Mass spectrometry based proteomics profiling of human monocytes

Comprehensive proteomics of monocytes indicates oxidative imbalance functionally related to inflammatory response in chronic kidney disease-related atherosclerosis

Atherosclerosis-induced cardiovascular events are the leading cause of mortality in chronic kidney disease (CKD) patients. Monocytes are involved in the formation of atherosclerotic plaques and mediate in the overproduction of ROS, promoting inflammation and oxidative stress. However, the relationship between monocytes, inflammation, and oxidative status in CKD-associated atherosclerosis has not been thoroughly investigated. Monocytes and plasma derived from two groups of CKD patients with varying degrees of atherosclerosis and two groups of patients with cardiovascular disease (CVD) and non-CKD atherosclerosis were analyzed. This study was designed to perform a comprehensive proteomic analysis of monocytes in combination with functional bioinformatics. In addition, a targeted investigation of oxidative stress- and inflammatory-related factors to explore CKD-associated atherosclerosis was applied. Dysregulation of proteins involved in lipid oxidation, cell survival, ROS synthesis and metabolism, and inflammatory responses has been revealed. The characteristic disturbances in the monocyte proteome changed with the progression of CKD. A closer examination of oxidative stress's triggers, mediators, and effects on protein and lipid levels showed alterations in the oxidative imbalance between CKD and CVD. CKD monocytes demonstrated a significant increase of oxidized glutathione without changing the level of its reduced form. Evaluation of enzymatic antioxidants, sources of ROS, and modifications caused by ROS also revealed significant alterations between the study groups. In CKD, inflammation and oxidative imbalance correlated and drove each other. However, in CVD, oxidative stress-related factors were associated with each other but not to inflammatory proteins. Moreover, lipid abnormalities were more specific to classical CVD and unrelated to CKD. Such a comprehensive characterization of monocytes and oxidative stress in CKD and CVD patients has never been presented so far. Obtained results support the involvement of distinct mechanisms underlying the acceleration of atherosclerotic and non-atherosclerotic CKD.

Postmenopausal osteoporosis: Effect of moderate-intensity treadmill exercise on bone proteomics in ovariectomized rats

Objectives

This study aimed to identify the key proteins in the bone mass of ovariectomized (OVX) rats after a period of regular moderate-intensity treadmill exercise and to investigate their effects using tag mass spectrometry and quantitative proteomics with a view to improving the understanding and treatment of postmenopausal osteoporosis.

Methods

Sixty three-month-old female Sprague-Dawley tats of specific-pathogen-free grade were randomly and equally divided into a sham operation group, ovariectomized group (OVX) and ovariectomized combined exercise (OVX + EX) group, and the latter took moderate-intensity treadmill exercise for 17 weeks. After this period of time, body composition and bone density were measured using dual-energy x-ray absorptiometry, and serum bone metabolism indicators were measured using an enzyme immunoassay. In addition, the bone microstructure was examined using micro-computed tomography and scanning of the femur, and femur proteins were subject to proteomic analysis.

Results

Compared with the rats in the OVX group, the bone metabolism indicators in the OVX + EX group decreased significantly, femur bone density increased significantly, the number of the trabeculae increased, and continuity was higher. In the OVX + EX group, 17 proteins were significantly upregulated and 33 significantly downregulated. The main gene ontology and signaling pathways enriched by the proteins were identified as the tumor necrosis factor-mediated signaling pathways. The protein-protein interaction network identified the key proteins, and the correlation analysis of these proteins and the bone parameters found histone deacetylase 8(HDAC8) and leucine-rich transmembrane and O-methyltransferase domain containing (LRTOMT) and trimethylguanosine synthase 1(TGS1) and ankyrin repeat domain 46(ANKRD46) to be the key targets of exercise in relation to postmenopausal osteoporosis.

Conclusion

Moderate-intensity treadmill exercise significantly improved the bone mass of OVX rats, and differentially expressed proteins, such as HDAC8 and LRTOMT and TGS1 and ANKRD46, could be the target of moderate-intensity treadmill exercise.

Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting

Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations.

Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and Animal-Modeling Techniques

The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits ("endophenotypes"), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.

Mass Spectrometry: A Powerful Method for Monitoring Various Type of Leukemia, Especially MALDI-TOF in Leukemia's Proteomics Studies Review

Recent success in studying the proteome, as a source of biomarkers, has completely changed our understanding of leukemia (blood cancer). The identification of differentially expressed proteins, such as relapse and drug resistance proteins involved in leukemia by using various ionization sources and mass analyzers of mass spectrometry techniques, has helped scientists find better diagnosis, prognosis, and treatment strategies. With the aid of this powerful analytical technique, we can investigate the qualification/quantification of proteins, protein-protein interactions, post-translational modifications, and find the correlation between proteins and their genes with the hope of finding the missing parts of the successful therapy puzzle. In this review, we followed different MS sources and analyzers which used for monitoring various type of leukemia, then focused on MALDI-TOF MS as a quick and reliable method for studying proteins. Due to several review published for other techniques, the present review is the first work in this field. Also, by classifying more than 400 proteins, we have found 42 proteins are involved in two or three different stages of leukemia. Finally, we have suggested six specific biomarkers for AML, one for ALL, three biomarkers with a role in the etiology of leukemia and 13 markers with the potential for further studies.

A road map for understanding molecular and genetic determinants of osteoporosis

Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in 'systems genetics and genomics'. In this Review, we highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis. Furthermore, we summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis. The integration of multiple technologies will provide a road map to illuminate the complex pathogenesis of osteoporosis, especially from molecular functional aspects, in vivo in humans.