Primary myeloid cell proteomics and transcriptomics: importance of β-tubulin isotypes for osteoclast function

SLC15A3 is transcriptionally regulated by HIF1α and p65 to worsen neuroinflammation in experimental ischemic stroke

Systemic inflammatory stimulus is a risk factor for the incidence of ischemic stroke and contributes to poorer clinical outcomes. Solute carrier 15A3 (SLC15A3) is a peptide/histidine transporter that is implicated in regulating inflammatory responses. However, whether SLC15A3 affects the progression of ischemic stroke associated with systemic inflammation is unclear. The transient middle cerebral artery occlusion (tMCAO) mice with LPS administration (LPS/tMCAO) were prepared as an in vivo model, and LPS-induced BV2 cells under oxygen-glucose deprivation (OGD) exposure were utilized as an in vitro model. We found that SLC15A3 was highly expressed in the ischemic penumbra of LPS/tMCAO mice, and its inhibition reduced infarct area, attenuated neurological deficit, recovered motor function, and mitigated apoptotic neurons. Knockdown of SLC15A3 suppressed the proinflammatory M1-type markers and promoted the levels of M2-associated genes. The in vitro results confirmed that SLC15A3 overexpression promoted microglia polarizing towards M1 subtypes, while SLC15A3 inhibition exerted an opposite effect. In addition, we demonstrated that the p65 signaling pathway and HIF1α were activated by LPS/OGD. Luciferase reporter assay showed that inhibiting p65 using its specific inhibitor BAY 11-7082 or silencing HIF1α using siRNAs reduced the transcriptional activity of SLC15A3 in LPS/OGD-induced BV2 cells. Results in NIH 3T3 cells also confirmed that p65 and HIF1α directly bound to the SLC15A3 promoter to activate SLC15A3 transcription. In conclusion, this work shows that SLC15A3, transcriptionally activated by p65 and HIF1α, contributes to poor outcomes in ischemic stroke associated with systemic inflammation by promoting microglial cells polarizing towards M1 types.

A proteomics approach to study mouse long bones: examining baseline differences and mechanical loading-induced bone formation in young-adult and old mice

With aging, bone mass declines and the anabolic effects of skeletal loading diminish. While much research has focused on gene transcription, how bone ages and loses its mechanoresponsiveness at the protein level remains unclear. We developed a novel proteomics approach and performed a paired mass spectrometry and RNA-seq analysis on tibias from young-adult (5-month) and old (22-month) mice. We report the first correlation estimate between the bone proteome and transcriptome (Spearman ρ = 0.40), which is in line with other tissues but indicates that a relatively low amount of variation in protein levels is explained by the variation in transcript levels. Of 71 shared targets that differed with age, eight were associated with bone mineral density in previous GWAS, including understudied targets Asrgl1 and Timp2. We used complementary RNA in situ hybridization to confirm that Asrgl1 and Timp2 had reduced expression in osteoblasts/osteocytes in old bones. We also found evidence for reduced TGF-beta signaling with aging, in particular Tgfb2. Next, we defined proteomic changes following mechanical loading. At the protein level, bone differed more with age than with loading, and aged bone had fewer loading-induced changes. Overall, our findings underscore the need for complementary protein-level assays in skeletal biology research.

Bone resorption by osteoclasts involves fine tuning of RHOA activity by its microtubule-associated exchange factor GEF-H1

Bone health is controlled by the balance between bone formation by osteoblasts and degradation by osteoclasts. A disequilibrium in favor of bone resorption leads to osteolytic diseases characterized by decreased bone density. Osteoclastic resorption is dependent on the assembly of an adhesion structure: the actin ring, also called podosome belt or sealing zone, which is composed of a unique patterning of podosomes stabilized by microtubules. A better understanding of the molecular mechanisms regulating the crosstalk between actin cytoskeleton and microtubules network is key to find new treatments to inhibit bone resorption. Evidence points to the importance of the fine tuning of the activity of the small GTPase RHOA for the formation and maintenance of the actin ring, but the underlying mechanism is not known. We report here that actin ring disorganization upon microtubule depolymerization is mediated by the activation of the RHOA-ROCK signaling pathway. We next show the involvement of GEF-H1, one of RHOA guanine exchange factor highly expressed in osteoclasts, which has the particularity of being negatively regulated by sequestration on microtubules. Using a CRISPR/Cas9-mediated GEF-H1 knock-down osteoclast model, we demonstrate that RHOA activation upon microtubule depolymerization is mediated by GEF-H1 release. Interestingly, although lower levels of GEF-H1 did not impact sealing zone formation in the presence of an intact microtubule network, sealing zone was smaller leading to impaired resorption. Altogether, these results suggest that a fine tuning of GEF-H1 through its association with microtubules, and consequently of RHOA activity, is essential for osteoclast sealing zone stability and resorption function.

Bone Trans-omics: Integrating Omics to Unveil Mechanistic Molecular Networks Regulating Bone Biology and Disease

PURPOSE OF REVIEW

Recent advancements in "omics" technologies and bioinformatics have afforded researchers new tools to study bone biology in an unbiased and holistic way. The purpose of this review is to highlight recent studies integrating multi-omics data gathered from multiple molecular layers (i.e.; trans-omics) to reveal new molecular mechanisms that regulate bone biology and underpin skeletal diseases.

RECENT FINDINGS

Bone biologists have traditionally relied on single-omics technologies (genomics, transcriptomics, proteomics, and metabolomics) to profile measureable differences (both qualitative and quantitative) of individual molecular layers for biological discovery and to investigate mechanisms of disease. Recently, literature has grown on the implementation of integrative multi-omics to study bone biology, which combines computational and informatics support to connect multiple layers of data derived from individual "omic" platforms. This emerging discipline termed "trans-omics" has enabled bone biologists to identify and construct detailed molecular networks, unveiling new pathways and unexpected interactions that have advanced our mechanistic understanding of bone biology and disease. While the era of trans-omics is poised to revolutionize our capacity to answer more complex and diverse questions pertinent to bone pathobiology, it also brings new challenges that are inherent when trying to connect "Big Data" sets. A concerted effort between bone biologists and interdisciplinary scientists will undoubtedly be needed to extract physiologically and clinically meaningful data from bone trans-omics in order to advance its implementation in the field.

A New Method to Sort Differentiating Osteoclasts into Defined Homogeneous Subgroups

Osteoclasts regulate skeletal development but also drive pathological osteolysis, making them prime therapeutic targets. Osteoclast research is limited by the heterogeneity of osteoclast populations generated in vitro, where the mixture of undifferentiated monocytes, binuclear pre-osteoclasts and multinucleated osteoclasts has by necessity been considered a single osteoclast population. This study describes the differentiation of primary human CD14+ monocyte-derived osteoclasts in 3D collagen gels. These osteoclasts remained small (>95% with ≤5 nuclei) but were viable and active; when released from the gel with collagenase, they fused rapidly when reseeded onto solid substrates and resorbed dentine for 2-3 weeks. 3D-generated osteoclasts expressed cell surface markers of osteoclast differentiation (e.g., CD9, RANK, OSCAR, CD63, CD51/61) which, with their small size, enabled live cell sorting of highly enriched viable subpopulations of human osteoclasts that retained full functional resorption capacity. Low-yield osteoclast preparations were strongly enriched to remove undifferentiated cells (e.g., 13.3% CD51/61+ to 84.2% CD51/61+), and subpopulations of CD9+CD51/61- early osteoclasts and CD9+CD51/61+ mature cells were distinguished. This novel approach allows the study of selected populations of differentiating osteoclasts in vitro and opens the door to in-depth transcriptomic and proteomic analysis of these cells, increasing our ability to study human osteoclast molecular mechanisms relevant to development, aging and disease.

Integrative analysis of DNA methylation and gene expression reveals key molecular signatures in acute myocardial infarction

BACKGROUNDS

Acute myocardial infarction (AMI) has been one of the most fatal diseases among all types of heart diseases due to its rapid onset and high rates of fatality. Understanding accurately how multi-omics molecular features change at the early stage of AMI is crucial for its treatment. Currently, the changes involved in DNA methylation modification and gene expression of multiple genes have remained unexplored.

RESULTS

We used the RNA-seq and MeDIP-seq on heart tissues from AMI mouse models at series of time points (Sham, AMI 10-min, 1-h, 6-h, 24-h and 72-h), to comprehensively describe the transcriptome and genome-wide DNA methylation changes at above time points. We identified 18814, 18614, 23587, 26018 and 33788 differential methylation positions (DMPs) and 123, 135, 731, 1419 and 2779 differentially expressed genes (DEGs) at 10-min, 1-h, 6-h, 24-h and 72-h AMI, respectively, compared with the sham group. Remarkably, the 6-h AMI with the drastic changes of DEGs and a large number of enriched functional pathways in KEGG may be the most critical stage of AMI process. The 4, 9, 40, 26, and 183 genes were further identified at each time point, based on the negative correlation (P < 0.05) between the differential mRNA expression and the differential DNA methylation. The mRNA and the promoter methylation expressions of five genes (Ptpn6, Csf1r, Col6a1, Cyba, and Map3k14) were validated by qRT-PCR and BSP methods, and the mRNA expressions were further confirmed to be regulated by DNA methylation in cardiomyocytes in vitro.

CONCLUSIONS

Our findings profiled the molecular variations from the perspective of DNA methylation in the early stage of AMI and provided promising epigenetic-based biomarkers for the early clinical diagnosis and therapeutic targets of AMI.

Predicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP

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.

The Beta-Tubulin Isotype TUBB6 Controls Microtubule and Actin Dynamics in Osteoclasts

Osteoclasts are bone resorbing cells that participate in the maintenance of bone health. Pathological increase in osteoclast activity causes bone loss, eventually resulting in osteoporosis. Actin cytoskeleton of osteoclasts organizes into a belt of podosomes, which sustains the bone resorption apparatus and is maintained by microtubules. Better understanding of the molecular mechanisms regulating osteoclast cytoskeleton is key to understand the mechanisms of bone resorption, in particular to propose new strategies against osteoporosis. We reported recently that β-tubulin isotype TUBB6 is key for cytoskeleton organization in osteoclasts and for bone resorption. Here, using an osteoclast model CRISPR/Cas9 KO for Tubb6, we show that TUBB6 controls both microtubule and actin dynamics in osteoclasts. Osteoclasts KO for Tubb6 have reduced microtubule growth speed with longer growth life time, higher levels of acetylation, and smaller EB1-caps. On the other hand, lack of TUBB6 increases podosome life time while the belt of podosomes is destabilized. Finally, we performed proteomic analyses of osteoclast microtubule-associated protein enriched fractions. This highlighted ARHGAP10 as a new microtubule-associated protein, which binding to microtubules appears to be negatively regulated by TUBB6. ARHGAP10 is a negative regulator of CDC42 activity, which participates in actin organization in osteoclasts. Our results suggest that TUBB6 plays a key role in the control of microtubule and actin cytoskeleton dynamics in osteoclasts. Moreover, by controlling ARHGAP10 association with microtubules, TUBB6 may participate in the local control of CDC42 activity to ensure efficient bone resorption.

Novel 2,7-Diazaspiro[4,4]nonane Derivatives to Inhibit Mouse and Human Osteoclast Activities and Prevent Bone Loss in Ovariectomized Mice without Affecting Bone Formation

Osteoporosis is currently treated with drugs targeting the differentiation or viability osteoclasts, the cells responsible for physiological and pathological bone resorption. Nevertheless, osteoporosis drugs that target only osteoclast activity are expected to preserve bone formation by osteoblasts in contrast to current treatments. We report here the design, synthesis, and biological characterization of a series of novel N-arylsufonamides featuring a diazaspiro[4,4]nonane nucleus to target the guanine nucleotide exchange activity of DOCK5, which is essential for bone resorption by osteoclasts. These compounds can inhibit both mouse and human osteoclast activity. In particular, 4-chlorobenzyl-4-hydroxy-2-phenyl-1-thia-2,7-diazaspiro[4,4]nonane 1,1-dioxide (compound E197) prevented pathological bone loss in mice. Most interestingly, treatment with E197 did not affect osteoclast and osteoblast numbers and hence did not impair bone formation. E197 could represent a lead molecule to develop new antiosteoporotic drugs targeting the mechanism of osteoclast adhesion onto the bone.

The osteoclast cytoskeleton - current understanding and therapeutic perspectives for osteoporosis

Osteoclasts are giant multinucleated myeloid cells specialized for bone resorption, which is essential for the preservation of bone health throughout life. The activity of osteoclasts relies on the typical organization of osteoclast cytoskeleton components into a highly complex structure comprising actin, microtubules and other cytoskeletal proteins that constitutes the backbone of the bone resorption apparatus. The development of methods to differentiate osteoclasts in culture and manipulate them genetically, as well as improvements in cell imaging technologies, has shed light onto the molecular mechanisms that control the structure and dynamics of the osteoclast cytoskeleton, and thus the mechanism of bone resorption. Although essential for normal bone physiology, abnormal osteoclast activity can cause bone defects, in particular their hyper-activation is commonly associated with many pathologies, hormonal imbalance and medical treatments. Increased bone degradation by osteoclasts provokes progressive bone loss, leading to osteoporosis, with the resulting bone frailty leading to fractures, loss of autonomy and premature death. In this context, the osteoclast cytoskeleton has recently proven to be a relevant therapeutic target for controlling pathological bone resorption levels. Here, we review the present knowledge on the regulatory mechanisms of the osteoclast cytoskeleton that control their bone resorption activity in normal and pathological conditions.