@article {69718, title = {Design and Generation of TEMPO Reagents for Sequential Labeling and Manipulation of Vertebrate Cell Lineages.}, journal = {Methods Mol Biol}, volume = {2886}, year = {2025}, month = {01/2025}, pages = {327-353}, abstract = {

During development, cells undergo a sequence of specification events to form functional tissues and organs. To investigate complex tissue development, it is crucial to visualize how cell lineages emerge and to be able to manipulate regulatory factors with temporal control. We recently developed TEMPO (Temporal Encoding and Manipulation in a Predefined Order), a genetic tool to label with different colors and genetically manipulate consecutive cell generations in vertebrates. TEMPO relies on CRISPR to activate a cascade of fluorescent proteins which can be imaged in vivo. Here, we explain the steps to design, generate, and express TEMPO constructs in zebrafish and mice.

}, keywords = {Animals, Cell Lineage, CRISPR-Cas Systems, Luminescent Proteins, Mice, Staining and Labeling, Zebrafish}, issn = {1940-6029}, doi = {10.1007/978-1-0716-4310-5_17}, author = {Espinosa-Medina, Isabel} } @article {69694, title = {Spatial single-cell Organellomics reveals nutrient dependent hepatocyte heterogeneity and predicts pathophysiological status in vivo}, journal = {bioRxiv}, year = {2024}, month = {2024 Dec 08}, abstract = {

Cellular heterogeneity within complex tissues and organs is essential to coordinate biological processes across biological scales. The effect of local cues and tissue microenvironments on cell heterogeneity has been mainly studied at the transcriptional level. However, it is within the subcellular scale - the organelles - that lays the machinery to conduct most metabolic reactions and maintain cells alive, ensuring proper tissue function. How changes in subcellular organization under different microenvironments define the functional diversity of cells within organs remains largely unexplored. Here we determine how organelles adapt to different microenvironments using the mouse liver as model system, in combination with computational approaches and machine-learning. To understand organelle adaptation in response to changing nutritional conditions, we analyzed 3D fluorescent microscopy volumes of liver samples labeled to simultaneously visualize mitochondria, peroxisomes, and lipid droplets from mice subjected to different diets: a control diet, a high-fat diet, and a control diet plus fasting. A Cellpose based pipeline was implemented for cell and organelle segmentation, which allowed us to measure 100 different organelle metrics and helped us define subcellular architectures in liver samples at the single cell level. Our results showed that hepatocytes display distinct subcellular architectures within different regions of the liver-close to the central vein, in the middle region, and near the portal vein- and across the various diet groups, thus reflecting their adaptation to specific nutritional inputs. Principal component analysis and clustering of hepatocytes based on organelle signatures revealed 12 different hepatocyte categories within the different experimental groups, highlighting a reduction in hepatocyte heterogeneity under nutritional perturbations. Finally, using single cell organelle signatures exclusively, we generated machine learning models that were able to predict with high accuracy different hepatocyte categories, diet groups, and the stages of MASLD. Our results demonstrate how organelle signatures can be used as hallmarks to define hepatocyte heterogeneity and their adaptation to different nutritional conditions. In the future, our strategy, which combines subcellular resolution imaging of liver volumes and machine learning, could help establish protocols to better define and predict liver disease progression.

}, doi = {10.1101/2024.12.06.627285}, url = {https://doi.org/10.1101/2024.12.06.627285}, author = {Hillsley, Alexander and Adhikari, Raghabendra and Johnson, Alana Dowdell and Espinosa-Medina, Isabel and Funke, Jan and Feliciano, Daniel} } @article {68606, title = {TEMPO enables sequential genetic labeling and manipulation of vertebrate cell lineages.}, journal = {Neuron}, volume = {111}, year = {2023}, month = {2023 Feb 01}, pages = {345-361.e10}, abstract = {

During development, regulatory factors appear in a precise order to determine cell fates over time. Consequently, to investigate complex tissue development, it is necessary to visualize and manipulate cell lineages with temporal control. Current strategies for tracing vertebrate cell lineages lack genetic access to sequentially produced cells. Here, we present TEMPO (Temporal Encoding and Manipulation in a Predefined Order), an imaging-readable genetic tool allowing differential labeling and manipulation of consecutive cell generations in vertebrates. TEMPO is based on CRISPR and powered by a cascade of gRNAs that drive orderly activation and inactivation of reporters and/or effectors. Using TEMPO to visualize zebrafish and mouse neurogenesis, we recapitulated birth-order-dependent neuronal fates. Temporally manipulating cell-cycle regulators in mouse cortex progenitors altered the proportion and distribution of neurons and glia, revealing the effects of temporal gene perturbation on serial cell fates. Thus, TEMPO enables sequential manipulation of molecular factors, crucial to study cell-type specification.

}, keywords = {Animals, Cell Differentiation, Cell Lineage, Gene Expression Regulation, Developmental, Mice, Neurogenesis, Neuroglia, Neurons, Zebrafish}, issn = {1097-4199}, doi = {10.1016/j.neuron.2022.10.035}, author = {Espinosa-Medina, Isabel and Feliciano, Daniel and Belmonte-Mateos, Carla and Linda Miyares, Rosa and Garcia-Marques, Jorge and Foster, Benjamin and Lindo, Sarah and Pujades, Cristina and Koyama, Minoru and Lee, Tzumin} } @article {68518, title = {TEMPO enables sequential genetic labeling and manipulation of vertebrate cell lineages.}, journal = {Neuron}, year = {2022}, month = {2022 Nov 18}, abstract = {

During development, regulatory factors appear in a precise order to determine cell fates over time. Consequently, to investigate complex tissue development, it is necessary to visualize and manipulate cell lineages with temporal control. Current strategies for tracing vertebrate cell lineages lack genetic access to sequentially produced cells. Here, we present TEMPO (Temporal Encoding and Manipulation in a Predefined Order), an imaging-readable genetic tool allowing differential labeling and manipulation of consecutive cell generations in vertebrates. TEMPO is based on CRISPR and powered by a cascade of gRNAs that drive orderly activation and inactivation of reporters and/or effectors. Using TEMPO to visualize zebrafish and mouse neurogenesis, we recapitulated birth-order-dependent neuronal fates. Temporally manipulating cell-cycle regulators in mouse cortex progenitors altered the proportion and distribution of neurons and glia, revealing the effects of temporal gene perturbation on serial cell fates. Thus, TEMPO enables sequential manipulation of molecular factors, crucial to study cell-type specification.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2022.10.035}, author = {Espinosa-Medina, Isabel and Feliciano, Daniel and Belmonte-Mateos, Carla and Linda Miyares, Rosa and Garcia-Marques, Jorge and Foster, Benjamin and Lindo, Sarah and Pujades, Cristina and Koyama, Minoru and Lee, Tzumin} } @article {68342, title = {TEMPO: A system to sequentially label and genetically manipulate vertebrate cell lineages}, journal = {bioRxiv}, year = {2021}, month = {10/2021}, abstract = {

During development, regulatory factors appear in a precise order to determine cell fates over time. To investigate complex tissue development, one should not just label cell lineages but further visualize and manipulate cells with temporal control. Current strategies for tracing vertebrate cell lineages lack genetic access to sequentially produced cells. Here we present TEMPO (Temporal Encoding and Manipulation in a Predefined Order), an imaging-readable genetic tool allowing differential labelling and manipulation of consecutive cell generations in vertebrates. TEMPO is based on CRISPR and powered by a cascade of gRNAs that drive orderly activation/inactivation of reporters/effectors. Using TEMPO to visualize zebrafish and mouse neurogenesis, we recapitulated birth-order-dependent neuronal fates. Temporally manipulating cell-cycle regulators in mouse cortex progenitors altered the proportion and distribution of neurons and glia, revealing the effects of temporal gene perturbation on serial cell fates. Thus, TEMPO enables sequential manipulation of molecular factors, crucial to study cell-type specification.One-Sentence Summary Gaining sequential genetic access to vertebrate cell lineages.Competing Interest StatementThe authors have declared no competing interest.

}, doi = {10.1101/2021.10.27.466134}, url = {https://www.biorxiv.org/content/early/2021/10/28/2021.10.27.466134}, author = {Espinosa-Medina, Isabel and Feliciano, Daniel and Belmonte-Mateos, Carla and Garcia-Marques, Jorge and Foster, Benjamin and Miyares, Rosa Linda and Pujades, Cristina and Koyama, Minoru and Lee, Tzumin} } @article {68341, title = {Dense reconstruction of elongated cell lineages: overcoming suboptimum lineage encoding and sparse cell sampling}, journal = {bioRxiv}, year = {2020}, month = {07/2020}, abstract = {

Acquiring both lineage and cell-type information during brain development could elucidate transcriptional programs underling neuronal diversification. This is now feasible with single-cell RNA-seq combined with CRISPR-based lineage tracing, which generates genetic barcodes with cumulative CRISPR edits. This technique has not yet been optimized to deliver high-resolution lineage reconstruction of protracted lineages. Drosophila neuronal lineages are an ideal model to consider, as multiple lineages have been morphologically mapped at single-cell resolution. Here we find the parameter ranges required to encode a representative neuronal lineage emanating from 100 stem cell divisions. We derive the optimum editing rate to be inversely proportional to lineage depth, enabling encoding to persist across lineage progression. Further, we experimentally determine the editing rates of a Cas9-deaminase in cycling neural stem cells, finding near ideal rates to map elongated Drosophila neuronal lineages. Moreover, we propose and evaluate strategies to separate recurring cell-types for lineage reconstruction. Finally, we present a simple method to combine multiple experiments, which permits dense reconstruction of protracted cell lineages despite suboptimum lineage encoding and sparse cell sampling.Competing Interest StatementThe authors have declared no competing interest.

}, doi = {10.1101/2020.07.27.223321}, url = {https://www.biorxiv.org/content/early/2020/07/29/2020.07.27.223321}, author = {Sugino, Ken and Miyares, Rosa L. and Espinosa-Medina, Isabel and Chen, Hui-Min and Potter, Christopher J and Lee, Tzumin} } @article {68340, title = {Theoretical modeling on CRISPR-coded cell lineages: efficient encoding and optimal reconstruction}, journal = {bioRxiv}, year = {2019}, month = {04/2019}, abstract = {

Delineating cell lineages is a prerequisite for interrogating the genesis of cell types. CRISPR/Cas9 can edit genomic sequence during development which enables to trace cell lineages. Recent studies have demonstrated the feasibility of this idea. However, the optimality of the encoding or reconstruction processes has not been adequately addressed. Here, we surveyed a multitude of reconstruction algorithms and found hierarchical clustering, with a metric based on the number of shared Cas9 edits, delivers the best reconstruction. However, the trackable depth is ultimately limited by the number of available coding units that typically decrease exponentially across cell generations. To overcome this limit, we established two strategies that better sustain the coding capacity. One involves controlling target availability via use of parallel gRNA cascades, whereas the other strategy exploits adjustable Cas9/gRNA editing rates. In summary, we provide a theoretical basis in understanding, designing, and analyzing robust CRISPR barcodes for dense reconstruction of protracted cell lineages.

}, doi = {10.1101/538488}, url = {https://www.biorxiv.org/content/early/2019/04/14/538488}, author = {Sugino, Ken and Garcia-Marques, Jorge and Espinosa-Medina, Isabel and Lee, Tzumin} } @article {68339, title = {The "sacral parasympathetic": ontogeny and anatomy of a myth.}, journal = {Clin Auton Res}, volume = {28}, year = {2018}, month = {2018 02}, pages = {13-21}, abstract = {

We recently defined genetic traits that distinguish sympathetic from parasympathetic neurons, both preganglionic and ganglionic (Espinosa-Medina et al., Science 354:893-897, 2016). By this set of criteria, we found that the sacral autonomic outflow is sympathetic, not parasympathetic as has been thought for more than a century. Proposing such a belated shift in perspective begs the question why the new criterion (cell types defined by their genetic make-up and dependencies) should be favored over the anatomical, physiological and pharmacological considerations of long ago that inspired the "parasympathetic" classification. After a brief reminder of the former, we expound the weaknesses of the latter and argue that the novel genetic definition helps integrating neglected anatomical and physiological observations and clearing the path for future research.

}, keywords = {Ganglia, Parasympathetic, Ganglia, Sympathetic, Humans, Sacrococcygeal Region, Spinal Cord}, issn = {1619-1560}, doi = {10.1007/s10286-017-0478-7}, author = {Espinosa-Medina, Isabel and Saha, Orthis and Boismoreau, Franck and Brunet, Jean-Fran{\c c}ois} }