SILAC for biomarker discovery

Socially transferred materials: why and how to study them

When biological material is transferred from one individual's body to another, as in ejaculate, eggs, and milk, secondary donor-produced molecules are often transferred along with the main cargo, and influence the physiology and fitness of the receiver. Both social and solitary animals exhibit such social transfers at certain life stages. The secondary, bioactive, and transfer-supporting components in socially transferred materials have evolved convergently to the point where they are used in applications across taxa and type of transfer. The composition of these materials is typically highly dynamic and context dependent, and their components drive the physiological and behavioral evolution of many taxa. Our establishment of the concept of socially transferred materials unifies this multidisciplinary topic and will benefit both theory and applications.

Alisol B 23-acetate-induced HepG2 hepatoma cell death through mTOR signaling-initiated G1 cell cycle arrest and apoptosis: A quantitative proteomic study

Objective

The present study aimed to investigate the molecular events in alisol B 23-acetate (ABA) cytotoxic activity against a liver cancer cell line.

Methods

First, we employed a quantitative proteomics approach based on stable isotope labeling by amino acids in cell culture (SILAC) to identify the different proteins expressed in HepG2 liver cancer cells upon exposure to ABA. Next, bioinformatics analyses through DAVID and STRING on-line tools were used to predict the pathways involved. Finally, we applied functional validation including cell cycle analysis and Western blotting for apoptosis and mTOR pathway-related proteins to confirm the bioinformatics predictions.

Results

We identified 330 different proteins with the SILAC-based quantitative proteomics approach. The bioinformatics analysis and the functional validation revealed that the mTOR pathway, ribosome biogenesis, cell cycle, and apoptosis pathways were differentially regulated by ABA. G1 cell cycle arrest, apoptosis and mTOR inhibition were confirmed.

Conclusions

ABA, a potential mTOR inhibitor, induces the disruption of ribosomal biogenesis. It also affects the mTOR-MRP axis to cause G1 cell cycle arrest and finally leads to cancer cell apoptosis.

Current Status of Proteomic Technologies for Discovering and Identifying Gingival Crevicular Fluid Biomarkers for Periodontal Disease

Periodontal disease is caused by bacteria in dental biofilms. To eliminate the bacteria, immune system cells release substances that inflame and damage the gums, periodontal ligament, or alveolar bone, leading to swollen bleeding gums, which is a sign of gingivitis. Damage from periodontal disease can cause teeth to loosen also. Studies have demonstrated the proteomic approach to be a promising tool for the discovery and identification of biochemical markers of periodontal diseases. Recently, many studies have applied expression proteomics to identify proteins whose expression levels are altered by disease. As a fluid lying in close proximity to the periodontal tissue, the gingival crevicular fluid (GCF) is the principal target in the search for periodontal disease biomarkers because its protein composition may reflect the disease pathophysiology. Biochemical marker analysis of GCF is effective for objective diagnosis in the early and advanced stages of periodontal disease. Periodontal diseases are also promising targets for proteomics, and several groups, including ours, have applied proteomics in the search for GCF biomarkers of periodontal diseases. This search is of continuing interest in the field of experimental and clinical periodontal disease research. In this article, we summarize the current situation of proteomic technologies to discover and identify GCF biomarkers for periodontal diseases.

Analytical techniques for characterization of biological molecules - proteins and aptamers/oligonucleotides

With the advent of the high-throughput technologies and exciting times for biology, the discipline of analytical methodology is experiencing a surge in the growth and the scope. Over the years, multitude of analytical techniques have evolved from a work-intensive, low sensitivity and high volume of reagent and sample consumption endeavor to automated, better selectivity, lower limit of quantification and cost-effective techniques for biological research. In this review, we give an overview of the currently available wide range of cell-based and noncell based and structural based analytical techniques, their principle and biological applications. The analytical techniques discussed in this paper includes surface plasmon resonance, electrophoresis, enzyme linked immunosorbent assay, Western blotting, flow cytometry, fluorescence activated cell sorting, mass spectrometry, nuclear magnetic resonance and x-ray crystallography.

Inhibition of Aurora kinases induces apoptosis and autophagy via AURKB/p70S6K/RPL15 axis in human leukemia cells

Leukemia is a common malignancy of blood cells with poor prognosis in many patients. Aurora kinases, a family of serine/threonine kinases, play a key role in regulating cell division and mitosis and are linked to tumorigenesis, metastasis, and poor prognosis in many human cancers including leukemia and lymphoma. Danusertib (Danu) is a pan-inhibitor of Aurora kinases with few data available in leukemia therapy. This study aimed to identify new molecular targets for Aurora kinase inhibition in human leukemia cells using quantitative proteomic analysis followed by verification experiments. There were at least 2932 proteins responding to Danu treatment, including AURKB, p70S6K, and RPL15, and 603 functional proteins and 245 canonical signaling pathways were involved in regulating cell proliferation, metabolism, apoptosis, and autophagy. The proteomic data suggested that Danu-regulated RPL15 signaling might contribute to the cancer cell killing effect. Our verification experiments confirmed that Danu negatively regulated AURKB/p70S6K/RPL15 axis with the involvement of PI3K/Akt/mTOR, AMPK, and p38 MAPK signaling pathways, leading to the induction of apoptosis and autophagy in human leukemia cells. Further studies are warranted to verify the feasibility via targeting AURKB/p70S6K/RPL15 axis for leukemia therapy.

Proteomic-Based Approaches for the Study of Cytokines in Lung Cancer

Proteomic techniques are currently used to understand the biology of different human diseases, including studies of the cell signaling pathways implicated in cancer progression, which is important in knowing the roles of different proteins in tumor development. Due to its poor prognosis, proteomic approaches are focused on the identification of new biomarkers for the early diagnosis, prognosis, and targeted treatment of lung cancer. Cytokines are proteins involved in inflammatory processes and have been proposed as lung cancer biomarkers and therapeutic targets because it has been reported that some cytokines play important roles in tumor development, invasion, and metastasis. In this review, we aim to summarize the different proteomic techniques used to discover new lung cancer biomarkers and therapeutic targets. Several cytokines have been identified as important players in lung cancer using these techniques. We underline the most important cytokines that are useful as biomarkers and therapeutic targets. We also summarize some of the therapeutic strategies targeted for these cytokines in lung cancer.

A universal SI-traceable isotope dilution mass spectrometry method for protein quantitation in a matrix by tandem mass tag technology

Isotope dilution mass spectrometry (IDMS), an important metrological method, is widely used for absolute quantification of peptides and proteins. IDMS employs an isotope-labeled peptide or protein as an internal standard although the use of a protein provides improved accuracy. Generally, the isotope-labeled protein is obtained by stable isotope labeling by amino acids in cell culture (SILAC) technology. However, SILAC is expensive, laborious, and time-consuming. To overcome these drawbacks, a novel universal SI-traceable IDMS method for absolute quantification of proteins in a matrix is described with human transferrin (hTRF). The hTRF and a human serum sample were labeled with different tandem mass tags (TMTs). After mixing the TMT-labeled hTRF and serum sample together followed by digestion, the peptides were separated by nano-liquid chromatography and analyzed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Using the signature peptides, we calculated the ratios of reporter ions from the TMT-labeled peptides which, in turn, allowed determination of the mass fraction of hTRF. The recovery ranged from 97% to 105% with a CV of 3.9%. The LOD and LOQ were 1.71 × 10(-5) g/g and 5.69 × 10(-5) g/g of hTRF in human serum, respectively, and the relative expanded uncertainty was 4.7% with a mass fraction of 2.08 mg/g. For comparison, an enzyme-linked immunosorbent assay (ELISA) method for hTRF yielded a mass fraction of 2.03 mg/g. This method provides a starting point for establishing IDMS technology to accurately determine the mass fractions of protein biomarkers in a matrix with traceability to SI units. This technology should support the development of a metrological method useful for quantification of a wide variety of proteins.

Diagnostics and Resistance Profiling of Bacterial Pathogens

Worldwide infectious disease is one of the leading causes of death. Despite improvements in technology and healthcare services, morbidity and mortality due to infections have remained unchanged over the past few decades. The high and increasing rate of antibiotic resistance is further aggravating the situation. Growing resistance hampers the use of conventional antibiotics, and substantial higher mortality rates are reported in patients given ineffective empiric therapy mainly due to resistance to the agents used. These infections cause suffering, incapacity, and death and impose an enormous financial burden on both healthcare systems and on society in general. The accelerating development of multidrug resistance is one of the greatest diagnostic and therapeutic challenges to modern medicine. The lack of new antibiotic options underscores the need for optimization of current diagnostics, therapies, and prevention of the spread of multidrug-resistant organisms. The so-called -omics technologies (genomics, transcriptomics, proteomics, and metabolomics) have yielded large-scale datasets that advanced the search for biomarkers of infectious diseases in the last decade. One can imagine that in the future the implementation of biomarker-driven molecular test systems will transform diagnostics of infectious diseases and will significantly accelerate the identification of the bacterial pathogens at the infected host site. Furthermore, molecular tests based on the identification of markers of antibiotic resistance will dramatically change resistance profiling. The replacement of culturing methods by molecular test systems for early diagnosis will provide the basis not only for a prompt and targeted therapy, but also for a much more effective stewardship of antibiotic agents and a reduction of the spread of multidrug resistance as well as the appearance of new antibiotic resistances.

CILAIR-Based Secretome Analysis of Obese Visceral and Subcutaneous Adipose Tissues Reveals Distinctive ECM Remodeling and Inflammation Mediators

In the context of obesity, strong evidences support a distinctive pathological contribution of adipose tissue depending on its anatomical site of accumulation. Therefore, subcutaneous adipose tissue (SAT) has been lately considered metabolically benign compared to visceral fat (VAT), whose location is associated to the risk of developing cardiovascular disease, insulin resistance, and other associated comorbidities. Under the above situation, the chronic local inflammation that characterizes obese adipose tissue, has acquired a major role on the pathogenesis of obesity. In this work, we have analyzed for the first time human obese VAT and SAT secretomes using an improved quantitative proteomic approach for the study of tissue secretomes, Comparison of Isotope-Labeled Amino acid Incorporation Rates (CILAIR). The use of double isotope-labeling-CILAIR approach to analyze VAT and SAT secretomes allowed the identification of location-specific secreted proteins and its differential secretion. Additionally to the very high percentage of identified proteins previously implicated in obesity or in its comorbidities, this approach was revealed as a useful tool for the study of the obese adipose tissue microenvironment including extracellular matrix (ECM) remodeling and inflammatory status. The results herein presented reinforce the fact that VAT and SAT depots have distinct features and contribute differentially to metabolic disease.