SBML2LaTEX: Conversion of SBML files into human-readable reports

Summary: The XML-based Systems Biology Markup Language (SBML) has emerged as a standard for storage, communication and interchange of models in systems biology. As a machine-readable format XML is difficult for humans to read and understand. Many tools are available that visualize the reaction pathways stored in SBML files, but many components, e.g. unit declarations, complex kinetic equations or links to MIRIAM resources, are often not made visible in these diagrams. For a broader understanding of the models, support in scientific writing and error detection, a human-readable report of the complete model is needed. We present SBML2LaTEX, a Java-based stand-alone program to fill this gap. A convenient web service allows users to directly convert SBML to various formats, including DVI, LaTEX and PDF, and provides many settings for customization

Indirect protein quantification of drug-transforming enzymes using peptide group-specific immunoaffinity enrichment and mass spectrometry

Immunoaffinity enrichment of proteotypic peptides, coupled with selected reaction monitoring, enables indirect protein quantification. However the lack of suitable antibodies limits its widespread application. We developed a method in which multi-specific antibodies are used to enrich groups of peptides, thus facilitating multiplexed quantitative protein assays. We tested this strategy in a pharmacokinetic experiment by targeting a group of homologous drug transforming proteins in human hepatocytes. Our results indicate the generic applicability of this method to any biological system

Indirect protein quantification of drug-transforming enzymes using peptide group-specific immunoaffinity enrichment and mass spectrometry

Immunoaffinity enrichment of proteotypic peptides, coupled with selected reaction monitoring, enables indirect protein quantification. However the lack of suitable antibodies limits its widespread application. We developed a method in which multi-specific antibodies are used to enrich groups of peptides, thus facilitating multiplexed quantitative protein assays. We tested this strategy in a pharmacokinetic experiment by targeting a group of homologous drug transforming proteins in human hepatocytes. Our results indicate the generic applicability of this method to any biological system

Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency.</p> <p>Results</p> <p>We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties.</p> <p>Conclusions</p> <p>For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics.</p

Association between IgG responses against the nucleocapsid proteins of alphacoronaviruses and COVID-19 severity.

Understanding immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial to contain the COVID-19 pandemic. Using a multiplex approach, serum IgG responses against the whole SARS-CoV-2 proteome and the nucleocapsid proteins of endemic human coronaviruses (HCoVs) were measured in SARS-CoV-2-infected donors and healthy controls. COVID-19 severity strongly correlated with IgG responses against the nucleocapsid (N) of SARS-CoV-2 and possibly with the number of viral antigens targeted. Furthermore, a strong correlation between COVID-19 severity and serum responses against N of endemic alpha- but not betacoronaviruses was detected. This correlation was neither caused by cross-reactivity of antibodies, nor by a general boosting effect of SARS-CoV-2 infection on pre-existing humoral immunity. These findings raise the prospect of a potential disease progression marker for COVID-19 severity that allows for early stratification of infected individuals