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.phasor analysis | single cell metabolism T he hallmark of stem cells is their ability to produce a new stem cell by self-renewing, as they generate daughter cells that are committed to differentiation and form specialized tissues (1). The modulation of the balance between self-renewing divisions and differentiation is a central mechanism for stem cells during embryo development, adult tissue regeneration, and homeostasis. Stem-cell differentiation is a complex process mediated both by intrinsic molecular mechanisms and extrinsic signaling. Intrinsic cell polarity, subcellular localization mechanism, asymmetric centrosome and spindles, as well as cell-cycle regulators can establish self-renewing asymmetry during stem-cell division (2, 3). The influence of external chemical and physical stimuli, such as molecular gradients, extracellular matrix remodeling, and niche signaling is crucial for stem-cell plasticity and tissue development (4-6). Extrinsic signals can be propagated through intracellular signal-transduction pathways that converge to genetic networks that control pluripotency. Many different signaling and transcriptional pathways, which are important for development and cell-cycle regulation, converge on regulation of the redox state of stem cells (5,7,8). In turn, histone posttranscriptional modifications and epigenetic mechanisms, such as phosphorylation, acetylation, and methylation, sense cellular metabolism and the variation of metabolites levels (9). Hence, redox balance plays an important role in the maintenance and modulation of stem cell self-renewal and differentiation (10-12).In stem-cell research there is a high demand for noninvasive techniques to investigate self-renewal and differentiation. Methods, such as immunohistochemistry, metabolic assays, and PCR are currently...

Controls of stem cell maintenance and early differentiation are known in several systems. However, the progression from stem cell self-renewal to overt signs of early differentiation is a poorly understood but important problem in stem cell biology. The Caenorhabditis elegans germ line provides a genetically defined model for studying that progression. In this system, a single-celled mesenchymal niche, the distal tip cell (DTC), employs GLP-1/Notch signaling and an RNA regulatory network to balance self-renewal and early differentiation within the "mitotic region," which continuously self-renews while generating new gametes. Here, we investigate germ cells in the mitotic region for their capacity to differentiate and their state of maturation. Two distinct pools emerge. The "distal pool" is maintained by the DTC in an essentially uniform and immature or "stem cell-like" state; the "proximal pool," by contrast, contains cells that are maturing toward early differentiation and are likely transit-amplifying cells. A rough estimate of pool sizes is 30-70 germ cells in the distal immature pool and ≈150 in the proximal transit-amplifying pool. We present a simple model for how the network underlying the switch between self-renewal and early differentiation may be acting in these two pools. According to our model, the self-renewal mode of the network maintains the distal pool in an immature state, whereas the transition between self-renewal and early differentiation modes of the network underlies the graded maturation of germ cells in the proximal pool. We discuss implications of this model for controls of stem cells more broadly.stem cell niche | self-renewal | transit amplification | network dynamics | developmental timing

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