Spinal motor neurons (MNs) integrate sensory stimuli and brain commands to generate movements. In vertebrates, the molecular identities of the cardinal MN types such as those innervating limb versus trunk muscles are well elucidated. Yet the identities of finer subtypes within these cell populations that innervate individual muscle groups remain enigmatic. Here we investigate heterogeneity in mouse MNs using single-cell transcriptomics. Among limb-innervating MNs, we reveal a diverse neuropeptide code for delineating putative motor pool identities. Additionally, we uncover that axial MNs are subdivided into three molecularly distinct subtypes, defined by mediolaterally-biased Satb2, Nr2f2 or Bcl11b expression patterns with different axon guidance signatures. These three subtypes are present in chicken and human embryos, suggesting a conserved axial MN expression pattern across higher vertebrates. Overall, our study provides a molecular resource of spinal MN types and paves the way towards deciphering how neuronal subtypes evolved to accommodate vertebrate motor behaviors. How molecular diversity in neurons links to versatile functions is elusive. Here the authors profiled embryonic spinal motor neurons with single-cell RNAseq and identified molecular subtypes targeting distinct muscle groups in different species. Thus, MNs are organized as columnar and pool subtypes, stereotypically positioned along the spinal cord axis  are the final hub that conveys commands from the central nervous system (CNS) to peripherals. MNs project their axons to target muscles and coordinate muscular contractions. To support the vast heterogeneity of muscular functions, MN diversity is generated during embryonic development to establish precise synaptic and motor circuit connectionsxis Fig. . Columnaxis Fig. . Within 1. These studies suggest that each motor pool is defined by the combinatorial expression of transcription factors (TFs)—including Hox proteins and others such as Etv4 (Pea3), Runx1 or Pou3f1 (Scip)—and genes encoding axon guidance ligands and receptors1. Some motor pool-specific TFs dictate the activity of downstream effector genes3. Misexpression of motor pool genes has been shown to alter different stages of the MN differentiation and maturation process, including identity specification, axon arborization and dendritic patterning, as well as axon navigation and circuit formation5. However, only a few motor pool genes have been identified to date. As a result, apart from a few TFs and guidance cues, the molecular repertoire of MN diversity remains largely unclear. Given that motor pool-specific gene expression drives distinct cell type-specific functions, we hypothesize that there might be a broader motor pool code that can be deciphered by means of comprehensive single-cell spinal MN transcriptomics. Identifying those pool codes would enable genetic targeting of a specific motor pool and reveal the underlying intrinsic or extrinsic mechanisms that establish cell type-specific properties and target connectivity.Previous studies have identified several genetic regulators of motor pools in LMC MNs and have shed light on the molecular mechanisms that determine MN identities and how motor pools regulate their target connectivity6. Comparative analyses across different species have identified the origin of limb motion and MN subtypes in the LMC9. Nevertheless, although axial MNs representing ancestral MNs are present in both aquatic and land vertebrates, they support distinct motor behaviors in these two groups7. Currently, our understanding of MMC MNs is much more incomplete relative to LMC MNs. It has been hypothesized that MMC subtypes may innervate distinct epaxial muscles12, but a systematic exploration of the molecular heterogeneity of MMC MNs is still lacking. A detailed study of axial MMC neuronal diversity is critical to investigations of how MNs have diversified during vertebrate evolution and might also help decipher how neuronal subtypes have co-evolved with the distinct modes of locomotion displayed by aquatic and terrestrial vertebrates.Although MNs control muscle contraction in all animals, motor outputs can vary among species. Fish utilize epaxial MNs to facilitate their lateral undulatory swimming patterns, whereas tetrapods use limb MNs and axial MNs to coordinate appendicular muscles for joint movement and trunk muscles for posture maintenance, respectively14. As MNs account for less than 1% of the cells within the spinal cord15, we use MN reporter mice (Mnx1-GFP) and establish a robust method to enrich for spinal MNs. Our study has generated a detailed atlas of MN transcriptional identities, including known and unreported segment-restricted MN subtypes. Within LMC MNs, we reveal transcriptional codes for 16 and 10 subclusters from brachial and lumbar limbs, respectively, which may correspond to putative motor pool groups. Moreover, we demonstrate unexpectedly diverse expression of neuropeptides in the LMC MNs. The discovery of underappreciated heterogeneity in axial MNs is validated by different marker expression patterns on distinct axonal branches. Finally, we have explored the MMC subtypes in other vertebrates, including humans. Our results serve as a valuable resource for investigating the multifaceted mechanisms underlying how cell-type-specific features and locomotor circuit development are established.In this work, we profile MNs at the embryonic stage to understand the uncharted diversity of motor pools when MNs have differentiated and make selective synaptic connections to form motor circuits given that the two recent single-cell studies of spinal cholinergic neuronal diversity indicated that motor pool identities become subtler in adult mice16. Given that MNs represent only a tiny fraction of all spinal cells, using the entire tissue as a source would not be an optimal approach for in-depth characterizations of MN diversity15. Thus, we isolated spinal cord tissues separately from the rostral and caudal spinal cord segments of a total 12 Mnx1-GFP mouse embryos from 2 pregnant mice in which GFP is expressed at a high level in MNs and in a small population of interneurons17. Using fluorescence-activated cell sorting (FACS), we collected cell populations with the highest GFP intensities (GFPhigh) and subjected the samples to scRNA-seq  and spinal MN marker (Mnx1), with spinal MNs accounting for ~91% of the total cells upon quality filtering  , which we excluded from further analyses  specifically in the spinal cord, we detected sparse 18 and assigned cluster identities based on the averaged expression of canonical marker genes (see “Methods”). Our analysis resulted in a total of 13 clusters and we were able to assign cell identities to 10 of them 19, MMC medial motor column (Mecom+ and Lhx3+)20, PGC preganglionic motor column (Nos1+ and Zeb2+), HMC hypaxial motor column  , Mnx1+ excitatory interneurons with a glutamatergic (Slc17a6+) property21, and nascent MNs (Neurod2high and Ebf2high)23. One cluster was denoted as “unknown” as we could not uncover a salient and characteristic gene set for it , and the caudally-restricted Nfib+Grm5+ cluster in which Nfib and Grm5 are the top markers  stages , which was previously described as being expressed by pain-related projection neurons and interneurons in the spinal cord27. However, its expression has not been reported before for MNs. In situ hybridization validated the selective expression of Tac1 in thoracic HMC MNs, representing a HMC genetic marker 29, we uncovered selective expression of IgLON neural adhesion molecules  within these neurons  identities3, whereas Isl1/Lhx1 distinguish their mediolateral (ml) positions34  that are already known to be differentially expressed between rostral  and caudal (Hoxc8+) MNs35   in the cm1/2 subcluster, Runx1 in the rl2 subcluster, and Pou3f1 (Scip) in the cm3 subcluster, corresponding to MNs innervating the pectoralis (pec)40/cutaneous maximus (CM)41, scapulohumeralis (Sca) and flexor carpi ulnaris (FCU) muscles42, respectively  in the late-born ventral nerve cord neurons of the fly44. We also further observed Nr2f1 expression in subsets of LMC MNs , or the average expression levels within a gene set ). Therefore, we anticipated that neuropeptides could be reliably used to distinguish LMC MNs. Similar to our observation for TFs, we validated a cohort of neuropeptides  from our single-cell results and indeed observed that they are spatially partitioned in different subsets of LMC MNs using in situ hybridization  expressed Sst and Grp, whereas the Pou3f1+ subcluster (cm3) displayed Penk expression  nts Fig. , but fivone Fig. . Althougent Fig. . OverallEbf2 and loss of this gene resulting in a reduction in the population of axial MNs51. To test our hypothesis, we clustered MMC MNs from the rostral sample and identified three major subclusters, namely Nr2f2+ (Coup-TFII), Satb2+, and Bcl11b+ (Ctip2)  did not manifest salient hallmarks  and Unc5c (enriched in Nr2f2+) in distinct branches of the dorsal ramus  Fig. . We valip2) Fig. . Althougrks Fig. . PreviouMNs Fig. . We alsoion Fig. . RNAscopons Fig. . Their dons Fig. . We alsomus Fig. , suggest7. Our identification of MMC subtypes in mouse embryos led us to examine further if similar subtype heterogeneity is conserved across higher vertebrates, including in chickens and humans. In the chicken spinal cord, we detected the MMC marker Mecom in the majority of Lhx3+ MMC MNs  7.9 55. Most of the ventromedial MMC MNs were MECOM+ ) and broader muscle groups ). We envisage that the molecular diversity uncovered in this study will enable tracking and comparisons of fine neuronal subtypes in disease models by means of lineage tracing, potentially revealing directly the molecular nature of subtype-specific susceptibility. Two subtypes identified in this study, rostral Calb1+ and caudal Nfib+ Grm5+, are marked by genes implicated as being protective against MN disease60. Several studies in rodents and humans have reported that higher expression levels of Calb1 and Grm5 are associated with resistance to ALS, a MN degenerative disease60. Calb1 has been shown to buffer excessive excitotoxic Ca2+, and Grm5 overexpression was found to prevent programmed cell death in in vitro cultures of rat cerebellar granule cells at the early maturation stage62. Further investigation of whether these clusters exhibit selective resistance to neurodegenerative disease would be a unique opportunity to understand the molecular nature underlying “disease resistance” in MNs and provide potential therapeutic targets.Differential vulnerability is a recurring theme in neurodegenerative diseases affecting MNs, in which motor pools respond differently to disease63. We hypothesize that these neuropeptides might: (1) modulate motor pool-specific electrophysiology via autocrine signaling; (2) regulate motor circuit formation by guiding premotor interneuronal innervation to MNs, or (3) ensure the fidelity of finer innervation patterns to the peripherals. To better understand the functions of neuropeptides in neurons, it is tempting to investigate if heterogeneous electrophysiological patterns are displayed by MNs and correspond to motor pools, as well as being associated with neuropeptide usage. Characterizing expression patterns of neuropeptide receptors in corticospinal projection neurons, spinal interneurons, and individual muscle groups will help narrow down the candidate receivers of neuropeptide signals and allow examinations of how connectivity is altered upon gain or loss of function of a given neuropeptide in MNs. Moreover, we also noted differential neuropeptide enrichment between brachial and lumbar segments, which might explain the potential differences in motor circuitry between these spinal cord segments. Consistent with this notion, we also report here that not all LMC subclusters are conserved between brachial and lumbar segments. In our pioneering study, while we attempted to compare cluster similarity at the transcriptome level, we also recognize that there might be functionally distinct clusters existing in different segments that are defined by other extrinsic factors, such as innervation target preference or pre-motor circuit involvement. Further experimental validations, including marker staining with axonal tracing, to complement computational analyses, are warranted.Although LMC MNs are classified according to their innervation of different limb muscles, the molecular differences between these neurons have remained largely unclear. Our study complements and extends the knowledge of LMC MN diversity by describing distinct expression patterns of combinations of transcription factors and neuropeptides among the MN subtypes. We have also validated in vivo a number of markers for these subtypes. Despite the roles of neuropeptides in MN development remaining unclear, their unexpected diversity in neurons could point to functions beyond neurotransmission in embryonic spinal MNs. Indeed, a few neuropeptides in MNs have been assessed in previous studies, which suggested they potentially serve as trophic factors to promote nicotinic acetylcholine receptor (AChR) accumulation and to facilitate formation of neuromuscular junctions65. Third, some neuronal identities may only be elicited by signaling or activity during spinal cord wiring at the postnatal stage66. Accordingly, a longitudinal examination of spinal MN identity integrated with later time-points may be enlightening66. Fourth, although we determined the number of subclusters using a robust ensemble approach based on mathematical spectral graph theory, single-cell transcriptomic data is inherently noisy and sparse in nature, which engenders additional challenges for estimating optimal numbers of clusters from such datasets. Further computational subclustering analysis with in vivo functional validation would likely enhance our understanding of LMC diversity.Although we have expanded the number of molecularly defined LMC subtypes, the number does not match the expected ~60 known LMC motor pools. There are a few possible reasons for this outcome. First, though motor pools are expected to be molecularly defined at the transcriptome level, the subtypes we identified could also correspond to one or multiple motor pools that manifest subtle transcriptomic differences. Second, motor pools at the embryonic stage might not be reflected by the transcriptome alone. An increasing number of studies have demonstrated that single-cell multi-omics analyses, such as joint single-cell transcriptomic and epigenomic profiling, can increase the ability to dissect cellular heterogeneity11, since receptor genes specific to either the Satb2+ or Nr2f2+ subtype are detected in distinct branches of the dorsal ramus. Future studies to confirm functional differences between these subtypes via retrograde labeling in embryonic muscles will be necessary, albeit technically challenging. In addition, the identified MMC subtype markers of Nr2f2, Satb2 and Bcl11b facilitate region patterning in the brain68. Whether they exert similar regulatory roles in MMC MNs warrants further investigation. Moreover, the mutually exclusive expression pattern of Nr2f2 and Satb2 suggests potential regulation between these two subtypes, which should prompt future genetic manipulation or lineage tracing studies.Axial MNs that control core muscles represent an evolutionarily ancient neuronal type and they play pivotal functions across most vertebrate species. Diversity within the relatively small population of MMC neurons in the spinal cord is less appreciated due to their largely unknown molecular profiles. In this study, we describe transcriptomic heterogeneity within MMC MNs. Notably, we observed mediolateral expression patterns for Satb2 and Nr2f2. We further speculated that these MMC MN subtypes might innervate different axial muscle groups, such as the spinalis, longissimus, iliocostalis or levator costae muscles9, highlighting that the common ancestor of most vertebrates already possessed a sophisticated blueprint for walking. While it remains unclear how axial neuronal subtypes and their innervating motor circuits changed during vertebrate evolution, axial muscles perform distinct functions in different species. For example, despite the presence of axial MNs in both aquatic and land animals, these animals utilize the axial muscles innervated by those MNs distinctly; most fish generate propulsive forces via rhythmic contraction of their axial muscles during swimming, whereas tetrapods employ axial muscles for non-locomotory spinal alignment and breathing69. It is tempting to speculate that the MMC subtypes co-evolved with different lifestyles and now serve different modes of locomotion. Therefore, we investigated MMC neuronal heterogeneity in embryos of three different vertebrates—chicken, mouse, and human—based on immunostaining of the Nr2f2/Satb2/Bcl11b markers and observed that the same set of proteins consistently labels subsets of MMC MNs in these species. Interestingly, we observed that the SATB2 and NR2F2 mediolateral positioning we observed in mouse embryos might be inverted in humans. Since the transcriptional program underlying MMC subtype identities might be critical to MMC subtype topographical organization, additional experiments on human embryos will be necessary in future to investigate if this inversion leads to a reorganization of the MMC topographical distribution and whether this change is functionally important. The conservation of markers provides genetic access to MMC subtypes for future comparative studies and allows the characterization of gene expression signatures and innervation patterns of MMC subtypes in various species. For example, at least two MN subtypes have been reported in zebrafish;6 their primary and secondary MNs are characterized based on birth order, cell body size and muscle innervation. The molecular nature of these subtypes has yet to be established, although they are known to express generic MN genes such as the mnx paralogs islet1 and islet271. It remains to be determined if the markers of mouse MMC subpopulations we have identified herein are also expressed in zebrafish or other aquatic vertebrates. Comparative transcriptomics would be needed to explore similarities and divergences among such species and would require challenging integration analysis of single-cell MNs and in situ hybridization validation experiments.An elegant recent survey revealed that the neuronal subtype essential for walking originated in primitive jawed fish72. This scenario may reflect that LMC MNs are intrinsically vulnerable to shear stress, regardless of how mild a dissociation approach is applied, and it is consistent with previous reports indicating that LMC MNs are more susceptible to degeneration in amyotrophic lateral sclerosis73. Additionally, we noticed that although the rostrocaudal identities of spinal cord cell types are determined and maintained by cross-regulation among Hox proteins33, our single-cell analysis revealed that Hox transcripts, such as Hoxa5 and Hoxc8, can still be co-expressed within the same cell, despite being segregated at the protein level. This outcome is consistent with our previous studies showing that post-transcriptional mechanisms, such as those exerted by microRNAs, are indispensable to the unambiguous governance of spatiotemporal Hox protein expression and for defining rostrocaudal MN subtype identities in the spinal cord23. Thus, although our single-cell gene expression analysis has facilitated the identification of transcriptionally distinct cell types and states, integrating other modalities such as proteomics with our dataset would reveal more information about gene regulation during the cell-type determination process. Furthermore, while we have also attempted to cluster the collected MNs after integrating rostral and caudal datasets  were incorrectly assigned to another cluster which does not express these marker genes  and validation through Tac1 in situ hybridization. Given that many previous elegant studies have provided rich knowledge on Hox-mediated segmental MN types33, which could be served as a reference for us to annotate known segmentally-restricted types with confidence, thus, in our study, we presented separate analyses for rostral and caudal samples to prevent overlooking subtle sample type-intrinsic differences. This also highlights that reliable integration between biological conditions remains challenging74, and future development with more advanced algorithms to overcome this issue is anticipated.Unexpectedly, either using trypsin- or papain-based dissociation approaches, we acquired equivalent numbers of MMC (2354 cells) and LMC (2248 cells) MNs, which is inconsistent with the population ratio of brachial LMC to MMC MNs (4:1) in E13.5 mouse embryosOverall, our study has deciphered the molecular repertoire of spinal MNs and conservation of subtypes across different vertebrates. Our identification of combinatorial TF/neuropeptide markers for each MN subtype could also facilitate a better understanding of axon targeting and selective neuronal connections, and help uncover differential susceptibility in disease models when seeking disease-protective pathways that could represent therapeutic targets.75 and none of the induced abortions were performed for reasons of fetal abnormality. Tissues were collected in absence of compensation, with written informed consent specifying the purpose of the research, in accordance with legal procedures agreed by the French Biomedicine Agency, Agence de la Biomédecine (authorized project number PFS12-002).All mice experimental procedures were performed in accordance to guidelines approved by the Institutional Animal Care and Use Committee (IACUC) at Academia Sinica (protocol number 19-12-1409 and 12-07-389). Human embryo spinal cords were harvested from material obtained following legally induced terminations of pregnancy (first trimester of pregnancy) from the Department of Obstetrics and Gynecology at the Antoine Béclère Hospital . Fetal age was calculated by measuring the length of limbs and feet according to a developed mathematical model73, Tau-mGFP76  and male P50-P180 Mnx1-GFP17, Npy-IRESCre/Cre 77 mice were used in the study. Mice were crossed to obtain embryos of desired genotypes. When a copulation plug was observed, the embryo stage was estimated as E0.5. All live animals were maintained in a C57BL/6J background and housed in the specific-pathogen-free (SPF) animal facility of Institute of Molecular Biology, Academia Sinica, with 12-h light/dark cycle, 45–55% humidity, 19–22 °C temperature and had ad libitum access to food and water in their home cages at all times, abiding by the IACUC Academia Sinica guidelines.Female P50-P150 wildtype C57BL/6J , Mnx1-RFPn = 12 embryos of two pregnant mice) were pooled to perform scRNA-seq. The embryos were decapitated and dissected to isolate spinal cords from rostral (C4-T3) and caudal (L1-S5) segments in Leibovitz’s (L-15) medium. These segments were independently processed until single-cell library construction. Tissue dissociation was performed using a Neural Tissue Dissociation Kit (P)  on a gentleMACS dissociator  according to the manufacturer’s instructions. Dissociated cells were resuspended in N2B27/DMEM-F12 and neurobasal medium containing N2  and B27 , 1% penicillin–streptomycin, 2 mM L-glutamine, 0.2 M β-mercaptoethanol and 0.5 μM ascorbic acid, supplemented with 1% inactivated fetal bovine serum (FBS), 1:10,000 Dnase-I , before filtering through a 70-μm strainer . Sorting was carried out using a BDFACSAria III cell sorter , with 85 μm nozzle diameter and 45 sheath pressure, to collect GFP+ cells at 4 °C into DMEM medium with 1% FBS. Collected cells were counted and adjusted to a final concentration of 700–1200 cells/μl.Mnx1-GFP mice were crossed to C57BL/6J mice for single-cell spinal MN collection. E13.5 embryos of pregnant mice  and Chromium Single Cell 3’ Reagent Kit v2 according to the manufacturers’ instructions. In brief, single-cell suspensions were loaded on the Chromium Controller Instrument to generate single-cell Gel Bead-In-Emulsions (GEMs). Upon breaking up of GEMs, the barcoded cDNA was purified and amplified. During library construction, the amplified barcoded cDNA was fragmented, A-tailed, and then adapter-ligated. A sample index was added. Pooled libraries were sequenced using Illumina NextSeq 500 and NovaSeq S4 systems, and then paired-ended  to an average depth of 85k mean reads per cell.The FASTQ files were processed using the standard Cell Ranger pipeline  for demultiplexing, mapping to the mm10 reference, filtering, barcoding, and counting unique molecular identifiers (UMI). From the Cell Ranger pipeline, the total number of cells were 5528 and 5288, median numbers of genes detected per cell were 2843 and 2722, and the median numbers of unique transcripts were 11,906 and 11,090, respectively, for rostral and caudal samples. For both rostral and caudal samples, cells were retained for subsequent analysis if they displayed a number of genes between 1000 and 5300, UMI counts <30,500, and <10% mitochondrial counts. Quality filtering led to 5460 and 5242 cells for rostral and caudal samples, respectively, which were used for downstream analysis.18. The digital data matrices were normalized by a global method, whereby the expression value of each gene was divided by the total expression in each cell and multiplied by a scale factor . These values were then log-transformed with a pseudocount of 1. Highly variable genes across cells were selected using the FindVariableGenes function . To identify cell clusters, principal component (PC) analysis was first performed using the top 34 PCs for the rostral sample and the top 31 PCs for the caudal sample, where the number of significant PCs was determined based on an elbow plot and jackstraw test. Cells were clustered using the Louvain community detection method in the FindClusters function (resolution = 0.05) and visualized using Uniform Manifold Approximation and Projection (UMAP). Motor neurons (MNs) and non-motor neurons were distinguished based on the expression of generic MN markers such as Mnx1 and the cholinergic genes Chat, Slc18a3, and Slc5a7. Only clusters expressing MN markers were considered, retaining 5162 and 4699 cells for rostral and caudal samples, respectively. These MNs were analyzed using the same pre-processing procedures described above, but with different numbers of PCs and cluster resolutions.We performed normalization, dimensionality reduction, and cell clustering using Seurat package version 2.3.4p values from the likelihood-ratio test was <0.05; (ii) the log fold-change was >0.25; and (iii) the percentage of cells expressing a given gene in the cluster was >25%.To cluster MNs, cell clusters were obtained using the top 31 PCs with a resolution of 0.08 for the rostral sample and the top 24 PCs with a resolution of 0.3 for the caudal sample. Cell identities were assigned using known markers established in previous studies and markers identified in our study. Marker genes of each cell cluster were identified using the FindAllMarkers function. Genes were considered marker genes if: (i) the adjusted Hox genes and LIM homeodomain factors. Cells in each “spatial quadrant” were then further clustered. In brief, for brachial LMC MNs, “spatial quadrants” were obtained by performing hierarchical clustering using Hox genes (Hoxa5 and Hoxc8) and LIM homeodomain factors (Lhx1 and Isl1). The robustness of assigned identities was confirmed by observing that the cells of a cluster within each “spatial quadrant” segregated from cells of a different cluster in UMAP space, which was established from PC analysis using highly variable genes as input. For the lumbar LMC MNs, “spatial quadrant” clusters were obtained using the FindClusters function with a resolution of 0.3. The robustness of the assigned identities was confirmed by predicting cell identities among lumbar LMC MNs from the assigned identities of brachial LMC MNs using a random forest model. This was achieved by training a random forest classifier based on the “spatial quadrant” identities of brachial LMC MNs using the ClassifyCells function in Seurat, which was subsequently applied to the lumbar LMC MNs.To subcluster LMC neurons, cells were first grouped into “spatial quadrants” based on their expression pattern of 78. Specifically, we first performed subclustering using the FindClusters function in Seurat with multiple resolutions ranging from 0.1 to 3 and an increment of 0.05. Next, we constructed a consensus matrix based on a set of clustering results from these multiple resolutions. Consensus matrix A was obtained by averaging the entries of a connectivity matrix B across all runs, where the entry Bij of the connectivity matrix B equals 1 if cells i and j are assigned to the same cluster for each run. Thus, each entry Aij for A varies from 0 to 1 and represents the probability of cells i and j being in the same cluster across multiple resolutions. The consensus matrix was further pruned by setting the elements to zero if they were <0.3 to ensure better robustness against noise. Finally, we estimated the number of clusters by computing the eigenvalues of the associated Laplacian matrix of the constructed consensus matrix. Based on perturbation theory and spectral graph theory, it has been theoretically proven that the number of clusters N equals the multiplicity of the eigenvalue 0 of the Laplacian matrix78. Therefore, in the ideal case of N completely disconnected clusters, the eigenvalue 0 has multiplicity N. More generally, the number of clusters N is usually given by the value of N that maximizes the eigenvalue gap , i.e., select the number N such that all eigenvalues To further subcluster LMC MNs in each “spatial quadrant” cluster, we adopted a multi-resolution ensemble method to determine the number of subclusters based on spectral graph theoryMMC MN subclusters were obtained using the top nine PCs with a resolution of 0.2.79. In brief, differentially expressed signatures (DES) were first identified using limma-trend data for each group of cells against all other cells within the dataset, whereby DES were computed by fitting a linear regression model. The similarity was then measured according to the Pearson’s correlation coefficient of DES between two groups.Similarity between two groups of cells representing rostral or caudal MNs was determined using the calculateDistMat function (method = “trend”) in the CIDER package49. To further quantify similarity among brachial and lumbar LMC subclusters, we assessed the degree of subcluster mixing across segments, quantified based on the overlap between one subcluster from brachial segments and another subcluster from lumbar segments in the joint UMAP space. Specifically, we first identified mutual nearest neighbors (MNNs) of each cell based on Euclidean distances in the UMAP space. Second, for each cell in one sample , we counted how many of its MNNs are cells in a certain subcluster from another sample . Third, for each subcluster in the brachial sample, we computed its overlap ratio with another subcluster in the lumbar sample by calculating its average MNNs for cells from the lumbar sample, representing the probability of cells from two subclusters being MNNs across brachial and lumbar segments. Finally, to increase the robustness of the estimated similarity, we computed an average overlap ratio by using different numbers of neighbors  to identify MNNs. The similarity matrix was visualized using the ComplexHeatmap R package80. To intuitively visualize the relationships of LMC subclusters between brachial and lumbar segments, we created an alluvial diagram using the ggalluvial R package . Lines of low similarity values  were omitted to accentuate relatively substantial similarity and enhance readability. This threshold was heuristically searched within a range supported by prior knowledge, such as on Etv448, which should be shared among non-segment-specific clusters, as well as the relatedness of a given pair of clusters with other clusters in the UMAP space.To visually examine relatedness among LMC subclusters of brachial and lumbar segments, we merged all LMC neurons from the brachial and lumbar segments and then performed joint dimensional reduction via UMAP using the corrected embedding learned from the Harmony integration methodp value <0.05 and log fold-change >0.25 were considered differentially expressed. Gene Ontology (GO) enrichment analysis of DEGs was performed using the clusterProfiler R package 81, focusing on Biological Processes (BP) and Molecular Functions (MF). Redundant GO terms were removed using the simplify function with default parameters.Differentially expressed genes (DEGs) between segments or subclusters were identified using the FindMarkers function by performing likelihood-ratio tests. Genes with an adjusted All E13.5 and E15.5 mouse embryos were fixed with 4% PFA for 2 h (for immunostaining) or 4 h (for in situ hybridization). To prepare samples for 20-μm cryosectioning, the samples were cryoprotected with 30% sucrose and embedded in OCT compound (Leica). For 300-μm vibratome sectioning, whole embryos were embedded in 4% low melting agarose and transversely sectioned. During the immunostaining step, sections were permeabilized and blocked with 10% FBS plus 0.3–0.5% Triton-X-100 for 1 h at room temperature or overnight at 4 °C. Antibodies were applied at respective titers and incubated at 4 °C for one or two nights for the 20- and 300-μm sections, respectively. Sections were washed frequently with wash buffer. For the 20-μm sections, samples were washed with 0.01% Triton X-100 in 1× PBS. For the 300-μm sections, an overnight wash with 0.5% Triton X-100 in 1× PBS (PBST) was performed. Secondary antibody was applied for 1 h at room temperature or overnight at 4 °C for the 20- and 300-μm sections, respectively. Finally, sections were washed with wash buffer and mounted. Primary antibodies used were: rabbit anti-Lhx3 ; rabbit anti-Foxp1; goat anti-Foxp1; rabbit anti-Hoxc8 ; sheep anti-GFP ; rabbit anti-RFP ; mouse anti-MNR2/MNX1/HB9 ; goat anti-Chat ; mouse anti-COUP-TF2/NR2F2 ; mouse anti-COUP-TF1/NR2F1 ; rabbit anti-Evi1/Mecom ; goat anti-Isl1 ; rabbit anti-Satb2 ; guinea pig anti-Satb2 ; rat anti-Bcl11b/Ctip2 ; rabbit anti-Zfhx4 ; rabbit anti-Calbindin D-28K/Calb1 ; rabbit anti-Nfib ; rabbit anti-Grm5 ; sheep anti-Ebf2 ; rabbit anti-Nrp2 . Guinea pig anti-Foxp1 (1:320000), anti-Isl1 , and anti-Lhx1 , anti-Unc5c (1:50), rabbit anti-Nkx6.1 (1:1000) antibodies were gifts from Thomas Jessell and guinea pig anti-Mnx1 (1:1000) was a gift from Hynek Wichterle. Guinea pig anti-Hoxa5  was made in-house. For secondary antibodies, donkey anti-Sheep lgG (H + L) Cross-Adsorbed, Alexa Fluor 488 ; Donkey Anti-Goat lgG (H + L), Alexa Fluor 488 ; 488-AffiniPure Donkey Anti-Rat lgG (H + L) ; Cy3-AffiniPure Donkey Anti-Guinea Pig lgG (H + L) ; Cy3-AffiniPure Donkey Anti-Mouse lgG (H + L) ; Cy3-AffiniPure Donkey Anti-Rabbit lgG (H + L) ; Cy5-AffiniPure Donkey AntiGuinea Pig lgG (H + L) ; Cy5-AffiniPure Donkey Anti-Mouse lgG (H + L) ; Cy5-AffiniPure Donkey Anti-Rabbit lgG (H + L)  were used at dilution titer of 1:1000.For in situ hybridization, sections were dried, post-fixed with 4% PFA for 15 min at room temperature. Slides were pretreated with 3 μg/ml Proteinase K for 5 min and acetylation buffer for 10 min. Prehybridization was performed for at least 2 h at room temperature. Riboprobes (150 ng) were heat-denatured at 80 °C for 5 min and hybridized to sections overnight at 58 °C. After washing and blocking, the slides were incubated with anti-digoxigenin-AP, Fab fragments overnight at 4 °C. After washing, the slides were color-developed with NBT/BCIP solution. Sequences for riboprobe generation are indicated in Supplementary Table Hoxa5; caudal: Hoxc8; medial: Foxp1+Isl1+; lateral: Foxp1+Isl1−). Boundaries were drawn and transferred to slides with marker staining.For mediolateral spatial delineation during LMC marker validation, adjacent slides were immunostained for spatial genes to determine the position of signals  and probes were detected with Akoya Biosciences Opal 520 (FP1487001KT), 570 (FP1488001KT) and 690 (FP1497001KT). The staining protocol followed the manufacturer’s recommendations with minor modification. E13.5 embryos were fixed at 4% PFA for 30 h at 4 °C and washed with 1× PBS at 4 °C. Embedded samples were subjected to 14-μm cryosectioning. The fresh-frozen protocol was adapted by skipping the 15 min post-fix stage and proceeding directly with pretreatment and the RNAscope hybridization assay. Details of probes used in this study are presented in Supplementary Table 00 and pr+ and Zfhx4+ immunostained cells, sequential sections of 20 µm every 450 µm were categorized into four regions along the rostrocaudal axis of the brachial or lumbar spinal cord. Cell segmentation masks were first generated using Ilastik82 for individual channels, and object center coordinates  of expressing cells were outputted to ImageJ CellCounter (NIH) for manual inspection and quantification. Cells were considered as co-expressing if the x,y coordinates from different channels were both unique within a diameter of 10 pixels.To quantify Nkx6.1z-stack images of DAPI. Masks were imported into Imaris for surface detection. RNAscope signals were detected with spot detection and split into surfaces. Nuclei were counted as expressed when ≥3 spots within a surface were detected.For quantification of neuropeptide-expressing cells by RNAscope-based ISH, sequential sections of 14 µm every 500 µm were categorized into three regions along the rostrocaudal axis of the brachial or lumbar spinal cord. 3D cell segmentation masks were produced based on The sample preparation and immunostaining procedures were performed similar to mouse embryos, except that spinal cords were fixed with fresh cold 4% PFA for 90 min and sectioned at 16 μm. After the immunostaining, sections were mounted in Fluoromount (Sigma-Aldrich or Cliniscience). All images were acquired with a DM6000 microscope (Leica) and a CoolSNAP EZ CDD camera.x, y) were assigned based on the position of each MMC MN using the “spots” function in the imaging software Imaris 9.5.1 (Bitplane). Four additional coordinates were exported, i.e., midpoints for the dorsoventral and mediolateral spinal cord boundary. To account for differences in spinal cord size and shape, sections were normalized to a standardized hemisection spinal cord . Density distributions for cells were plotted using the ggplot2 ‘geom_density’ function.Coordinates . All statistical results are presented as mean ± SD (standard deviation) of three or more independent biological replicates or the median ± interquartile range (IQR), as indicated. Appropriate statistical tests are performed for each analysis and specified in the respective figure legend. All staining experiment were repeated on at least three independent biological replicates unless indicated otherwise and representative images were presented in the manuscript. No statistical method was used to predetermine sample size. The experiments were not randomized nor blinded because the quantification analysis and the assessment was performed in an objective and semi-automated manner.Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting Summary


Fibers come from natural and fossil resources and are an essential commodity widely used by textile industries. Considering current supply and future demands, the repurposing of agricultural residues into fibers is an eco-friendly, attractive option that might mitigate environmental pollution. In this review, we have summarized multiple alternate secondary sources for fiber production, with a case study using banana plant residual biomass, a common agricultural waste in many developing countries. Specifically, in this review we have compared the different processing methods, e.g., chemical, mechanical, or biological methods, for repurposing agricultural residual biomass (including banana waste) into fibers. The development and analysis of an integrated biorefinery approach is needed to promote the fiber production from various agro-residual biomasses within the framework of circular bioeconomic concepts. This also includes forest biomass (~4.6 Gt.Y−1), in which 60% goes for energy generation and the remaining is waste biomass [Globally, ~140 gigatons per year : Plant stems or plant materials are soaked in water under a controlled condition and rely on natural microbial action to remove gummy materials. It produces fibers with uniform quality. High water requirements, foul odors, and high costs make this process less attractive.Dew Retting (duration~14 to 21 days): Plant stems or parts are harvested and left in a field for natural air decomposition of materials with pectinaceous properties. This is an easy method to extract gummy material, but the quality of the fibers will be inconsistent, and their properties will vary.Enzymatic Retting (duration~12 to 24 h): This process relies on specific enzymes such as pectinase and xylanase that act to remove pectinaceous substances under controlled conditions. This process produces low fiber strength material, which is a significant drawback.Chemical Retting (duration~1 to 2 h): This process requires the use of chemicals, such as sodium hydroxide, sodium benzoate, or hydrogen peroxide, for the removal of pectinaceous substances and is a more efficient method to produce long, clean fibers. The processing cost is one of the drawbacks, but it produces a fiber with a natural color and tensile strength.Mechanical Processing or Mechanical Retting (duration~2 to 30 min): This process is usually completed in only a few minutes. In a mechanical process, the fibers are decorticated, followed by cleaning, which produces many short fibers. Ball mills, hammer mills, or crushing rollers are used for decortication. The produced materials are sorted, screened, and size segregated for cleaning and use.Millions of people are employed in natural fiber producing industries, especially those in developing countries where the industries consist of small-and large-scale operations. Fiber producing crops are cultivated throughout the world, but mostly in tropical and sub-tropical climates (mainly from developing countries). In recent years, the bioprocessing of cellulosic agricultural biomass for fiber production has gained momentum. Agricultural biomass, such as oil palm, bagasse, corn stalks, coir, bamboo, pineapple, banana, and rice husk are becoming useful. These are considered secondary sources of fiber. They are grouped as field residues and processed residues. Field residues are usually left unutilized in the field after harvest , while the processed residues are biomass that is produced during the process of extracting the standard main product . Chemical method: This method aims to remove non-cellulosic fiber materials. Sulfuric acid, hydrochloric acids, and hydrogen peroxide-based methods are widely reported to extract the fibers from agro-residues.Mechanical method: Mainly homogenization, ultrasonication, cryo-crushing, refining, grinding, micro fluidization, and electro spinning methods are developed and used. The steam explosion method has been developed, and it uses high pressure and temperatures to break the cell-wall fractions and separate the fibers.Combined method: The combination of chemical and mechanical methods is used more efficiently. This combination can produce high quantity fibers in a short retention time .Biological method: The use of biological agents or enzymes to remove and extract cellulose are low-cost technologies. This method requires thorough optimization and process engineering for the different types of source materials used. Compared to chemical or mechanical methods, it is a time-consuming procedure, and the careful selection of biological agents is a key step to improve process efficiency.The processing and extraction of cellulosic fibers from agricultural residues mainly aim to remove non-cellulosic content, including lignin, hemicellulose, and pectin (if present). Several factors govern the selection of extraction methods, but the chemical composition of agricultural residue is the key parameter. The most used methods for the extraction of cellulosic fibers from agricultural residues are:In this section, we present a case study of the bio-refinery processing of residual biomass from banana plantations to produce fibers and value-added products.Banana plants are grown in almost every country in the world, especially in tropical and subtropical climates . AccordiBananas are one of the earliest crops cultivated in the history of human agriculture. Many tropical and subtropical regions cultivate the land for banana plants. Land used for banana cultivation stretches from India to Papua New Guinea, as well as to the Southeast Asia region. Banana plant biomass and its by-products a remarkable source of priceless raw materials for other industries that recycle agricultural waste. For instance, the typical composition of banana residue is cellulose (50–60%), hemicellulose (25–30%), pectin (3–5%), lignin (12–18%), water-soluble materials (2–3%), fat and wax (3–5%), and ash (1–1.5%). Recycling this biomass helps to prevent the ultimate loss of a huge amount of untapped biomass and helps prevent environmental issues. Especially in banana farming, enormous quantities of biomass will mostly go to waste due to the non-availability of suitable technology for its commercial utilization. All types of banana species and waste from banana plantations could be used for fiber production. More research is needed to develop a sustainable workflow process for producing fibers and biorefinery concepts to maximize or re-purpose the value of residual biomass.Bananas are one of the largest herb groups in the world . This plBanana fibers, also known as musa fibers, are one of the world’s strongest natural fibers. Banana fiber is like natural bamboo fiber, but its spinnability, fineness, and tensile strength are said to be better. Banana fiber can be used to make several different textiles with different weights and thicknesses, based which part of the banana stem the fiber was extracted from. The thicker, sturdier fibers are taken from the banana trees’ outer sheaths, whereas the inner sheaths result in softer fibers. Banana fibers can be used to make ropes, mats, and woven fabrics, as well as handmade papers. Compared to various natural fibers, such as jute, coir, palm, etc., the banana fibers have a better tensile strength, i.e., 458 Mpa, with a 17.14 gigapascal modulus . The ban4, benzoyl chloride, stearic acid, etc., are not eco-friendly methods to use. The mechanical extraction methods are unable to remove the non-cellulose compounds; however, they are not replaceable for the processing and segregation of biomass. As shown in The extraction of fibers from residual plant biomass relies on chemical, mechanical, and biological methods. The chemical methods for extraction use NaOH, KMnOTraditionally, people processed the fibers using manual extraction methods, such as the splitting and scraping methods. They previously used knives and currently, the raspador machine is used for extracting fibers from banana pseudo stems. Other parts of the banana plant contain cellulose, which is extracted using biological methods for composite material preparations. The biological methods applied are solid-state fermentation and enzymatic methods, and they ultimately show promise for processing the biomass into fibers. There were excellent results that showed their ability to avoid fiber breakage. The most used enzymes are pectinase and xylanase . DevelopBanana fabric is a beautiful, animal-free textile that mimics real silk, and acts as an excellent vegan alternative. The main material of the fiber comes from the stalk of the banana plant and is commonly referred to as banana silk . While iThe banana residual biomass is a good source to produce nutraceutical products, biofertilizers, biopolymers, nanomaterials, bioenergy, and biofuels  are great secondary sources to be processed into natural fibers. The proper management of agricultural residues will help to significantly reduce the environmental problems caused by current disposal practices and support circular bioeconomy concepts that revolve around creating a framework of renewable resources, such as banana fibers, to be used for food management, health, land, and industrial systems using methods such as creating fibers from biomass waste. Bioeconomy economy is economy powered by nature. It is a new model of economy that uses the renewable product to reduce waste and replace the range of non-renewable waste. It is the idea of turning waste into a useful commodity for society . With th


Conventional fire-retardant composite coatings are typically made of organic-based materials that reduce flame spread rates. However, the associated chemical reactions and starting precursors produce toxic and hazardous gases, affecting the environment and contributing to climate change. Wood is one of the most common materials used in construction and households, and thin-film fire-retardant coatings are needed to protect it from fire. Here, we derive high-performance nanocomposite paint-based coatings from naturally occurring and highly insulating layered vermiculite. The coatings are made using different weight percentages of shear-exfoliated vermiculite nanosheets in an epoxy matrix and are brush-coated onto teak wood. A series of tests using coated wooden rods and standard fire retardancy tests confirm a reduction in flame spread and combustion velocity with minimal toxic smoke release. Samples coated with the vermiculite/epoxy nanocomposite paint resist fire propagation, and post-combustion analysis indicates their resistance to thermal degradation. Our results offer a novel and eco-efficient solution to minimize the flame propagation rate, enhancing char development, and expand the scope of applications of ultra-thin vermiculite in nanocomposite coatings as a fire retardant, exploiting its low thermal conductivity in thermal insulation systems. A nanocomposite made of exfoliated vermiculite nanosheets and epoxy is developed for extinguishing fire and protecting wood from fire degradation. Phyllosilicates are the group of minerals that form parallel sheets of silicate tetrahedra, e.g. talc, mica, serpentine and other clay minerals.6 Vermiculite is an exciting and naturally occurring clay-based layered material.7 It has incredibly low thermal conductivity due to phonon scattering at ordered interfaces as well as a very low density.8 Recently, Paolo et al.9 reported the thermal insulation properties of vermiculite nanosheets exfoliated in acidic solvent from their 3D precursors. They found that the exfoliated vermiculite nanosheets (<0.1 W m−1 K−1) had ultra-low thermal conductivity and proposed possible applications in thermal insulation and protection. Therefore, vermiculite nanosheets can be used effectively as nanofillers in epoxy or polymer matrices.10,11Since the discovery of graphene, a variety of 2D nanomaterials with interesting properties have been continuously evolving. In fact, their properties are controlled by the number of layers and the functional groups embedded in them.12 Phosphorus-based coatings that form char when ignited and dramatically swell when exposed to fire are widely used in passive fire protection of structures, but at the cost of releasing toxic gases.13 Layered double hydroxide nanofillers have been extensively studied for fire retardant applications owing to the ability of the divalent and trivalent cations to suppress flame.14,15 Carbon nanotube (CNT) and graphene-based polymer composites are good fire retardants that use the barrier mechanism to retard flame spread.16,17 Carbon nanotubes are expensive to synthesize. Experimental difficulties in aligning high-thermal-conductivity graphene nanosheets parallel to the substrate surface and volatility in reducing heat resistance limit their use in thermal protection systems.18Wood is used in construction and interior design due to its unique characteristics such as natural insulation and low-energy production; however, it is highly flammable.19 aerogels,20 polyurethane-based vermiculite composites,21 heterostructures22 and clay along with polyethylenimine and chitosan23,24 have been effectively used in thermal insulation and flame retardant applications to reduce thermal resistance, and the addition of vermiculite has been found to delay the decomposition temperature and impede oxygen supply. To the best of our knowledge, there is presently no coating material that satisfactorily protects wood against fire using a sustainable two-dimensional material with ultra-low thermal conductivity. The range of sustainable materials and methods to develop next-generation fire-resistant materials is continuously expanding.25Exfoliated boron nitride (BN) nanosheets,In this work, high-aspect-ratio exfoliated vermiculite nanosheets (ex-VN) are prepared by shear exfoliation of the bulk precursor in an aqueous medium, and a vermiculite-based nanocomposite paint is formulated using epoxy as the matrix. Due to its natural abundance, low cost and ultra-low thermal conductivity, the fire-retardant properties of wood are enhanced after coating with the ex-VN/epoxy nanocomposite paint. The addition of ex-VN to the epoxy leads to flame-extinguishing properties, reduced smoke production in the combustion test, and protection of the underlying structure.26The as-received bulk vermiculite had a light brownish-yellow appearance, as shown in 27 To analyze the quality of the nanosheets and lateral dimensions of the exfoliated vermiculite, TEM was performed.To avoid the aggregation or sedimentation of the exfoliated vermiculite, we used a surfactant to stabilize the vermiculite nanosheets in water; a photograph of the dispersion is shown in 28 as shown in As shown in the images in 29 such as thermal degradation30 and combustion velocity, fire tests were performed on coated wooden rods, including rods coated with the control sample. Brush-coating using brush strokes in a single direction yielded uniform coatings, as can be seen from the surface smoothness of the coated rod.Subsequently, a solvent-exchange procedure was carried out to exchange the solvent from water to acetone. via brush strokes on the wooden surface.The thickness of the coated film was measured using an optical microscope for samples on which 5, 7 and 15 coatings of the 5 wt% ex-VN/epoxy had been brush-painted. A representative optical microscopy image is shown in 31,32 It also provides the time taken for the flame to spread.33t1. After the flame is completely extinguished, the same process is repeated, and time t2 is noted. Often, even after the flame is extinguished, a reddish afterglow remains, which slowly fades away. The time taken for this glow to disappear is recorded as time t3. Depending upon the values of t1, t2, and t3 obtained from the UL-94 test, a polymer composite can be given a fire retardant rating of V0, V1, or V2. Materials that exhibit slow burning or extinguish themselves suddenly without any dripping are given the highest UL-94 ranking.34,35The Underwriters Laboratory-94 (UL-94) test is a standard plastics flammability test based on the tendency of material to extinguish flame and resist dripping.V0 category, which is considered to be the best class of fire-retardant materials.36 The sample coated five times with the 20 wt% ex-VN-filled epoxy composite was able to extinguish the flame within 10 s upon the first exposure to flame in the UL-94 test, qualifying it as V0.Rod-shaped wooden samples with a length of 10 cm and diameter of 10 mm were rigidly fixed to the stand. In the UL-94 test, if the flame is extinguished in less than 10 s after the first ignition and less than 50 s after the second ignition, then it is ranked as 37 Since combustible and non-combustible gases were also released, the total and solid mass loss of the sample were quantified by tapping the samples with minimal force to see how much black char disintegrated from the edges of the tested samples. The results are shown in The control sample did not display any fire extinguishing properties and had to be forcefully extinguished after the entire length of the rod was burnt 67 s after the first ignition. On the other hand, the ex-VN/epoxy-coated wood sample extinguished the flame in just 10 s, while the bare wood sample extinguished the flame in 31 s. On the vermiculite nanosheets–epoxy-coated sample, the flame propagated over only 4% of the wooden rod after the first ignition. This more favourable time duration shows that the ex-VN/epoxy nanocomposite coating can hold the fire static for a longer time by forming a physical barrier to propagation.As shown in i.e., 10 mm. In the case of the epoxy-coated samples, the pin at the centre point travelled a distance of >1 mm at the edges that were exposed to the flame. The same test was also performed on the ex-VN–epoxy coated samples. It was observed that at all points of the sample, the pin travelled <1 mm. This test leads to the conclusion that the vermiculite nanosheets are able to successfully reduce the penetration of the flame into the wood sample.We performed a simple experiment to determine the depth of the structure disintegration. Sharp wooden pins were inserted at various points on the surface of the tested samples, as shown in 38 As shown in −1, which is reduced by 40% in the 10 wt% sample and by 68.3% in the 30 wt% sample. There is a reduction in the spread of flame with increasing vermiculite nanosheet content in the epoxy, which gives rise to a mechanism in which the heat is dissipated gradually during the combustion process. Fire tests were conducted on the epoxy and ex-VN/epoxy nanocomposites with different weight percentages of the nanofiller to measure the flame extinguishing time, combustion velocity and flame height. The set-up used to measure the fire-resistance properties is shown in the inset of 8,39 As shown in A substantial reduction in smoke release and other harmful chemical fumes is observed. This reduction in smoke can be attributed to the inorganic nature of the vermiculite nanofiller. Its water content and intercalated ions enhance the formation of the char layer post-combustion. In the absence of the coating, the char layer formed is quite weak and often cracks into powdery ash, allowing gases to be released from the wood surface and form smoke. However, the presence of the coating leads to the formation of an enhanced thick char layer, which acts as an insulation barrier, preventing the gases from escaping and mixing with the air to form smoke.Wooden rods of varying diameter were coated five times using the 10 wt%, 20 wt%, or 30 wt% ex-VN–epoxy nanocomposite. The optimum fire-retardant effect in terms of combustion velocity and flame spread was observed for the 5 mm diameter rods. The thin 3 mm rod samples have the advantage of having less fuel for combustion. The 30 wt% nanocomposite coating shows superior fire-retardant properties, with the flame self-extinguishing within 2 s when ignited in the case of the 3 mm wooden rods, while the 5 mm samples took 8 s longer to extinguish. The flame spread is faster on the 3 mm wood samples, indicating a high combustion velocity. Hence, the 5 mm wooden rods can hold the flame static for a longer time and prevent it from spreading, as the cross-section of the sample is larger. As a result, the flame spreads gradually on the samples with larger cross-sections for the same coating thickness.k) values of exfoliated vermiculite allow it to act as a physical barrier forming interconnections over the wood surface.9 The dispersion of the compact ex-VN network is shown in Fig. S10.37 In addition to thermal conductivity, thermal diffusivity and thermal effusivity are important properties for heat transmission through the material and its surroundings. Thermal diffusivity through a material is expressed as:where α is the thermal diffusivity (m2 s−1), k is the thermal conductivity of the nanofiller (∼0.1 W m−1 K−1),9ρ is the density of the nanofiller (225 kg m−3) and CP is the specific heat capacity of the nanofiller (∼108 J kg−1 K−1). By substituting these values into the equation, the thermal diffusivity of vermiculite is calculated to be ∼4.11 × 10−6 m2 s−1. This diffusivity value is much lower than the reported values.40 During combustion, an ultra-small amount of thermal energy is transmitted through the material. Thermal effusivity is defined as:and its value is 1558 W (s)1/2 m−2 K−1. Although this value is slightly higher than the reported values,40 in terms of thermal conduction and mass transfer, the low-regime thermal conductivity leads to enhanced fire-retardant properties.41The reason that the exfoliated vermiculite nanosheets work as a fire-retardant film coating on wooden surfaces is a combination of three important factors. The mechanism is schematically depicted in −2). The temperature of a lighter flame is different in different areas of the flame. The high temperature zone of the lighter flame, i.e., the non-luminous zone, was used for the combustion analysis of wood. The temperature of the non-luminous zone is above ∼1500 K. We found that most of the lighter heat flux values in the literature were greater than ∼50 kW m−2.42 Thus, we used 50 kW m−2 as the approximate heat flux value to study the fire-retardant property of the wooden rods. Additionally, most materials are ignited with a heat flux between 10 and 20 kW m−2.43 In cone calorimetry studies, heat flux values in the range of 10–100 kW m−2 are typically used to study the peak heat release rate (PHRR), mass loss rate and ignition time of FR materials. Our observations of reductions in the mass loss, flame height, combustion velocity and smoke density corroborate the cone calorimetry measurements. These parameters were effectively used to evaluate the fire-retardant properties of vermiculite nanosheets–epoxy-coated wood.Heat flux is an important factor in the combustion analysis of materials, particularly wood-like structures, and is best described by the fire triangle . It is understood as the flow of energy per unit area per unit time  steady-state equation to probe the heat flux values through the vermiculite–epoxy-coated wooden rod. We considered the 1D steady-state because the rod dimensions seems to be 1D-like in nature.where ΔT is the temperature difference (T2 − T1), T2 is the temperature of the wood on the ignited side, and T1 is the temperature of the other side of the wooden rod. Here, T2 is ∼1000 K (close to the lighter temperature) and T1 is ∼300 K (room temperature). L is the length of the wooden rod , and k is the thermal conductivity of ex-VN–epoxy composites (∼0.1 W m−1 K−1). After substituting these values, the steady-state heat flux through the wooden rod was found to be ∼7 kW m−2, which is lower than that of most of the nanomaterials used for the study. Secondly, the presence of water molecules, which make up ∼10% of the composition between the layers of vermiculite, helps to reduce the release of toxic gases by reacting with them to produce less harmful by-products; it also reduces the heat release by absorbing heat for evaporation.8 Thirdly, under the conditions in which the ex-VN/epoxy nanocomposite coating catches fire, char formation occurs. The pyrolysis chain reaction is not sustained, thereby reducing thermal degradation to a great extent. During the combustion, vermiculite layer creates more char due to the metal ions  in its structure.44,45 The produced char forms a protective layer on the substrate, which cuts off the oxygen supply, thus inhibiting the combustion reaction and extinguishing the flame. The black char between the ignition source and the material that has not undergone combustion acts as an oxygen-trapping barrier.46,47 As a result, the trapped oxygen is unable to reach the wooden surface beneath, and the combustion process does not take place in the absence of oxygen. It has also been noted that the ability of vermiculite to retain its structure is maintained even after repeated ignitions. To probe the fire-retardant mechanism, the surfaces of a wooden rod coated with ex-VN and a control sample were analyzed using electron microscopy, and the images are shown in The heat flux formula for 1D conduction is:Vermiculite has a variety of metal ions and few interchangeable cations in its structure. To confirm the presence of nanosheets in the epoxy, we conducted energy dispersive X-ray analysis (EDAX) and elemental mapping; the resulting images are shown in via a broken char layer, which is known as the blowing-out effect.48 Vermiculite contains fire-resistant compounds such as SiO2, Al2O3 and MgO, which are responsible for the formation of inert gas from the char layer. During combustion, vermiculite releases H2O, CO2, NO and SO2.49 These gases are all well-known fire extinguishers.The inclusion of the exfoliated vermiculite nanosheets in the epoxy matrix successfully introduces flame-retardant characteristics to the nanocomposite, such as decreased combustion velocity, flame extinguishing, decreased flame height and heat release rate, and suppression of toxic smoke release, as well as reduced thermal degradation of the wooden sample. Demonstration of the fire-retardant behaviour of wood with and without ex-VN in epoxy is shown in the ESI Video.i.e., the condensed portion, extinguishes the fire.50 During combustion, a thermally stable thin layer is formed between the wood surface and the fire. This char layer insulates the wood from fire and instantaneously forms non-flammable gases inside the char. The accumulation of the non-flammable gases in char leads to increased pressure, and these gases then completely extinguish the fire.49 In our experiments, there was a remarkable decrease in the thermal degradation of the wooden substrate beneath the coating due to the introduction of vermiculite nanosheets in the nanocomposite. The heat flow always chooses the path which offers less resistance. Vermiculite provides more resistance to heat flow through the coating due to its low value of through-plane thermal conductivity. For this reason, heat does not travel across the surface of the coating. Therefore, the coating can prevent the heat from penetrating into the wooden substrate, thus preserving its integrity after the fire testing. Thus, vermiculite can stop heat from reaching deeper into the samples by forming a physical barrier to heat flow. This is indicative of the fact that vermiculite can withstand heat without undergoing any considerable chemical changes or damages to its internal structure.The jetting of these gases outward from the char layer, Bulk vermiculite samples were received from Tamil Nadu Minerals Limited, Chennai, India. Apcolite 2 pack epoxy finish was purchased from Asian Paints. Sodium dodecyl benzene sulphonate (SDBS) was purchased from Sigma Aldrich. Acetone with 99.5% purity was used in this work and was purchased from S. R. L. Chemicals. Distilled water was used throughout the experiments. Wood samples with a length of 10 cm and diameters of 3 mm, 5 mm and 10 mm were procured from local woodworks, and commercial emery paper was used to polish their surfaces before painting. A commercial lighter was used for fire testing.26 For this, initially, 10 g of grade 5  bulk vermiculite was added to 500 ml of water with 0.8 mg ml−1 dissolved SDBS. This dispersion was subjected to exfoliation using a kitchen blender for 1 h with an on and off timer to avoid heating effects. After this step, the resultant dispersion was allowed to stand overnight, and the supernatant was recovered using a Pasteur pipette for further dispersion analysis and characterization; the sediment was discarded. Centrifugation of the resultant dispersion was performed at 6000 rpm for 30 min using a Thermo Scientific Sorvall ST8R small benchtop centrifuge to recover the exfoliated vermiculite nanosheets in paste form; the nanosheets were then dried in a vacuum oven at 60 °C for ∼8 h. The exfoliated vermiculite nanosheets were redispersed in acetone using bath sonication. This process was repeated twice to transfer the material from the aqueous solution to acetone solvent, and bath sonication was applied for 30 min to homogenize the sample.In this work, we used a liquid-phase exfoliation technique, namely, shear exfoliation, to delaminate the bulk vermiculite into thin layers of the parent component in a water/SDBS surfactant dispersion.via the in situ polymerization of the epoxy monomer with a hardener in the presence of the nanofiller. Acetone is used as a paint thinner and solvent medium for ex-VN. To prepare the epoxy/ex-VN nanocomposite, 50 mg of ex-VN  was initially added to 634 mg of epoxy and bath-sonicated  for 30 min to disperse the nanofiller in the epoxy. After this step, 316 mg of hardener (3 : 1 ratio of epoxy to hardener) was added to the ex-VN/epoxy monomer, and bath sonication was applied again to disperse the hardener throughout the system. This process was repeated to prepare the 10, 20 and 30 wt% nanocomposites. Acetone was used in the nanocomposite preparation process for homogenization and for thinning the formulated paint before coating it on the wood. Upon the addition of ex-VN into the epoxy matrix, there was a notable change in the colour of the epoxy. The epoxy–hardener is pure white in appearance, and the ex-VN/epoxy ink is essentially light brown. The mixing of these two results in a change in the colour of the matrix; the coating mix is light brown in colour and becomes russet or dark brown when the weight percentage is high.The coating paint was formulated using a commercial epoxy (Asian Paints) filled with various weight percentages of ex-VN. The coating was prepared All the teak wood samples were treated with electro-coated SiC grain emery paper of 220 grit size to improve the adhesion. The as-received epoxy polymerized with a cross-linking agent was also prepared as per the mixing requirements and used as the control sample. The preparation of the control coating did not require bath sonication as it could be homogenized with mechanical stirring. All the samples were coated using flat brushes. The interval between the application of each coat was approximately 2 min, and the specimens were cured at room temperature for 24 h.−1. Fourier transform infrared spectra were obtained using an IRTracer 100 (Shimadzu) in ATR mode. A custom-made Underwriters Laboratory-94 fire retardant standard test was performed on wood samples 10 cm in height and 10 mm in diameter to characterize the fabricated ex-VN/epoxy nanocomposites.A field emission scanning electron microscope  was operated at 15 kV to obtain the morphology, elemental composition, and mapping of the charred and uncharred regions of the coated samples. A turbo-pumped sputter coater  was used to cover the sample surface with Cr before placing the samples under an electron microscope to avoid charging effects, with a sputtering time of 25 s and a film thickness of ∼7 to 10 nm. Transmission electron microscopy (TEM) analysis of the exfoliated vermiculite nanosheets was carried out using a Hi-Resolution Transmission Electron Microscope . Images were also obtained using an Olympus BX51 optical microscope. Thermogravimetric analysis (TGA) was carried out using a simultaneous thermogravimetric analyzer  in an Ar atmosphere with a rate of 10° C mink vermiculite filler into the matrix was found to reduce the flame height and, consequently, the heat released during combustion by up to ∼62% in the case of the 10 wt% sample. The thermal degradation tests showed a decrease of ∼42% due to the addition of exfoliated vermiculite nanosheets. A 68.3% decrease in combustion velocity was observed for the samples with 30% vermiculite by weight in their matrix. It was also observed that the samples without vermiculite showed no self-extinguishing properties and burned to completion, thereby leading to the complete disintegration of the wooden structure beneath the coating. This work opens up new opportunities for using insulating layered 2D materials to resolve common issues related to fire retardants and to develop alternative environmentally friendly, high-performance materials.In this work, we have demonstrated an eco-efficient fire-retardant coating using epoxy filled with shear exfoliated vermiculite nanosheets on a wooden surface. A simple and scalable brush-coating technique was used, and a film thickness of ∼100 μm was achieved. Fire tests were performed on samples with varying weight percentages of vermiculite nanosheet filler (5–30 wt%) in the epoxy matrix to test the effect of the vermiculite loading. The introduction of the low-E. V. initiated the idea and designed experiments. A. S. and A. M. prepared vermiculite nanosheets and ex-VN/epoxy composites. A. S. characterized samples by TEM, SEM, EDAX and OM. A. M., A. S. and A. B. performed the fire testing, UL-94 and recorded observations. E. V., A. S., A. M. carried out result analysis and drafted the initial manuscript. E. V., H. W. and K. O. revised the manuscript. All authors contributed to the revision and discussion of the manuscript.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.NA-003-D1NA00207D-s001NA-003-D1NA00207D-s002


Wnt10b and thereby promoted the nuclear translocation of β-catenin in SSCs. Importantly, the suppression of Wnt/β-catenin signaling restored both the cytoplasmic expression of β-catenin and SSC maintenance in BMI1-deficient SSCs. Finally, we demonstrated that Wnt/β-catenin signaling was also involved in BMI1-mediated SSC maintenance in vivo. Altogether, our study not only reveals a novel mechanism for BMI1 in the process of SSC maintenance, but also provides a potential new strategy for treating male infertility.The self-renewal of spermatogonial stem cells (SSCs) requires a special microenvironment and is strictly controlled. Previously, we identified BMI1 as a key regulator of spermatogenesis in a knock-out mouse model. However, the mechanisms by which BMI1 regulates SSC maintenance remain largely unknown. Herein, we show that BMI1 is essential for SSC maintenance. BMI1 directs the transcriptional repression of target genes by increasing H2AK119ub and reducing H3K4me3 in SSCs. Furthermore, BMI1 inhibition resulted in the transcriptional activation of  Spermatogonial stem cells (SSCs) originate from a population of the most primitive spermatogonia, which have the capacity for self-renewal and differentiation, and can maintain spermatogenesis throughout a man's lifetime Bmi1 knock-out mice showed impaired mitochondrial function and excessive reactive oxygen species (ROS) production, which resulted in defective hematopoietic cell self-renewal, premature ageing phenotypes, and a shortened lifespan Bmi1 knock-out mice exhibited impaired spermatogenesis, reduced serum testosterone levels, and male infertility in vitroPtprm, the gene encoding Protein tyrosine phosphatase receptor type M (PTPRM) BMI1 is a component of the Polycomb repressive complex 1 (PRC1), whose function is to epigenetically repress targeted genes The Wnt signaling pathway is largely comprised of the canonical Wnt/β-catenin pathway and the noncanonical polarity pathway Wnt10b expression and the subsequent nuclear translocation of β-catenin both in vitro and in vivo. Our data strongly indicate that BMI1 is a crucial epigenetic mediator in SSC maintenance, and provide new targets for the treatment of male infertility.In this study, we predominantly focused on the role and regulatory mechanism of BMI1 in SSC maintenance, and demonstrate that BMI1 is essential for SSC maintenance by epigenetically repressing Bmi1 mutant mice were maintained in a specific-pathogen-free (SPF) grade experimental animal center of Nanjing Medical University. Bmi1 heterozygous (+/-) mice were intercrossed to obtain Bmi1 homozygous  mice, which were genotyped by PCR amplification, as previously described in vitro murine SSC cultures was previously described 2.The establishment of long-term w/v) paraformaldehyde (PFA) for 15 minutes, blocked with 1% (w/v) bovine serum albumin  for 2 hours at room temperature, and then labeled with the indicated primary antibodies (w/v) PFA, dehydrated, embedded in paraffin, and cut into 5 μm sections. Sections were deparaffinized, rehydrated, and further labeled with the indicated primary antibodies , and the protein concentrations were assayed using a BCA kit (Beyotime Institute of Biotechnology) according to the manufacturer's instructions. Western blotting analysis was performed according to a routine protocol as previously reported Cell Counting Kit-8 (CCK-8) (Beyotime Institute of Biotechnology) was used to measure SSCs viability, according to the manufacturer's instructions. Shortly, SSCs were seeded into a feeder-free 96-well plate at 2,000 cells/well. The time point of cell seeding was identified as 0 hours. For each time point, the CCK-8 solution was added to the wells at a dilution of 1:200 and incubated for 2 hours. Thereafter, the absorbance at 450 nm was assayed using a microplate reader .Cellular apoptosis was detected using a Terminal deoxynucleotidyl transferase-dUTP nick-end labeling (TUNEL) kit , according to the manufacturer's instructions. Apoptotic signals were observed using an LSM810 confocal laser microscope (Carl Zeiss).SSCs were harvested and separated from feeder cells by gentle pipetting, reaching > 90% purity Total RNA was extracted using the TRIzol reagent (Invitrogen), and subsequently reverse transcribed into cDNA using a HiScript III 1st Strand cDNA Synthesis Kit (Vazyme), according to the manufacturer's instructions. PCR reactions were run on an ABI 7500 system , using a SYBR green qPCR MasterMix (Vazyme). 18S rRNA was used as a reference control. The primers used for quantitative real-time PCR are listed in Gapdh  gene was used as a negative control.The ChIP assay was carried out using an EZ-Magna ChIP Kit (Millipore), as previously described P-values were calculated using a Student's t-test or one-way ANOVA followed by post-hoc Dunnett test with * P < 0.05; **P < 0.01; ***P < 0.001 denoting significance.GraphPad Prism 8 software was used for statistical analysis. Bmi1 was involved in controlling SSC maintenance, we established an in vitro murine SSC culture system, in which SSCs were cultured with feeder cells and growth factors, as previously described To test whether To further investigate the roles of BMI1 in SSC maintenance, we examined the cell cycle dynamics of SSCs by flow cytometry after they were treated for 48 hours with PTC-209. After treatment with 5 μM PTC-209, BMI1-deficient SSCs were arrested at G0/G1 phase, with a marked decline in cells in the G2/M phase and an unaltered S phase distribution   28932 3A)Esrrb, Inhba, Meis1, Nodal, Otx1, Wnt10b, and Zic3) out of the 21 BMI1 targets  is the catalytic subunit of Polycomb repressive complex 2 (PRC2), which play conserved roles in catalyzing the transcriptional repression of target genes via the trimethylation of Lys27 on histone H3 (H3K27me3) Taken together, these results indicate that BMI1 mediates transcriptional repression and modulates chromatin accessibility via H2AK119ub and H3K4me3, independently of the PRC2 complex.Wnt10b was the most up-regulated target of BMI1 in PTC-209-treated SSCs  compared to wild-type (+/+Bmi1) mice  resulted in testicular atrophy and decreased the proliferation of undifferentiated spermatogonia, subsequently triggering germ cell maintenance defects β-catenin under the control of Prm1-Cre led to significant germ cell loss, increased germ cell apoptosis, and impaired fertility β-catenin in differentiating spermatogonia and early spermatocytes under the control of Stra8-Cre did not affect male fertility and spermatogenesis β-catenin in germ cell development, gain-of-function studies of β-catenin in vivo also elicit conflicting data. It was reported that the constitutive activation of β-catenin in the primordial germ cells (PGCs) in the Ctnnb1tm1Mmt/tm1Mmt; TNAPcre/+ model markedly reduced PGC numbers and induced cycle arrest in these cells tm1Mmt/tm1Mmt; Ddx4cre/+ model showed that the constitutive activation of β-catenin in fetal gonocytes triggered SSC proliferation and spermatocyte depletion tm1Mmt/tm1Mmt; Ddx4cre/+ model, Boyer et al., found that the constitutive activation of β-catenin in fetal gonocytes compromised SSCs activity and promoted SSCs differentiation tm1Mmt/tm1Mmt; Nanos3cre/+ model reduced the GFRα1+ SSC pool tm1Mmt/tm1Mmt; Amhcre/+ mouse model led to testis malformation and germ cell depletion from embryonic day 15.5 onwards tm1Mmt/tm1Mmt; Amhr2cre/+ mouse model caused a progressive loss of germ cells and attenuated SSC activity due to SSC niche disruption Recent studies have indicated that the action of Wnt/β-catenin signaling was more complex than previously thought, and that β-catenin was able to induce various reproductive phenotypes in different mouse models. For instance, the genetic elimination of in vitro and in vivo approaches. Unlike the pro-proliferative activity of Wnt6 in SSCs In this study, we systematically explored the role of the BMI1/Wnt/β-catenin signaling axis in SSC maintenance, using both in vitro and in vivo approaches, we revealed a novel regulatory mechanism of BMI1-mediated Wnt/β-catenin signaling in SSCs, providing potential therapeutic targets for the clinical diagnosis and treatment of SSC maintenance defects.In conclusion, to the best of our knowledge, the present study for the first time reveals the major role of BMI1 in SSC maintenance via autonomous cell effects. Using Supplementary figures and tables.Click here for additional data file.