Label-free quantification in clinical proteomics

Mass spectrometry-based proteomic approaches for salivary protein biomarkers discovery and dental caries diagnosis: A critical review

Dental caries is a multifactorial chronic disease resulting from the intricate interplay among acid-generating bacteria, fermentable carbohydrates, and several host factors such as saliva. Saliva comprises several proteins which could be utilized as biomarkers for caries prevention, diagnosis, and prognosis. Mass spectrometry-based salivary proteomics approaches, owing to their sensitivity, provide the opportunity to investigate and unveil crucial cariogenic pathogen activity and host indicators and may demonstrate clinically relevant biomarkers to improve caries diagnosis and management. The present review outlines the published literature of human clinical proteomics investigations on caries and extensively elucidates frequently reported salivary proteins as biomarkers. This review also discusses important aspects while designing an experimental proteomics workflow. The protein-protein interactions and the clinical relevance of salivary proteins as biomarkers for caries, together with uninvestigated domains of the discipline are also discussed critically.

Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.

Proteomic analyses of venom from a Spider Hawk, Pepsis decorata

Background

The composition of the venom from solitary wasps is poorly known, although these animals are considered sources of bioactive substances. Until the present moment, there is only one proteomic characterization of the venom of wasps of the family Pompilidae and this is the first proteomic characterization for the genus Pepsis.

Methods

To elucidate the components of Pepsis decorata venom, the present work sought to identify proteins using four different experimental conditions, namely: (A) crude venom; (B) reduced and alkylated venom; (C) trypsin-digested reduced and alkylated venom, and; (D) chymotrypsin-digested reduced and alkylated venom. Furthermore, three different mass spectrometers were used (Ion Trap-Time of Flight, Quadrupole-Time of Flight, and Linear Triple Quadruple).

Results

Proteomics analysis revealed the existence of different enzymes related to the insect's physiology in the venom composition. Besides toxins, angiotensin-converting enzyme (ACE), hyaluronidase, and Kunitz-type inhibitors were also identified.

Conclusion

The data showed that the venom of Pepsis decorata is mostly composed of proteins involved in the metabolism of arthropods, as occurs in parasitic wasps, although some classical toxins were recorded, and among them, for the first time, ACE was found in the venom of solitary wasps. This integrative approach expanded the range of compounds identified in protein analyses, proving to be efficient in the proteomic characterization of little-known species. It is our understanding that the current work will provide a solid base for future studies dealing with other Hymenoptera venoms.

Next-generation proteomics technologies in Alzheimer's disease: from clinical research to routine diagnostics

INTRODUCTION

Clinical proteomics studies of Alzheimer's disease (AD) research aim to identify biomarkers useful for clinical research, diagnostics, and improve our understanding of the pathological processes involved in the disease. The rapidly increasing performance of proteomics technologies is likely to have great impact on AD research.

AREAS COVERED

We review recent proteomics approaches that have advanced the field of clinical AD research. Specifically, we discuss the application of targeted mass spectrometry (MS), labeling-based and label-free MS-based as well as affinity-based proteomics to AD biomarker development, underpinning their importance with the latest impactful clinical studies. We evaluate how proteomics technologies have been adapted to meet current challenges. Finally, we discuss the limitations and potential of proteomics techniques and whether their scope might extend beyond current research-based applications.

EXPERT OPINION

To date, proteomics technologies in the AD field have been largely limited to AD biomarker discovery. The recent development of the first successful disease-modifying treatments of AD will further increase the need for blood biomarkers for early, accurate diagnosis, and CSF biomarkers that reflect specific pathological processes. Proteomics has the potential to meet these requirements and to progress into clinical routine practice, provided that current limitations are overcome.

Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD)

Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.

Protein Profiling of a Cellular Model of NAFLD by Advanced Bioanalytical Approaches

Advanced quantitative bioanalytical approaches in combination with network analyses allow us to answer complex biological questions, such as the description of changes in protein profiles under disease conditions or upon treatment with drugs. In the present work, three quantitative proteomic approaches-either based on labelling or not-in combination with network analyses were applied to a new in vitro cellular model of nonalcoholic fatty liver disease (NAFLD) for the first time. This disease is characterized by the accumulation of lipids, inflammation, fibrosis, and insulin resistance. Hepatic G2 cells were used as model, and NAFLD was induced by a complex of oleic acid and bovine albumin. The development of the disease was verified by lipid vesicle staining and by the increase in the expression of perilipin-2-a protein constitutively present in the vesicles during NAFLD. The nLC-MS/MS analyses of peptide samples obtained from three different proteomic approaches resulted in accurate and reproducible quantitative data of protein fold-change expressed in NAFLD versus control cells. The differentially regulated proteins were used to evaluate the involved and statistically enriched pathways. Network analyses highlighted several functional and disease modules affected by NAFLD, such as inflammation, oxidative stress defense, cell proliferation, and ferroptosis. Each quantitative approach allowed the identification of similar modulated pathways. The combination of the three approaches improved the power of statistical network analyses by increasing the number of involved proteins and their fold-change. In conclusion, the application of advanced bioanalytical approaches in combination with pathway analyses allows the in-depth and accurate description of the protein profile of an in vitro cellular model of NAFLD by using high-resolution quantitative mass spectrometry data. This model could be extremely useful in the discovery of new drugs to modulate the equilibrium NAFLD health state.

Analyzing BMP2, FGFR, and TGF Beta Expressions in High-Grade Osteosarcoma Untreated and Treated Autografts Using Proteomic Analysis

In the last few decades, biological reconstruction techniques have improved greatly for treating high-grade osteosarcoma patients. To conserve the limb, and its function the affected tumor-bearing bones have been treated using liquid nitrogen and irradiation processes that enable the removal of entire tumors from the bone, and these treated autografts can be reconstructed for the patients. Here, we focus on the expressions of the growth factor family proteins from the untreated and treated autografts that play a crucial role in bone union, remodeling, and regeneration. In this proteomic study, we identify several important cytoskeletal, transcriptional, and growth factor family proteins that showed substantially low levels in untreated autografts. Interestingly, these protein expressions were elevated after treating the tumor-bearing bones using liquid nitrogen and irradiation. Therefore, from our preliminary findings, we chose to determine the expressions of BMP2, TGF-Beta, and FGFR proteins by the target proteomics approach. Using a newly recruited validation set, we successfully validate the expressions of the selected proteins. Furthermore, the increased growth factor protein expression after treatment with liquid nitrogen may contribute to bone regeneration healing, assist in faster recovery, and reduce local recurrence and metastatic spread in high-grade sarcoma patients.

Proteomic profiling of the carbon-starved Escherichia coli reveals upregulation of stress-inducible pathways implicated in biological adhesion and methylglyoxal metabolism

Starvation in bacteria is a complex adaptive response to deprivation of nutrients that has been shown to implicate a number of stress networks that modulate pathogenicity and antibiotic resistance. Starvation in nature is qualitatively different from in-culture late stationary phase energy source depletion. To look into proteome-level alterations elicited by complete elimination of carbon source, we used Escherichia coli HT115-derived SLE1 strain cells and a combination of label-free and metabolic isotope labeling approaches. We isolated pathways differentially affected by carbon starvation and observed robust upregulation of proteins implicated in networks belonging to Gene Ontology terms 'Biological adhesion' and 'Methylglyoxal metabolism'.

QKI-6 Suppresses Cell Proliferation, Migration, and EMT in Non-Small Cell Lung Cancer

The RNA-binding protein quaking homolog 6 (QKI-6) is a tumor-suppressor gene in several cancers. However, its role in non-small cell lung cancer (NSCLC) is unclear. In this study, we aimed to determine the association between QKI-6 expression and survival and clinicopathological features in patients with NSCLC and identify the related mechanisms. Western blot and immunohistochemistry (IHC) were used to detect QKI-6 expression in NSCLC. The effect of QKI-6 on NSCLC cells was determined by overexpression and knockdown assays, and label-free quantitative proteomics and Western blot were used to identify the underlying mechanisms. Low QKI-6 expression level was positively correlated with poor overall survival in patients with NSCLC. Furthermore, QKI-6 overexpression inhibited NSCLC cell proliferation and migration and induced a block in the G0/G1 phase, and QKI-6 downregulation increased proliferation and migration. QKI-6 inhibited EMT processes via EGFR/SRC/STAT3 signaling by upregulating AGR2. In conclusion, QKI-6 could be used to develop novel strategies for the treatment of NSCLC.

Mass Spectrometry-Based Proteomics for Biomarker Discovery

Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.

Comparative Proteomics Analysis Reveals the Reversal Effect of Cryptotanshinone on Gefitinib-Resistant Cells in Epidermal Growth Factor Receptor-Mutant Lung Cancer

Cryptotanshinone (CTS) is a lipophilic constituent of Salvia miltiorrhiza, with a broad-spectrum anticancer activity. We have observed that CTS enhances the efficacy of gefitinib in human lung cancer H1975 cells, yet little is known about its molecular mechanism. To explore how CTS enhances H1975 cell sensitivity to gefitinib, we figured out differential proteins of H1975 cells treated by gefitinib alone or in combination with CTS using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) bioinformatic analyses of the differential proteins were performed. CTS enhanced H1975 cell sensitivity to gefitinib in vitro and in vivo, with 115 and 128 differential proteins identified, respectively. GO enrichment, KEGG analysis, and PPI network comprehensively demonstrated that CTS mainly impacted the redox process and fatty acid metabolism in H1975 cells. Moreover, three differential proteins, namely, catalase (CAT), heme oxygenase 1 (HMOX1), and stearoyl-CoA desaturase (SCD) were validated by RT-qPCR and Western blot. In conclusion, we used a proteomic method to study the mechanism of CTS enhancing gefitinib sensitivity in H1975 cells. Our finding reveals the potential protein targets of CTS in overcoming gefitinib resistance, which may be therapeutical targets in lung cancer.

Raw walnut kernel: A natural source for dietary proteases and bioactive proteins

Walnut kernels are health-promoting nuts, which are mainly attributed to polyunsaturated fatty acids, phenolics, and phytosterols. However, the information concerning benefits of walnut proteins are limited. In this study, endopeptidases, aminopeptidases, carboxypeptidases, superoxide dismutases, catalases, and phospholipases with respective relative abundance of 2.730, 1.728, 0.477, 3.148, 0.743, and 0.173‰ were identified by liquid chromatography tandem mass spectrometry. These endogenous proteases exhibited activity in a broad pH range of 2-6.5, and optimal at pH 4.5 and 50 °C. Aspartic endopeptidases were predominant endopeptidases, followed by cysteine ones. There were two types of aspartic endopeptidases, one (not inhibited by pepstatin A) exerted activity at pH 2-3 and the other (inhibited by pepstatin A) optimal at pH 4.5. Carboxypeptidases were optimal at pH 4.5, and aminopeptidases exerted activity at pH near 6.5. These endogenous proteases assisted the digestion of walnut proteins, and soaking, especially peeling, greatly improved the in vitro digestibility.

Label-Free Quantitative Proteomic Analysis of Three Strains of Viscerotropic Leishmania Isolated from Patients with Different Epidemiological Types of Visceral Leishmaniasis in China

BACKGROUND

There are three epidemiological types of visceral leishmaniasis in China, which are caused by Leishmania strains belonging to the L. donovani complex. The mechanisms underlying their differences in the population affected, disease latency, and animal host, etc., remain unclear. We investigated the protein abundance differences among Leishmania strains isolated from three types of visceral leishmaniasis endemic areas in China.

METHODS

Promastigotes of the three Leishmania strains were cultured to the log phase and harvested. The protein tryptic digests were analyzed with liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS), followed by label-free quantitative analysis. The MS experiment was performed on a Q Exactive mass spectrometer. Raw spectra were quantitatively analyzed with the MaxQuant software (ver 1.3.0.5) and matched with the reference database. Differentially expressed proteins were analyzed using the bioinformatics method. The MS analysis was repeated three times for each sample.

RESULTS

A total of 5012 proteins were identified across the KS-2, JIASHI-5 and SC6 strains in at least 2 of the three samples replicate. Of them, 1758 were identified to be differentially expressed at least between 2 strains, including 349 with known names. These differentially expressed proteins with known names are involved in biological functions such as energy and lipid metabolic process, nucleotide acid metabolic process, amino acid metabolic process, response to stress, cell membrane/cytoskeleton, cell cycle and proliferation, biological adhesion and proteolysis, localization and transport, regulation of the biological process, and signal transduction.

CONCLUSION

The differentially expressed proteins and their related biological functions may shed light on the pathogenicity of Leishmania and targets for the development of vaccines and medicines.

Unraveling the Neuroprotective Effect of Tinospora cordifolia in a Parkinsonian Mouse Model through the Proteomics Approach

Stress-induced dopaminergic (DAergic) neuronal death in the midbrain region is the primary cause of Parkinson's disease (PD). Following the discovery of l-dopa, multiple drugs have been developed to improve the lifestyle of PD patients; however, none have been suitable for clinical use due to their multiple side effects. Tinospora cordifolia has been used in traditional medicines to treat neurodegenerative diseases. Previously, we reported the neuroprotective role of Tc via inhibition of NF-κB-associated proinflammatory cytokines against MPTP-intoxicated Parkinsonian mice. In the present study, we investigated the neuroprotective molecular mechanism of Tc in a rotenone (ROT)-intoxicated mouse model, using a proteomics approach. Mice were pretreated with Tc extract by oral administration, followed by ROT intoxication. Behavioral tests were performed to check motor functions of mice. Protein was isolated, and label-free quantification (LFQ) was carried out to identify differentially expressed protein (DEP) in control vs PD and PD vs treatment groups. Results were validated by qRT-PCR with the expression of target genes correlating with the proteomics data. In this study, we report 800 DEPs in control vs PD and 133 in PD vs treatment groups. In silico tools demonstrate significant enrichment of biochemical and molecular pathways with DEPs, which are known to be important for PD progression including mitochondrial gene expression, PD pathways, TGF-β signaling, and Alzheimer's disease. This study provides novel insights into the PD progression as well as new therapeutic targets. More importantly, it demonstrates that Tc can exert therapeutic effects by regulating multiple pathways, resulting in neuroprotection.

Integration of transcriptomic and proteomic approaches for snake venom profiling

INTRODUCTION

Snake venoms contain many protein and peptide isoforms with high levels of sequence variation, even within a single species.

AREAS COVERED

In this review, we highlight several examples, from both published and unpublished work in our lab, demonstrating how a combined venom gland transcriptome and proteome methodology allows for comprehensive characterization of venoms, including those from understudied rear-fanged snake species, and we provide recommendations for using these approaches.

EXPERT OPINION

When characterizing venoms, peptide mass fingerprinting using databases built predominately from protein sequences originating from model organisms can be disadvantageous, especially when the intention is to document protein diversity. Therefore, the use of species-specific venom gland transcriptomes corrects for the absence of these unique peptide sequences in databases. The integration of transcriptomics and proteomics improves the accuracy of either approach alone for venom profiling.

Water-Soluble Tomato Extract Fruitflow Alters the Phosphoproteomic Profile of Collagen-Stimulated Platelets

Platelet hyperactivity is a risk factor for cardiovascular disease and thrombosis. Recent studies reported that the tomato extract Fruitflow inhibited platelet function, but the molecular mechanism is still unclear. The present study used proteomics to quantitatively analyze the effect of fruitflow on the inhibition of collagen-stimulated platelets and validated the involvement of several signaling molecules. Fruitflow significantly inhibited human platelet aggregation and P-selectin expression that were induced by collagen. Proteomics analysis revealed that compared fruitflow-treated collagen-stimulated platelets with only collagen-stimulated platelets, 60 proteins were upregulated and 10 proteins were downregulated. Additionally, 66 phosphorylated peptides were upregulated, whereas 37 phosphorylated peptides were downregulated. Gene Ontology analysis indicated that fruitflow treatment downregulated phosphoinositide 3-kinase (PI3K)/protein kinase B and guanosine triphosphatase-mediated signal transduction in collagen-activated platelets. Biological validation indicated that fruitflow decreased Akt, glycogen synthase kinase 3β, p38 mitogen-activated protein kinase (MAPK), and heat shock protein (Hsp27) phosphorylation in collagen-stimulated platelets. Fruitflow recovered cyclic adenosine monophosphate levels in collagen-activated platelets and reduced protein kinase A substrate phosphorylation that was induced by collagen. These findings suggest that fruitflow is a functional food that can inhibit platelet function, conferring beneficial effects for people who are at risk for platelet hyperactivity-associated thrombosis.

Glycoengineering of Mammalian Expression Systems on a Cellular Level

Mammalian expression systems such as Chinese hamster ovary (CHO), mouse myeloma (NS0), and human embryonic kidney (HEK) cells serve a critical role in the biotechnology industry as the production host of choice for recombinant protein therapeutics. Most of the recombinant biologics are glycoproteins that contain complex oligosaccharide or glycan attachments representing a principal component of product quality. Both N-glycans and O-glycans are present in these mammalian cells, but the engineering of N-linked glycosylation is of critical interest in industry and many efforts have been directed to improve this pathway. This is because altering the N-glycan composition can change the product quality of recombinant biotherapeutics in mammalian hosts. In addition, sialylation and fucosylation represent components of the glycosylation pathway that affect circulatory half-life and antibody-dependent cellular cytotoxicity, respectively. In this chapter, we first offer an overview of the glycosylation, sialylation, and fucosylation networks in mammalian cells, specifically CHO cells, which are extensively used in antibody production. Next, genetic engineering technologies used in CHO cells to modulate glycosylation pathways are described. We provide examples of their use in CHO cell engineering approaches to highlight these technologies further. Specifically, we describe efforts to overexpress glycosyltransferases and sialyltransfereases, and efforts to decrease sialidase cleavage and fucosylation. Finally, this chapter covers new strategies and future directions of CHO cell glycoengineering, such as the application of glycoproteomics, glycomics, and the integration of 'omics' approaches to identify, quantify, and characterize the glycosylated proteins in CHO cells. Graphical Abstract.

Comparative proteomics elucidates the dynamics of ovarian development in the Chinese mitten crab Eriocheir sinensis

Ovarian development is a complex physiological process for crustacean reproduction that is divided into the oogonium proliferation stage, endogenous vitellogenic stage, exogenous vitellogenic stage, and oocyte maturation stage. Proteomics analysis offers a feasible approach to reveal the proteins involved in the complex physiological processes of any organism. Therefore, this study performed a comparative proteomics analysis of the ovary and hepatopancreas at three key ovarian stages, including stages I (oogonium proliferation), II (endogenous vitellogenesis) and IV (exogenous vitellogenesis), of the Chinese mitten crab Eriocheir sinensis using a label-free quantitative approach. The results showed that a total of 2,224 proteins were identified, and some key proteins related to ovarian development and nutrition metabolism were differentially expressed. The 26 key proteins were mainly involved in the ubiquitin/proteasome pathway (UPP), cyclic AMP-protein kinase A (cAMP-PKA) signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway during oogenesis. Fifteen differentially abundant proteins (DAPs) were found to participate in vitellogenesis and oocyte development, such as vitelline membrane outer layer protein 1 homolog, vitellogenin, vitellogenin receptor, heat shock 70 kDa protein cognate 3 and farnesyl pyrophosphate synthase. Forty-seven DAPs related to nutrition metabolism were identified, including the protein digestion, fatty acid metabolism, prostaglandin metabolism, lipid digestion and transportation, i.e. short-chain specific acyl-CoA dehydrogenase, acyl-CoA desaturase, fatty acid-binding protein, long-chain fatty acid CoA ligase 4, and hematopoietic prostaglandin D synthase. These results not only indicate proteins involved in ovarian development and nutrient deposition but also enhance the understanding of the regulatory pathways and physiological processes of crustacean ovarian development.

Mutual enlightenment: A toolbox of concepts and methods for integrating evolutionary and clinical toxinology via snake venomics and the contextual stance

Snakebite envenoming is a neglected tropical disease that may claim over 100,000 human lives annually worldwide. Snakebite occurs as the result of an interaction between a human and a snake that elicits either a defensive response from the snake or, more rarely, a feeding response as the result of mistaken identity. Snakebite envenoming is therefore a biological and, more specifically, an ecological problem. Snake venom itself is often described as a "cocktail", as it is a heterogenous mixture of molecules including the toxins (which are typically proteinaceous) responsible for the pathophysiological consequences of envenoming. The primary function of venom in snake ecology is pre-subjugation, with defensive deployment of the secretion typically considered a secondary function. The particular composition of any given venom cocktail is shaped by evolutionary forces that include phylogenetic constraints associated with the snake's lineage and adaptive responses to the snake's ecological context, including the taxa it preys upon and by which it is predated upon. In the present article, we describe how conceptual frameworks from ecology and evolutionary biology can enter into a mutually enlightening relationship with clinical toxinology by enabling the consideration of snakebite envenoming from an "ecological stance". We detail the insights that may emerge from such a perspective and highlight the ways in which the high-fidelity descriptive knowledge emerging from applications of -omics era technologies - "venomics" and "antivenomics" - can combine with evolutionary explanations to deliver a detailed understanding of this multifactorial health crisis.

Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data

Mass spectrometry is frequently used in quantitative proteomics to detect differentially regulated proteins. A very important but unfortunately oftentimes neglected part in detecting differential proteins is the statistical analysis. Data from proteomics experiments are usually high-dimensional and hence require profound statistical methods. It is especially important to already correctly design a proteomic experiment before it is conducted in the laboratory. Only this can ensure that the statistical analysis is capable of detecting truly differential proteins afterward. This chapter thus covers aspects of both statistical planning as well as the actual analysis of quantitative proteomic experiments.

A Simple Optimization Workflow to Enable Precise and Accurate Imputation of Missing Values in Proteomic Data Sets

Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for clinical DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a strategy to assess imputation methods on clinical label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight imputation methods with multiple parameters at different levels of protein quantification: a dilution series data set, a small pilot data set, and a clinical proteomic data set comparing paired tumor and stroma tissue. We found that imputation methods based on local structures within the data, like local least-squares (LLS) and random forest (RF), worked well in our dilution series data set, whereas imputation methods based on global structures within the data, like BPCA, performed well in the other two data sets. We also found that imputation at the most basic protein quantification level-fragment level-improved accuracy and the number of proteins quantified. With this analytical framework, we quickly and cost-effectively evaluated different imputation methods using two smaller complementary data sets to narrow down to the larger proteomic data set's most accurate methods. This acquisition strategy allowed us to provide reproducible evidence of the accuracy of the imputation method, even in the absence of a ground truth. Overall, this study indicates that the most suitable imputation method relies on the overall structure of the data set and provides an example of an analytic framework that may assist in identifying the most appropriate imputation strategies for the differential analysis of proteins.

Label-free quantitative proteomic analysis of the inhibition effect of Lactobacillus rhamnosus GG on Escherichia coli biofilm formation in co-culture

BACKGROUND

Escherichia coli (E. coli) is the principal pathogen that causes biofilm formation. Biofilms are associated with infectious diseases and antibiotic resistance. This study employed proteomic analysis to identify differentially expressed proteins after coculture of E. coli with Lactobacillus rhamnosus GG (LGG) microcapsules.

METHODS

To explore the relevant protein abundance changes after E. coli and LGG coculture, label-free quantitative proteomic analysis and qRT-PCR were applied to E. coli and LGG microcapsule groups before and after coculture, respectively.

RESULTS

The proteomic analysis characterised a total of 1655 proteins in E. coli K12MG1655 and 1431 proteins in the LGG. After coculture treatment, there were 262 differentially expressed proteins in E. coli and 291 in LGG. Gene ontology analysis showed that the differentially expressed proteins were mainly related to cellular metabolism, the stress response, transcription and the cell membrane. A protein interaction network and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis indicated that the differentiated proteins were mainly involved in the protein ubiquitination pathway and mitochondrial dysfunction.

CONCLUSIONS

These findings indicated that LGG microcapsules may inhibit E. coli biofilm formation by disrupting metabolic processes, particularly in relation to energy metabolism and stimulus responses, both of which are critical for the growth of LGG. Together, these findings increase our understanding of the interactions between bacteria under coculture conditions.

Sesame water-soluble proteins fraction contains endopeptidases and exopeptidases with high activity: A natural source for plant proteases

Recently, the interest in the plant proteases has greatly increased. However, only a few of proteases are isolated from the hugely produced oilseeds for the practical utilizations. In this study, the raw sesame milk prepared from peeled sesame seeds was separated into floating, skim, and precipitate fractions by centrifugation. The predominant aspartic endopeptidases and serine carboxypeptidases, which exerted high synergetic activity at pH 4.5-5 and 50-60 °C, were identified in the skim by the liquid chromatography tandem mass spectrometry, Tricine-sodium dodecyl sulfate-polyacrylamide gel electrophoresis, protease inhibitor assay, trichloroacetic acid-nitrogen soluble index (TCA-NSI), and free amino acid analyses. By incubating the mixture (protein content, 2%) of skim and precipitate at pH 4.5 and 50 °C for 6 h, the TCA-NSI and free amino acids achieved to 38.42% and 3148 mg/L, respectively. Moreover, these proteases efficiently degraded the proteins from soybean, peanut, and bovine milk.

Comprehensive serum proteomic analysis in early endometrial cancer

OBJECTIVE

Endometrial cancer is the most common gynecologic cancer and yet much is still unknown about this disease. Our goal was to identify unique biomarkers of disease by performing a comprehensive proteomic analysis of early stage, low-grade endometrial cancer through analysis of serum collected from patients pre- and post-definitive surgery.

METHODS

We used mass spectrometry (MS)-based proteomics to identify serum proteins from these patients. Serum samples from women undergoing hysterectomy with bilateral salpingo-oophorectomy for benign reasons served as control samples for the correlative studies. We then correlated our findings with The Cancer Genome Atlas (TCGA) database for additional confirmation.

RESULTS

The Ingenuity Pathway Analysis of proteins that were differentially expressed in endometrial cancer showed increased cell survival and decreased organismal death, the most common hallmarks of cancer. We identified over expression of FAM83D (family with sequence similarity 83, member D) in the serum of patients with early stage low-grade endometrial cancer and verified the same in the endometrial cancer cell lines and patient tumors. We also confirmed our hypothesis that FAM83D may serve as a biomarker for endometrial cancer in a cohort of patients with endometrial cancer from The Cancer Genome Atlas (TCGA) project.

CONCLUSION

Comprehensive proteomic analysis is a feasible strategy for potential biomarker identification. Using this technique, FAM83D was identified as a candidate biomarker in early endometrial cancer in our patient samples and was not present in benign control samples. FAM83D has been associated with poor clinical outcomes in several human malignancies.

SIGNIFICANCE

Our manuscript describes an alternative approach to comprehensive protein analysis in a model pre and post tumor removal for a sample of patients with early endometrial cancer. The model is innovative and the findings of over expression FAM83D in this population of early cancer may be useful in the study of a disease where there are few biomarkers or targetable therapies.

Application of Label-Free Proteomics for Quantitative Analysis of Urothelial Carcinoma and Cystitis Tissue

A label-free approach based on a highly reproducible and stable workflow allows for quantitative proteome analysis . Due to advantages compared to labeling methods, the label-free approach has the potential to measure unlimited samples from clinical specimen monitoring and comparing thousands of proteins. The presented label-free workflow includes a new sample preparation technique depending on automatic annotation and tissue isolation via FTIR-guided laser microdissection, in-solution digestion, LC-MS/MS analyses, data evaluation by means of Proteome Discoverer and Progenesis software, and verification of differential proteins. We successfully applied this workflow in a proteomics study analyzing human cystitis and high-grade urothelial carcinoma tissue regarding the identification of a diagnostic tissue biomarker. The differential analysis of only 1 mm² of isolated tissue cells led to 74 significantly differentially abundant proteins.

MS-based proteomics for comprehensive investigation of protein O-GlcNAcylation

Protein O-GlcNAcylation refers to the covalent binding of a single N-acetylglucosamine (GlcNAc) to the serine or threonine residue. This modification primarily occurs on proteins in the nucleus and the cytosol, and plays critical roles in many cellular events, including regulation of gene expression and signal transduction. Aberrant protein O-GlcNAcylation is directly related to human diseases such as cancers, diabetes and neurodegenerative diseases. In the past decades, considerable progress has been made for global and site-specific analysis of O-GlcNAcylation in complex biological samples using mass spectrometry (MS)-based proteomics. In this review, we summarized previous efforts on comprehensive investigation of protein O-GlcNAcylation by MS. Specifically, the review is focused on methods for enriching and site-specifically mapping O-GlcNAcylated peptides, and applications for quantifying protein O-GlcNAcylation in different biological systems. As O-GlcNAcylation is an important protein modification for cell survival, effective methods are essential for advancing our understanding of glycoprotein functions and cellular events.

A Primer and Guidelines for Shotgun Proteomic Analysis in Non-model Organisms

During the last decade, we have witnessed outstanding advances in proteomics led mostly by great technological improvements in mass spectrometry field allowing high-throughput production of high-quality data used for massive protein identification and quantification. From a practical viewpoint, these advances have been mainly exploited in research projects involving model organisms with abundant genomic and proteomic information available in public databases. However, there is a growing number of organisms of high interest in different disciplines, such as ecological, biotechnological, and evolutionary research, yet poorly represented in these databases. Important advances in massive parallel sequencing technology and easy accessibility of this technology to many research laboratories have made nowadays possible to produce customized genomic and proteomic databases of any organism. Along this line, the use of proteogenomic approaches by combining in the same analysis the data obtained from different omic levels has emerged as a very useful and powerful strategy to run shotgun proteomic experiments specially focused on non-model organisms. In this chapter, we provide detailed procedures to undertake shotgun quantitative proteomic experiments following either a label-free or an isobaric labeling approach in non-model organisms, emphasizing also a few key aspects related to experimental design and data analysis.

Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages

Insights into the modes of action (MoAs) of xenobiotics are of utmost importance for the definition of adverse outcome pathways (AOPs), which are essential for a mechanism-based risk assessment. A well-established strategy to reveal MoAs of xenobiotics is the use of omics. However, often an even more comprehensive approach is needed, which can be achieved using multi-omics. Since the immune system plays a central role in the defense against foreign substances and pathogens, with the innate immune system building a first barrier, we systematically reviewed multi-omics studies investigating the effects of xenobiotics on macrophages. Surprisingly, only nine publications were identified, combining proteomics with transcriptomics or metabolomics. We summarized pathways and single proteins, transcripts, or metabolites, which were described to be affected upon treatment with xenobiotics in the reviewed studies, thus revealing a broad range of effects. In summary, we show that macrophages are a relevant model system to investigate the toxicological effects induced by xenobiotics. Furthermore, the multi-omics approaches led to a more comprehensive overview compared to only one omics layer with slight advantages for combinations that complement each other directly, e.g., proteome and metabolome.

Exploring the Proteomic Alterations from Untreated and Cryoablation and Irradiation Treated Giant Cell Tumors of Bone Using Liquid-Chromatography Tandem Mass Spectrometry

Giant cell tumors of bone (GCT) are benign tumors that show a locally aggressive nature and affect bones' architecture. Recently, cryoablation and irradiation treatments have shown promising results in GCT patients with faster recovery and less recurrence and metastasis. Therefore, it became a gold standard surgical treatment for patients. Hence, we have compared GCT-untreated, cryoablation, and irradiation-treated samples to identify protein alterations using high-frequency liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS). Our label-free quantification analysis revealed a total of 107 proteins (p < 0.01) with 26 up-regulated (< 2-folds to 5-fold), and 81 down-regulated (> 0.1 to 0.5 folds) proteins were identified from GCT-untreated and treated groups. Based on pathway analysis, most of the identified up-regulated proteins involved in critical metabolic functions associated with tumor proliferation, angiogenesis, and metastasis. On the other hand, the down-regulated proteins involved in glycolysis, tumor microenvironment, and apoptosis. The observed higher expressions of matrix metalloproteinase 9 (MMP9) and TGF-beta in the GCT-untreated group associated with bones' osteolytic process. Interestingly, both the proteins showed reduced expressions after cryoablation treatment, and contrast expressions identified in the irradiation treated group. Therefore, these expressions were confirmed by immunoblot analysis. In addition to these, several glycolytic enzymes, immune markers, extracellular matrix (ECM), and heat shock proteins showed adverse expressions in the GCT-untreated group were identified with favorable regulations after treatment. Therefore, the identified expression profiles will provide a better picture of treatment efficacy and effect on the molecular environment of GCT.

Tryptic digestion of human serum for proteomic mass spectrometry automated by centrifugal microfluidics

Mass spectrometry has become an important analytical tool for protein research studies to identify, characterise and quantify proteins with unmatched sensitivity in a highly parallel manner. When transferred into clinical routine, the cumbersome and error-prone sample preparation workflows present a major bottleneck. In this work, we demonstrate tryptic digestion of human serum that is fully automated by centrifugal microfluidics. The automated workflow comprises denaturation, digestion and acidification. The input sample volume is 1.3 μl only. A triplicate of human serum was digested with the developed microfluidic chip as well as with a manual reference workflow on three consecutive days to assess the performance of our system. After desalting and liquid chromatography tandem mass spectrometry, a total of 604 proteins were identified in the samples digested with the microfluidic chip and 602 proteins with the reference workflow. Protein quantitation was performed using the Hi3 method, yielding a 7.6% lower median intensity CV for automatically digested samples compared to samples digested with the reference workflow. Additionally, 17% more proteins were quantitated with less than 30% CV in the samples from the microfluidic chip, compared to the manual control samples. This improvement can be attributed to the accurate liquid metering with all volume CVs below 1.5% on the microfluidic chip. The presented automation solution is attractive for laboratories in need of robust automation of sample preparation from small volumes as well as for labs with a low or medium throughput that does not allow for large investments in robotic systems.

Ubiquitin-proteasome system, lipid metabolism and DNA damage repair are triggered by antipsychotic medication in human oligodendrocytes: implications in schizophrenia

Schizophrenia is a chronic, severe and disabling psychiatric disorder, whose treatment is based on psychosocial interventions and the use of antipsychotic drugs. While the effects of these drugs are well elucidated in neuronal cells, they are still not so clear in oligodendrocytes, which play a vital role in schizophrenia. Thus, we aimed to characterize biochemical profiles by proteomic analyses of human oligodendrocytes (MO3.13) which were matured using a protocol we developed and treated with either haloperidol (a typical antipsychotic), clozapine (an atypical antipsychotic) or a clozapine + D-serine co-treatment, which has emerged lately as an alternative type of treatment. This was accomplished by employing shotgun proteomics, using nanoESI-LC-MS/MS label-free quantitation. Proteomic analysis revealed biochemical pathways commonly affected by all tested antipsychotics were mainly associated to ubiquitination, proteasome degradation, lipid metabolism and DNA damage repair. Clozapine and haloperidol treatments also affected proteins involved with the actin cytoskeleton and with EIF2 signaling. In turn, metabolic processes, especially the metabolism of nitrogenous compounds, were a predominant target of modulation of clozapine + D-serine treatment. In this context, we seek to contribute to the understanding of the biochemical and molecular mechanisms involved in the action of antipsychotics on oligodendrocytes, along with their possible implications in schizophrenia.

Target identification of natural medicine with chemical proteomics approach: probe synthesis, target fishing and protein identification

Natural products are an important source of new drugs for the treatment of various diseases. However, developing natural product-based new medicines through random moiety modification is a lengthy and costly process, due in part to the difficulties associated with comprehensively understanding the mechanism of action and the side effects. Identifying the protein targets of natural products is an effective strategy, but most medicines interact with multiple protein targets, which complicate this process. In recent years, an increasing number of researchers have begun to screen the target proteins of natural products with chemical proteomics approaches, which can provide a more comprehensive array of the protein targets of active small molecules in an unbiased manner. Typically, chemical proteomics experiments for target identification consist of two key steps: (1) chemical probe design and synthesis and (2) target fishing and identification. In recent decades, five different types of chemical proteomic probes and their respective target fishing methods have been developed to screen targets of molecules with different structures, and a variety of protein identification approaches have been invented. Presently, we will classify these chemical proteomics approaches, the application scopes and characteristics of the different types of chemical probes, the different protein identification methods, and the advantages and disadvantages of these strategies.

Analysis of proximal ALOX5 promoter binding proteins by quantitative proteomics

5-Lipoxygenase (5-LO) is the initial enzyme in the biosynthesis of leukotrienes, which are mediators involved in pathophysiological conditions such as asthma and certain cancer types. Knowledge of proteins involved in 5-LO pathway regulation, including gene regulatory proteins, is needed to evaluate all options for therapeutic intervention in these diseases. Here, we present a mass spectrometric screening of ALOX5 promoter-interacting proteins, obtained by DNA pulldown and label-free quantitative mass spectrometry. Protein preparations from myeloid and B-lymphocytic cell lines were screened for promoter DNA interactors. Through statistical analysis, 66 proteins were identified as specific ALOX5 promotor binding proteins. Among those, the 15 most likely candidates for a prominent role in ALOX5 gene regulation are the known ALOX5 interactors Sp1 and Sp3, the related factor Sp2, two Krüppel-like factors (KLF13 and KLF16) and six other zinc finger proteins (MAZ, PRDM10, VEZF1, ZBTB7A, ZNF281 and ZNF579). Intriguingly, we also identified two helicases (BLM and DHX36) and the proteins hnRNPD and hnRNPK, which are, together with the protein MAZ, known to interact with DNA G-quadruplex structures. As G-quadruplexes are implicated in gene regulation, spectroscopic and antibody-based methods were used to confirm their presence within the GC-rich sequence of the ALOX5 promoter. In summary, we have systematically characterized the interactome of the ALOX5 promoter, identifying several zinc finger proteins as novel potential ALOX5 gene regulators. Further, we have shown that the ALOX5 promoter can form DNA G-quadruplex structures, which may play a functional role in ALOX5 gene regulation.

Pathological myopia-induced antioxidative proteins in the vitreous humor

Background

This study aimed to investigate differentially expressed proteins in the vitreous humor (VH) of pathological myopia (PM) and normal eyes.

Methods

VH samples were collected from patients undergoing surgical treatment for rhegmatogenous retinal detachment (RRD), idiopathic epiretinal membrane (ERM), myopic retinoschisis (MRS) or macular hole (MH). A label-free quantitative proteomic analysis was performed to detect the differentially expressed proteins, and expression of three differentially expressed proteins was confirmed by ELISA.

Results

In PM patients (MH-PM, MRS-PM and RRD-PM), the expression of prostaglandin-H2 D-isomerase (PGDS) and glutathione peroxidase 3 (GPX3) was significantly lower than in controls (MH, ERM, and RRD). The versican core protein expression decreased in the PM group. The vitreous concentrations of PGDS and GPX3 in patients with axial length (AL) of 26.5–29.0 mm were higher than in patients with AL >29.0 mm or AL <26.5 mm. NRF-2 expression was the lowest in patients with AL >29.0 mm.

Conclusions

Our study provides new evidence on the molecular changes in the VH of PM patients, and these molecules have the potential to become new targets for the therapy of PM.

Proteomics Profiling of Autologous Blood and Semen Exosomes from HIV-infected and Uninfected Individuals Reveals Compositional and Functional Variabilities

Blood and semen are important body-fluids that carry exosomes for bioinformation transmission. Therefore, characterization of their proteomes is necessary for understanding body-fluid-specific physiologic and pathophysiologic functions. Using systematic multifactorial proteomic profiling, we characterized the proteomes of exosomes and exosome-free fractions from autologous blood and semen from three HIV-uninfected and three HIV-infected participants (total of 24 samples). We identified exosome-based protein signatures specific to blood and semen along with HIV-induced tissue-dependent proteomic perturbations. We validated our findings with samples from 16 additional donors and showed that unlike blood exosomes (BE), semen exosomes (SE) are enriched in clusterin. SE but not BE promote Protein·Nucleic acid binding and increase cell adhesion irrespective of HIV infection. This is the first comparative study of the proteome of autologous BE and SE. The proteins identified may be developed as biomarkers applicable to different fields of medicine, including reproduction and infectious diseases.

Identification and characterization of proteins that are differentially expressed in adipose tissue of olanzapine-induced insulin resistance rat by iTRAQ quantitative proteomics

Olanzapine is commonly used to treat schizophrenia. However, long-term administration of olanzapine causes metabolic side effects, such as insulin resistance (IR), which seriously affects patients' quality of life. Both diagnostic and prognostic markers are urgently needed to increase patient compliance. We applied isobaric tags for relative and absolute quantitation (iTRAQ) labeling combined with 2D LC/MS/MS technology to identify the differentially expressed proteins in olanzapine-induced IR rats. A total of 3194 proteins were identified from rat adipose tissues, and 270 differentially expressed proteins were screened out with a ratio threshold >1.5-fold or <0.67-fold. Based on a bioinformatics analysis and literature search, we selected six candidates (MYH1, MYL2, Cp, FABP4, apoA-IV, and Ywhaz) from a set of 270 proteins and verified these proteins by western blot; the expression of these proteins coincided with the LC-MS/MS results. Finally, the biological roles of FABP4 and apoA-IV, which are two novel IR-related proteins identified in the present study, were verified in 3T3-L1 cells. These data suggest that these two proteins acted on olanzapine-induced IR via the IRS-1/AKT signaling pathway. Our results provide a dataset of potential targets to explore the mechanism in olanzapine-induced IR and reveal the new roles of FABP4 and apoA-IV in olanzapine-induced IR. SIGNIFICANCE: The proteomic analysis of this study revealed the target associated with olanzapine-induced IR and provided relevant insights into the molecular functions, biological processes, and signaling pathways in these targets. Protein MYH1, MYL2, Cp, FABP4, apoA-IV, and Ywhaz may be potential biomarkers, and protein FABP4 and apoA-IV were considered as promising targets in olanzapineinduced IR. Therefore, if the performance of the proposed biomarkers is further confirmed, these proteins can provide powerful targets for exploring the mechanism of olanzapine-induced IR.

Determination of variability due to biological and technical variation in urinary extracellular vesicles as a crucial step in biomarker discovery studies

Urinary extracellular vesicles (EVs) are an attractive source of biomarkers for urological diseases. A crucial step in biomarker discovery studies is the determination of the variation parameters to perform a sample size calculation. In this way, a biomarker discovery study with sufficient statistical power can be performed to obtain biologically significant biomarkers. Here, a variation study was performed on both the protein and lipid content of urinary EVs of healthy individuals, aged between 52 and 69 years. Ultrafiltration (UF) in combination with size exclusion chromatography (SEC) was used to isolate the EVs from urine. Different experimental variation set-ups were used in this variation study. The calculated standard deviations (SDs) of the 90% least variable peptides and lipids did not exceed 2 and 1.2, respectively. These parameters can be used in a sample size calculation for a well-designed biomarker discovery study at the cargo of EVs.

Quantitative Proteome Profiling of Coxiella burnetii Reveals Major Metabolic and Stress Differences Under Axenic and Cell Culture Cultivation

Coxiella burnetii is the causative agent of the zoonotic disease Q fever. To date, the lipopolysaccharide (LPS) is the only defined and characterized virulence determinant of C. burnetii. In this study, proteome profiles of C. burnetii Nine Mile phase I (RSA 493, NMI) and its isogenic Nine Mile phase II (RSA 439 NMII) isolate with a deep rough LPS were compared on L-929 mouse fibroblasts and in complex (ACCM-2), and defined (ACCM-D) media. Whole proteome extracts were analyzed using a label-free quantification approach. Between 659 and 1,046 C. burnetii proteins of the 2,132 annotated coding sequences (CDS) were identified in any particular experiment. Proteome profiles clustered according to the cultivation conditions used, indicating different regulation patterns. NMI proteome profiles compared to NMII in ACCM-D indicate transition from an exponential to a stationary phase. The levels of regulatory proteins such as RpoS, CsrA2, UspA1, and UspA2 were increased. Comparison of the oxidative stress response of NMI and NMII indicated that ACCM-2 represents a high oxidative stress environment. Expression of peroxidases, superoxide dismutases, as well as thioredoxins was increased for NMI. In contrast, in ACCM-D, only osmoregulation seems to be necessary. Proteome profiles of NMII do not differ and indicate that both axenic media represent similar oxidative stress environments. Deep rough LPS causes changes of the outer membrane stability and fluidity. This might be one reason for the observed differences. Proteins associated with the T4SS and Sec translocon as well as several effector proteins were detectable under all three conditions. Interestingly, none of these putatively secreted proteins are upregulated in ACCM-2 compared to ACCM-D, and L-929 mouse fibroblasts. Curiously, a higher similarity of proteomic patterns (overlapping up- and downregulated proteins) of ACCM-D and bacteria grown in cell culture was observed. Particularly, the proteins involved in a better adaptation or homeostasis in response to the harsh environment of the parasitophorous vacuole were demonstrated for NMI. This semi-quantitative proteomic analysis of C. burnetii compared axenically grown bacteria to those propagated in cell culture.

Electrospun Nanofibers for Label-Free Sensor Applications

Electrospinning is a simple, low-cost and versatile method for fabricating submicron and nano size fibers. Due to their large surface area, high aspect ratio and porous structure, electrospun nanofibers can be employed in wide range of applications. Biomedical, environmental, protective clothing and sensors are just few. The latter has attracted a great deal of attention, because for biosensor application, nanofibers have several advantages over traditional sensors, including a high surface-to-volume ratio and ease of functionalization. This review provides a short overview of several electrospun nanofibers applications, with an emphasis on biosensor applications. With respect to this area, focus is placed on label-free sensors, pertaining to both recent advances and fundamental research. Here, label-free sensor properties of sensitivity, selectivity, and detection are critically evaluated. Current challenges in this area and prospective future work is also discussed.

A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation

Label-free mass spectrometry (MS) has developed into an important tool applied in various fields of biological and life sciences. Several software exist to process the raw MS data into quantified protein abundances, including open source and commercial solutions. Each software includes a set of unique algorithms for different tasks of the MS data processing workflow. While many of these algorithms have been compared separately, a thorough and systematic evaluation of their overall performance is missing. Moreover, systematic information is lacking about the amount of missing values produced by the different proteomics software and the capabilities of different data imputation methods to account for them.In this study, we evaluated the performance of five popular quantitative label-free proteomics software workflows using four different spike-in data sets. Our extensive testing included the number of proteins quantified and the number of missing values produced by each workflow, the accuracy of detecting differential expression and logarithmic fold change and the effect of different imputation and filtering methods on the differential expression results. We found that the Progenesis software performed consistently well in the differential expression analysis and produced few missing values. The missing values produced by the other software decreased their performance, but this difference could be mitigated using proper data filtering or imputation methods. Among the imputation methods, we found that the local least squares (lls) regression imputation consistently increased the performance of the software in the differential expression analysis, and a combination of both data filtering and local least squares imputation increased performance the most in the tested data sets.

Recent Technological Advances in the Mass Spectrometry-based Nanomedicine Studies: An Insight from Nanoproteomics

Nanoscience becomes one of the most cutting-edge research directions in recent years since it is gradually matured from basic to applied science. Nanoparticles (NPs) and nanomaterials (NMs) play important roles in various aspects of biomedicine science, and their influences on the environment have caused a whole range of uncertainties which require extensive attention. Due to the quantitative and dynamic information provided for human proteome, mass spectrometry (MS)-based quantitative proteomic technique has been a powerful tool for nanomedicine study. In this article, recent trends of progress and development in the nanomedicine of proteomics were discussed from quantification techniques and publicly available resources or tools. First, a variety of popular protein quantification techniques including labeling and label-free strategies applied to nanomedicine studies are overviewed and systematically discussed. Then, numerous protein profiling tools for data processing and postbiological statistical analysis and publicly available data repositories for providing enrichment MS raw data information sources are also discussed.

Molecular cross-talk in a unique parasitoid manipulation strategy

Envenomation of cockroach cerebral ganglia by the parasitoid Jewel wasp, Ampulex compressa, induces specific, long-lasting behavioural changes. We hypothesized that this prolonged action results from venom-induced changes in brain neurochemistry. Here, we address this issue by first identifying molecular targets of the venom, i.e., proteins to which venom components bind and interact with to mediate altered behaviour. Our results show that venom components bind to synaptic proteins and likely interfere with both pre- and postsynaptic processes. Since behavioural changes induced by the sting are long-lasting and reversible, we hypothesized further that long-term effects of the venom must be mediated by up or down regulation of cerebral ganglia proteins. We therefore characterize changes in cerebral ganglia protein abundance of stung cockroaches at different time points after the sting by quantitative mass spectrometry. Our findings indicate that numerous proteins are differentially expressed in cerebral ganglia of stung cockroaches, many of which are involved in signal transduction, such as the Rho GTPase pathway, which is implicated in synaptic plasticity. Altogether, our data suggest that the Jewel wasp commandeers cockroach behaviour through molecular cross-talk between venom components and molecular targets in the cockroach central nervous system, leading to broad-based alteration of synaptic efficacy and behavioural changes that promote successful development of wasp progeny.

Proteomic analysis of synovial fluid: current and potential uses to improve clinical outcomes

INTRODUCTION

Synovial fluid (SF) is in close proximity to tissues which are primarily altered during articular disease and has significant potential to better understand the underlying disease pathogeneses of articular pathologies and biomarker discovery. Although development of mass spectrometry-based methods has allowed faster and higher sensitivity techniques, interrogation of the SF proteome has been hindered by its large protein concentration dynamic range, impeding quantification of lower abundant proteins. Areas covered: Recent advances have developed methodologies to reduce the large protein concentration dynamic range of SF and subsequently allow deeper exploration of the SF proteome. This review concentrates on methods to overcome biofluid complexity, mass spectrometry proteomics methodologies, extracellular vesicles proteomics and the application of advances within the field in clinical disease, including osteoarthritis, rheumatoid arthritis, spondyloarthritis and juvenile arthritis. A narrative review was conducted with articles searched using PubMed, 1991-2018. Expert opinion: The SF proteomics field faces various challenges, including the requirement for rigorous and standardised methods of sample collection/storage, the sensitivity and specificity of proteomic assays, techniques to combat the large protein concentration dynamic range and comprehensive data analysis to reduce falsely identified markers. Additionally, there are challenges in developing multi 'omic' integration techniques, with computational integration enhancing analysis.

Application of Proteomics to Inflammatory Bowel Disease Research: Current Status and Future Perspectives

Inflammatory bowel disease (IBD) is a chronic relapsing/remitting inflammatory illness of the gastrointestinal tract of unknown aetiology. Despite recent advances in decoding the pathophysiology of IBD, many questions regarding disease pathogenesis remain. Genome-wide association studies (GWAS) and knockout mouse models have significantly advanced our understanding of genetic susceptibility loci and inflammatory pathways involved in IBD pathogenesis. Despite their important contribution to a better delineation of the disease process in IBD, these genetic findings have had little clinical impact to date. This is because the presence of a given gene mutation does not automatically correspond to changes in its expression or final metabolic or structural effect(s). Furthermore, the existence of these gene susceptibility loci in the normal population suggests other driving prerequisites for the disease manifestation. Proteins can be considered the main functional units as almost all intracellular physiological functions as well as intercellular interactions are dependent on them. Proteomics provides methods for the large-scale study of the proteins encoded by the genome of an organism or a cell, to directly investigate the proteins and pathways involved. Understanding the proteome composition and alterations yields insights into IBD pathogenesis as well as identifying potential biomarkers of disease activity, mucosal healing, and cancer progression. This review describes the state of the art in the field with respect to the study of IBD and the potential for translation from biomarker discovery to clinical application.