A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages.

Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of early molecular choices orchestrating the emergence of neural crest heterogeneity from the embryonic ectoderm remains elusive. Gene-regulatory-networks (GRN) govern early development and cell specification toward definitive neural crest. Here, we combine ultradense single-cell transcriptomes with machine-learning and large-scale transcriptomic and epigenomic experimental validation of selected trajectories, to provide the general principles and highlight specific features of the GRN underlying neural crest fate diversification from induction to early migration stages using Xenopus frog embryos as a model. During gastrulation, a transient neural border zone state precedes the choice between neural crest and placodes which includes multiple converging gene programs. During neurulation, transcription factor connectome, and bifurcation analyses demonstrate the early emergence of neural crest fates at the neural plate stage, alongside an unbiased multipotent-like lineage persisting until epithelial-mesenchymal transition stage. We also decipher circuits driving cranial and vagal neural crest formation and provide a broadly applicable high-throughput validation strategy for investigating single-cell transcriptomes in vertebrate GRNs in development, evolution, and disease.

Contribution of fetal microchimeric cells to maternal wound healing in sickle cell ulcers.

Leg ulcers are a major complication of sickle cell disease (SCD). They are particularly challenging to treat and innovative therapies are needed. We previously showed that the healing of SCD ulcers is delayed because of decreased angiogenesis. During pregnancy, fetal microchimeric cells (FMC) transferred to the mother are recruited to maternal wounds and improve angiogenesis. After delivery, FMC persist in maternal bone marrow for decades. Here, we investigated whether fetal cells could also improve SCD ulcers in the post-partum setting. We found that skin healing was similarly improved in post-partum mice and in pregnant mice, through increased proliferation and angiogenesis. In a SCD mouse model that recapitulates refractory SCD ulcers, we showed that the ulcers of post-partum SCD mice healed more quickly than those of virgin mice. This was associated with the recruitment of fetal cells in maternal wounds where they harbored markers of leukocytes and endothelial cells. In a retrospective cohort of SCD patients, using several parameters we found that SCD women who had ever had a baby had less of a burden related to leg ulcers compared to nulliparous women. Taken together, these results indicate that healing capacities of FMC are maintained long after delivery and may be exploited to promote wound healing in post-partum SCD patients.

RiboDoc: A Docker-based package for ribosome profiling analysis.

Ribosome profiling (RiboSeq) has emerged as a powerful technique for studying the genome-wide regulation of translation in various cells. Several steps in the biological protocol have been improved, but the bioinformatics part of RiboSeq suffers from a lack of standardization, preventing the straightforward and complete reproduction of published results. Too many published studies provide insufficient detail about the bioinformatics pipeline used. The broad range of questions that can be asked with RiboSeq makes it difficult to use a single bioinformatics tool. Indeed, many scripts have been published for addressing diverse questions. Here (https://github.com/equipeGST/RiboDoc), we propose a unique tool (for use with multiple operating systems, OS) to standardize the general steps that must be performed systematically in RiboSeq analysis, together with the statistical analysis and quality control of the sample. The data generated can then be exploited with more specific tools. We hope that this tool will help to standardize bioinformatics analyses pipelines in the field of translation.