ABSTRACT: Bone metabolism is a dynamic process involving osteoblasts, osteoclasts, and osteocytes, which maintain skeletal integrity through continuous remodelling. Disruptions in this homeostasis – caused by mineral or hormonal imbalances, systemic metabolic or inflammatory conditions, or genetic predispositions – can lead to diseases like osteoporosis and osteoarthritis, increased fracture risk and impaired bone healing. Understanding the molecular mechanisms within the bone tissue underlying these conditions is crucial for developing targeted therapies. Proteomic analyses using liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) can advance bone research by identifying crucial proteins and their dynamic interplay involved in bone health and disease. However, extracting meaningful proteomic data from bone tissue presents unique challenges due to its dense, mineral-rich matrix and the predominance of type I collagen. High-abundance bone proteins impede the detection of low-abundant non-collagenous and cellular proteins that are critical for understanding bone physiology and pathology, thereby limit the depth of proteomic analyses. To address this challenge, previous approaches have attempted to reduce collagen interference by enzymatic digestion with bacterial collagenase or by applying multi-step extraction protocols using various buffers. This study aimed to develop a novel two-step proteome extraction protocol, that 1) minimizes collagen interference while enhancing the detection of low-abundance proteins, including non-collagenous and cellular proteins; 2) is reproducible and time-efficient; and 3) is multi-omics-compatible by integrating upstream metabolite extraction. We conducted a systematic comparison of our newly proposed two-step bone proteome extraction procedure with two existing protein extraction methods: one based on enzymatic digestion with collagenase after a single-step extraction, and another using sequential extraction with four different buffers. We evaluated their performance in terms of reproducible protein quantification, variance, collagen content, as well as handling and instrument time. The enzymatic digestion of collagens in the single-step extraction method successfully reduced collagen content and improved reproducibility but still resulted in fewer quantifiable proteins compared to sequential extraction protocols (2,689 proteins). Although more complex extraction protocols identified a greater number of different collagens, they also provided greater coverage of low-abundance proteins. The four-step protocol achieved the highest quantification rate (4,934 proteins) but required twice the extraction time and produced more fractions, with no significant improvement in coefficients of variation (CVs) and high collagen content in the last fraction. Our proposed 2-step protocol combined short extraction time with effective protein quantification of 4,518 proteins, achieving a dynamic range over four orders of magnitude and reasonable reproducibility. Implementing a chloroform-methanol-based metabolite extraction before proteome extraction by the two-step protocol reduced the number of reproducibly quantified proteins by only 3% to 4,393 proteins, making it suitable for application in multi-omics approaches. By sequentially using different buffers, this protocol reduces collagen content in the extracts, enabling better coverage of the diverse range of proteins present in bone tissue. This approach not only enhances proteome coverage but also is compatible with simultaneous metabolite extraction, facilitating comprehensive multi-omics analyses.
Vivien Wiltzsch