Effective protein extraction combined with data independent acquisition analysis reveals a comprehensive and quantifiable insight into the proteomes of articular cartilage and subchondral bone

RanGAP1 maintains chromosome stability in limb bud mesenchymal cells during bone development

BACKGROUND

Bone development involves the rapid proliferation and differentiation of osteogenic lineage cells, which makes accurate chromosomal segregation crucial for ensuring cell proliferation and maintaining chromosomal stability. However, the mechanism underlying the maintenance of chromosome stability during the rapid proliferation and differentiation of Prx1-expressing limb bud mesenchymal cells into osteoblastic precursor cells remains unexplored.

METHODS

A transgenic mouse model of RanGAP1 knockout of limb and head mesenchymal progenitor cells was constructed to explore the impact of RanGAP1 deletion on bone development by histomorphology and immunostaining. Subsequently, G-banding karyotyping analysis and immunofluorescence staining were used to examine the effects of RanGAP1 deficiency on chromosome instability. Finally, the effects of RanGAP1 deficiency on chromothripsis and bone development signaling pathways were elucidated by whole-genome sequencing, RNA-sequencing, and qPCR.

RESULTS

The ablation of RanGAP1 in limb and head mesenchymal progenitor cells expressing Prx1 in mice resulted in embryonic lethality, severe cartilage and bone dysplasia, and complete loss of cranial vault formation. Moreover, RanGAP1 loss inhibited chondrogenic or osteogenic differentiation of mesenchymal stem cells (MSCs). Most importantly, we found that RanGAP1 loss in limb bud mesenchymal cells triggered missegregation of chromosomes, resulting in chromothripsis of chromosomes 1q and 14q, further inhibiting the expression of key genes involved in multiple bone development signaling pathways such as WNT, Hedgehog, TGF-β/BMP, and PI3K/AKT in the chromothripsis regions, ultimately disrupting skeletal development.

CONCLUSIONS

Our results establish RanGAP1 as a critical regulator of bone development, as it supports this process by preserving chromosome stability in Prx1-expressing limb bud mesenchymal cells.

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies

OBJECTIVE

Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades.

DESIGN

We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease.

RESULTS

Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues.

CONCLUSIONS

Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

Proteomics Analysis of Knee Subchondral Bone Identifies Differentially Expressed Proteins Associated with Osteoarthritis

Osteoarthritis (OA) is a prevalent debilitating whole-joint disorder. Currently, a growing number of proteomic studies have been performed to evaluate molecular biomarkers in several tissues from OA patients; however, little is known about the protein profiles in subchondral bone of OA. In this study, proteomic analysis was performed on subchondral bone from patients with OA to identify differentially expressed proteins (DEPs). Bioinformatics tools were used to further investigate these DEPs. Thereafter, DEPs were validated in the samples from patients with OA, as well as in bilateral ovariectomy-induced OA (OVX-OA) rats using immunohistochemistry. A comprehensive subchondral bone proteome profile of patients with OA was constructed. Additionally, biological information analysis showed that a majority of DEPs participated in the dysregulation of the complement and coagulation cascades. The validation experiments suggested that SerpinA5, the protein involved in the complement and coagulation cascades, was significantly increased in severely damaged subchondral bone of patients with OA compared to the control group. Furthermore, the increase of SerpinA5 in OVX-OA rats compared to control rats was also confirmed. Our results indicated that the dysregulation of coagulation and complement pathways plays a role in the progression of OA, and it provides a promising therapeutic target of OA.

Skeletal muscle-derived extracellular vesicles transport glycolytic enzymes to mediate muscle-to-bone crosstalk

Identification of cues originating from skeletal muscle that govern bone formation is essential for understanding the crosstalk between muscle and bone and for developing therapies for degenerative bone diseases. Here, we identified that skeletal muscle secreted multiple extracellular vesicles (Mu-EVs). These Mu-EVs traveled through the bloodstream to reach bone, where they were phagocytized by bone marrow mesenchymal stem/stromal cells (BMSCs). Mu-EVs promoted osteogenic differentiation of BMSCs and protected against disuse osteoporosis in mice. The quantity and bioactivity of Mu-EVs were tightly correlated with the function of skeletal muscle. Proteomic analysis revealed numerous proteins in Mu-EVs, some potentially regulating bone metabolism, especially glycolysis. Subsequent investigations indicated that Mu-EVs promoted the glycolysis of BMSCs by delivering lactate dehydrogenase A into these cells. In summary, these findings reveal that Mu-EVs play a vital role in BMSC metabolism regulation and bone formation stimulation, offering a promising approach for treating disuse osteoporosis.

Single-cell transcriptional profiling reveals immunomodulatory properties of stromal and epithelial cells in periodontal immune milieu with diabetes in rats

Periodontitis is the sixth major complication of diabetes. Gingiva, as an important component of periodontal tissues, serves as the first defense barrier against infectious stimuli. However, relatively little is known about cellular heterogeneity and cell-specific changes in gingiva in response to diabetes-associated periodontitis. To characterize molecular changes linking diabetes with periodontitis, we profiled single-cell transcriptome analyses of a total of 45,259 cells from rat gingiva with periodontitis under normoglycemic and diabetic condition. The single-cell profiling revealed that stromal and epithelial cells of gingiva contained inflammation-related subclusters enriched in functions of immune cell recruitment. Compared to normoglycemic condition, diabetes led to a reduction in epithelial basal cells, fibroblasts and smooth muscle cells in gingiva with periodontitis. Analysis of differentially expressed genes indicated that stromal and epithelial populations were reprogrammed towards pro-inflammatory phenotypes promoting immune cell recruitment in diabetes-related periodontitis. In aspect of immune cells, diabetes prominently enhanced neutrophil and M1 macrophage infiltration in periodontitis lesions. Cell-cell communications revealed enhanced crosstalk between stromal/epithelial cells and immune cells mediating by chemokine/chemokine receptor interplay in diabetes-associated periodontitis. Our findings deconvolved cellular heterogeneity of rat gingiva associated with periodontitis and diabetes, uncovered altered immune milieu caused by the disease, and revealed immunomodulatory functions of stromal and epithelial cells in gingival immune niche. The present study improves the understanding of the link between the diabetes and periodontitis and helps in formulating precise therapeutic strategies for diabetes-enhanced periodontitis.

The Genetic Diversity of Stallions of Different Breeds in Russia

The specifics of breeding and selection significantly affect genetic diversity and variability within a breed. We present the data obtained from the genetic analysis of 21 thoroughbred and warmblood horse breeds. The most detailed information is described from the following breeds: Arabian, Trakehner, French Trotter, Standardbred, and Soviet Heavy Horse. The analysis of 509,617 SNP variants in 87 stallions from 21 populations made it possible to estimate the genetic diversity at the genome-wide level and distinguish the studied horse breeds from each other. In this study, we searched for heterozygous and homozygous ROH regions, evaluated inbreeding using FROH analysis, and generated a population structure using Admixture 1.3 software. Our findings indicate that the Arabian breed is an ancestor of many horse breeds. The study of the full-genome architectonics of breeds is of great practical importance for preserving the genetic characteristics of breeds and managing breeding. Studies were carried out to determine homozygous regions in individual breeds and search for candidate genes in these regions. Fifty-six candidate genes for the influence of selection pressure were identified. Our research reveals genetic diversity consistent with breeding directions and the breeds' history of origin.

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass spectrometry (MS). Despite improved instrumentation and software, de novo MS data analysis remains challenging. In recent years, deep learning models have represented a performance breakthrough. Incorporating that technology into de novo protein sequencing workflows require machine-learning models capable of handling highly diverse MS data. In this study, we analyzed the requirements for assembling such generalizable deep learning models by systemcally varying the composition and size of the training set. We assessed the generated models' performances using two test sets composed of peptides originating from the multienzyme digestion of samples from various species. The peptide recall values on the test sets showed that the deep learning models generated from a collection of highly N- and C-termini diverse peptides generalized 76% more over the termini-restricted ones. Moreover, expanding the training set's size by adding peptides from the multienzymatic digestion with five proteases of several species samples led to a 2-3 fold generalizability gain. Furthermore, we tested the applicability of these multienzyme deep learning (MEM) models by fully de novo sequencing the heavy and light monomeric chains of five commercial antibodies (mAbs). MEMs extracted over 10000 matching and overlapped peptides across six different proteases mAb samples, achieving a 100% sequence coverage for 8 of the ten polypeptide chains. We foretell that the MEMs' proven improvements to de novo analysis will positively impact several applications, such as analyzing samples of high complexity, unknown nature, or the peptidomics field.

In Vitro Models and Proteomics in Osteoarthritis Research

This review summarizes and exemplifies the current understanding of osteoarthritis in vitro models and describes their relevance for new insights in the future of osteoarthritis research. Our friend and highly appreciated colleague, Prof. Alan Grodzinsky has contributed greatly to the understanding of joint tissue biology and cartilage biomechanics. He frequently utilizes in vitro models and cartilage explant cultures, and recent work also includes proteomics studies. This review is dedicated to honor his 75-year birthday and will focus on recent proteomic in vitro studies related to osteoarthritis, and within this topic highlight some of his contributions to the field.