Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it

A classic prescription alleviates inflammation in CUMS model mice via modulating MYDGF/MAP4K4/NF-κB signaling pathway, verified through UPLC-HRMS and proteomics analysis

Background

Xiaoyaosan (XYS), a renowned classical traditional Chinese medicinal formula utilized in addressing major depressive disorder (MDD), has garnered significant acclaim for its remarkable efficacy in clinical application. The onset of major depressive disorder (MDD) often correlates with chronic unpredictable mild stress (CUMS), a pivotal instigating factor in its development.Aim of the study: This study aims to clarify the potential anti-inflammatory mechanisms of XYS in treating CUMS model mice.

Materials and methods

Utilizing cutting-edge ultra high-performance liquid chromatography - high-resolution mass spectrometry (UPLC-HRMS), the active constituents of XYS were discerned, while employing proteomics analysis to delve into the potential mechanisms of its efficacy. Molecular docking studies, alongside subsequent in vivo experiments utilizing CUMS model mice, were conducted to corroborate the findings derived from the proteomics analysis.

Results

In vivo experiments demonstrated that XYS not only markedly ameliorated behavioral markers but also attenuated serum inflammatory markers and suppressed IL-6 and TNF-α expression within the brains of CUMS model mice. Proteomics analysis suggested that the pivotal anti-inflammatory mechanism of XYS against CUMS-induced damage might involve modulation of the MAPK signaling pathway. Utilizing UPLC-HRMS, the active constituents of XYS were successfully identified, while molecular docking investigations explored interactions between XYS and MYDGF, PKC, MAP4K4, P-p65, p65, P-IKBα, and IKBα. The findings revealed XYS's regulatory influence on the MYDGF/MAP4K4/NF-κB signaling cascade.

Conclusions

This study is the first to our knowledge to demonstrate that XYS can alleviate inflammation in CUMS model mice by modulating the MYDGF/MAP4K4/NF-κB signaling pathway.

Combining multiomics to analyze the molecular mechanism of hair follicle cycle change in cashmere goats from Inner Mongolia

Sheep body size can directly reflect the growth rates and fattening rates of sheep and is also an important index for measuring the growth performance of meat sheep.Inner Mongolia Cashmere Goat is a local excellent breed of cashmere and meat dual-purpose, which is a typical heterogeneous indumentum. The hair follicles cycle through periods of vigorous growth (anagen), a regression caused by apoptosis (catagen), and relative rest (telogen). At present, it is not clear which genes affect the cycle transformation of hair follicles and unclear how proteins impact the creation and expansion of hair follicles.we using multi-omics joint analysis methodologies to investigated the possible pathways of transformation and apoptosis in goat hair follicles. The results showed that 917,1,187, and 716 proteins were specifically expressed in anagen, catagen andtelogen. The result of gene ontology (GO) annotation showed that differentially expressed proteins (DEPs) are in different growth cycle periods, and enriched GO items are mostly related to the transformation of cells and proteins. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment result indicated that the apoptosis process has a great impact on hair follicle's growth cycle. The results of the protein interaction network of differential proteins showed that the ribosomal protein family (RPL4, RPL8, RPS16, RPS18, RPS2, RPS27A, RPS3) was the core protein in the network. The results of combined transcriptome and proteomics analysis showed that there were 16,34, and 26 overlapped DEGs and DEPs in the comparison of anagen VS catagen, catagen VS telogen and anagen VS telogen, of which API5 plays an important role in regulating protein and gene expression levels. We focused on API5 and Ribosomal protein and found that API5 affected the apoptosis process of hair follicles, and ribosomal protein was highly expressed in the resting stage of hair follicles. They are both useful as molecular marker candidate genes to study hair follicle growth and apoptosis,and they both have an essential function in the cycle transition process of hair follicles. The results of this study may provide a theoretical basis for further research on the growth and development of hair follicles in Inner Mongolian Cashmere goats.

Proteomics and its application in the research of acupuncture: An updated review

As a complementary and alternative therapy, acupuncture is widely used in the prevention and treatment of various diseases. However, the understanding of the mechanism of acupuncture effects is still limited due to the lack of systematic biological validation. Notably, proteomics technologies in the field of acupuncture are rapidly evolving, and these advances are greatly contributing to the research of acupuncture. In this study, we review the progress of proteomics research in analyzing the molecular mechanisms of acupuncture for neurological disorders, pain, circulatory disorders, digestive disorders, and other diseases, with an in-depth discussion around acupoint prescription and acupuncture manipulation modalities. The study found that proteomics has great potential in understanding the mechanisms of acupuncture. This study will help explore the mechanisms of acupuncture from a proteomic perspective and provide information to support future clinical decisions.

Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction

The attrition rate of drugs in clinical trials is generally quite high, with estimates suggesting that approximately 90% of drugs fail to make it through the process. The identification of unexpected toxicity issues during preclinical stages is a significant factor contributing to this high rate of failure. These issues can have a major impact on the success of a drug and must be carefully considered throughout the development process. These late-stage rejections or withdrawals of drug candidates significantly increase the costs associated with drug development, particularly when toxicity is detected during clinical trials or after market release. Understanding drug-biological target interactions is essential for evaluating compound toxicity and safety, as well as predicting therapeutic effects and potential off-target effects that could lead to toxicity. This will enable scientists to predict and assess the safety profiles of drug candidates more accurately. Evaluation of toxicity and safety is a critical aspect of drug development, and biomolecules, particularly proteins, play vital roles in complex biological networks and often serve as targets for various chemicals. Therefore, a better understanding of these interactions is crucial for the advancement of drug development. The development of computational methods for evaluating protein-ligand interactions and predicting toxicity is emerging as a promising approach that adheres to the 3Rs principles (replace, reduce, and refine) and has garnered significant attention in recent years. In this review, we present a thorough examination of the latest breakthroughs in drug toxicity prediction, highlighting the significance of drug-target binding affinity in anticipating and mitigating possible adverse effects. In doing so, we aim to contribute to the development of more effective and secure drugs.

Advances in Integrated Multi-omics Analysis for Drug-Target Identification

As an essential component of modern drug discovery, the role of drug-target identification is growing increasingly prominent. Additionally, single-omics technologies have been widely utilized in the process of discovering drug targets. However, it is difficult for any single-omics level to clearly expound the causal connection between drugs and how they give rise to the emergence of complex phenotypes. With the progress of large-scale sequencing and the development of high-throughput technologies, the tendency in drug-target identification has shifted towards integrated multi-omics techniques, gradually replacing traditional single-omics techniques. Herein, this review centers on the recent advancements in the domain of integrated multi-omics techniques for target identification, highlights the common multi-omics analysis strategies, briefly summarizes the selection of multi-omics analysis tools, and explores the challenges of existing multi-omics analyses, as well as the applications of multi-omics technology in drug-target identification.

Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure

Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.

Elucidating the role of the GC/GR/GLUT1 axis in steroid-induced osteonecrosis of the femoral head: A proteomic approach

BACKGROUND

Steroid-induced osteonecrosis of the femoral head (SONFH) is a prevalent and incapacitating condition that affects the hip joint. Unfortunately, early diagnostic and treatment measures are limited.

METHODS

Our study employed Tandem Mass Tag (TMT) labeling mass spectrometry (MS)-based quantitative proteome to compare the proteins of femoral head tissues in patients with SONFH with those of patients who sustained femoral neck fracture (FNF). We investigated the level and effects of glucose transporter member 1 (GLUT1) in SONFH patients and MC3T3-E1 cells and examined the function and molecular mechanism of GLUT1 in the context of SONFH using in vivo and in vitro approaches.

RESULTS

The SONFH group exhibited significant changes in protein expression levels compared to the fracture group. Specifically, we observed the up-regulation of 86 proteins and the down-regulation of 138 proteins in the SONFH group. Among the differentially expressed proteins, GLUT1 was down-regulated and associated with glucose metabolic processes in the SONFH group. Further analysis using Parallel Reaction Monitoring (PRM), WB, and PCR confirmed that the protein was significantly down-regulated in both femoral head tissue samples from SONFH patients and dexamethasone-treated MC3T3-E1 cells. Moreover, overexpression of GLUT1 effectively reduced glucocorticoid (GC)-induced apoptosis and the suppression of osteoblast proliferation and osteogenic differentiation in MC3T3-E1 cells, as well as GC-induced femoral head destruction in GC-induced ONFH rat models. Additionally, our research demonstrated that GC down-regulated GLUT1 transcription via glucocorticoid receptors in MC3T3-E1 cells.

CONCLUSIONS

GLUT1 was down-regulated in patients with SONFH; furthermore, down-regulated GLUT1 promoted apoptosis and inhibited osteoblast ossification in dexamethasone-induced MC3T3-E1 cells and contributed to GC-induced femoral head destruction in a SONFH rat model. Glucocorticoids inhibited the transcriptional activity of GLUT1, leading to a reduction in the amount and activity of GLUT1 in the cells and ultimately promoting apoptosis and inhibiting osteoblast ossification via the GC/GR/GLUT1 axis in SONFH.

Bringing proteomics to bear on male fertility: key lessons

INTRODUCTION

Male infertility is a major public health concern globally. Proteomics has revolutionized our comprehension of male fertility by identifying potential infertility biomarkers and reproductive defects. Studies comparing sperm proteome with other male reproductive tissues have the potential to refine fertility diagnostics and guide infertility treatment development.

AREAS COVERED

This review encapsulates literature using proteomic approaches to progress male reproductive biology. Our search methodology included systematic searches of databases such as PubMed, Scopus, and Web of Science for articles up to 2023. Keywords used included 'male fertility proteomics,' 'spermatozoa proteome,' 'testis proteomics,' 'epididymal proteomics,' and 'non-hormonal male contraception.' Inclusion criteria were robust experimental design, significant contributions to male fertility, and novel use of proteomic technologies.

EXPERT OPINION

Expert analysis shows a shift from traditional research to an integrative approach that clarifies male reproductive health's molecular intricacies. A gap exists between proteomic discoveries and clinical application. The expert opinions consolidated here not only navigate the current findings but also chart the future proteomic applications for scientific and clinical breakthroughs. We underscore the need for continued investment in proteomic research - both in the technological and collaborative arenas - to further unravel the secrets of male fertility, which will be central to resolving fertility issues in the coming era.

Potential Drug-Nutrient Interactions of 45 Vitamins, Minerals, Trace Elements, and Associated Dietary Compounds with Acetylsalicylic Acid and Warfarin-A Review of the Literature

In cardiology, acetylsalicylic acid (ASA) and warfarin are among the most commonly used prophylactic therapies against thromboembolic events. Drug-drug interactions are generally well-known. Less known are the drug-nutrient interactions (DNIs), impeding drug absorption and altering micronutritional status. ASA and warfarin might influence the micronutritional status of patients through different mechanisms such as binding or modification of binding properties of ligands, absorption, transport, cellular use or concentration, or excretion. Our article reviews the drug-nutrient interactions that alter micronutritional status. Some of these mechanisms could be investigated with the aim to potentiate the drug effects. DNIs are seen occasionally in ASA and warfarin and could be managed through simple strategies such as risk stratification of DNIs on an individual patient basis; micronutritional status assessment as part of the medical history; extensive use of the drug-interaction probability scale to reference little-known interactions, and application of a personal, predictive, and preventive medical model using omics.

Use of the traditional Chinese medicine "compound healthy ear agent" to protect against age-related hearing loss in mice: A proteomics study

Background

Previous studies have shown that the traditional Chinese medicine (TCM) called "compound healthy ear agent" (CHEA) had anti-apoptosis effects in cochlear hair cells and spiral ganglion neurons, and could protect mice hearing against presbycusis or age-related hearing loss (AHL), as well as aminoglycoside antibiotic-induced ototoxicity. Because its mechanisms of action are still unclear, we investigated the mechanism of action of CHEA against AHL in mice using proteomics techniques.

Methods

Eighteen C57BL/6J mice at 1 month of age were randomly divided into three groups: (A) drinking water until 2 months of age, K2M); (B) drinking water until 7 months of age to induce AHL, K7M; (C) drinking water containing CHEA daily until 7 months of age as treatment group, Z7M. At 2 or 7 months mice were sacrificed and their cochleae were removed for proteomics analysis.

Results

The numbers of proteins with a false discovery rate (FDR) < 1% were respectively 5873 for qualitative and 5492 for quantitative statistics. The numbers of proteins with differential enrichment at least 1.5-fold (p < 0.05) were respectively 351 for K7M vs K2M groups, 52 for Z7M vs K7M groups, 264 for Z7M vs K2M groups. The differentially expressed proteins in the Z7M group were involved in synaptic molecular transmission, energy metabolism, immune response, antioxidant defenses, and anti-apoptosis.

Conclusion

The TCM CHEA played a protective role against AHL in mice by regulating the expression of specific proteins and genes in cochlear hair cells and spiral ganglion neurons. Besides the pathways expected to be involved (antioxidant and anti-apoptosis), proteins related to immune response is a new finding of the present study.

Deciphering Glioblastoma: Fundamental and Novel Insights into the Biology and Therapeutic Strategies of Gliomas

Gliomas constitute a diverse and complex array of tumors within the central nervous system (CNS), characterized by a wide range of prognostic outcomes and responses to therapeutic interventions. This literature review endeavors to conduct a thorough investigation of gliomas, with a particular emphasis on glioblastoma (GBM), beginning with their classification and epidemiological characteristics, evaluating their relative importance within the CNS tumor spectrum. We examine the immunological context of gliomas, unveiling the intricate immune environment and its ramifications for disease progression and therapeutic strategies. Moreover, we accentuate critical developments in understanding tumor behavior, focusing on recent research breakthroughs in treatment responses and the elucidation of cellular signaling pathways. Analyzing the most novel transcriptomic studies, we investigate the variations in gene expression patterns in glioma cells, assessing the prognostic and therapeutic implications of these genetic alterations. Furthermore, the role of epigenetic modifications in the pathogenesis of gliomas is underscored, suggesting that such changes are fundamental to tumor evolution and possible therapeutic advancements. In the end, this comparative oncological analysis situates GBM within the wider context of neoplasms, delineating both distinct and shared characteristics with other types of tumors.

Applications of single-cell omics for chimeric antigen receptor T cell therapy

Chimeric antigen receptor (CAR) T cell therapy is a promising cancer treatment modality. The breakthroughs in CAR T cell therapy were, in part, possible with the help of cell analysis methods, such as single-cell analysis. Bulk analyses have provided invaluable information regarding the complex molecular dynamics of CAR T cells, but their results are an average of thousands of signals in CAR T or tumour cells. Since cancer is a heterogeneous disease where each minute detail of a subclone could change the outcome of the treatment, single-cell analysis could prove to be a powerful instrument in deciphering the secrets of tumour microenvironment for cancer immunotherapy. With the recent studies in all aspects of adoptive cell therapy making use of single-cell analysis, a comprehensive review of the recent preclinical and clinical findings in CAR T cell therapy was needed. Here, we categorized and summarized the key points of the studies in which single-cell analysis provided insights into the genomics, epigenomics, transcriptomics and proteomics as well as their respective multi-omics of CAR T cell therapy.

The cellular consequences of particulate matter pollutants in plants: Safeguarding the harmonious integration of structure and function

Particulate matter (PM) pollution is one of the pressing environmental concerns confronting human civilization in the face of the Anthropocene era. Plants are continuously exposed to an accelerating PM, threatening their growth and productivity. Although plants and plant-based infrastructures can potentially reduce ambient air pollutants, PM still affects them morphologically, anatomically, and physiologically. This review comprehensively summarizes an up-to-date review of plant-PM interaction among different functional plant groups, PM deposition and penetration through aboveground and belowground plant parts, and plants' cellular strategies. Upon exposure, PM represses lipid desaturases, eventually leading to modification of cell wall and membrane and altering cell fluidity; consequently, plants can sense the pollutants and, thus, adapt different cellular strategies. The PM also causes a reduction in the photosynthetically active radiation. The study demonstrated that plants reduce stomatal density to avoid PM uptake and increase stomatal index to compensate for decreased gaseous exchange efficiency and transpiration rates. Furthermore, genes and gene sets associated with photosynthesis, glycolysis, gluconeogenesis, and the TCA cycle were dramatically lowered by PM stress. Several transcription factors, including MYB, C2H2, C3H, G2-like, and WRKY were induced, and metabolites such as proline and soluble sugar were accumulated to increase resistance against stressors. In addition, enzymatic and non-enzymatic antioxidants were also accumulated to scavenge the PM-induced reactive oxygen species (ROS). Taken together, this review provides an insight into plants' underlying cellular mechanisms and gene regulatory networks in response to the PM to determine strategies to preserve their structural and functional blend in the face of particulate pollution. The study concludes by recommending that future research should precisely focus on plants' response to short- and long-term PM exposure.

Pine wilt disease: what do we know from proteomics?

Pine wilt disease (PWD) is a devastating forest disease caused by the pinewood nematode (PWN), Bursaphelenchus xylophilus, a migratory endoparasite that infects several coniferous species. During the last 20 years, advances have been made for understanding the molecular bases of PWN-host trees interactions. Major advances emerged from transcriptomic and genomic studies, which revealed some unique features related to PWN pathogenicity and constituted fundamental data that allowed the development of postgenomic studies. Here we review the proteomic approaches that were applied to study PWD and integrated the current knowledge on the molecular basis of the PWN pathogenicity. Proteomics has been useful for understanding cellular activities and protein functions involved in PWN-host trees interactions, shedding light into the mechanisms associated with PWN pathogenicity and being promising tools to better clarify host trees PWN resistance/susceptibility.

Identification of differentially expressed exosome proteins in serum as potential biomarkers for cognitive impairments in cerebral small vessel disease

BACKGROUND

Cognitive impairment arising from cerebral small vessel disease (CSVD) represents a critical subtype of vascular cognitive impairments (VCI) and is the primary cause of vascular dementia. However, identifying reliable clinical and laboratory indicators for this disease remain elusive. We hypothesize that plasma exosome proteins hold the potential to serve as biomarkers for the onset of cognitive dysfunction associated with cerebrovascular diseases.

METHODS

We employed TMT-based proteomics to discern variations in serum exosome proteomes between individuals with cognitive impairments due to CSVD and healthy volunteers.

RESULTS

Each group comprised 18 subjects, and through differential expression analysis, we identified 22 down-regulated and 8 up-regulated proteins between the two groups. Our research revealed 30 differentially expressed plasma exosome proteins, including histone, proteasome, clusterin and coagulation factor XIII, in individuals with cognitive impairments caused by CSVD.

CONCLUSION

The 30 differentially expressed plasma exosome proteins identified in our study are promising as biomarkers for diagnosing cognitive impairments resulting from CSVD. These findings may help us better understand the underlying pathological mechanisms involved in the diseases.

The Inheritance of Hearing Loss and Deafness: A Historical Perspective

If the term "genetics" is a relatively recent proposition, introduced in 1905 by English biologist William Bateson, who rediscovered and spread in the scientific community Mendel's principles of inheritance, since the dawn of human civilization the influence of heredity has been recognized, especially in agricultural crops and animal breeding. And, later, in familial dynasties. In this concise review, we outline the evolution of the idea of hereditary hearing loss, up to the current knowledge of molecular genetics and epigenetics.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

Effect of Sparc knockout on the extracellular matrix of mouse periodontal ligament cells

The periodontal ligament (PDL) is a critical component in maintaining tooth stability. It is composed of cells and an extracellular matrix (ECM), each with unique roles in tissue function and homeostasis. Secreted protein acidic and rich in cysteine (SPARC), a calcium-binding matricellular glycoprotein, plays a crucial role in regulating ECM assembly and turnover, alongside facilitating cellular-ECM interactions. In the present study, mass spectrometry-based proteomics was used to assess the impacts of Sparc-knockout (KO) on PDL-derived cells. Results demonstrated that Sparc-KO significantly reduces ECM production and alters its composition with increased levels of type I collagen. Despite this increase in Sparc-KO, type I collagen was not likely to be effectively integrated into the fibrils due to collagen cross-linking impairment. Furthermore, the pathway and process enrichment analyses suggested that SPARC plays a protective role against ECM degradation by antagonistically interacting with cell-surface collagen receptors. These findings provide detailed insights into the multifaceted role of SPARC in ECM organization, including its impact on ECM production, collagen regulation, and interactions with various cellular compartments. A better understanding of these complex mechanisms is crucial for comprehending the causes of periodontal disease and tissue regeneration, where precise control of ECM organization is necessary.

Proteomic Analysis of In Vitro Plant Tissues (Coffea canephora): A Case of Study

Since the term proteomics was coined by Marc Wilkins in 1994, there has been an explosion in the number of articles reporting the use of the proteomics technique. As the layers of biological organization and their regulation increase, the complexity of living beings increases. Thus, we go from the genome to tissues, cells, cellular compartments, and phenotypes and the complexity of the tools used to study this complexity also increases. Unlike the genome study, in the case of the proteome, we have a more complex panorama. We have a spatial and temporal proteome. Proteomics helps to answer complex biological questions since proteins' function depends on their molecular structure, subcellular localization, and posttranslational modifications. In this protocol, we describe a methodology to extract proteins using different methods, separating proteins by electrophoresis in double-dimensional gels and analyzing the gels using specialized software that allows obtaining information on the number and abundance of the proteins from the gels.

Proteomic-Based Studies on Memory Formation in Normal and Neurodegenerative Disease-Affected Brains

A critical aspect of cognition is the ability to acquire, consolidate, and evoke memories, which is considerably impaired by neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. These mnemonic processes are dependent on signaling cascades, which involve protein expression and degradation. Recent mass spectrometry (MS)-based proteomics has opened a range of possibilities for the study of memory formation and impairment, making it possible to research protein systems not studied before. However, in the context of synaptic proteome related to learning processes and memory formation, a deeper understanding of the synaptic proteome temporal dynamics after induction of synaptic plasticity and the molecular changes underlying the cognitive deficits seen in neurodegenerative diseases is needed. This review analyzes the applications of proteomics for understanding memory processes in both normal and neurodegenerative conditions. Moreover, the most critical experimental studies have been summarized using the PANTHER overrepresentation test. Finally, limitations associated with investigations of memory studies in physiological and neurodegenerative disorders have also been discussed.

Fn-HMGB1 Adsorption Behavior Initiates Early Immune Recognition and Subsequent Osteoinduction of Biomaterials

Implantable biomaterials are widely used in bone tissue engineering, but little is still known about how they initiate early immune recognition and the initial dynamics. Herein, the early immune recognition and subsequent osteoinduction of biphasic calcium phosphate (BCP) after implantation to the protein adsorption behavior is attributed. By liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis, the biomaterial-related molecular patterns (BAMPs) formed after BCP implantation are mapped, dominated by the highly expressed extracellular matrix protein fibronectin (Fn) and the high mobility group box 1 (HMGB1). Molecular dynamics simulations show that Fn has the ability to bind more readily to the BCP surface than HMGB1. The preferential binding of Fn provides a higher adsorption energy for HMGB1. Furthermore, multiple hydrogen bonding sites between HMGB1 and Fn are demonstrated using a molecular docking approach. Ultimately, the formation of BAMPs through HMGB1 antagonist glycyrrhizic acid (GA), resulting in impaired immune recognition of myeloid differentiation factor 88 (MYD88) mediated dendritic cells (DCs) and macrophages (Mφs), as well as failed osteoinduction processes is obstructed. This study introduces a mechanism for early immune recognition of implant materials based on protein adsorption, providing perspectives for future design and application of tissue engineering materials.

Proteomic Analysis of Dictyostelium discoideum by Mass Spectrometry

The large-scale proteomic analysis of Dictyostelium discoideum has contributed to our understanding of intracellular as well as secreted proteins in this versatile model eukaryote. Mass spectrometry-based proteomic analysis is a robust, sensitive, and rapid analytical method for identification and characterization of proteins extracted from tissues, cells, cell fractions, or pull-down assays. The availability of core facilities which make proteomics inexpensive and easy to do has facilitated a wide range of research projects. In this chapter, we present a simple standard methodology to extract proteins and prepare samples from D. discoideum for mass spectrometry and methods to analyze the identified proteins.

Top-Down Proteomics and the Challenges of True Proteoform Characterization

Top-down proteomics (TDP) aims to identify and profile intact protein forms (proteoforms) extracted from biological samples. True proteoform characterization requires that both the base protein sequence be defined and any mass shifts identified, ideally localizing their positions within the protein sequence. Being able to fully elucidate proteoform profiles lends insight into characterizing proteoform-unique roles, and is a crucial aspect of defining protein structure-function relationships and the specific roles of different (combinations of) protein modifications. However, defining and pinpointing protein post-translational modifications (PTMs) on intact proteins remains a challenge. Characterization of (heavily) modified proteins (>∼30 kDa) remains problematic, especially when they exist in a population of similarly modified, or kindred, proteoforms. This issue is compounded as the number of modifications increases, and thus the number of theoretical combinations. Here, we present our perspective on the challenges of analyzing kindred proteoform populations, focusing on annotation of protein modifications on an "average" protein. Furthermore, we discuss the technical requirements to obtain high quality fragmentation spectral data to robustly define site-specific PTMs, and the fact that this is tempered by the time requirements necessary to separate proteoforms in advance of mass spectrometry analysis.

Review on the systems biology research of Yin-deficiency-heat syndrome in traditional Chinese medicine

Traditional Chinese medicine (TCM) is a systematic medical method that has existed for more than 3,000 years. Unlike Western medicine, the disease diagnosis in TCM is carried out by inspection, auscultation, olfaction, interrogation, and palpation. The patient is then treated according to the disease and corresponding TCM syndrome. However, the development of Chinese medicine is stagnated, partially because it can be influenced by subjective factors, such as the experience and knowledge of TCM practitioners, and there is a lack of relevant biological research on TCM syndromes. Yin-deficiency-heat (YDH) syndrome in TCM is characterized by a series of pathological changes caused by the insufficiency of Yin-fluid, inability to moisturize, and the failure to suppress Yang. In recent years, systems biology research on TCM syndromes has gradually become the focus of TCM research, including syndrome differentiation and functional research using systems biology methodologies such as proteomics, transcriptomics, and metabolomics. This journal aims to publish a series of issues on the systems biology research of TCM syndromes that can provide biological indicators for the syndrome differentiation of YDH syndrome and can provide perspectives on the biological research of YDH syndrome.

Proteomic analysis of Biliverdin protected cerebral ischemia-reperfusion injury in rats

Biliverdin, a heme metabolite, has been previously reported to alleviate cerebral ischemic reperfusion injury (CIRI). However, the alterations of brain proteome profiles underlying this treatment remain elusive. The objective of this study is to analyze the differential protein expression profile in cerebral cortex of rats involved in anti-CIRI effects of Biliverdin, providing experimental foundation for searching specific marker proteins. Rat model of MCAO/R was established, HE staining, TTC staining, TUNEL staining, and neurological behavioral examination, corner turning test, adhesive removal test, were performed to validate the effects of Biliverdin, and the results indicated that Biliverdin plays a significant role in alleviating CIRI. Furthermore, proteomic analysis of brain tissues of rats subjected to CIRI following Biliverdin treatment was performed using an integrated TMT-based quantitative proteomic approach coupled with LC-MS/MS technology to clarify the comprehensive mechanisms of Biliverdin in CIRI. First, we conducted strict quality control data for TMT experiments. Finally, a total of 7366 proteins were identified, of which 95 proteins were differentially expressed (DEPs) between the CIRI group and the Sham group and 52 between the CIRI and BV groups. In addition, two overlapping proteins among the 147 DEPs, Atg4c and Camlg, were validated by RT-qPCR and western blotting, and their levels were consistent with the results of TMT analysis. Taken together, the current findings firstly mapped comprehensive proteomic changes after CIRI treated with Biliverdin, providing a foundation for developing potentially therapeutic targets of anti-CIRI of Biliverdin and clinically prognostic biomarkers of stroke.

Whole-Transcriptome RNA Sequencing Uncovers the Global Expression Changes and RNA Regulatory Networks in Duck Embryonic Myogenesis

Duck meat is pivotal in providing high-quality protein for human nutrition, underscoring the importance of studying duck myogenesis. The regulatory mechanisms governing duck myogenesis involve both coding and non-coding RNAs, yet their specific expression patterns and molecular mechanisms remain elusive. To address this knowledge gap, we performed expression profiling analyses of mRNAs, lncRNAs, circRNAs, and miRNAs involved in duck myogenesis using whole-transcriptome RNA-seq. Our analysis identified 1733 differentially expressed (DE)-mRNAs, 1116 DE-lncRNAs, 54 DE-circRNAs, and 174 DE-miRNAs when comparing myoblasts and myotubes. A GO analysis highlighted the enrichment of DE molecules in the extracellular region, protein binding, and exocyst. A KEGG analysis pinpointed pathways related to ferroptosis, PPAR signaling, nitrogen metabolism, cell cycle, cardiac muscle contraction, glycerolipid metabolism, and actin cytoskeleton. A total of 51 trans-acting lncRNAs, including ENSAPLT00020002101 and ENSAPLT00020012069, were predicted to participate in regulating myoblast proliferation and differentiation. Based on the ceRNAs, we constructed lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA ceRNA networks involving five miRNAs (miR-129-5p, miR-133a-5p, miR-22-3p, miR-27b-3p, and let-7b-5p) that are relevant to myogenesis. Furthermore, the GO and KEGG analyses of the DE-mRNAs within the ceRNA network underscored the significant enrichment of the glycerolipid metabolism pathway. We identified five different DE-mRNAs, specifically ENSAPLG00020001677, ENSAPLG00020002183, ENSAPLG00020005019, ENSAPLG00020010497, and ENSAPLG00020017682, as potential target genes that are crucial for myogenesis in the context of glycerolipid metabolism. These five mRNAs are integral to ceRNA networks, with miR-107_R-2 and miR-1260 emerging as key regulators. In summary, this study provides a valuable resource elucidating the intricate interplay of mRNA-lncRNA-circRNA-miRNA in duck myogenesis, shedding light on the molecular mechanisms that govern this critical biological process.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

Quantitative proteomic analysis of the mechanism of Cd toxicity in Enterobacter sp. FM-1: Comparison of different growth stages

Enterobacter sp. are widely used in bioremediation, but the mechanism of Cadmium (Cd) toxicity in Enterobacter sp. has been poorly studied. In the present study, we determined the tolerance of Enterobacter sp. FM-1 to Cd by analyzing the physiological and biochemical responses of FM-1 induced under Cd stress. Differentially expressed proteins (DEPs) under exposure to different Cd environments were analyzed by 4D-label-free proteomics to provide a comprehensive understanding of Cd toxicity in FM-1. The greatest total number of DEPs, 1148, was found in the High concentration vs. Control comparison group at 10 h. When protein expression was compared after different incubation times, FM-1 showed the highest Cd tolerance at 48 h. Additionally, with an increasing incubation time, different comparison groups gradually began to show similar growth patterns, which was reflected in the GO enrichment analysis. Notably, only 815 proteins were identified in the High concentration vs. Control group, and KEGG enrichment analysis revealed that these proteins were significantly enriched in the pyruvate metabolism, oxidative phosphorylation, peroxisome, glyoxylate and dicarboxylate metabolism, and citrate cycle pathways. These results suggested that an increased incubation time allows FM-1 adapt and survive in an environment with Cd toxicity, and protein expression significantly increased in response to oxidative stress in a Cd-contaminated environment during the pre-growth period. This study provides new perspectives on bacterial participation in bioremediation and expands our understanding of the mechanism of bacterial resistance under Cd exposure.

Insight into the underlying molecular mechanism of dilated cardiomyopathy through integrative analysis of data mining, iTRAQ-PRM proteomics and bioinformatics

BACKGROUND

DCM is a common cardiomyopathy worldwide, which is characterized by ventricular dilatation and systolic dysfunction. DCM is one of the most widespread diseases contributing to sudden death and heart failure. However, our understanding of its molecular mechanisms is limited because of its etiology and underlying mechanisms. Hence, this study explored the underlying molecular mechanism of dilated cardiomyopathy through integrative analysis of data mining, iTRAQ-PRM proteomics and bioinformatics METHODS: DCM target genes were downloaded from the public databases. Next, DCM was induced in 20 rats by 8 weeks doxorubicin treatment (2.5 mg/kg/week). We applied isobaric tags for a relative and absolute quantification (iTRAQ) coupled with proteomics approach to identify differentially expressed proteins (DEPs) in myocardial tissue. After association analysis of the DEPs and the key target genes, subsequent analyses, including functional annotation, pathway enrichment, validation, were performed.

RESULTS

Nine hundred thirty-five genes were identified as key target genes from public databases. Meanwhile, a total of 782 DEPs, including 348 up-regulated and 434 down-regulated proteins, were identified in our animal experiment. The functional annotation of these DEPs revealed complicated molecular mechanisms including TCA cycle, Oxidative phosphorylation, Cardiac muscle contraction. Moreover, the DEPs were analyzed for association with the key target genes screened in the public dataset. We further determined the importance of these three pathways.

CONCLUSION

Our results demonstrate that TCA cycle, Oxidative phosphorylation, Cardiac muscle contraction played important roles in the detailed molecular mechanisms of DCM.

Can single-cell and spatial omics unravel the pathophysiology of pre-eclampsia?

Pre-eclampsia is a leading cause of maternal and fetal morbidity and mortality. Characterised by the onset of hypertension and proteinuria in the second half of pregnancy, it can lead to maternal end-organ injury such as cerebral ischemia and oedema, pulmonary oedema and renal failure, and potentially fatal outcomes for both mother and fetus. The causes of the different maternal end-organ phenotypes of pre-eclampsia and why some women develop pre-eclampsia condition early in pregnancy have yet to be elucidated. Omics methods include proteomics, genomics, metabolomics, transcriptomics. These omics techniques, previously mostly used on bulk tissue and individually, are increasingly available at a single cellular level and can be combined with each other. Multi-omics techniques on a single-cell or spatial level provide us with a powerful tool to understand the pathophysiology of pre-eclampsia. This review will explore the status of omics methods and how they can and could contribute to understanding the pathophysiology of pre-eclampsia.

Acquired Male Hypogonadism in the Post-Genomic Era-A Narrative Review

Although precision medicine took its first steps from genomic medicine, it has gone far beyond genomics, considering the full complexity of cellular physiology. Therefore, the present time can be considered as the "post-genomic era". In detail, proteomics captures the overall protein profile of an analyzed sample, whilst metabolomics has the purpose of studying the molecular aspects of a known medical condition through the measurement of metabolites with low molecular weight in biological specimens. In this review, the role of post-genomic platforms, namely proteomics and metabolomics, is evaluated with a specific interest in their application for the identification of novel biomarkers in male hypogonadism and in the identification of new perspectives of knowledge on the pathophysiological function of testosterone. Post-genomic platforms, including MS-based proteomics and metabolomics based on ultra-high-performance liquid chromatography-HRMS, have been applied to find solutions to clinical questions related to the diagnosis and treatment of male hypogonadism. In detail, seminal proteomics helped us in identifying novel non-invasive markers of androgen activity to be translated into clinical practice, sperm proteomics revealed the role of testosterone in spermatogenesis, while serum metabolomics helped identify the different metabolic pathways associated with testosterone deficiency and replacement treatment, both in patients with insulin sensitivity and patients with insulin resistance.

Analysis of Altered Flowering Related Genes in a Multi-Silique Rapeseed (Brassica napus L.) Line zws-ms Based on Combination of Genome, Transcriptome and Proteome Data

Based on previous researches, we further investigated the multi-silique trait in rapeseed (Brassica napus L.) line zws-ms. In this study, we used a relatively comprehensive list of flowering related genes in rapeseed and compared them between zws-ms and its near-isogenic line (NIL) zws-217. Genes were studied on genome, transcriptome and proteome levels and then we focused on genes with non-synonymous single nucleotide polymorphism (SNP) or frame-shift insertion-deletion (InDel), finding some genes on the list which changes their sequences. Then, combined with their annotation and the information of their orthologs, certain genes such as BnaA09g05900D, ortholog of AGAMOUS-LIKE 42 (AGL42), which encodes an MADS-box protein, were assumed as probably responsible for the multi-silique trait. Also, we analyzed the Differentially Accumulated Proteins (DAPs) between zws-ms and zws-217, revealing some genes involved in homologous recombination and mismatch repair pathways. Since the development of flowers/siliques is crucial to crops and it influences the yield of rapeseed, this study paved a way to deeply understand the mechanism of the multi-pistil flower formation, which may facilitate researches on rapeseed production in future.

Functional proteomics based on protein microarray technology for biomedical research

This chapter traces a route through Proteomics from its origins to the present day. The different proteomics applications are discussed with a focus on microarray technology. Analytical microarrays, functional microarrays and reverse phase microarrays and their different applications are discussed. Several studies are mentioned where the great versatility of this approach is shown. Finally, the advantages and future challenges of microarray technology are outlined.

Protective effects of Qing-Re-Huo-Xue formula on bleomycin-induced pulmonary fibrosis through the p53/IGFBP3 pathway

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrosing lung disease with high mortality. Inflammation and epithelial mesenchymal transformation (EMT) may play an important role in the occurrence and development of IPF. Qing-Re-Huo-Xue formula (QRHXF) has been used clinically by our team for half a century and has obvious therapeutic effects on lung disease. Nevertheless, the role and mechanism of QRHXF in the treatment of IPF have never been studied.

Methods

A mouse pulmonary fibrosis model was established by intratracheal injection of BLM. The effects of QRHXF on the treatment of pulmonary fibrosis were studied by pulmonary function testing, imaging examination, pathological staining, transmission electron microscopy (TEM) observation and mRNA expression. Tandem mass tag (TMT)-based quantitative proteomics was carried out to analyse the lung protein expression profiles between the control (CTL), bleomycin (BLM) and QRHXF (BLM + QRHXF) groups. Immunohistochemistry and qRT-PCR were used to verify the possible existence of drug target proteins and signalling pathways.

Results

The results of pulmonary function, lung pathology and imaging examinations showed that QRHXF could significantly alleviate BLM-induced pulmonary fibrosis in vivo. Additionally, inflammatory cell infiltration and EMT were markedly reduced in BLM-induced PF mice administered QRHXF. Proteomics detected a total of 35 proteins, of which 17 were upregulated and 18 were downregulated. A total of 19 differentially expressed proteins (DEPs) overlapped between the BLM versus CTL groups and the BLM + QRHXF versus BLM groups. The expression of p53 and IGFBP3 was reversed in the QRHXF intervention group, which was verified by immunohistochemistry and qRT-PCR.

Conclusions

QRHXF attenuated BLM-induced pulmonary fibrosis, and regulation of the p53/IGFBP3 pathway might be associated with its efficacy, which holds promise as a novel treatment strategy for pulmonary fibrosis patients.

Graphical Abstract

A Standardized Protocol for Assuring the Validity of Proteomics Results from Liquid Chromatography-High-Resolution Mass Spectrometry

Significant advances in the technological development of mass spectrometry in the field of proteomics and the generation of extremely large amounts of data require a very critical approach to assure the validity of results. Commonly used procedures involved liquid chromatography followed by high-resolution mass spectrometry measurements. Proteomics analysis is used in many fields including the investigation of the metabolism of biologically active substances in organisms. Thus, there is a need to care about the validity of the obtained results. In this work, we proposed a standardized protocol for proteomic analysis using liquid chromatography-high-resolution mass spectrometry, which covers all of these analytical steps to ensure the validity of the results. For this purpose, we explored the requirements of the ISO/IEC 17025:2017 standard as a reference document for quality control in biochemistry research-based mass spectrometry.

Sex-Biased Expression of Genes Allocated in the Autosomal Chromosomes: Blood LC-MS/MS Protein Profiling in Healthy Subjects

Background

Sex and gender have a large impact in human health and disease prediction. According to genomic/genetics, men differ from women by a limited number of genes in Y chromosome, while the phenotypes of the 2 sexes differ markedly.

Methods

In this study, serum samples from six healthy Bahraini men and women were analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Bioinformatics databases and tools were used for protein/peptide (PPs) identification and gene localization. The PPs that differed significantly (p < 0.05, ANOVA) in abundance with a fold change (FC) of ≥1.5 were identified.

Results

Revealed 20 PPs, 11 were upregulated in women with very high FC (up to 8 folds), and 9 were upregulated in men but with much lower FC. The PPs are encoded by genes located in autosomal chromosomes, indicative of sex-biased gene expression. The only PP related to sex, the sex hormone-binding globulin, was upregulated in women. The remaining PPs were involved in immunity, lipid metabolism, gene expression, connective tissue, and others, with some overlap in function.

Conclusions

The upregulated PPs in men or women are mostly reflecting the functon or risk/protection provided by the PPs to the specific sex, e.g., Apo-B100 of LDLC. Finally, the basis of sex-biased gene expression and sex phenotypic differences needs further investigation.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Application of Proteomics Analysis and Animal Models in Optic Nerve Injury Diseases

Optic nerve damage is a common cause of blindness. Optic nerve injury is often accompanied by fundus vascular disease, retinal ganglion cell apoptosis, and changes in retinal thickness. These changes can cause alterations in protein expression within neurons in the retina. Proteomics analysis offers conclusive evidence to decode a biological system. Furthermore, animal models of optic nerve injury made it possible to gain insight into pathological mechanisms, therapeutic targets, and effective treatment of such injuries. Proteomics takes the proteome as the research object and studies protein changes in cells and tissues. At present, a variety of proteomic analysis methods have been widely used in the research of optic nerve injury diseases. This review summarizes the application of proteomic research in optic nerve injury diseases and animal models of optic nerve injury. Additionally, differentially expressed proteins are summarized and analyzed. Various optic nerve injuries, including those associated with different etiologies, are discussed along with their potential therapeutic targets and future directions.

Progress in understanding primary glomerular disease: insights from urinary proteomics and in-depth analyses of potential biomarkers based on bioinformatics

Chronic kidney disease (CKD) has become a global public health challenge. While primary glomerular disease (PGD) is one of the leading causes of CKD, the specific pathogenesis of PGD is still unclear. Accurate diagnosis relies largely on invasive renal biopsy, which carries risks of bleeding, pain, infection and kidney vein thrombosis. Problems with the biopsy procedure include lack of glomeruli in the tissue obtained, and the sampling site not being reflective of the overall lesion in the kidney. Repeated renal biopsies to monitor disease progression cannot be performed because of the significant risks of bleeding and kidney vein thrombosis. On the other hand, urine collection, a noninvasive method, can be performed repeatedly, and urinary proteins can reflect pathological changes in the urinary system. Advancements in proteomics technologies, especially mass spectrometry, have facilitated the identification of candidate biomarkers in different pathological types of PGD. Such biomarkers not only provide insights into the pathogenesis of PGD but also are important for diagnosis, monitoring treatment, and prognosis. In this review, we summarize the findings from studies that have used urinary proteomics, among other omics screens, to identify potential biomarkers for different types of PGD. Moreover, we performed an in-depth bioinformatic analysis to gain a deeper understanding of the biological processes and protein-protein interaction networks in which these candidate biomarkers may participate. This review, including a description of an integrated analysis method, is intended to provide insights into the pathogenesis, noninvasive diagnosis, and personalized treatment efforts of PGD and other associated diseases.

Teeth with acute apical abscess vs. teeth with chronic apical periodontitis: a quantitative and qualitative proteomic analysis

OBJECTIVE

To quantitatively and qualitatively analyze the proteomic profile of teeth with acute apical abscesses (AAA) compared with teeth with chronic apical periodontitis (CAP) and to correlate the expression of detected human proteins with their main biological functions.

MATERIALS AND METHODS

Samples were obtained from root canals of 9 patients diagnosed with AAA and 9 with CAP. Samples were analyzed by reversed-phase liquid chromatography coupled to mass spectrometry. Label-free quantitative proteomic analysis was performed by Protein Lynx Global Service software. Differences in protein expression were calculated using the t-test (p < 0.05).

RESULTS

In total, 246 human proteins were identified from all samples. Proteins exclusively found in the AAA group were mainly associated with the immunoinflammatory response and oxidative stress response. In the quantitative analysis, 17 proteins were upregulated (p < 0.05) in the AAA group, including alpha-1-acid glycoprotein, hemopexin, fibrinogen gamma chain, and immunoglobulin. Additionally, 61 proteins were downregulated (p < 0.05), comprising cathepsin G, moesin, gelsolin, and transketolase. Most of the proteins were from the extracellular matrix, cytoplasm, and nucleus.

CONCLUSIONS

The common proteins between the groups were mainly associated with the immune response at both expression levels. Upregulated proteins mostly belonged to the acute-phase proteins, while the downregulated proteins were associated with DNA/RNA regulation and repair, and structural function.

CLINICAL RELEVANCE

The host response is directly related to the development of apical abscesses. Thus, understanding the behavior of human proteins against the endodontic pathogens involved in this condition might contribute to the study of new approaches related to the treatment of this disease.

Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles

The progressive loss of skeletal muscle mass and concomitant reduction in contractile strength plays a central role in frailty syndrome. Age-related neuronal impairments are closely associated with sarcopenia in the elderly, which is characterized by severe muscular atrophy that can considerably lessen the overall quality of life at old age. Mass-spectrometry-based proteomic surveys of senescent human skeletal muscles, as well as animal models of sarcopenia, have decisively improved our understanding of the molecular and cellular consequences of muscular atrophy and associated fiber-type shifting during aging. This review outlines the mass spectrometric identification of proteome-wide changes in atrophying skeletal muscles, with a focus on contractile proteins as potential markers of changes in fiber-type distribution patterns. The observed trend of fast-to-slow transitions in individual human skeletal muscles during the aging process is most likely linked to a preferential susceptibility of fast-twitching muscle fibers to muscular atrophy. Studies with senescent animal models, including mostly aged rodent skeletal muscles, have confirmed fiber-type shifting. The proteomic analysis of fast versus slow isoforms of key contractile proteins, such as myosin heavy chains, myosin light chains, actins, troponins and tropomyosins, suggests them as suitable bioanalytical tools of fiber-type transitions during aging.

An analysis of neurovascular disease markers in the hippocampus of Tupaia chinensis at different growth stages

Introduction

It is considered that Tupaia chinensis can replace laboratory primates in the study of nervous system diseases. To date, however, protein expression in the brain of Tupaia chinensis has not been fully understood.

Method

Three age groups of T. chinensis-15 days, 3 months and 1.5 years-were selected to study their hippocampal protein expression profiles.

Results

A significant difference was observed between the 15-day group and the other two age groups, where as there were no significant differences between the 3-month and 1.5-year age groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that differentially expressed proteins could be enriched in several pathways related to neurovascular diseases, such as metabolic pathways for Alzheimer's disease (AD), Huntington's disease, Parkinson's disease, and other diseases. The KEGG enrichment also showed that relevant protein involved in oxidative phosphorylation in the hippocampus of T. chinensis for 15days were downregulated, and ribosomal proteins (RPs) were upregulated, compared to those in the hippocampus of the other two age groups.

Discussion

It was suggested that when the hippocampus of T. chinensis developed from day 15 to 3 months, the expression of oxidatively phosphorylated proteins and RPs would vary over time. Meanwhile, the hippocamppal protein expression profile of T. chinensis after 3 months had become stable. Moreover, the study underlines that, during the early development of the hippocampus of T. chinensis, energy demand increases while protein synthesis decreases. The mitochondria of T. chinensis changes with age, and the oxidative phosphorylation metabolic pathway of mitochondria is closely related to neurovascular diseases, such as stroke and cerebral ischemia.

The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics

Background

Hyperuricemia and gout are a group of disorders of purine metabolism. In recent years, the incidence of hyperuricemia and gout has been increasing, which is a severe threat to people's health. Several studies on hyperuricemia and gout in proteomics and metabolomics have been conducted recently. Some literature has identified biomarkers that distinguish asymptomatic hyperuricemia from acute gout or remission of gout. We summarize the physiological processes in which these biomarkers may be involved and their role in disease progression.

Methodology

We used professional databases including PubMed, Web of Science to conduct the literature review. This review addresses the current landscape of hyperuricemia and gout biomarkers with a focus on proteomics and metabolomics.

Results

Proteomic methods are used to identify differentially expressed proteins to find specific biomarkers. These findings may be suggestive for the diagnosis and treatment of hyperuricemia and gout to explore the disease pathogenesis. The identified biomarkers may be mediators of the link between hyperuricemia, gout and kidney disease, metabolic syndrome, diabetes and hypertriglyceridemia. Metabolomics reveals the main influential pathways through small molecule metabolites, such as amino acid metabolism, lipid metabolism, or other characteristic metabolic pathways. These studies have contributed to the discovery of Chinese medicine. Some traditional Chinese medicine compounds can improve the metabolic disorders of the disease.

Conclusions

We suggest some possible relationships of potential biomarkers with inflammatory episodes, complement activation, and metabolic pathways. These biomarkers are able to distinguish between different stages of disease development. However, there are relatively few proteomic as well as metabolomic studies on hyperuricemia and gout, and some experiments are only primary screening tests, which need further in-depth study.

Investigation of the Effects of Glabridin on the Proliferation, Apoptosis, and Migration of the Human Colon Cancer Cell Lines SW480 and SW620 and Its Mechanism Based on Reverse Virtual Screening and Proteomics

Colon cancer is a relatively common malignant tumor of the digestive tract. Currently, most colon cancers originate from adenoma carcinogenesis. By screening various licorice flavonoids with anticancer effects, we found that glabridin (GBN) has a prominent anticolon cancer effect. First, we initially explored whether GBN can inhibit proliferation, migration, and invasion and induce apoptosis in SW480 and SW620 cells. Next, we exploited reverse virtual and proteomics technologies to screen out closely related target pathways on the basis of a drug and target database. At the same time, we constructed the structure of the GBN target pathway in colon cancer. We predicted that GBN can regulate the phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT)-mammalian target of the rapamycin pathway (mTOR) pathway to fight colon cancer. Finally, through Western blot analysis and qRT-PCR, we verified that the expression levels of the PI3K, AKT, and mTOR proteins and genes in this pathway were significantly reduced after GBN administration. In short, the promising discovery of the anticolon cancer mechanism of GBN provides a reliable experimental basis for subsequent new drug development.

Proteomic profiling of canine fibrosarcoma and adjacent peritumoral tissue

Fibrosarcoma (FSA) are rare soft tissue tumors that display aggressive local behavior and invasive growth leading to high rates of tumor recurrence. While the low incidence in humans hampers detailed understanding of the disease, FSA are frequent in dogs and present potential models for the human condition. However, a lack of in-depth molecular characterization of FSA and unaffected peritumoral tissue (PTT) in both species impedes the translational potential of dogs. To address this shortcoming, we characterized canine FSA and matched skeletal muscle, adipose and connective tissue using laser-capture microdissection (LCM) and LC-MS/MS in 30 formalin-fixed paraffin embedded (FFPE) specimens. Principal component analysis of 3'530 different proteins detected across all samples clearly separates the four tissues, with several targets strongly differentiating tumor from all three PTTs. 25 proteins were exclusively found in tumor tissue in ≥80% of cases. Among these, CD68 (a macrophage marker), Optineurin (OPTN), Nuclear receptor coactivator 5 (NCOA5), RAP1GDS1 (Rap1 GTPase-GDP dissociation stimulator 1) and Stromal cell derived factor 2 like 1 (SDF2L1) were present in ≥90% of FSA. Protein expression across all FSA was highly homogeneous and characterized by MYC and TP53 signaling, hyperactive EIF2 and immune-related changes as well as strongly decreased oxidative phosphorylation and oxidative lipid metabolism. Finally, we demonstrate significant molecular homology between canine FSA and human soft-tissue sarcomas, emphasizing the relevance of studying canine FSA as a model for human FSA. In conclusion, we provide the first detailed overview of proteomic changes in FSA and surrounding PTT with relevance for the human disease.

Statistical and Computational Methods for Proteogenomic Data Analysis

Proteins are the functional molecules for almost all cellular and biological processes. They are also the targets of most drugs. Proteins employ complex, multilevel regulations, so their abundance levels do not well correlated with their mRNA expression levels. The structure, activity, and functional roles of proteins are affected by posttranslational modifications (PTM), which are even less correlated with mRNA expression levels than protein abundances. Comprehensive characterization of the proteomics data is critical for understanding the molecular and cellular mechanisms of biological systems and developing news therapeutics. Current large-scale proteomic profiling technologies, such as mass spectrometry, provide relative identification of peptides and proteins, with data vulnerable to outliers, batch effects, and nonrandom missingness. In order to perform high-quality proteomic data analysis, we will first introduce a data preprocessing and quality control pipeline that includes normalization, outlier detection and removal, batch effect identification and handling, and missing data imputation. Then, we will describe several statistical methods that leverage well-processed proteomic data to generate scientific discoveries, especially with an integration with genomics and transcriptomics. These methods cover topics like association analysis, network construction, clustering, and cell-type deconvolution. To demonstrate these methods, we will use the proteogenomic data from the lung squamous cell carcinoma study of the Clinical Proteomic Tumor Analysis Consortium and provide sample codes for data access and analyses.