Sec22b is a critical and nonredundant regulator of plasma cell maintenance.

Despite the essential role of plasma cells in health and disease, the cellular mechanisms controlling their survival and secretory capacity are still poorly understood. Here, we identified the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) Sec22b as a unique and critical regulator of plasma cell maintenance and function. In the absence of Sec22b, plasma cells were hardly detectable and serum antibody titers were dramatically reduced. Accordingly, Sec22b-deficient mice fail to mount a protective immune response. At the mechanistic level, we demonstrated that Sec22b contributes to efficient antibody secretion and is a central regulator of plasma cell maintenance through the regulation of their transcriptional identity and of the morphology of the endoplasmic reticulum and mitochondria. Altogether, our results unveil an essential and nonredundant role for Sec22b as a regulator of plasma cell fitness and of the humoral immune response.

Global genome decompaction leads to stochastic activation of gene expression as a first step toward fate commitment in human hematopoietic cells.

When human cord blood-derived CD34+ cells are induced to differentiate, they undergo rapid and dynamic morphological and molecular transformations that are critical for fate commitment. In particular, the cells pass through a transitory phase known as "multilineage-primed" state. These cells are characterized by a mixed gene expression profile, different in each cell, with the coexpression of many genes characteristic for concurrent cell lineages. The aim of our study is to understand the mechanisms of the establishment and the exit from this transitory state. We investigated this issue using single-cell RNA sequencing and ATAC-seq. Two phases were detected. The first phase is a rapid and global chromatin decompaction that makes most of the gene promoters in the genome accessible for transcription. It results 24 h later in enhanced and pervasive transcription of the genome leading to the concomitant increase in the cell-to-cell variability of transcriptional profiles. The second phase is the exit from the multilineage-primed phase marked by a slow chromatin closure and a subsequent overall down-regulation of gene transcription. This process is selective and results in the emergence of coherent expression profiles corresponding to distinct cell subpopulations. The typical time scale of these events spans 48 to 72 h. These observations suggest that the nonspecificity of genome decompaction is the condition for the generation of a highly variable multilineage expression profile. The nonspecific phase is followed by specific regulatory actions that stabilize and maintain the activity of key genes, while the rest of the genome becomes repressed again by the chromatin recompaction. Thus, the initiation of differentiation is reminiscent of a constrained optimization process that associates the spontaneous generation of gene expression diversity to subsequent regulatory actions that maintain the activity of some genes, while the rest of the genome sinks back to the repressive closed chromatin state.

Differentiation is accompanied by a progressive loss in transcriptional memory.

BACKGROUND: Cell differentiation requires the integration of two opposite processes, a stabilizing cellular memory, especially at the transcriptional scale, and a burst of gene expression variability which follows the differentiation induction. Therefore, the actual capacity of a cell to undergo phenotypic change during a differentiation process relies upon a modification in this balance which favors change-inducing gene expression variability. However, there are no experimental data providing insight on how fast the transcriptomes of identical cells would diverge on the scale of the very first two cell divisions during the differentiation process. RESULTS: In order to quantitatively address this question, we developed different experimental methods to recover the transcriptomes of related cells, after one and two divisions, while preserving the information about their lineage at the scale of a single cell division. We analyzed the transcriptomes of related cells from two differentiation biological systems (human CD34+ cells and T2EC chicken primary erythrocytic progenitors) using two different single-cell transcriptomics technologies (scRT-qPCR and scRNA-seq). CONCLUSIONS: We identified that the gene transcription profiles of differentiating sister cells are more similar to each other than to those of non-related cells of the same type, sharing the same environment and undergoing similar biological processes. More importantly, we observed greater discrepancies between differentiating sister cells than between self-renewing sister cells. Furthermore, a progressive increase in this divergence from first generation to second generation was observed when comparing differentiating cousin cells to self renewing cousin cells. Our results are in favor of a gradual erasure of transcriptional memory during the differentiation process.

In Vivo Raman Spectroscopy of Muscle Is Highly Sensitive for Detection of Healthy Muscle and Highly Specific for Detection of Disease.

Raman spectroscopy of muscle provides a molecular fingerprint to identify the disease. Previous work has demonstrated effectiveness in differentiating between two groups of equal sizes (e.g., healthy vs disease) but imbalanced multiclass scenarios are more common in medicine. We performed in vivo Raman spectroscopy in a total of 151 mice across four different histopathologies (healthy, acute myopathy, chronic myopathy, neurogenic), with variable numbers in each (class "imbalance"). Using hierarchical modeling and synthetic data generation, we demonstrate high sensitivity (94%) for detection of healthy muscle and high specificity (≥97%) for disease. Further, we demonstrate the potential for unique biomarker development by demonstrating variations in the protein structure across different pathologies. The findings demonstrate the potential of Raman spectroscopy to provide accurate disease identification and unique molecular insights.

Integrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment.

Individual cells take lineage commitment decisions in a way that is not necessarily uniform. We address this issue by characterising transcriptional changes in cord blood-derived CD34+ cells at the single-cell level and integrating data with cell division history and morphological changes determined by time-lapse microscopy. We show that major transcriptional changes leading to a multilineage-primed gene expression state occur very rapidly during the first cell cycle. One of the 2 stable lineage-primed patterns emerges gradually in each cell with variable timing. Some cells reach a stable morphology and molecular phenotype by the end of the first cell cycle and transmit it clonally. Others fluctuate between the 2 phenotypes over several cell cycles. Our analysis highlights the dynamic nature and variable timing of cell fate commitment in hematopoietic cells, links the gene expression pattern to cell morphology, and identifies a new category of cells with fluctuating phenotypic characteristics, demonstrating the complexity of the fate decision process (which is different from a simple binary switch between 2 options, as it is usually envisioned).

Combination of imaging flow cytometry and time-lapse microscopy for the study of label-free morphology dynamics of hematopoietic cells.

Cell differentiation is a longitudinal and dynamic process. Studying and quantifying such a process require tools combining precise time resolution and statistical power. Imaging flow cytometry (IFC) provides statistically significant number of microscopy images of individual cells in a sample at a given time point. Time-lapse microscopy (TLM) is the method of choice for studying the dynamics of cell processes at a high temporal, but low statistical resolution. In this work, we show that the dynamic changes of cord-blood derived CD34+ cells in response to cytokine stimulation can be successfully studied, in a label-free way, by the combination of the IFCs statistical power and the TLM's high time resolution. Cell morphology phenotypes were quantified through roundness and surface area, measured both in IFC and with a homemade segmentation algorithm in TLM. Two distinct morphologies-polarized and round-were observed in cord-blood derived CD34+. We show that some cells have the ability to fluctuate between these morphologies, suggesting that the apparent stable composition of round and polarized cells may actually represent a dynamic equilibrium. This example demonstrates that the different resolutions and modalities of IFC and TLM are complementary and allow the study of complex dynamic biological processes. © 2017 International Society for Advancement of Cytometry.

Inhibition of the myostatin/Smad signaling pathway by short decorin-derived peptides.

Myostatin, also known as growth differentiation factor 8, is a member of the transforming growth factor-beta superfamily that has been shown to play a key role in the regulation of the skeletal muscle mass. Indeed, while myostatin deletion or loss of function induces muscle hypertrophy, its overexpression or systemic administration causes muscle atrophy. Since myostatin blockade is effective in increasing skeletal muscle mass, myostatin inhibitors have been actively sought after. Decorin, a member of the small leucine-rich proteoglycan family is a metalloprotein that was previously shown to bind and inactivate myostatin in a zinc-dependent manner. Furthermore, the myostatin-binding site has been shown to be located in the decorin N-terminal domain. In the present study, we investigated the anti-myostatin activity of short and soluble fragments of decorin. Our results indicate that the murine decorin peptides DCN48-71 and 42-65 are sufficient for inactivating myostatin in vitro. Moreover, we show that the interaction of mDCN48-71 to myostatin is strictly zinc-dependent. Binding of myostatin to activin type II receptor results in the phosphorylation of Smad2/3. Addition of the decorin peptide 48-71 decreased in a dose-dependent manner the myostatin-induced phosphorylation of Smad2 demonstrating thereby that the peptide inhibits the activation of the Smad signaling pathway. Finally, we found that mDCN48-71 displays a specificity towards myostatin, since it does not inhibit other members of the transforming growth factor-beta family.

Improving Interpretability of Leucocyte Classification with Multimodal Network.

White blood cell classification plays a key role in the diagnosis of hematologic diseases. Models can perform classification either from images or based on morphological features. Image-based classification generally yields higher performance, but feature-based classification is more interpretable for clinicians. In this study, we employed a Multimodal neural network to classify white blood cells, utilizing a combination of images and morphological features. We compared this approach with image-only and feature-only training. While the highest performance was achieved with image-only training, the Multimodal model provided enhanced interpretability by the computation of SHAP values, and revealed crucial morphological features for biological characterization of the cells.

Trem2-expressing multinucleated giant macrophages are a biomarker of good prognosis in head and neck squamous cell carcinoma.

Patients with head and neck squamous cell carcinomas (HNSCC) often have poor outcomes due to suboptimal risk-management and treatment strategies; yet integrating novel prognostic biomarkers into clinical practice is challenging. Here, we report the presence of multinucleated giant cells (MGC) - a type of macrophages - in tumors from patients with HNSCC, which are associated with a favorable prognosis in treatment-naive and preoperative-chemotherapy-treated patients. Importantly, MGC density increased in tumors following preoperative therapy, suggesting a role of these cells in the anti-tumoral response. To enable clinical translation of MGC density as a prognostic marker, we developed a deep-learning model to automate its quantification on routinely stained pathological whole slide images. Finally, we used spatial transcriptomic and proteomic approaches to describe the MGC-related tumor microenvironment and observed an increase in central memory CD4 T cells. We defined an MGC-specific signature resembling to TREM2-expressing mononuclear tumor associated macrophages, which co-localized in keratin tumor niches.

Artificial intelligence workflow quantifying muscle features on Hematoxylin-Eosin stained sections reveals dystrophic phenotype amelioration upon treatment.

Cell segmentation is a key step for a wide variety of biological investigations, especially in the context of muscle science. Currently, automated methods still struggle to perform skeletal muscle fiber quantification on Hematoxylin-Eosin (HE) stained histopathological whole slide images due to low contrast. On the other hand, the Deep Learning algorithm Cellpose offers new perspectives considering its increasing adoption for segmentation of a wide range of cells. Combining two open-source tools, Cellpose and QuPath, we developed MyoSOTHES, an automated Myofibers Segmentation wOrkflow Tuned for HE Staining. MyoSOTHES enables solving segmentation inconsistencies encountered by default Cellpose model in presence of large range size cells and provides information related to muscle Feret's diameter distribution and Centrally Nucleated Fibers, thus depicting muscle health and treatment effects. MyoSOTHES achieves high quality segmentation compared to baseline workflow with a detection F1-score increasing from 0.801 to 0.919 and a Root Mean Square Error (RMSE) on diameter improved by 31%. MyoSOTHES was validated on an animal study featuring gene transfer in [Formula: see text]-Sarcoglycanopathy, for which dose-response effect is visible and conclusions drawn are consistent with those previously published. MyoSOTHES thus paves the way for wide quantification of HE stained muscle sections and retrospective analysis of HE labeled slices used in laboratories for decades.