Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Knowledge Management Approaches for predicting Biomarker and Assessing its Impact on Clinical Trials

The recent success of companion diagnostics along with the increasing regulatory pressure for better identification of the target population has created an unprecedented incentive for the drug discovery companies to invest into novel strategies for stratified biomarker discovery. Catching with this trend, trials with stratified biomarker in drug development have quadrupled in the last decade but represent a small part of all Interventional trials reflecting multiple co-developmental challenges of therapeutic compounds and companion diagnostics. To overcome the challenge, varied knowledge management and system biology approaches are adopted in the clinics to analyze/interpret an ever increasing collection of OMICS data. By semi-automatic screening of more than 150,000 trials, we filtered trials with stratified biomarker to analyse their therapeutic focus, major drivers and elucidated the impact of stratified biomarker programs on trial duration and completion. The analysis clearly shows that cancer is the major focus for trials with stratified biomarker. But targeted therapies in cancer require more accurate stratification of patient population. This can be augmented by a fresh approach of selecting a new class of biomolecules i.e. miRNA as candidate stratification biomarker. miRNA plays an important role in tumorgenesis in regulating expression of oncogenes and tumor suppressors; thus affecting cell proliferation, differentiation, apoptosis, invasion, angiogenesis. miRNAs are potential biomarkers in different cancer. However, the relationship between response of cancer patients towards targeted therapy and resulting modifications of the miRNA transcriptome in pathway regulation is poorly understood. With ever-increasing pathways and miRNA-mRNA interaction databases, freely available mRNA and miRNA expression data in multiple cancer therapy have created an unprecedented opportunity to decipher the role of miRNAs in early prediction of therapeutic efficacy in diseases. We present a novel SMARTmiR algorithm to predict the role of miRNA as therapeutic biomarker for an anti-EGFR monoclonal antibody i.e. cetuximab treatment in colorectal cancer. The application of an optimised and fully automated version of the algorithm has the potential to be used as clinical decision support tool. Moreover this research will also provide a comprehensive and valuable knowledge map demonstrating functional bimolecular interactions in colorectal cancer to scientific community. This research also detected seven miRNA i.e. hsa-miR-145, has-miR-27a, has- miR-155, hsa-miR-182, hsa-miR-15a, hsa-miR-96 and hsa-miR-106a as top stratified biomarker candidate for cetuximab therapy in CRC which were not reported previously. Finally a prospective plan on future scenario of biomarker research in cancer drug development has been drawn focusing to reduce the risk of most expensive phase III drug failures

Incorporating standardised drift-tube ion mobility to enhance non-targeted assessment of the wine metabolome (LC×IM-MS)

Liquid chromatography with drift-tube ion mobility spectrometry-mass spectrometry (LCxIM-MS) is emerging as a powerful addition to existing LC-MS workflows for addressing a diverse range of metabolomics-related questions [1,2]. Importantly, excellent precision under repeatability and reproducibility conditions of drift-tube IM separations [3] supports the development of non-targeted approaches for complex metabolome assessment such as wine characterisation [4]. In this work, fundamentals of this new analytical metabolomics approach are introduced and application to the analysis of 90 authentic red and white wine samples originating from Macedonia is presented. Following measurements, intersample alignment of metabolites using non-targeted extraction and three-dimensional alignment of molecular features (retention time, collision cross section, and high-resolution mass spectra) provides confidence for metabolite identity confirmation. Applying a fingerprinting metabolomics workflow allows statistical assessment of the influence of geographic region, variety, and age. This approach is a state-of-the-art tool to assess wine chemodiversity and is particularly beneficial for the discovery of wine biomarkers and establishing product authenticity based on development of fingerprint libraries

Exploring the chemical space of post-translationally modified peptides in Streptomyces with machine learning

The ongoing increase in antimicrobial resistance combined with the low discovery of novel antibiotics is a serious threat to our health care. Genome mining has given new potential to the field of natural product discovery, as thousands of biosynthetic gene clusters (BGCs) are discovered for which the natural product is not known.Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a highly diverse class of natural products. The large number of different modifications that can be applied to a RiPP results in a large variety of chemical structures, but also stems from a large genetic variety in BGCs. As a result, no single method can effectively mine for all RiPP BGCs, making it an interesting source for new molecules.In this thesis, new methods are explored to mine genomes for the BGCs of novel RiPP variants, with a focus on discovering RiPPs that have new modifications. RRE-Finder is a new tool for the detection of RiPP Recognition Elements, domains that are often found in RiPP BGCs. DecRiPPter is another tool that employs machine learning models to discover new RiPP precursor genes encoded in the genomes. Both tools can be used to prioritize novel RiPP BGCs. Two candidate BGCs are characterized, one of which could be shown to specify a new RiPP, validating the approach.Grant 731.014.206 (Syngenopep, TKI Chemie) from the Dutch Research Council (NWO)Microbial Biotechnolog

Mass Spectrometric Proteomics

As suggested by the title of this Special Issue, liquid chromatography-mass spectrometry plays a pivotal role in the field of proteomics. Indeed, the research and review articles  published in the Issue clearly evidence how the data produced by this sophisticated methodology may promote impressive advancements in this area. From among the topics discussed in the Issue, a few point to the development of  new procedures for the  optimization of the experimental conditions that should be applied  for the identification of proteins present in complex mixtures.  Other applications  described in these articles show  the huge potential of  these strategies in the protein profiling of organs and  range from  to the study of post-translational tissue modifications to the investigation of the molecular mechanisms behind human disorders and the identification of potential biomarkers of these diseases

Iron uptake and homeostasis in the veterinary pathogen Rhodococcus equi: an integrated omics approach

Rhodococcus equi, a veterinary pathogen that causes pyogranulomatous pneumonia, can secrete low molecular weight chelators called siderophores to scavenge iron when its bioavailability is limited. When iron is plentiful, synthesis of siderophores and ferri–siderophore transport systems are repressed. Current literature on bacterial iron regulation and homeostasis indicates two distinct protein families of global iron-dependent transcriptional repressor: Fur and DtxR. Gram-negative bacteria produce Fur to regulate iron uptake genes and the biosynthesis of siderophores in response to the iron level in the cell. However, the Gram-positive Corynebacteriaceae produce DtxR-like proteins to regulate analogous genes. Much remains undefined with respect to rhodococcal siderophore biosynthesis and uptake. Detailed analysis of the R. equi 103S genome for genes related to iron homeostasis identified two potential metal regulatory genes each from the Fur and DtxR families: iron dependent regulatory protein (IdeR), Diphtheria toxin repressor (DtxR), Ferric uptake regulator A (FurA) and Ferric uptake regulator B (FurB). Bioinformatic analysis confirmed that this complement of genes was conserved throughout Rhodococcus and the Corynebacteriaceae in general. To investigate their individual roles in metal homeostasis, molecular cloning and gene expression was performed, to facilitate analysis of regulator-metal specificities. Each gene was cloned but over-expression for functional analysis could only be achieved for ideR; thus, a thorough systematic analysis could not be achieved. In order to address their individual roles, homology-based protein modelling was used, and comparisons made with characterised homologues from M. tuberculosis. The geometrical conservation of key ligand amino acid residues strongly suggests R. equi utilises ideR as an iron regulator; furB as a zinc regulator, dtxR as a manganese regulator and furA as an oxidative stress response protein. Most bacteria generate an exaggerated response to iron limitation in vitro, however R. equi produces very small siderophore yields s, which has complicated their characterisation. In-frame deletion of the putative metal regulator genes ideR, dtxR, furA and furB was attempted in order to address the hypothesis that de-repression might generate greater yields. All genes were deleted individually; a marked phenotypic difference was noted only for R. equi-ΔfurA, which significantly upregulated the catalase encoded by the neighbouring gene and was coincidentally hyper-resistant to hydrogen peroxide. Surprisingly, analysis of siderophore production in the mutants indicated no increase in yield. The thesis discusses the relevance of this observation to microbial ecology. The availability of these mutants in combination with their predicted metal specificities facilitates the design of experiments to define their individual roles in metal homeostasis beyond the scope of this thesis. The combination of ‘omic’ analyses was attempted here to initiate the ultimate definition of the complex molecular network associated with iron uptake. The genomic investigation informed hypothesis building for the other omic analyses. It suggested R. equi is capable of synthesising two siderophores, rhequibactin and rhequichelin; up to three had previously been postulated in the literature. Culture optimisation was required to deliver a robust experimental design to impose iron limitation in isolation from other stresses. Once medium composition and biomarker-indicated harvesting criteria were established, biomass and associated secretomes were produced en masse for integrated omics analysis. A comparative untargeted metabolomics study demonstrated an adapted iron-starved metabolome; strong siderophore candidates were then investigated using a targeted strategy. A strong candidate metabolite was identified by mass that appeared to be responsible for a heterobactin-like chromophore, however further biochemical characterisation has been elusive. Interestingly, the metabolite readily precipitates on complexation with iron, an observation also made for heterobactins. Secondly, a transcriptomic study was attempted to study the global gene expression under iron starvation, and the impact of the loss of the IdeR in the deletion mutant generated in this work. However, the RNA extraction proved particularly challenging likely due to difficulties arising from lysis of the mycolic acid-containing cell wall. In the absence of a high-quality transcriptome sample, the study did not advance further and other aspects of the study were prioritised. Finally, a comparative proteomic analysis into iron regulatory mechanisms associated with the rhodococcal cell wall was performed. Current literature deliberates how R. equi uses a range of strategies to overcome iron limitation through proposed uptake mechanisms associated with translocation across the cytoplasmic membrane via ABC transport systems, while no consideration has yet been made with regards to transport across the mycolic acid-containing cell wall structure. In this study no obvious candidate proteins for ferri-sideophore transport across the mycolate region were identified, therefore it is possible that R. equi utilises facilitated diffusion via a porin for entry of ferri-siderophore complexes into the pseudoperiplasm, where a substrate-binding lipoprotein may act as the primary receptor to facilitate cytosolic transfer through an ABC transport system

Fruit Metabolism and Metabolomics

Over the past ten years, metabolomics strategies have allowed the relative or absolute quantitation of metabolite levels for the study of various biological questions in plant sciences. For fruit studies, in particular, they have participated in the identification of the genes underpinning fruit development and ripening. This book proposes examples of the current use of metabolomics studies of fruit for basic research or practical applications. It includes articles about several tropical and temperate fruit species. The studies concern fruit biochemical phenotyping, fruit metabolism during development and after harvest, including primary and specialized metabolisms, or bioactive compounds involved in fruit growth and environmental responses. The analytical strategies used are based mostly on liquid or gas chromatography coupled with mass spectrometry, but also on nuclear magnetic resonance and near-infrared spectroscopy. The effect of genotype, stages of development, or fruit tissue type on metabolomic profiles and corresponding metabolism regulations are addressed for fruit metabolism studies. The interest in combining other omics with metabolomics is also exemplified

BIOINFORMATICS STRATEGIES FOR GENOMICS: EXAMPLES AND APPROACHES FOR TOMATO

My PhD is funded by the Solanaceae Pollen thermotolerance – Initial Training Network (SPOT-ITN) in the frame of the European Marie Curie Actions. The consortium aims to investigate fundamental and applied aspects contributing to the protection of pollen at increased environmental temperatures, deciphering the underlying of pollen development and its response to heat stress, starting from analyses on Tomato. Obviously, the findings are supposed to be a guideline, and the procedures to be applicable to other plants in the future. In the light of the SPOT-ITN project objectives, and to provide a comprehensive bioinformatics infrastructure to support extensive genomics analyses in tomato, we collected, processed and integrated different resources; and organized them into dedicated databases with appropriate query user interfaces. This bioinformatics effort required the design of the most adequate software to reconcile the manifold resources from different cell information levels (genomics, transcriptomics, epigenomics). This is fundamental for data integration and analysis. The development of appropriate tools to mine the data from the “omics” approaches employed to trace the pollen development and the heat stress response has also been necessary to the project. In this thesis, the main efforts undertaken and the analyses conducted on the basis of such resources with the strategies and approaches developed are reported in details