More than just a pool.

An intricate stem cell niche boundary formed by finger-like extensions generates asymmetry in stem cell divisions.

Quantification of in vivo progenitor mutation accrual with ultra-low error rate and minimal input DNA using SIP-HAVA-seq.

Assaying in vivo accrual of DNA damage and DNA mutations by stem cells and pinpointing sources of damage and mutations would further our understanding of aging and carcinogenesis. Two main hurdles must be overcome. First, in vivo mutation rates are orders of magnitude lower than raw sequencing error rates. Second, stem cells are vastly outnumbered by differentiated cells, which have a higher mutation rate-quantification of stem cell DNA damage and DNA mutations is thus best performed from small, well-defined cell populations. Here we report a mutation detection technique, based on the "duplex sequencing" principle, with an error rate below ∼10-10 and that can start from as little as 50 pg DNA. We validate this technique, which we call SIP-HAVA-seq, by characterizing Caenorhabditis elegans germline stem cell mutation accrual and asking how mating affects that accrual. We find that a moderate mating-induced increase in cell cycling correlates with a dramatic increase in accrual of mutations. Intriguingly, these mutations consist chiefly of deletions in nonexpressed genes. This contrasts with results derived from mutation accumulation lines and suggests that mutation spectrum and genome distribution change with replicative age, chronological age, cell differentiation state, and/or overall worm physiological state. We also identify single-stranded gaps as plausible deletion precursors, providing a starting point to identify the molecular mechanisms of mutagenesis that are most active. SIP-HAVA-seq provides the first direct, genome-wide measurements of in vivo mutation accrual in stem cells and will enable further characterization of underlying mechanisms and their dependence on age and cell state.

Intermittent Stem Cell Cycling Balances Self-Renewal and Senescence of the C. elegans Germ Line.

Self-renewing organs often experience a decline in function in the course of aging. It is unclear whether chronological age or external factors control this decline, or whether it is driven by stem cell self-renewal-for example, because cycling cells exhaust their replicative capacity and become senescent. Here we assay the relationship between stem cell cycling and senescence in the Caenorhabditis elegans reproductive system, defining this senescence as the progressive decline in "reproductive capacity," i.e. in the number of progeny that can be produced until cessation of reproduction. We show that stem cell cycling diminishes remaining reproductive capacity, at least in part through the DNA damage response. Paradoxically, gonads kept under conditions that preclude reproduction keep cycling and producing cells that undergo apoptosis or are laid as unfertilized gametes, thus squandering reproductive capacity. We show that continued activity is in fact beneficial inasmuch as gonads that are active when reproduction is initiated have more sustained early progeny production. Intriguingly, continued cycling is intermittent-gonads switch between active and dormant states-and in all likelihood stochastic. Other organs face tradeoffs whereby stem cell cycling has the beneficial effect of providing freshly-differentiated cells and the detrimental effect of increasing the likelihood of cancer or senescence; stochastic stem cell cycling may allow for a subset of cells to preserve proliferative potential in old age, which may implement a strategy to deal with uncertainty as to the total amount of proliferation to be undergone over an organism's lifespan.

Semi-permeable Diffusion Barriers Enhance Patterning Robustness in the C. elegans Germline.

Positional information derived from local morphogen concentration plays an important role in patterning. A key question is how morphogen diffusion and gene expression regulation shape positional information into an appropriate profile with suitably low noise. We address this question using a model system--the C. elegans germline--whose regulatory network has been well characterized genetically but whose spatiotemporal dynamics are poorly understood. We show that diffusion within the germline syncytium is a critical control of stem cell differentiation and that semi-permeable diffusion barriers present at key locations make it possible--in combination with a feedback loop in the germline regulatory network--for mitotic zone size to be robust against spatial noise in Notch signaling. Spatial averaging within compartments defined by diffusion barriers is an advantageous patterning strategy, which attenuates noise while still allowing for sharp transitions between compartments. This strategy could apply to other organs.

Analysis of in vivo single cell behavior by high throughput, human-in-the-loop segmentation of three-dimensional images.

BACKGROUND: Analysis of single cells in their native environment is a powerful method to address key questions in developmental systems biology. Confocal microscopy imaging of intact tissues, followed by automatic image segmentation, provides a means to conduct cytometric studies while at the same time preserving crucial information about the spatial organization of the tissue and morphological features of the cells. This technique is rapidly evolving but is still not in widespread use among research groups that do not specialize in technique development, perhaps in part for lack of tools that automate repetitive tasks while allowing experts to make the best use of their time in injecting their domain-specific knowledge. RESULTS: Here we focus on a well-established stem cell model system, the C. elegans gonad, as well as on two other model systems widely used to study cell fate specification and morphogenesis: the pre-implantation mouse embryo and the developing mouse olfactory epithelium. We report a pipeline that integrates machine-learning-based cell detection, fast human-in-the-loop curation of these detections, and running of active contours seeded from detections to segment cells. The procedure can be bootstrapped by a small number of manual detections, and outperforms alternative pieces of software we benchmarked on C. elegans gonad datasets. Using cell segmentations to quantify fluorescence contents, we report previously-uncharacterized cell behaviors in the model systems we used. We further show how cell morphological features can be used to identify cell cycle phase; this provides a basis for future tools that will streamline cell cycle experiments by minimizing the need for exogenous cell cycle phase labels. CONCLUSIONS: High-throughput 3D segmentation makes it possible to extract rich information from images that are routinely acquired by biologists, and provides insights - in particular with respect to the cell cycle - that would be difficult to derive otherwise.

Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation.

BACKGROUND: Stem cells are thought to play a critical role in minimizing the accumulation of mutations, but it is not clear which strategies they follow to fulfill that performance objective. Slow cycling of stem cells provides a simple strategy that can minimize cell pedigree depth and thereby minimize the accumulation of replication-dependent mutations. Although the power of this strategy was recognized early on, a quantitative assessment of whether and how it is employed by biological systems is missing. RESULTS: Here we address this problem using a simple self-renewing organ - the C. elegans gonad - whose overall organization is shared with many self-renewing organs. Computational simulations of mutation accumulation characterize a tradeoff between fast development and low mutation accumulation, and show that slow-cycling stem cells allow for an advantageous compromise to be reached. This compromise is such that worm germ-line stem cells should cycle more slowly than their differentiating counterparts, but only by a modest amount. Experimental measurements of cell cycle lengths derived using a new, quantitative technique are consistent with these predictions. CONCLUSIONS: Our findings shed light both on design principles that underlie the role of stem cells in delaying aging and on evolutionary forces that shape stem-cell gene regulatory networks.

Live imaging reveals active infiltration of mitotic zone by its stem cell niche.

Stem cells niches are increasingly recognized as dynamic environments that play a key role in transducing signals that allow an organism to exert control on its stem cells. Live imaging of stem cell niches in their in vivo setting is thus of high interest to dissect stem cell controls. Here we report a new microfluidic design that is highly amenable to dissemination in biology laboratories that have no microfluidics expertise. This design has allowed us to perform the first time lapse imaging of the C. elegans germline stem cell niche. Our results show that this niche is strikingly dynamic, and that morphological changes that take place during development are the result of a highly active process. These results lay the foundation for future studies to dissect molecular mechanisms by which stem cell niche morphology is modulated, and by which niche morphology controls stem cell behavior.

Phasor approach to fluorescence lifetime microscopy distinguishes different metabolic states of germ cells in a live tissue.

We describe a label-free imaging method to monitor stem-cell metabolism that discriminates different states of stem cells as they differentiate in living tissues. In this method we use intrinsic fluorescence biomarkers and the phasor approach to fluorescence lifetime imaging microscopy in conjunction with image segmentation, which we use to introduce the concept of the cell phasor. In live tissues we are able to identify intrinsic fluorophores, such as collagen, retinol, retinoic acid, porphyrin, flavins, and free and bound NADH. We have exploited the cell phasor approach to detect a trend in metabolite concentrations along the main axis of the Caenorhabditis elegans germ line. This trend is consistent with known changes in metabolic states during differentiation. The cell phasor approach to lifetime imaging provides a label-free, fit-free, and sensitive method to identify different metabolic states of cells during differentiation, to sense small changes in the redox state of cells, and may identify symmetric and asymmetric divisions and predict cell fate. Our method is a promising noninvasive optical tool for monitoring metabolic pathways during differentiation or disease progression, and for cell sorting in unlabeled tissues.