Introduction to Proteomics Technologies

The interplay between lysosome, protein corona and biological effects of cationic carbon dots: Role of surface charge titratability

Carbon dots (CDs) are nanoparticles (NPs) with potential applications in the biomedical field. When in contact with biological fluids, most NPs are covered by a protein corona. As well, upon cell entry, most NP are sequestered in the lysosome. However, the interplay between the lysosome, the protein corona and the biological effects of NPs is still poorly understood. In this context, we investigated the role of the lysosome in the toxicological responses evoked by four cationic CDs exhibiting protonatable or non-protonatable amine groups at their surface, and the associated changes in the CD protein corona. The four CDs accumulated in the lysosome and led to lysosomal swelling, loss lysosome integrity, cathepsin B activation, NLRP3 inflammasome activation, and cell death by pyroptosis in a human macrophage model, but with a stronger effect for CDs with titratable amino groups. The protein corona formed around CDs in contact with serum partially dissociated under lysosomal conditions with subsequent protein rearrangement, as assessed by quantitative proteomic analysis. The residual protein corona still contained binding proteins, catalytic proteins, and proteins involved in the proteasome, glycolysis, or PI3k-Akt KEGG pathways, but with again a more pronounced effect for CDs with titratable amino groups. These results demonstrate an interplay between lysosome, protein corona and biological effects of cationic NPs in link with the titratability of NP surface charges.

Molecular Mechanism of Male Sterility Induced by 60Co γ-Rays on Plutella xylostella (Linnaeus)

Plutella xylostella (Linnaeus) is one of the notorious pests causing substantial loses to numerous cruciferous vegetables across many nations. The sterile insect technique (SIT) is a safe and effective pest control method, which does not pollute the environment and does not produce drug resistance. We used proteomics technology and bioinformatics analysis to investigate the molecular mechanisms responsible for the effects of different doses of radiation treatment on the reproductive ability of male P. xylostella. A total of 606 differentially expressed proteins (DEPs) were identified in the 200 Gy/CK group, 1843 DEPs were identified in the 400 Gy/CK group, and 2057 DEPs were identified in the 400 Gy/200 Gy group. The results showed that after 200 Gy irradiation, the testes resisted radiation damage by increasing energy supply, amino acid metabolism and transport, and protein synthesis, while transcription-related pathways were inhibited. After 400 Gy irradiation, the mitochondria and DNA in the testis tissue of P. xylostella were damaged, which caused cell autophagy and apoptosis, affected the normal life activities of sperm cells, and greatly weakened sperm motility and insemination ability. Meanwhile, Western blotting showed that irradiation affects tyrosine phosphorylation levels, which gradually decrease with increasing irradiation dose.

Surface charge influences protein corona, cell uptake and biological effects of carbon dots

Carbon dots are emerging nanoparticles (NPs) with tremendous applications, especially in the biomedical field. Herein is reported the first quantitative proteomic analysis of the protein corona formed on CDs with different surface charge properties. Four CDs were synthesized from citric acid and various amine group-containing passivation reagents, resulting in cationic NPs with increasing zeta (ζ)-potential and density of positive charges. After CD contact with serum, we show that protein corona identity is influenced by CD surface charge properties, which in turn impacts CD uptake and viability loss in macrophages. In particular, CDs with high ζ-potential (>+30 mV) and charge density (>2 μmol mg^-1) are the most highly internalized, and their cell uptake is strongly correlated with a corona enriched in vitronectin, fibulin, fetuin, adiponectin and alpha-glycoprotein. On the contrary, CDs with a lower ζ-potential (+11 mV) and charge density (0.01 μmol mg^-1) are poorly internalized, while having a corona with a very different protein signature characterized by a high abundance of apolipoproteins (APOA1, APOB and APOC), albumin and hemoglobin. These data illustrate how corona characterization may contribute to a better understanding of CD cellular fate and biological effects, and provide useful information for the development of CDs for biomedical applications.

Identification of the Secreted Proteins Originated from Primary Human Hepatocytes and HepG2 Cells

The liver plays a pivotal role in whole-body carbohydrate, lipid, and protein metabolism. One of the key regulators of glucose and lipid metabolism are hepatokines, which are found among the liver secreted proteins, defined as liver secretome. To elucidate the composition of the human liver secretome and identify hepatokines in primary human hepatocytes (PHH), we conducted comprehensive protein profiling on conditioned medium (CM) of PHH. Secretome profiling using liquid chromatography-electrospray ionization tandem mass spectrometry (LC-MS/MS) identified 691 potential hepatokines in PHH. Subsequently, pathway analysis assigned these proteins to acute phase response, coagulation, and complement system pathways. The secretome of PHH was compared to the secreted proteins of the liver hepatoma cell line HepG2. Although the secretome of PHH and HepG2 cells show a high overlap, the HepG2 secretome rather mirrors the fetal liver with some cancer characteristics. Collectively, our study represents one of the most comprehensive secretome profiling approaches for PHH, allowing new insights into the composition of the secretome derived from primary human material, and points out strength and weakness of using HepG2 cell secretome as a model for the analysis of the human liver secretome.

Comparative Proteomics of Phytase-transgenic Maize Seeds Indicates Environmental Influence is More Important than that of Gene Insertion

Proteomic differences were compared between phytase-transgenic (PT) maize seeds and nontransgenic (NT) maize seeds through two-dimensional electrophoresis (2-DE) with mass spectrometry (MS). When maize was grown under field conditions, 30 differentially accumulated proteins (DAPs) were successfully identified in PT seeds (PT/NT). Clusters of Orthologous Groups (COG) functional classification of these proteins showed that the largest group was associated with posttranslational modifications. To investigate the effects of environmental factors, we further compared the seed protein profiles of the same maize planted in a greenhouse or under field conditions. There were 76 DAPs between the greenhouse- and field-grown NT maize seeds and 77 DAPs between the greenhouse- and field-grown PT maize seeds However, under the same planting conditions, there were only 43 DAPs (planted in the greenhouse) or 37 DAPs (planted in the field) between PT and NT maize seeds. The results revealed that DAPs caused by environmental factors were more common than those caused by the insertion of exogenous genes, indicating that the environment has much more important effects on the seed protein profiles. Our maize seed proteomics results also indicated that the occurrence of unintended effects is not specific to genetically modified crops (GMCs); instead, such effects often occur in traditionally bred plants. Our data may be beneficial for biosafety assessments of GMCs at the protein profile level in the future.

Coupling of CE-MS for protein and peptide analysis

The review is focused on the latest developments in the analysis of proteins and peptides by capillary electrophoresis techniques coupled to mass spectrometry. First, the methodology and instrumentation are overviewed. In this section, recent progress in capillary electrophoresis with mass spectrometry interfaces and capillary electrophoresis with matrix-assisted laser desorption/ionization is mentioned, as well as separation tasks. The second part is devoted to applications-mainly bottom-up and top-down proteomics. It is obvious that capillary electrophoresis with mass spectrometry methods are well suited for peptide and protein analysis (proteomic research) and it is described how these techniques are complementary and not competitive with the often used liquid chromatography with mass spectrometry methods.

Proteomic analysis of phytase transgenic and non-transgenic maize seeds

Proteomics has become a powerful technique for investigating unintended effects in genetically modified crops. In this study, we performed a comparative proteomics of the seeds of phytase-transgenic (PT) and non-transgenic (NT) maize using 2-DE and iTRAQ techniques. A total of 148 differentially expressed proteins (DEPs), including 106 down-regulated and 42 up-regulated proteins in PT, were identified. Of these proteins, 32 were identified through 2-DE and 116 were generated by iTRAQ. It is noteworthy that only three proteins could be detected via both iTRAQ and 2-DE, and most of the identified DEPs were not newly produced proteins but proteins with altered abundance. These results indicated that many DEPs could be detected in the proteome of PT maize seeds and the corresponding wild type after overexpression of the target gene, but the changes in these proteins were not substantial. Functional classification revealed many DEPs involved in posttranscriptional modifications and some ribosomal proteins and heat-shock proteins that may generate adaptive effects in response to the insertion of exogenous genes. Protein-protein interaction analysis demonstrated that the detected interacting proteins were mainly ribosomal proteins and heat-shock proteins. Our data provided new information on such unintended effects through a proteomic analysis of maize seeds.

Automated multigroup outlier identification in molecular high-throughput data using bagplots and gemplots

Background

Analyses of molecular high-throughput data often lack in robustness, i.e. results are very sensitive to the addition or removal of a single observation. Therefore, the identification of extreme observations is an important step of quality control before doing further data analysis. Standard outlier detection methods for univariate data are however not applicable, since the considered data are high-dimensional, i.e. multiple hundreds or thousands of features are observed in small samples. Usually, outliers in high-dimensional data are solely detected by visual inspection of a graphical representation of the data by the analyst. Typical graphical representation for high-dimensional data are hierarchical cluster tree or principal component plots. Pure visual approaches depend, however, on the individual judgement of the analyst and are hard to automate. Existing methods for automated outlier detection are only dedicated to data of a single experimental groups.

Results

In this work we propose to use bagplots, the 2-dimensional extension of the boxplot, to automatically identify outliers in the subspace of the first two principal components of the data. Furthermore, we present for the first time the gemplot, the 3-dimensional extension of boxplot and bagplot, which can be used in the subspace of the first three principal components. Bagplot and gemplot surround the regular observations with convex hulls and observations outside these hulls are regarded as outliers. The convex hulls are determined separately for the observations of each experimental group while the observations of all groups can be displayed in the same subspace of principal components. We demonstrate the usefulness of this approach on multiple sets of artificial data as well as one set of gene expression data from a next-generation sequencing experiment, and compare the new method to other common approaches. Furthermore, we provide an implementation of the gemplot in the package ‘gemPlot’ for the R programming environment.

Conclusions

Bagplots and gemplots in subspaces of principal components are useful for automated and objective outlier identification in high-dimensional data from molecular high-throughput experiments. A clear advantage over other methods is that multiple experimental groups can be displayed in the same figure although outlier detection is performed for each individual group.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1645-5) contains supplementary material, which is available to authorized users.