Zhenwei Qian

Cleft palate is one of the most common congenital craniofacial disorders that affects children’s appearance and oral functions. Investigating the transcriptomes during palatogenesis is crucial for understanding the etiology of this disorder and facilitating prenatal molecular diagnosis. However, there is limited knowledge about the single-cell differentiation dynamics during mid-palatogenesis and late-palatogenesis, specifically regarding the subpopulations and developmental trajectories of periderm, a rare but critical cell population. Here, we explored the single-cell landscape of mouse developing palates from embryonic day (E) 10.5 to E16.5. We systematically depicted the single-cell transcriptomes of mesenchymal and epithelial cells during palatogenesis, including subpopulations and differentiation dynamics. Additionally, we identified four subclusters of palatal periderm and constructed two distinct trajectories of cell fates for periderm cells. Our findings reveal that claudin-family coding genes and Arhgap29 play a role in the non-stick function of the periderm before the palatal shelves contact, and Pitx2 mediates the adhesion of periderm during the contact of opposing palatal shelves. Furthermore, we demonstrate that epithelial–mesenchymal transition (EMT), apoptosis, and migration collectively contribute to the degeneration of periderm cells in the medial epithelial seam. Taken together, our study suggests a novel model of periderm development during palatogenesis and delineates the cellular and molecular transitions in periderm cell determination.

Cleft palate is one of the most common congenital craniofacial disorders that affects children’s appearance and oral functions. Investigating the transcriptomics during palatogenesis is crucial for comprehending the etiology of this disorder and facilitating prenatal molecular diagnosis. However, there is limited knowledge about the single-cell differentiation dynamics during mid- and late-palatogenesis, specifically regarding the subpopulations and developmental trajectories of periderm, a rare but critical cell population. Here we explore the single-cell landscape of mouse developing palates from E10.5 to E16.5. We systematically depict the single-cell transcriptomics of mesenchymal and epithelial cells during palatogenesis, including subpopulations and differentiation dynamics. Additionally, we identify four subclusters of palatal periderm and construct two distinct trajectories of cell fates for periderm cells. Our findings reveal that Claudins and Arhgap29 play a role in the non-stick function of the periderm before the palatal shelves contact, and Pitx2 mediates the adhesion of periderm during the contact of opposing palatal shelves. Furthermore, we demonstrate that epithelial-mesenchymal transition (EMT), apoptosis, and migration collectively contribute to the degeneration of periderm cells in the medial epithelial seam. Taken together, our study suggests a novel model of periderm development during palatogenesis and delineates the cellular and molecular transitions in periderm cell determination.

The dysfunction of astrocytes in response to environmental factors contributes to many neurological diseases by impacting neuroinflammation responses, glutamate and ion homeostasis, and cholesterol and sphingolipid metabolism, which calls for comprehensive and high-resolution analysis. However, single-cell transcriptome analyses of astrocytes have been hampered by the sparseness of human brain specimens. Here, we demonstrate how large-scale integration of multi-omics data, including single-cell and spatial transcriptomic and proteomic data, overcomes these limitations. We created a single-cell transcriptomic dataset of human brains by integration, consensus annotation, and analyzing 302 publicly available single-cell RNA-sequencing (scRNA-seq) datasets, highlighting the power to resolve previously unidentifiable astrocyte subpopulations. The resulting dataset includes nearly one million cells that span a wide variety of diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), multiple sclerosis (MS), epilepsy (Epi), and chronic traumatic encephalopathy (CTE). We profiled the astrocytes at three levels, subtype compositions, regulatory modules, and cell–cell communications, and comprehensively depicted the heterogeneity of pathological astrocytes. We constructed seven transcriptomic modules that are involved in the onset and progress of disease development, such as the M2 ECM and M4 stress modules. We validated that the M2 ECM module could furnish potential markers for AD early diagnosis at both the transcriptome and protein levels. In order to accomplish a high-resolution, local identification of astrocyte subtypes, we also carried out a spatial transcriptome analysis of mouse brains using the integrated dataset as a reference. We found that astrocyte subtypes are regionally heterogeneous. We identified dynamic cell–cell interactions in different disorders and found that astrocytes participate in key signaling pathways, such as NRG3-ERBB4, in epilepsy. Our work supports the utility of large-scale integration of single-cell transcriptomic data, which offers new insights into underlying multiple CNS disease mechanisms where astrocytes are involved.

We developed a highly efficient passive mixing device based on a split-and-recombine (SAR) configuration. This micromixer was constructed by simply bonding two identical microfluidic periodical open-trench patterns face to face. The structure parameters of periodical units were optimized through numerical simulation to facilitate the mixing efficiency. Despite the simplicity in design and fabrication, it provided rapid mixing performance in both experiment and simulation conditions. To better illustrate the mixing mechanism, we developed a novel scheme to achieve high-resolution confocal imaging of serial channel cross-sections to accurately characterize the mixing details and performance after each SAR cycle. Using fluorescent IgG as an indicator, nearly complete mixing was achieved using only four SAR cycles in an aqueous solution within a device’s length of less than 10 mm for fluids with a Péclet number up to 8.7 × 10⁴. Trajectory analysis revealed that each SAR cycle transforms the input fluids using three synergetic effects: rotation, combination, and stretching to increase the interfaces exponentially. Furthermore, we identified that the pressure gradients in the parallel plane of the curved channel induced vertical convection, which is believed to be the driving force underlying these effects to accelerate the mixing process.