The influence of microinjection parameters on cell survival and procedure efficiency.

Microinjection is a method commonly used to deliver various substances into cells. The procedure is performed on a widefield microscope stage using fine glass needle to penetrate the cell membrane. Microinjection can be carried out using a manual or semi-automatic mode. For commercially available equipment currently reported microinjection success rate and cell viability are relatively low (around 50% for both indicators). Here, for the first time, we systematically show how the microinjection effectiveness and cell viability are influenced by needle diameter and chosen microinjection mode. We found that manual mode entailed a higher injection rate, reducing cell viability at the same time. The reduction in needle diameter caused a significant increase in cell survival rate (from 43 to 73% for manual mode and from 58% to 86% for semi-automatic mode) and did not affect significantly the success rate. Our findings will help optimize this method in the context of cell biology research.•This study shows how to improve microinjection parameters, such as procedure efficiency and cell survival rate, for commercially available equipment.•Manual mode, in comparison with semi-automatic mode, results in higher microinjection efficiency, but lower cell survival rate.•The increase in micropipette diameter causes lower cell viability and a higher microinjection success rate.

Exploring Gas-Phase MS Methodologies for Structural Elucidation of Branched N-Glycan Isomers.

Structural isomers of N-glycans that are identical in mass and atomic composition provide a great challenge to conventional mass spectrometry (MS). This study employs additional dimensions of structural elucidation including ion mobility (IM) spectroscopy coupled to hydrogen/deuterium exchange (HDX) and electron capture dissociation (ECD) to characterize three main A2 N-glycans and their conformers. A series of IM-MS experiments were able to separate the low abundance N-glycans and their linkage-based isomers (α1-3 and α1-6 for A2G1). HDX-IM-MS data indicated the presence of multiple gas-phase structures for each N-glycan including the isomers of A2G1. Identification of A2G1 isomers by their collision cross section was complicated due to the preferential collapse of sugars in the gas phase, but it was possible by further ECD fragmentation. The cyclic IM-ECD approach was capable of assigning and identifying each isomer to its IM peak. Two unique cross-ring fragments were identified for each isomer: m/z = 624.21 for α1-6 and m/z = 462.16 for α1-3. Based on these key fragments, the first IM peak, indicating a more compact conformation, was assigned to α1-3 and the second IM peak, a more extended conformer, was assigned to α1-6.

Interaction analysis of glycoengineered antibodies with CD16a: a native mass spectrometry approach.

Minor changes in the quality of biologically manufactured monoclonal antibodies (mAbs) can affect their bioactivity and efficacy. One of the most important variations concerns the N-glycosylation pattern, which directly affects an anti-tumor mechanism called antibody-dependent cell-meditated cytotoxicity (ADCC). Thus, careful engineering of mAbs is expected to enhance both protein-receptor binding and ADCC. The specific aim of this study is to evaluate the influence of terminal carbohydrates within the Fc region on the interaction with the FcγRIIIa/CD16a receptor in native and label-free conditions. The single mAb molecule comprises variants with minimal and maximal galactosylation, as well as α2,3 and α2,6-sialic acid isomers. Here, we apply native electrospray ionization mass spectrometry to determine the solution-phase antibody-receptor equilibria and by using temperature-controlled nanoelectrospray, a thermal stability of the complex is examined. Based on these, we prove that the galactosylation of a fucosylated Fc region increases the binding to CD16a 1.5-fold when compared with the non-galactosylated variant. The α2,6-sialylation has no significant effect on the binding, whereas the α2,3-sialylation decreases it 1.72-fold. In line with expectation, the galactoslylated and α2,6-sialylated mAb:CD16a complex exhibit higher thermal stability when measured in the temperature gradient from 20 to 50°C. The similar binding pattern is observed based on surface plasmon resonance analysis and immunofluorescence staining using natural killer cells. The results of our study provide new insight into N-glycosylation-based interaction of the mAb:CD16a complex.

Monitoring of antibody glycosylation pattern based on microarray MALDI-TOF mass spectrometry.

Biologically manufactured monoclonal antibodies (mAb) can strongly vary in their efficacy and affinity. Therefore, engineering and production of the mAb is highly regulated and requires product monitoring, especially in terms of N-glycosylation patterns. In this work, we present a high-throughput matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) method based on a microarray technology to monitor N-glycopeptides of IgG1 produced in a perfusion cell culture. A bottom-up approach combined with zwitterionic-hydrophilic interaction liquid chromatography for sample purification was used to determine the day-by-day variation of the terminal galactose within two major N-glycoforms. Our results show that microarrays for mass spectrometry (MAMS) are a robust platform for the rapid determination of the carbohydrate distribution. The spectral repeatability is characterized by a low coefficient of variations (1.7% and 7.1% for the FA2 and FA2G1 structures, respectively) and allows to detect the N-glycosylation variability resulting from operating conditions during the bioreactor process. The observed trend of released N-glycans was confirmed using capillary gel electrophoresis with laser-induced fluorescence detection. Therefore, the microarray technology is a promising analytical tool for glycosylation control during the production process of recombinant proteins.

Understanding Ovarian Cancer: iTRAQ-Based Proteomics for Biomarker Discovery.

Despite many years of studies, ovarian cancer remains one of the top ten cancers worldwide. Its high mortality rate is mainly due to lack of sufficient diagnostic methods. For this reason, our research focused on the identification of blood markers whose appearance would precede the clinical manifestation of the disease. ITRAQ-tagging (isobaric Tags for Relative and Absolute Quantification) coupled with mass spectrometry technology was applied. Three groups of samples derived from patients with: ovarian cancer, benign ovarian tumor, and healthy controls, were examined. Mass spectrometry analysis allowed for highlighting the dysregulation of several proteins associated with ovarian cancer. Further validation of the obtained results indicated that five proteins (Serotransferrin, Amyloid A1, Hemopexin, C-reactive protein, Albumin) were differentially expressed in ovarian cancer group. Interestingly, the addition of Albumin, Serotransferrin, and Amyloid A1 to CA125 (cancer antigen 125) and HE4 (human epididymis protein4) improved the diagnostic performance of the model discriminating between benign and malignant tumors. Identified proteins shed light on the molecular signaling pathways that are associated with ovarian cancer development and should be further investigated in future studies. Our findings indicate five proteins with a strong potential to use in a multimarker test for screening and detection of ovarian cancer.

MALDI-TOF-MS analysis in discovery and identification of serum proteomic patterns of ovarian cancer.

BACKGROUND: Due to high mortality and lack of efficient screening, new tools for ovarian cancer (OC) diagnosis are urgently needed. To broaden the knowledge on the pathological processes that occur during ovarian cancer tumorigenesis, protein-peptide profiling was proposed. METHODS: Serum proteomic patterns in samples from OC patients were obtained using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF). Eighty nine serum samples (44 ovarian cancer and 45 healthy controls) were pretreated using solid-phase extraction method. Next, a classification model with the most discriminative factors was identified using chemometric algorithms. Finally, the results were verified by external validation on an independent test set of samples. RESULTS: Main outcome of this study was an identification of potential OC biomarkers by applying liquid chromatography coupled with tandem mass spectrometry. Application of this novel strategy enabled the identification of four potential OC serum biomarkers (complement C3, kininogen-1, inter-alpha-trypsin inhibitor heavy chain H4, and transthyretin). The role of these proteins was discussed in relation to OC pathomechanism. CONCLUSIONS: The study results may contribute to the development of clinically useful multi-component diagnostic tools in OC. In addition, identifying a novel panel of discriminative proteins could provide a new insight into complex signaling and functional networks associated with this multifactorial disease.

PROTEOMIC ANALYSIS OF APIS MELLIFERA VENOM DETERMINED BY LIQUID CHROMATOGRAPHY (LC) COUPLED WITH NANO-LC-MALDI-TOF/TOF MS.

The integration of multidimensional liquid chromatography and mass spectrometry analytical plat- form was proposed for proteomic exploration of honeybee venom. The combination of HPLC with nanoLC-MALDI-TOF/TOF MS system was our method of choice for compressing the dynamic range of honeybee venom protein concentration. Honeybee venom samples were separated into 6 fractions using HPLC and further analyzed by nanoLC-MALDI-TOF/TOF. Applied approach allowed to identify in total 394 peptides giving the identification of 50 components including putative toxins and trace elements. Moreover, all 12 known honeybee venom allergens were acknowledged. Additionally, four novel hypothetical proteins have been observed which were not observed in other studies. The newly recognized proteins should be further investigated, in order to characterize their functions in the venom of Apis mellifera.

Challenges in biomarker discovery with MALDI-TOF MS.

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

Identification of Serum Peptidome Signatures of Non-Small Cell Lung Cancer.

Due to high mortality rates of lung cancer, there is a need for identification of new, clinically useful markers, which improve detection of this tumor in early stage of disease. In the current study, serum peptide profiling was evaluated as a diagnostic tool for non-small cell lung cancer patients. The combination of the ZipTip technology with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the analysis of peptide pattern of cancer patients (n = 153) and control subjects (n = 63) was presented for the first time. Based on the observed significant differences between cancer patients and control subjects, the classification model was created, which allowed for accurate group discrimination. The model turned out to be robust enough to discriminate a new validation set of samples with satisfactory sensitivity and specificity. Two peptides from the diagnostic pattern for non-small cell lung cancer (NSCLC) were identified as fragments of C3 and fibrinogen α chain. Since ELISA test did not confirm significant differences in the expression of complement component C3, further study will involve a quantitative approach to prove clinical utility of the other proteins from the proposed multi-peptide cancer signature.

Hyphenated LC-MALDI-ToF/ToF and LC-ESI-QToF approach in proteomic characterization of honeybee venom.

To increase in the depth characterization of venom proteome of Apis mellifera the hyphenated LC-MALDI-ToF/ToF-MS (liquid chromatography-matrix-assisted laser desorption/ionization-time of flight/time of flight tandem mass spectrometry) and LC-ESI-QToF-MS (liquid chromatography-electrospray ionization-quadrupole time of flight tandem mass spectrometry) techniques combined with combinatorial peptide ligand library enrichment method is proposed in this study. The novel approach simplifies pretreatment protocol in venom investigation. By using the protein preparation kit with sequential multi-step elution, the honeybee venom was dispensed into four different fractions. In total 269 proteins were detected, among these 49 honeybee toxins, allergens and components involved in mechanism of envenoming belonging to venom enzyme classes of esterases, proteases/peptidases, protease inhibitors, hydrolases and major royal jelly proteins. Moreover 5 additional putative toxins were identified. Their role in envenoming process was discussed. We concluded that different mass spectrometry techniques increased the detection of the honeybee venom proteins, underscoring the complementary character of analytical methods. The combination of MALDI and ESI ionization has resulted in numerous proteins identifications, not possible to reach with single proteomic technique. The study will contribute to broadening the knowledge about the complexity of honeybee venom. The newly identified proteins may serve not only as toxins and allergens, but also as substances with potential pharmacological activity. Although, the most detected proteins belong to trace elements of honeybee venom without toxic activity or action on vital system of victims, they should be taken into account in characterization of living organism response on Apis mellifera sting.

Prevalence of ocular abnormalities in prediabetic patients.

AIM: The aim of our study was to evaluate the prevalence of ocular abnormalities in prediabetic individuals. MATERIAL AND METHODS: 61 subjects aged 37-78 (41 women, 20 men), with impaired fasting glucose and/or impaired glucose tolerance, were enrolled in the study and compared to 30 healthy volunteers, aged 39-75 (20 women, 10 men), without prediabetes and history of previous ocular diseases. Both groups of patients underwent a complete physical examination, biochemical tests and ophthalmic examination: visual acuity testing, intraocular pressure measurement, anterior and posterior segment evaluation, fundus photographs, optical coherence tomography, colour vision and letter contrast sensitivity tests. RESULTS: The prevalence rates of various ocular abnormalities in prediabetic subjects as compared to healthy controls were as follows: acquired colour vision impairment 8.2% vs. 0% (p<0.05), signs of retinopathy: 9.8% vs. 0% (p<0.05), cataract: 32.8%/ vs. 6.7% (p<0.05), and corneal surface disorders: 19.7% vs. 3.3% (p<0.05). Optical coherence tomography revealed increased prevalence of posterior vitreous detachments and epiretinal membranes in prediabetic individuals as compared to healthy controls. There were no statistically significant differences in central retinal thickness, mean visual acuity and mean intraocular pressure between the two groups. CONCLUSION: Patients with prediabetes present with numerous ocular abnormalities. The prevalence of ocular disorders in prediabetic subjects is significantly higher as compared to healthy population. Regular ophthalmic monitoring seems to be essential at this stage of hyperglycemic disorders. A dedicated prevention and screening programs should be implemented in prediabetic population in order to early detect ocular abnormalities and identify individuals at risk of other diabetic complications.

A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus.

The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, L-citrulline, L-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.

The application of fuzzy statistics and linear discriminant analysis as criteria for optimizing the preparation of plasma for matrix-assisted laser desorption/ionization mass spectrometry peptide profiling.

An alternative bioinformatics approach based on fuzzy theory statistics and linear discriminant analysis is proposed for the interpretation of MALDI MS spectra in peptide profiling. When applied, the methodology enables the establishment of a reproducible plasma preparation protocol appropriate for the evaluation of small data sets. The samples were collected from pregnant women affected by gestational diabetes mellitus (GDM), n=18 and control group, n=13. The following pre-treatment sets were tested: pipette tips with C18 stationary phase (ZipTip, Millipore and Omix, Agilent) and magnetic bead-based weak cation exchange chromatography kit (MB WCX, Bruker Daltonics). The spectra were recorded using a MALDI TOF mass spectrometer (UltrafleXtreme, Bruker Daltonics) for a mass range of m/z from 1000 to 10,000. The significant features were selected using the wrapper selection method, and two classification systems were tested: discriminant analysis (DA) and fuzzy inference system (FIS). ClinProTools software was employed to compare the usefulness of the proposed methodology. The study showed that the optimum results for MS spectra were obtained after the use of the ZipTip as pre-treatment method in plasma preparation. Chemometric analysis allowed the differentiation of the GDM group from the control with a high degree of accuracy: 0.7333 (DA) and 0.8065 (FIS).

Influence of honeybee sting on peptidome profile in human serum.

The aim of this study was to explore the serum peptide profiles from honeybee stung and non-stung individuals. Two groups of serum samples obtained from 27 beekeepers were included in our study. The first group of samples was collected within 3 h after a bee sting (stung beekeepers), and the samples were collected from the same person a second time after at least six weeks after the last bee sting (non-stung beekeepers). Peptide profile spectra were determined using MALDI-TOF mass spectrometry combined with Omix, ZipTips and magnetic beads based on weak-cation exchange (MB-WCX) enrichment strategies in the mass range of 1-10 kDa. The samples were classified, and discriminative models were established by using the quick classifier, genetic algorithm and supervised neural network algorithms. All of the statistical algorithms used in this study allow distinguishing analyzed groups with high statistical significance, which confirms the influence of honeybee sting on the serum peptidome profile. The results of this study may broaden the understanding of the human organism's response to honeybee venom. Due to the fact that our pilot study was carried out on relatively small datasets, it is necessary to conduct further proteomic research of the response to honeybee sting on a larger group of samples.

Trace element concentrations in lichens collected in the Beskidy Mountains, the Outer Western Carpathians.

The aim of the study was to assess trace metal air pollution in the Beskidy Mountains, the Outer Western Carpathians, Poland, with a widely used bioaccumulating organism, a lichen, Hypogymnia physodes. Lichens were collected at five stands (mountains) in parallel transect and analyzed for cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) content. Concentrations of Cd, Pb and Zn in lichens were elevated, indicating moderate air pollution. The studied sites grouped in two clusters, with the three more contaminated sites being at the west end of the transect, and the two less polluted sites being situated more eastward. Such a pattern can be explained by the location of industrial centers and prevailing wind direction in southern Poland. The strongest correlation was noticed between Zn and Pb, which are known to occur jointly in ore deposits and are being processed in nearby Polish and Czech industrial regions.

Shotgun proteome analysis of honeybee venom using targeted enrichment strategies.

The aim of this study was to explore the honeybee venom proteome applying a shotgun proteomics approach using different enrichment strategies (combinatorial peptide ligand libraries and solid phase extraction). The studies were conducted using nano-LC/MALDI-TOF/TOF-MS system. The MS analysis of peptide profiles (in the range of 900-4500 Da) and virtual gel-image of proteins from Lab-on-Chip assay (in the range of 10-250 kDa) confirm that use of targeted enrichment strategies increase detection of honeybee venom components. The gel-free shotgun strategy and sophisticated instrumentation led to a significant increase of the sensitivity and higher number of identified peptides in honeybee venom samples, comparing with the current literature. Moreover, 11 of 12 known honeybee venom allergens were acknowledged and 4 new, so far uncharacterized proteins were identified. In addition, similarity searches were performed in order to investigate biological relations and homology between newly identified proteins sequences from Apis mellifera and other Hymenoptera.