Improving biologics development by high performance glycoanalysis

Glycomics is a rapidly emerging field that can be viewed as a complement to other „omics“ approaches including proteomics and genomics. Hence, there is a dramatic increase in the demand for analytical tools and specific databases in glycobiology, respectively, glycobiotechnology. In order to enhance and improve the comparatively small existing glycoanalytical toolbox, fully automated, highly sensitive, reliable, high-throughput and high-resolution analysis methods including automated data evaluation are required. One very promising method is based on multiplexed capillary gelelectrophoresis with laser induced fluorescence detection (xCGE-LIF). The glycoanalytical approach established includes sample preparation and measuring methods, software, and database solutions to tackle challenges in a great number of application fields. First, an optimized modular sample preparation workflow is presented with respect to performance and feasibility regarding high-throughput analytics [1-5]. Second, parallel sample-measurement is shown to result in massive reduction of the effective run-time per sample [4]. Third, automated data analysis with a newly developed modular software-tool for data processing and data analysis is demonstrated that involves integration of a corresponding oligosaccharide-database [6-8]. Using this high-performance xCGE-LIF based glycoanalysis system, the generated “normalized” electropherograms of glycomoieties (“fingerprints”) can be evaluated on three levels: (1) “simple” qualitative and quantitative pattern comparison (“fingerprinting”), (2) identification of compounds in complex mixtures via database matching (“glycoprofiling”) and (3) extended structural analysis using exoglycosidase sequencing in combination with xCGE-LIF based glycoprofiling. The broad applicability of the system is demonstrated for different types of glycosamples: from manufacturing of biologics and vaccines (including recombinant and viral glycoproteins) [1-3], to human stem cells, blood serum [4,5] and milk [8]

Response of pseudomonas putida KT2440 to phenol at the level of membrane proteome

This study led to the extension and refinement of our current model for the global response of Pseudomonas putida KT2440 to phenol by getting insights into the adaptive response mechanisms involving the membrane proteome. A two-dimensional gel electrophoresis based protocol was optimized to allow the quantitative comparison of membrane proteins, by combining inner and outer membrane fractionation with membrane protein solubilization using the detergent dodecylmaltoside. Following phenol exposure, a coordinate increased content of protein subunits of known or putative solvent efflux pump systems (e.g. TtgA, TtgC, Ttg2A, Ttg2C, and PP_1516-7) and a decreased content of porins OprB, OprF, OprG and OprQ was registered, consistent with an adaptive response to reduce phenol intracellular concentration. This adaptive response may in part be mediated by post-translational modifications, as suggested by the relative content of the multiple forms identified for a few porins and efflux pump subunits. Results also suggest the important role of protein chaperones, of cell envelope and cell surface and of a more active respiratory chain in the response to phenol. All these mechanistic insights may be extended to Pseudomonas adaptation to solvents, of possible impact in biodegradation, bioremediation and biocatalysis.PhD scholarship SFRH/BD/38805/200

Viewing the proteome: How to visualize proteomics data?

Proteomics has become one of the main approaches for analyzing and understanding biological systems. Yet similar to other high-throughput analysis methods, the presentation of the large amounts of obtained data in easily interpretable ways remains challenging. In this review, we present an overview of the different ways in which proteomics software supports the visualization and interpretation of proteomics data. The unique challenges and current solutions for visualizing the different aspects of proteomics data, from acquired spectra via protein identification and quantification to pathway analysis, are discussed, and examples of the most useful visualization approaches are highlighted. Finally, we offer our ideas about future directions for proteomics data visualization.acceptedVersio

The impact of sequence database choice on metaproteomic results in gut microbiota studies

Background: Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics, the study of the whole protein complement of a microbial community, can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification. Results: Here, we present a systematic investigation of variables concerning database construction and annotation and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. In particular, the contribution of experimental metagenomic databases was revealed to be mandatory when dealing with mouse samples. Moreover, the use of a "merged" database, containing all metagenomic sequences from the population under study, was found to be generally preferable over the use of sample-matched databases. We also observed that taxonomic and functional results are strongly database-dependent, in particular when analyzing the mouse gut microbiota. As a striking example, the Firmicutes/Bacteroidetes ratio varied up to tenfold depending on the database used. Finally, assembling reads into longer contigs provided significant advantages in terms of functional annotation yields. Conclusions: This study contributes to identify host- and database-specific biases which need to be taken into account in a metaproteomic experiment, providing meaningful insights on how to design gut microbiota studies and to perform metaproteomic data analysis. In particular, the use of multiple databases and annotation tools has to be encouraged, even though this requires appropriate bioinformatic resources

DeNovoGUI: an open source graphical user interface for de novo sequencing of tandem mass spectra

De novo sequencing is a popular technique in proteomics for identifying peptides from tandem mass spectra without having to rely on a protein sequence database. Despite the strong potential of de novo sequencing algorithms, their adoption threshold remains quite high. We here present a user-friendly and lightweight graphical user interface called DeNovoGUI for running parallelized versions of the freely available de novo sequencing software PepNovo+, greatly simplifying the use of de novo sequencing in proteomics. Our platform-independent software is freely available under the permissible Apache2 open source license. Source code, binaries, and additional documentation are available at http://denovogui.googlecode.com.acceptedVersio

Purification and characterization of hydroquinone dioxygenase from Sphingomonas sp. strain TTNP3

Hydroquinone-1,2-dioxygenase, an enzyme involved in the degradation of alkylphenols in Sphingomonas sp. strain TTNP3 was purified to apparent homogeneity. The extradiol dioxygenase catalyzed the ring fission of hydroquinone to 4-hydroxymuconic semialdehyde and the degradation of chlorinated and several alkylated hydroquinones. The activity of 1 mg of the purified enzyme with unsubstituted hydroquinone was 6.1 μmol per minute, the apparent Km 2.2 μM. ICP-MS analysis revealed an iron content of 1.4 moles per mole enzyme. The enzyme lost activity upon exposure to oxygen, but could be reactivated by Fe(II) in presence of ascorbate. SDS-PAGE analysis of the purified enzyme yielded two bands of an apparent size of 38 kDa and 19 kDa, respectively. Data from MALDI-TOF analyses of peptides of the respective bands matched with the deduced amino acid sequences of two neighboring open reading frames found in genomic DNA of Sphingomonas sp strain TTNP3. The deduced amino acid sequences showed 62% and 47% identity to the large and small subunit of hydroquinone dioxygenase from Pseudomonas fluorescens strain ACB, respectively. This heterotetrameric enzyme is the first of its kind found in a strain of the genus Sphingomonas sensu latu

Minimal B Cell Extrinsic IgG Glycan Modifications of Pro- and Anti-Inflammatory IgG Preparations in vivo

Select residues in the biantennary sugar moiety attached to the fragment crystallizable of immunoglobulin G (IgG) antibodies can modulate IgG effector functions. Thus, afucosylated IgG glycovariants have enhanced cytotoxic activity, whereas IgG glycovariants rich in terminal sialic acid residues can trigger anti-inflammatory effects. More recent evidence suggests that terminal α2,6 linked sialic acids can be attached to antibodies post IgG secretion. These findings raise concerns for the use of therapeutic antibodies as they may change their glycosylation status in the patient and hence affect their activity. To investigate to what extent B cell extrinsic sialylation processes modify therapeutic IgG preparations in vivo, we analyzed changes in human intravenous IgG (IVIg) sialylation upon injection in mice deficient in B cells or in mice lacking the sialyltransferase 1, which catalyzes the addition of α2,6 linked sialic acid residues. By performing a time course of IgG glycan analysis with HILIC-UPLC-FLR (plus MS) and xCGE-LIF our study suggests that therapeutic IgG glycosylation is stable upon injection in vivo. Only a very small fraction of IgG molecules acquired sialic acid structures predominantly in the Fab- but not the Fc-portion upon injection in vivo, suggesting that therapeutic antibody glycosylation will remain stable upon injection in vivo

Macrophage- and CD4+ T cell-derived SIV differ in glycosylation, infectivity and neutralization sensitivity

The human immunodeficiency virus (HIV) envelope protein (Env) mediates viral entry into host cells and is the primary target for the humoral immune response. Env is extensively glycosylated, and these glycans shield underlying epitopes from neutralizing antibodies. The glycosylation of Env is influenced by the type of host cell in which the virus is produced. Thus, HIV is distinctly glycosylated by CD4+ T cells, the major target cells, and macrophages. However, the specific differences in glycosylation between viruses produced in these cell types have not been explored at the molecular level. Moreover, it remains unclear whether the production of HIV in CD4+ T cells or macrophages affects the efficiency of viral spread and resistance to neutralization. To address these questions, we employed the simian immunodeficiency virus (SIV) model. Glycan analysis implied higher relative levels of oligomannose-type N-glycans in SIV from CD4+ T cells (T-SIV) compared to SIV from macrophages (M-SIV), and the complex-type N-glycans profiles seem to differ between the two viruses. Notably, M-SIV demonstrated greater infectivity than T-SIV, even when accounting for Env incorporation, suggesting that host cell-dependent factors influence infectivity. Further, M-SIV was more efficiently disseminated by HIV binding cellular lectins. We also evaluated the influence of cell type-dependent differences on SIV’s vulnerability to carbohydrate binding agents (CBAs) and neutralizing antibodies. T-SIV demonstrated greater susceptibility to mannose-specific CBAs, possibly due to its elevated expression of oligomannose-type N-glycans. In contrast, M-SIV exhibited higher susceptibility to neutralizing sera in comparison to T-SIV. These findings underscore the importance of host cell-dependent attributes of SIV, such as glycosylation, in shaping both infectivity and the potential effectiveness of intervention strategies