Hyaluronan, a key component of the extracellular matrix, plays a crucial role in joint development and maintenance. In order to determine the role of hyaluronan function in joint development and homeostasis, conditional loss-of-function experiments of Hyaluronan Synthase 2 (Has2) were carried out in mice. Has2 depletion in limb mesenchymal cells led to severely shortened limbs with appendicular joints that are deformed, decreased proteoglycan content as characterized by Safranin-O staining, and severely pitted epiphyseal ends of long bones and deformed joints as viewed by micro-CT reconstructions. The embryonic deletion of Has2 in mesoderm mesenchyme of limbs by Prx1-Cre confirmed its involvement in joint development, while in situ hybridization and hyaluronan staining confirmed Has2 expression and abundant accumulation of hyaluronan in the onset of joint formation, the joint interzone. These findings position Has2 as the main hyaluronan-making enzyme in articular cartilage and highlight its essential function in joint formation and retention of proteoglycans of the extracellular matrix of the cartilage.

Heterotopic ossifications (HOs) are the pathologic process by which bone inappropriately forms outside of the skeletal system. Despite HOs being a persistent clinical problem in the general population, there are no definitive strategies for their prevention and treatment due to a limited understanding of the cellular and molecular mechanisms contributing to lesion development. One disease in which the development of heterotopic subcutaneous ossifications (SCOs) leads to morbidity is Albright hereditary osteodystrophy (AHO). Albright hereditary osteodystrophy is caused by heterozygous inactivation of GNAS, the gene that encodes the α-stimulatory subunit (Gαs) of G proteins. Previously, we had shown using our laboratory's AHO mouse model that SCOs develop around hair follicles. Here we show that SCO formation occurs due to inappropriate expansion and osteogenic differentiation of cells that express alpha-smooth muscle actin and that are located within the dermal sheath. We also show in AHO patients and mice that secreted frizzled related protein 2 (SFRP2) expression is upregulated in regions of SCO formation and that elimination of Sfrp2 in male AHO mice leads to earlier development, greater severity, and acceleration of formation of SCOs. These studies provide key insights into the cellular and molecular mechanisms contributing to SCO development and have implications for potential therapeutic modalities not only for AHO patients but also for patients suffering from HOs with other etiologies.

In the original publication [...].

Heterotopic ossifications (HOs) are the pathologic process by which bone inappropriately forms outside of the skeletal system. Despite HOs being a persistent clinical problem in the general population, there are no definitive strategies for their prevention and treatment due to a limited understanding of the cellular and molecular mechanisms contributing to lesion development. One disease in which the development of heterotopic subcutaneous ossifications (SCOs) leads to morbidity is Albright hereditary osteodystrophy (AHO). AHO is caused by heterozygous inactivation of GNAS, the gene that encodes the α-stimulatory subunit (Gαs) of G proteins. Previously, we had shown using our laboratory's AHO mouse model that SCOs develop around hair follicles (HFs). Here we show that SCO formation occurs due to inappropriate expansion and differentiation of HF-resident stem cells into osteoblasts. We also show in AHO patients and mice that Secreted Frizzled Related Protein 2 (SFRP2) expression is upregulated in regions of SCO formation and that elimination of Sfrp2 in male AHO mice exacerbates SCO development. These studies provide key insights into the cellular and molecular mechanisms contributing to SCO development and have implications for potential therapeutic modalities not only for AHO patients but also for patients suffering from HOs with other etiologies.

Single cell RNA sequencing technology has been dramatically changing how gene expression studies are performed. However, its use has been limited to identifying subtypes of cells by comparing cells' gene expression levels in an unbiased manner to produce a 2D plot (e.g., UMAP/tSNE). We developed a new method of placing cells in 2D space. This system, called vSPACE, shows a virtual spatial representation of scRNAseq data obtained from human articular cartilage by emulating the concept of spatial transcriptomics technology, but virtually. This virtual 2D plot presentation of human articular cartage cells generates several zonal distribution patterns, in one or multiple genes at a time, reveling patterns that scientists can appreciate as imputed spatial distribution patterns along the zonal axis. The discovered patterns are explainable and remarkably consistent across all six healthy doners despite their respectively different clinical variables (age and sex), suggesting the confidence of the discovered patterns.

Cell-cell communication is crucial in maintaining cellular homeostasis, cell survival and various regulatory relationships among interacting cells. Thanks to recent advances of spatial transcriptomics technologies, we can now explore if and how cells' proximal information available from spatial transcriptomics datasets can be used to infer cell-cell communication. Here we present a cell-cell communication inference framework, called CGCom, which uses a graph neural network (GNN) to learn communication patterns among interacting cells by combining single-cell spatial transcriptomic datasets with publicly available ligand-receptor information and the molecular regulatory information down-stream of the ligand-receptor signaling. To evaluate the performance of CGCom, we applied it to mouse embryo seqFISH datasets. Our results demonstrate that CGCom can not only accurately infer cell communication between individual cell pairs but also generalize its learning to predict communication between different cell types. We compared the performance of CGCom with two existing methods, CellChat and CellPhoneDB, and our comparative study revealed both common and unique communication patterns from the three approaches. Commonly found communication patterns include three sets of ligand-receptor communication relationships, one between surface ectoderm cells and spinal cord cells, one between gut tube cells and endothelium, and one between neural crest and endothelium, all of which have already been reported in the literature thus offering credibility of all three methods. However, we hypothesize that CGCom is superior in reducing false positives thanks to its use of cell proximal information and its learning between specific cell pairs rather than between cell types. CGCom is a GNN-based solution that can take advantage of spatially resolved single-cell transcriptomic data in predicting cell-cell communication with a higher accuracy.

Albright hereditary osteodystrophy (AHO) is caused by heterozygous inactivation of GNAS, a complex locus that encodes the alpha-stimulatory subunit of GPCRs (Gsα) in addition to NESP55 and XLαs due to alternative first exons. AHO skeletal manifestations include brachydactyly, brachymetacarpia, compromised adult stature, and subcutaneous ossifications. AHO patients with maternally-inherited GNAS mutations develop pseudohypoparathyroidism type 1A (PHP1A) with resistance to multiple hormones that mediate their actions through GPCRs requiring Gsα (eg., PTH, TSH, GHRH, calcitonin) and severe obesity. Paternally-inherited GNAS mutations cause pseudopseudohypoparathyroidism (PPHP), in which patients have AHO skeletal features but do not develop hormonal resistance or marked obesity. These differences between PHP1A and PPHP are caused by tissue-specific reduction of paternal Gsα expression. Previous reports in mice have shown loss of Gsα causes osteopenia due to impaired osteoblast number and function and suggest AHO patients could display evidence of reduced bone mineral density (BMD). However, we previously demonstrated PHP1A patients display normal-increased BMD measurements without any correlation to body mass index or serum PTH. Due to these observed differences between PHP1A and PPHP, we utilized our laboratory’s AHO mouse model to address whether Gsα heterozygous inactivation by the targeted disruption of exon 1 of Gnas differentially affects bone remodeling based on the parental inheritance of the mutation. Mice with paternally-inherited (GnasE1+/−p) and maternally-inherited (GnasE1+/−m) mutations displayed reductions in osteoblasts along the bone surface compared to wildtype. GnasE1+/−p mice displayed reduced cortical and trabecular bone parameters due to impaired bone formation and excessive bone resorption. GnasE1+/−m mice however displayed enhanced bone parameters due to increased osteoblast activity and normal bone resorption. These distinctions in bone remodeling between GnasE1+/−p and GnasE1+/−m mice appear to be secondary to changes in the bone microenvironment driven by calcitonin-resistance within GnasE1+/−m osteoclasts and therefore warrant further studies into understanding how Gsα influences osteoblast-osteoclast coupling interactions.

Background Interferon regulatory factor-8 (IRF8) and nuclear factor-activated T cells c1 (NFATc1) are two transcription factors that have an important role in osteoclast differentiation. Thanks to ChIP-seq technology, scientists can now estimate potential genome-wide target genes of IRF8 and NFATc1. However, finding target genes that are consistently up-regulated or down-regulated across different studies is hard because it requires analysis of a large number of high-throughput expression studies from a comparable context. Method We have developed a machine learning based method, called, Cohort-based TF target prediction system (cTAP) to overcome this problem. This method assumes that the pathway involving the transcription factors of interest is featured with multiple “functional groups” of marker genes pertaining to the concerned biological process. It uses two notions, Gene-Present Sufficiently (GP) and Gene-Absent Insufficiently (GA), in addition to log2 fold changes of differentially expressed genes for the prediction. Target prediction is made by applying multiple machine-learning models, which learn the patterns of GP and GA from log2 fold changes and four types of Z scores from the normalized cohort’s gene expression data. The learned patterns are then associated with the putative transcription factor targets to identify genes that consistently exhibit Up/Down gene regulation patterns within the cohort. We applied this method to 11 publicly available GEO data sets related to osteoclastgenesis. Result Our experiment identified a small number of Up/Down IRF8 and NFATc1 target genes as relevant to osteoclast differentiation. The machine learning models using GP and GA produced NFATc1 and IRF8 target genes different than simply using a log2 fold change alone. Our literature survey revealed that all predicted target genes have known roles in bone remodeling, specifically related to the immune system and osteoclast formation and functions, suggesting confidence and validity in our method. Conclusion cTAP was motivated by recognizing that biologists tend to use Z score values present in data sets for the analysis. However, using cTAP effectively presupposes assembling a sizable cohort of gene expression data sets within a comparable context. As public gene expression data repositories grow, the need to use cohort-based analysis method like cTAP will become increasingly important.

A transgenic mouse approach using bacterial artificial chromosomes (BAC) was used to identify regulatory regions that direct Müllerian duct expression for Amhr2 and Osterix (Osx, also known as Sp7). Amhr2 encodes the receptor that mediates anti-Müllerian hormone (AMH) signaling for Müllerian duct regression in male embryos. Amhr2 is expressed in the Müllerian duct mesenchyme of both male and female embryos. A ∼147-kb BAC clone containing the Amhr2 locus was used to generate transgenic mice. The transgene was able to rescue the block in Müllerian duct regression of Amhr2-null males, suggesting that the BAC clone contains regulatory sequences active in male embryos. Osx is expressed in the developing skeleton of male and female embryos but is also an AMH-induced gene that is expressed in the Müllerian duct mesenchyme exclusively in male embryos. Osx-Cre transgenic mice were previously generated using a ∼204-kb BAC clone. Crosses of Osx-Cre mice to Cre-dependent lacZ reporter mice resulted in reporter expression in the developing skeleton and in the Müllerian duct mesenchyme of male but not female embryos. Osx-Cherry transgenic mice were previously generated using a 39-kb genomic region surrounding the Osx locus. Osx-Cherry embryos expressed red fluorescence in the developing skeleton and Müllerian duct mesenchyme of male but not female embryos. In addition, female Osx-Cherry embryos ectopically expressing human AMH from an Mt1-AMH transgene activated red fluorescence in the Müllerian duct mesenchyme. These results suggest that the 39-kb region used to generate Osx-Cherry contains male-specific Müllerian duct mesenchyme regulatory sequences that are responsive to AMH signaling. These BAC transgenic mouse approaches identify two distinct regions that direct Müllerian duct mesenchyme expression and contribute fundamental knowledge to define a gene regulatory network for sex differentiation.

With recent advances of single cell RNA (scRNA) sequencing technology, several methods have been proposed to infer cell-cell communication by analyzing ligand-receptor pairs. However, existing methods have limited ways of using what we call "prior knowledge", i.e., what are already known (albeit incompletely) about the upstream for the ligand and the downstream for the receptor. In this paper, we present a novel framework, called rCom, capable of inferring cell-cell interactions by considering portions of pathways that would be associated with upstream of the ligand and downstream of receptors under examination. The rCom framework integrates knowledge from multiple biological databases including transcription factor-target database, ligand-receptor database and publicly available curated signaling pathway databases. We combine both algorithmic methods and heuristic rules to score how each putative ligand-receptor pair may matchup between all possible cell subtype pairs. Permutation test is performed to rank the hypothesized cell-cell communication routes. We performed a case study using single cell transcriptomic data from bone biology. Our literature survey suggests that rCom could be effective in discovering novel cell-cell communication relationships that have been only partially known in the field.

Abstract Albright hereditary osteodystrophy (AHO) is caused by the heterozygous inactivation of GNAS, encoding the α-stimulatory subunit (Gαs) of G protein-coupled receptors. Skeletal manifestations of AHO include adult short stature, brachydactyly and subcutaneous ossifications. AHO patients with maternally-derived GNAS mutations develop pseudohypoparathyroidism type 1A (PHP1A) and are obese with resistance to hormones requiring Gαs (eg., PTH, TSH and GHRH) due to tissue-specific GNAS imprinting. Paternally-derived GNAS mutations cause pseudopseudohypoparathyroidism (PPHP) in which patients have AHO skeletal features but do not develop severe obesity or hormonal resistance. Mouse models have shown loss of Gα s signaling in osteoblasts or osteoclasts leads to osteopenia, and suggest AHO patients would display a reduced bone mineral density (BMD). Interestingly, PHP1A patients have been shown to have normal to increased BMD without any correlation to body mass index or serum PTH measurement. Based on the differences observed clinically and hormonally between PHP1A and PPHP, we hypothesize that there may also be distinctions in overall bone remodeling between these two disorders due to GNAS imprinting. This study addressed whether the heterozygous inactivation of Gnas differentially affects Gα s-receptor bioactivity within osteoclasts (OCs) based upon parental inheritance. Bone Marrow Macrophages (BMMs) were harvested from our laboratory’s AHO mouse model with either maternally-inherited (Gnas+/-m) mutations correlating to PHP1A or paternally-inherited (Gnas+/-p) mutations correlating to PPHP. BMMs were exposed to 10-7M salmon calcitonin (sCT), 10-5M forskolin or PBS for 6 hrs. OC receptor activity was measured by fluorescent microscopy to visualize actin ring morphology and RT-PCR analysis of Gα s-PKA signaling transcripts Crem and Ramp3. Forskolin treatment displayed no significant variations in OC ring morphology or Crem and Ramp3 mRNA expression between Gnas+/-m, Gnas+/-p and WT cultures. Both WT and Gnas+/-p OCs displayed appropriate responses to sCT, as indicated by a significant disruption in actin ring morphology and increased Crem and Ramp3 mRNA expression when compared to vehicle-treated controls. SCT-treated Gnas+/-m OCs, however, displayed only mild disruptions in actin ring morphology, and we observed significant reductions in Ramp3 expression compared to WT as well as reductions in Crem compared to WT and Gnas+/-p. These data suggest evidence of partial calcitonin resistance within Gnas+/-m OCs due to impaired Gα s- signaling. These data correlate with previous clinical observations of calcitonin resistance in PHP1A patients. Because these findings were observed only within Gnas+/-m cultures, future work is warranted to determine whether this impaired receptor activity may be attributed to partial Gnas imprinting within OCs or the myeloid lineage.

Cherubism is a rare genetic disorder caused primarily by mutations in SH3BP2 resulting in excessive bone resorption and fibrous tissue overgrowth in the lower portions of the face. Bone marrow derived cell cultures derived from a murine model of cherubism display poor osteogenesis and spontaneous osteoclast formation. To develop a deeper understanding for the potential underlying mechanisms contributing to these phenotypes in mice, we compared global gene expression changes in hematopoietic and mesenchymal cell populations between cherubism and wild type mice. In the hematopoietic population, not surprisingly, upregulated genes were significantly enriched for functions related to osteoclastogenesis. However, these upregulated genes were also significantly enriched for functions associated with inflammation including arachidonic acid/prostaglandin signaling, regulators of coagulation and autoinflammation, extracellular matrix remodeling, and chemokine expression. In the mesenchymal population, we observed down regulation of osteoblast and adventitial reticular cell marker genes. Regulators of BMP and Wnt pathway associated genes showed numerous changes in gene expression, likely implicating the down regulation of BMP signaling and possibly the activation of certain Wnt pathways. Analyses of the cherubism derived mesenchymal population also revealed interesting changes in gene expression related to inflammation including the expression of distinct granzymes, chemokines, and sulfotransferases. These studies reveal complex changes in gene expression elicited from a cherubic mutation in Sh3bp2 that are informative to the mechanisms responding to inflammatory stimuli and repressing osteogenesis. The outcomes of this work are likely to have relevance not only to cherubism, but other inflammatory conditions impacting the skeleton.

The IMPC/KOMP program provides the opportunity to screen mice harboring well defined gene-inactivation mutations in a uniform genetic background. The program performs a global tissue phenotyping survey that includes skeletal x-rays and bone density measurements. Because of the relative insensitivity of the two screening tests for detecting variance in bone architecture, we initiated a secondary screen based on μCT and a cryohistolomorphological workflow that was performed on the femur and vertebral compartments on 220 randomly selected knockouts (KOs) and 36 control bone samples over a 2 1/2 year collection period provided by one of the production/phenotyping centers. The performance of the screening protocol was designed to balance throughput and cost versus sensitivity and informativeness such that the output would be of value to the skeletal biology community. Here we report the reliability of this screening protocol to establish criteria for control skeletal variance at the architectural, dynamic and cellular histomorphometric level. Unexpected properties of the control population include unusually high variance in BV/TV in male femurs and greater bone formation and bone turnover rates in the female femur and vertebral trabeculae bone compartments. However, the manner for maintaining bone formation differed between these two bone sites. The vertebral compartment relies on maintaining a greater number of bone forming surfaces while the femoral compartment utilized more matrix production per cell. The comparison of the architectural properties obtained by μCT and histomorphology revealed significant differences in values for BV/TV, Tb.Th and Tb.N which is attributable to sampling density of the two methods. However, as a screening tool, expressing the ratio of KO to the control line as obtained by either method was remarkably similar. It identified KOs with significant variance which led to a more detailed histological analysis. Our findings are exemplified by the Efna4 KO, in which a high BV/TV was identified by μCT and confirmed by histomorphometry in the femur but not in the vertebral compartment. Dynamic labeling showed a marked increase in BFR which was attributable to increased labeling surfaces. Cellular analysis confirmed partitioning of osteoblast to labeling surfaces and a marked decrease in osteoclastic activity on both labeling and quiescent surfaces. This pattern of increased bone modeling would not be expected based on prior studies of the Ephrin-Ephrin receptor signaling pathways between osteoblasts and osteoclasts. Overall, our findings underscore why unbiased screening is needed because it can reveal unknown or unanticipated genes that impact skeletal variation.