that we term somatic restriction. Somatic restriction acts in opposition to strategies that ensure continued germline replication and regeneration. We thus consider the plasticity of aging as a process not fixed to the pace of chronological time but one that can speed up or slow down depending on the rate of intrinsic cellular clocks. We further describe how germline factor reprogramming might be used to slow the rate of aging and potentially reverse it by causing the clocks to tick backward. Therefore, reprogramming may eventually lead to therapeutic strategies to treat degenerative diseases by altering aging itself, the one condition common to us all

Identification of human embryonic progenitor cell targeting peptides using phage display.

Human pluripotent stem (hPS) cells are capable of differentiation into derivatives of all three primary embryonic germ layers and can self-renew indefinitely. They therefore offer a potentially scalable source of replacement cells to treat a variety of degenerative diseases. The ability to reprogram adult cells to induced pluripotent stem (iPS) cells has now enabled the possibility of patient-specific hPS cells as a source of cells for disease modeling, drug discovery, and potentially, cell replacement therapies. While reprogramming technology has dramatically increased the availability of normal and diseased hPS cell lines for basic research, a major bottleneck is the critical unmet need for more efficient methods of deriving well-defined cell populations from hPS cells. Phage display is a powerful method for selecting affinity ligands that could be used for identifying and potentially purifying a variety of cell types derived from hPS cells. However, identification of specific progenitor cell-binding peptides using phage display may be hindered by the large cellular heterogeneity present in differentiating hPS cell populations. We therefore tested the hypothesis that peptides selected for their ability to bind a clonal cell line derived from hPS cells would bind early progenitor cell types emerging from differentiating hPS cells. The human embryonic stem (hES) cell-derived embryonic progenitor cell line, W10, was used and cell-targeting peptides were identified. Competition studies demonstrated specificity of peptide binding to the target cell surface. Efficient peptide targeted cell labeling was accomplished using multivalent peptide-quantum dot complexes as detected by fluorescence microscopy and flow cytometry. The cell-binding peptides were selective for differentiated hPS cells, had little or no binding on pluripotent cells, but preferential binding to certain embryonic progenitor cell lines and early endodermal hPS cell derivatives. Taken together these data suggest that selection of phage display libraries against a clonal progenitor stem cell population can be used to identify progenitor stem cell targeting peptides. The peptides may be useful for monitoring hPS cell differentiation and for the development of cell enrichment procedures to improve the efficiency of directed differentiation toward clinically relevant human cell types

Transcriptome-Wide Analyses of Human Neonatal Articular Cartilage and Human Mesenchymal Stem Cell-Derived Cartilage Provide a New Molecular Target for Evaluating Engineered Cartilage

Cellular differentiation comprises a progressive, multistep program that drives cells to fabricate a tissue with specific and site distinctive structural and functional properties. Cartilage constitutes one of the potential differentiation lineages that mesenchymal stem cells (MSCs) can follow under the guidance of specific bioactive agents. Single agents such as transforming growth factor beta (TGF-β) and bone morphogenetic protein 2 in unchanging culture conditions have been historically used to induce in vitro chondrogenic differentiation of MSCs. Despite the expression of traditional chondrogenic biomarkers such as type II collagen and aggrecan, the resulting tissue represents a transient cartilage rather than an in vivo articular cartilage (AC), differing significantly in structure, chemical composition, cellular phenotypes, and mechanical properties. Moreover, there have been no comprehensive, multicomponent parameters to define high-quality and functional engineered hyaline AC. To address these issues, we have taken an innovative approach based on the molecular interrogation of human neonatal articular cartilage (hNAC), dissected from the knees of 1-month-old cadaveric specimens. Subsequently, we compared hNAC-specific transcriptional regulatory elements and differentially expressed genes with adult human bone marrow (hBM) MSC-derived three-dimensional cartilage structures formed in vitro . Using microarray analysis, the transcriptome of hNAC was found to be globally distinct from the transient, cartilage-like tissue formed by hBM-MSCs in vitro . Specifically, over 500 genes that are highly expressed in hNAC were not expressed at any time point during in vitro human MSC chondrogenesis. The analysis also showed that the differences were less variant during the initial stages (first 7 days) of the in vitro chondrogenic differentiation program. These observations suggest that the endochondral fate of hBM-MSC-derived cartilage may be rerouted at earlier stages of the TGF-β-stimulated chondrogenic differentiation program. Based on these analyses, several key molecular differences (transcription factors and coded cartilage-related proteins) were identified in hNAC that will be useful as molecular inductors and identifiers of the in vivo AC phenotype. Our findings provide a new gold standard of a molecularly defined AC phenotype that will serve as a platform to generate novel approaches for AC tissue engineering

Labeling of embryonic progenitor cell line using peptide targeted Qdot605.

<p>(A) Cell targeting by fluorescent Qdots. Qdot605-ITK-SA were complexed with an excess of chemically synthesized C-terminal biotinylated peptide; unbound peptide was removed by dialysis. W10 progenitor cells were incubated for 16 h at 37°C with 5 nM of Qdot complexes, washed and imaged using a fluorescence microscope. (B) Competition with free peptide or peptide-targeted Qdots. Cells were pre-incubated with 5nM peptide, peptide targeted Qdots, or untargeted Qdots, for 30 min at 4°C, followed by addition of peptide phage (2×10¹⁰pfu) for an additional 1 h at 4°C. After washing, the recovered phage was quantified by titration. The competition is shown as percentage of no-peptide control. Values are from triplicate experiments and shown as mean ± standard deviation. Competition by corresponding free peptide or peptide-Qdot complex at 5 nM was statistically significant. Competition by uncoupled Qdots was not statistically significant (ANOVA with Dunnett’s multiple comparison tests; p values: *: <0.05. **: <0.01 and ***: <0.001) (C) Flow cytometry analysis. Cells were labeled as in (A), dissociated from the tissue culture plate using TrypLE, resuspended in PBS and analyzed in LSRFortessa flow cytometer. 10,000 events were recorded for each sample; cells were excited using the 405 nm laser and fluorescence emission was detected with the 605/12 bandpass filter. Cells labeled with W10-R3-18 peptide-Qdot complexes (green) showed higher mean fluorescent intensity than cells labeled with untargeted Qdots (red) or unlabeled W10 cells (blue).</p

Selectivity of Qdot peptide complexes.

<p>Embryonic progenitor cell lines were labeled with Qdot complexes in their corresponding growth media and analyzed by flow cytometry as in (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058200#pone-0058200-g005" target="_blank">Figure 5C</a>). Percentage of labeled cells was calculated by setting up gates (allowing up to 1%) using the embryonic progenitor cell line labeled with untargeted Qdots and unlabeled cells. 10,000 events were recorded for each sample. Values are from triplicate experiments and shown as mean ± standard deviation.</p

Phage binding competition with free peptide.

<p>Competition of the peptide phage with free peptide was measured using (A) Immunofluorescent detection of bound peptide phages. Chemically synthesized peptides were added to compete with binding of peptide phages to W10 progenitor cells. Cells were pre-incubated with different peptides at 100 µM or without peptide for 30 min at 4°C, followed by peptide phages (2×10¹⁰pfu) for an additional 1 h at 4°C. After washing, the bound peptide phages were detected by immunofluorescence. Peptide sequences are: W10-R2-11-biotin: GWVIDYDYYPMRGGGK(biotin); FITC-W10-R2-11: FITC-GWVIDYDYYPMRGGG and FITC-unrelated: FITC-NHVHRMHATPAY (B) Percentage of input phage recovered from cell lysate. Cells were pre-incubated with peptides at 5 µM or 5 nM, or without peptide for 30 min at 4°C, followed by peptide phages (2×10¹⁰pfu) for an additional 1h at 4°C. After washing, the recovered phage was quantified by titration. The competition is shown as percentage of no-peptide control. Values are from triplicate experiments shown as mean ± standard deviation. Competition by the corresponding free peptide was statistically significant at 5 nM and 5 µM with the exception of W10-R2-21 (only significant at 5 µM). Competition by scrambled or unrelated peptide was not statistically significant. (ANOVA with Dunnett’s multiple comparison tests; p values: *: <0.05. **: <0.01 and ***: <0.001). Peptide sequences are: peptide: X₁₂GGGK(biotin); unrelated: biotin-NHVHRMHATPAY; W10-R2-11-scrambled: DYWDVGPIYRMYGGGG; W10-R2-21-scrambled: LGTMDWFWPYNEGGGG; W10-R3-18-scrambled: VSDPFDNLWTAWGGGK.</p