Improving phylogeny reconstruction at the strain level using peptidome datasets

Typical bacterial strain differentiation methods are often challenged by high genetic similarity between strains. To address this problem, we introduce a novel in silico peptide fingerprinting method based on conventional wet-lab protocols that enables the identification of potential strain-specific peptides. These can be further investigated using in vitro approaches, laying a foundation for the development of biomarker detection and application-specific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate that the two approaches can most likely be used complementarily even in other organismal groups. The obtained results confirm previous reports about the misclassification of many strains within the B. cereus group. Moreover, our method was able to separate the B. anthracis strains with high resolution, similarly to the GBDP results as benchmarked via Bayesian inference and both Maximum Likelihood and Maximum Parsimony. In addition to the presented phylogenomic applications, whole-peptide fingerprinting might also become a valuable complementary technique to digital DNA-DNA hybridization, notably for bacterial classification at the species and subspecies level in the future.This research was funded by Grant AGL2013-44039-R from the Spanish “Plan Estatal de I+D+I”, and by Grant EM2014/046 from the “Plan Galego de investigación, innovación e crecemento 2011-2015”. BS was recipient of a Ramón y Cajal postdoctoral contractfrom the Spanish Ministry of Economyand Competitiveness. This work was also partially funded by the [14VI05] Contract-Programme from the University of Vigo and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273).The research leading to these results has also received funding from the European Union’s Seventh Framework Programme FP7/REGPOT-2012-2013.1 under grant agreement n˚ 316265, BIOCAPS. This document reflects only the authors’ views and the European Union is not liable for any use that may be made of the information contained herein. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

P4P: a peptidome-based strain-level genome comparison web tool

Peptidome similarity analysis enables researchers to gain insights into differential peptide profiles, providing a robust tool to discriminate strain-specific peptides, true intra-species differences among biological replicates or even microorganism-phenotype variations. However, no in silico peptide fingerprinting software existed to facilitate such phylogeny inference. Hence, we developed the Peptidomes for Phylogenies (P4P) web tool, which enables the survey of similarities between microbial proteomes and simplifies the process of obtaining new biological insights into their phylogeny. P4P can be used to analyze different peptide datasets, i.e. bacteria, viruses, eukaryotic species or even metaproteomes. Also, it is able to work with whole proteome datasets and experimental mass-to-charge lists originated from mass spectrometers. The ultimate aim is to generate a valid and manageable list of peptides that have phylogenetic signal and are potentially sample-specific. Sample-to-sample comparison is based on a consensus peak set matrix, which can be further submitted to phylogenetic analysis. P4P holds great potential for improving phylogenetic analyses in challenging taxonomic groups, biomarker identification or epidemiologic studies. Notably, P4P can be of interest for applications handling large proteomic datasets, which it is able to reduce to small matrices while maintaining high phylogenetic resolution. The web server is available at http://sing-group.org/p4p.Spanish ‘Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad’ [AGL2013-44039R]; Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020[POCI-01-0145-FEDER-006684];INOU16-05project from the University of Vigo; Fundación AECC. Funding for open access charge: Spanish ‘Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad’ [AGL2013-44039R].info:eu-repo/semantics/publishedVersio

Characterization of the Human Host Gut Microbiome with an Integrated Genomics / Proteomics Approach

The new field of ‘omics’ has spawned the development of metaproteomics, an approach that has the ability to identify and decipher the metabolic functions of a proteome derived from a microbial community that is largely uncultivable. With the development and availabilities of high throughput proteomics, high performance liquid chromatography coupled to mass spectrometry (MS) has been leading the field for metaproteomics. MS-based metaproteomics has been successful in its’ investigations of complex microbial communities from soils to the human body. Like the environment, the human body is host to a multitude of microorganisms that reside within the skin, oral cavity, vagina, and gastrointestinal tract, referred to as the human microbiome. The human microbiome is made up of trillions of bacteria that outnumber human genes by several orders of magnitude. These microbes are essential for human survival with a significant dependence on the microbes to encode and carryout metabolic functions that humans have not evolved on their own. Recently, metaproteomics has emerged as the primary technology to understand the metabolic functional signature of the human microbiome. Using a newly developed integrated approach that combines metagenomics and metaproteomics, we attempted to address the following questions: i) do humans share a core functional microbiome and ii) how do microbial communities change in response to disease. This resulted in a comprehensive identification and characterization of the metaproteome from two healthy human gut microbiomes. These analyses have resulted in an extended application to characterize how Crohn’s disease affects the functional signature of the microbiota. Contrary to measuring highly complex and representative gut metaproteomes is a less complex, controlled human-derived microbial community present in the gut of gnotobiotic mice. This human gut model system enhanced the capability to directly monitor fundamental interactions between two dominant phyla, Bacteroides and Firmicutes, in gut microbiomes colonized with two or more phylotypes. These analyses revealed membership abundance and functional differences between phylotypes when present in either a binary or 12-member consortia. This dissertation aims to characterize host microbial interactions and develop MS-based methods that can provide a better understanding of the human gut microbiota composition and function using both approaches

Characterization of Human Gut Microbiota Dynamics Using Model Communities in Gnotobiotic Mice

The human gut is colonized by a diverse array of microbes, collectively referred to as the microbiota. The microbiota\u27s complexity poses significant challenges in characterizing the rules dictating its assembly, inferring the functional roles of its component species, and understanding how communities sense and respond to changes in their habitat. We developed defined, representative model communities comprised of sequenced human gut bacteria that could be characterized in a highly controlled manner in gnotobiotic mice, plus a suite of scalable molecular tools for assaying community properties. These tools were first used to evaluate how the microbiota is impacted by probiotic bacterial strains found in fermented milk products: FMP). Introduction of a consortium of five FMP strains resulted in only minimal changes in the structural configuration of a 15-member model microbiota. However, RNA-Seq and follow-up mass spectrometry revealed numerous functional responses, many related to carbohydrate metabolism. Results from a study performed in monozygotic twin pairs confirmed many of our observations in the model microbiota, showing that lessons learned from preclinical models can inform the design and interpretation of human studies. In a second set of experiments, we evaluated the impact of food on both a model community and its constituent taxa by feeding gnotobiotic mice oscillating diets of disparate composition. In addition to prompt and reversible structural reconfigurations suggesting rules-based diet effects, we noted consistent, staggered changes in the representation of many functions within the metatranscriptome related to carbohydrate and amino acid metabolism. One prominent community member, Bacteroides cellulosilyticus WH2, was identified as an adaptive forager that tailors its versatile carbohydrate utilization strategy to the dietary polysaccharides available. The specific carbohydrates that trigger expression of many of this organism\u27s 113 predicted polysaccharide utilization loci were identified by RNA-Seq analysis during in vitro growth on 31 distinct carbohydrate substrates, aiding our interpretation of in vivo RNA-Seq and high resolution proteomics data. These results offer insight into how gut microbes adapt to dietary perturbations, both at a community level and from the perspective of a well-adapted symbiont with exceptional saccharolytic capabilities, and illustrate the value of studying defined models of the human gut microbiota

An integrative polyomics investigation of bovine mastitis

Bovine mastitis, inflammation of the mammary gland, is one of the most costly and prevalent diseases in the dairy industry. It is commonly caused by bacteria, and Streptococcus uberis is one of the most prevalent causative agents. With advancements in omics technologies, the analysis of system-wide changes in the expression of proteins and metabolites in milk has become possible, and such analyses have broadened the knowledge of molecular changes in bovine mastitis. The work presented in this thesis aims to understand the dynamics of molecular changes in bovine mastitis caused by Streptococcus uberis through system-wide profiling and integrated analysis of milk proteins and metabolites. To this end, archived milk samples collected at specific intervals during the course of an experimentally induced model of Streptococcus uberis mastitis were used. Label-free quantitative proteomics and untargeted metabolomics data were generated from the archived milk samples obtained from six cows at six time-points (0, 36, 42, 57, 81 & 312 hours post-challenge). A total of 570 bovine proteins and 690 putative metabolites were quantified. Hierarchical cluster analysis and principal component analysis showed clustering of samples by the stage of infection, with similarities between pre-infection and resolution stages (0 and 312 hours post-challenge), early infection stages (36 and 42 hours post-challenge) and late infection stages (57 and 81 hours post-challenge). The proteomics and metabolomics data were analysed at both individual omics-layer level and combined inter-layer-level. At individual omics layer-level, the temporal changes identified include changes in the expression of proteins in acute-phase response signalling, FXR/RXR activation, complement system, IL-6 and IL-10 pathways, and changes in the expression of metabolites related to amino acid, carbohydrate, lipid and nucleotide metabolisms. The combined inter-layer-level analyses revealed functional relevance of proteins and metabolites enriched in the co-expression modules. For example, possible immunomodulatory role of bile acids via the FXR/RXR activation pathways could be inferred. Similarly, the actin-binding proteins could be linked to endocytic trafficking of signalling receptors. Overall, the work presented in this thesis provides deeper understanding of molecular changes in mastitis. On a secondary note, it also serves as a case study in the use of integrative polyomics analysis methods in the investigation of host-pathogen interactions

Novel Computational Methods for the Analysis and Interpretation of MS/MS Data in Metaproteomics

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016von Dipl.-Bioinf. Thilo MuthLiteraturverzeichnis: Seite 151-17

26th Fungal Genetics Conference at Asilomar

Program and abstracts from the 26th Fungal Genetics Conference, March 15-20, 2011