Omics meets hypothesis-driven research. Partnership for innovative discoveries in vascular biology and angiogenesis.

The emergence of omics technologies allowing the global analysis of a given biological or molecular system, rather than the study of its individual components, has revolutionized biomedical research, including cardiovascular medicine research in the past decade. These developments raised the prospect that classical, hypothesis-driven, single gene-based approaches may soon become obsolete. The experience accumulated so far, however, indicates that omic technologies only represent tools similar to those classically used by scientists in the past and nowadays, to make hypothesis and build models, with the main difference that they generate large amounts of unbiased information. Thus, omics and classical hypothesis-driven research are rather complementary approaches with the potential to effectively synergize to boost research in many fields, including cardiovascular medicine. In this article we discuss some general aspects of omics approaches, and review contributions in three areas of vascular biology, thrombosis and haemostasis, atherosclerosis and angiogenesis, in which omics approaches have already been applied (vasculomics).

Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population

The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study, we quantified the transcriptome--a subset of the metabolome--and, using targeted proteomics, quantified a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein, and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. These integrated molecular profiles also allowed further characterization of complex pathways, particularly the mitochondrial unfolded protein response (UPR(mt)). UPR(mt) shows strikingly variant responses at the transcript and protein level that are remarkably conserved among C. elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.

The plant ovule omics : an integrative approach for pollen−pistil interactions and pollen tube guidance studies in solanaceous species

Chez les plantes à fleurs, l’ovaire est l’organe reproducteur femelle et il interagit de façon importante avec les gamètes mâles durant la croissance, le guidage, la réception et la rupture du tube pollinique ainsi que la fusion des gamètes. Le processus débute lorsque de nombreux gènes de l’ovule sont activés à longue distance lors de la réception du pollen sur le stigmate. Afin d’explorer les signaux provenant de l’ovule ayant un impact important sur les interactions pollen–pistil, particulièrement les molécules sécrétées impliquées dans la signalisation espècespécifique, l’expression génique des ovules sous forme d’ARNm ainsi et la sécrétion protéique ont été étudiées chez Solanum chacoense, une espèce diploïde de pomme de terre sauvage. S. chacoense a subi beaucoup d’hybridation interspécifique avec d’autres espèces sympathiques de solanacées, facilitant ainsi grandement l’étude des interactions pollen–ovule de façon espècespécifique ainsi que leur évolution. Dans ce projet, des ovules provenant de trois conditions différentes ont été comparés: des ovules matures de type sauvage, des ovules légèrement immatures, récoltés deux jours avant l’anthèse et des ovules provenant du mutant frk1 pour lesquels le sac embryonnaire est absent. Un séquençage d’ARN à haut débit a d’abord été effectué sur les ovules de type sauvage de S. chacoense afin de générer un assemblage de référence comprenant 33852 séquences codantes. D’autres séquençages ont été effectués sur les trois conditions d’ovules et sur les feuilles afin de faire une analyse d’expression différentielle des gènes. En comparaison avec les ovules de type sauvage, 818 gènes sont réprimés dans les ovules du mutant frk1. Un sous-groupe de 284 gènes, étaient également sous-exprimés dans les ovules légèrement immatures, suggérant un rôle spécifique dans les stades tardifs de la maturation du sac embryonnaire (stade de développent FG6 à FG7) ainsi que du guidage du tube pollinique, puisque ni les ovules du mutant frk1 ni ceux légèrement immatures ne sont capables d’attirer les tubes polliniques lors d’essais de croissance semi in vivo. De plus, 21% de ces gènes sont des peptides riches en cystéines (CRPs). En utilisant un transcriptome assemblé de novo provenant de deux proches parents de S. chacoense, S. gandarillasii et S. tarijense, une analyse d’orthologie a été effectuée sur ces CRPs, révélant une grande variabilité et une évolution rapide chez les solanacées. De nouveaux motifs de cystéine uniques à cette famille ont également été découverts. En comparant avec des études similaires chez Arabidopsis, le sac embryonnaire de S. chacoense montre un transcriptome fortement divergent, particulièrement en en ce qui a trait à la catégorisation fonctionnelle des gènes et de la similarité entre les gènes orthologues. De plus,même si la glycosylation n’est pas requise lors du guidage mycropylaire du tube pollinique chez Arabidopsis, Torenia ou le maïs, des extraits d’ovules glycosylés de S. chacoense sont capables d’augmenter la capacité de guidage de 18%. Cette étude est donc la première à montrer une corrélation entre glycosylation et le guidage du tube pollinique par l’ovule. En complément à l’approche transcriptomique, une approche protéomique portant sur les protéine sécrétées par l’ovule (le secrétome) a été utilisée afin d’identifier des protéines impliquées dans l’interaction entre ovule et tube pollinique. Des exsudats d’ovules matures (capables d’attirer le tube pollinique) et d’ovules immatures (incapables d’attirer le tube pollinique) ont été récoltés en utilisant une nouvelle méthode d’extraction par gravité permettant de réduire efficacement les contaminants cytosoliques à moins de 1% de l’échantillon. Un total de 305 protéines sécrétées par les ovules (OSPs) ont été identifiées par spectrométrie de masse, parmi lesquelles 58% étaient spécifiques aux ovules lorsque comparées avec des données de protéines sécrétées par des tissus végétatifs. De plus, la sécrétion de 128 OSPs est augmentée dans les ovules matures par rapport aux ovules immatures. Ces 128 protéines sont donc considérées en tant que candidates potentiellement impliquées dans la maturation tardive de l’ovule et dans le guidage du tube pollinique. Cette étude a également montré que la maturation du sac embryonnaire du stade FG6 au stade FG7 influence le niveau de sécrétion de 44% du sécrétome total de l’ovule. De façon surprenante, la grande majorité (83%) de ces protéines n’est pas régulée au niveau de l’ARN, soulignant ainsi l’importance de cette approche dans l’étude du guidage du tube pollinique comme complément essentiel aux études transcriptomiques. Parmi tous les signaux sécrétés par l’ovule et reliés au guidage, obtenus à partir des approches transcriptomiques et protéomiques décrites ci-haut, nous avons spécifiquement évalué l’implication des CRPs dans le guidage du tube pollinique par l’ovule chez S. chacoense, vu l’implication de ce type de protéine dans les interactions pollen-pistil et le guidage du tube pollinique chez d’autres espèces. Au total, 28 CRPs étaient présentes dans les ovules capables d’attirer le tube pollinique tout en étant absentes dans les ovules incapables de l’attirer, et ce, soit au niveau de l’ARNm et/ou au niveau du sécrétome. De celles-ci, 17 CRPs ont été exprimées dans un système bactérien et purifiées en quantité suffisante pour tester le guidage. Alors que des exsudats d’ovules ont été utilisés avec succès pour attirer par chimiotactisme le tube pollinique, les candidats exprimés dans les bactéries n’ont quant à eux pas été capables d’attirer les tubes polliniques. Comme l’utilisation de systèmes d’expression hétérologue eucaryote peut permettre un meilleur repliement et une plus grande activité des protéines, les candidats restants seront de nouveau exprimés, cette fois dans un système de levure ainsi que dans un système végétal pour produire les peptides sécrétés. Ceux-ci seront ensuite utilisés lors d’essais fonctionnels pour évaluer leur capacité à guider les tubes polliniques et ainsi isoler les attractants chimiques responsable du guidage du tube pollinique chez les solanacées comme S. chacoense.

Studying the Human Gut Microbiota in the Trans-Omics Era - Focus on Metagenomics and Metabonomics

The human gut microbiota comprises a diverse microbial consortium closely co-evolved with the human genome and diet. The importance of the gut microbiota in regulating human health and disease has however been largely overlooked due to the inaccessibility of the intestinal habitat, the complexity of the gut microbiota itself and the fact that many of its members resist cultivation and are in fact new to science. However, with the emergence of 16S rRNA molecular tools and "post-genomics" high resolution technologies for examining microorganisms as they occur in nature without the need for prior laboratory culture, this limited view of the gut microbiota is rapidly changing. This review will discuss the application of molecular microbiological tools to study the human gut microbiota in a culture independent manner. Genomics or metagenomics approaches have a tremendous capability to generate compositional data and to measure the metabolic potential encoded by the combined genomes of the gut microbiota. Another post-genomics approach, metabonomics, has the capacity to measure the metabolic kinetic or flux of metabolites through an ecosystem at a particular point in time or over a time course. Metabonomics thus derives data on the function of the gut microbiota in situ and how it responds to different environmental stimuli e. g. substrates like prebiotics, antibiotics and other drugs and in response to disease. Recently these two culture independent, high resolution approaches have been combined into a single "transgenomic" approach which allows correlation of changes in metabolite profiles within human biofluids with microbiota compositional metagenomic data. Such approaches are providing novel insight into the composition, function and evolution of our gut microbiota.

Studying the Human Gut Microbiota in the Trans-Omics Era - Focus on Metagenomics and Metabonomics

The human gut microbiota comprises a diverse microbial consortium closely co-evolved with the human genome and diet. The importance of the gut microbiota in regulating human health and disease has however been largely overlooked due to the inaccessibility of the intestinal habitat, the complexity of the gut microbiota itself and the fact that many of its members resist cultivation and are in fact new to science. However, with the emergence of 16S rRNA molecular tools and "post-genomics" high resolution technologies for examining microorganisms as they occur in nature without the need for prior laboratory culture, this limited view of the gut microbiota is rapidly changing. This review will discuss the application of molecular microbiological tools to study the human gut microbiota in a culture independent manner. Genomics or metagenomics approaches have a tremendous capability to generate compositional data and to measure the metabolic potential encoded by the combined genomes of the gut microbiota. Another post-genomics approach, metabonomics, has the capacity to measure the metabolic kinetic or flux of metabolites through an ecosystem at a particular point in time or over a time course. Metabonomics thus derives data on the function of the gut microbiota in situ and how it responds to different environmental stimuli e.g. substrates like prebiotics, antibiotics and other drugs and in response to disease. Recently these two culture independent, high resolution approaches have been combined into a single "transgenomic" approach which allows correlation of changes in metabolite profiles within human biofluids with microbiota compositional metagenomic data. Such approaches are providing novel insight into the composition, function and evolution of our gut microbiota.

Control of fruit postharvest diseases by thermotherapy: understanding the mechanisms of action by –omics approaches

In recent years the hot water treatment (HW) represents an effective and safe approach for managing postharvest decay. This study reported the effect of an HW (60°C for 60 s and 45°C for 10 min) on brown rot and blue mould respectively. Peaches was found more thermotolerant compared to apple fruit, otherwise Penicillium expansum was more resistant to heat with respect to Monilinia spp. In semi-commercial and commercial trials, the inhibition of brown rot in naturally infected peaches was higher than 78% after 6 days at 0°C and 3 days at 20°C. Moreover, in laboratory trials a 100% disease incidence reduction was obtained by treating artificially infected peaches at 6-12 h after inoculation revealing a curative effect of HW. The expression levels of some genes were evaluated by qRT-PCR. Specifically, the cell wall genes (β-GAL, PL, PG, PME) showed a general decrease of expression level whereas PAL, CHI, HSP70 and ROS-scavenging genes were induced in treated peaches compared to the control ones. Contrarily, HW applied on artificially infected fruit before the inoculum was found to increase brown rot susceptibility. This aspect might be due to an increase of fruit VOCs emission as revealed by PTR-ToF-MS analysis. In addition a microarray experiment was conducted to analyze molecular mechanisms underneath the apple response to heat. Our results showed a largest amount of induced Heat shock proteins (HSPs), Heat shock cognate proteins (HSCs), Heat shock transcription factors (HSTFs) genes found at 1 and 4 hours from the treatment. Those genes required for the thermotolerance process could be involved in induced resistance response. The hypothesis was confirmed by 30% of blue mold disease reduction in artificially inoculated apple after 1 and 4 hours from the treatment. In order to improve peaches quality and disease management during storage, an innovative tool was also used: Da-meter.

One Hundred Years of Grain Omics: Identifying the Glutens That Feed the World.

Glutens, the storage proteins in wheat grains, are a major source of protein in human nutrition. The protein composition of wheat has therefore been an important focus of cereal research. Proteomic tools have been used to describe the genetic diversity of wheat germplasms from different origins at the level of polymorphisms in alleles encoding glutenin and gliadin, the two main proteins of gluten. More recently, proteomics has been used to understand the impact of specific gluten proteins on wheat quality. Here we review the impact of proteomics on the study of gluten proteins as it has evolved from fractionation and electrophoretic techniques to advanced mass spectrometry. In the postgenome era, proteomics is proving to be essential in the effort to identify and understand the interactions between different gluten proteins. This is helping to fill in gaps in our knowledge of how the technological quality of wheat is determined by the interaction between genotype and environment. We also collate information on the various storage protein alleles identified and their prevalence, which makes it possible to infer the effects of wheat selection on grain protein content. We conclude by reviewing the more recent use of transgenesis aimed at improving the quality of gluten.

Omics for Investigating Chitosan as an Antifungal and Gene Modulator

Chitosan is a biopolymer with a wide range of applications. The use of chitosan in clinical medicine to control infections by fungal pathogens such as Candida spp. is one of its most promising applications in view of the reduced number of antifungals available. Chitosan increases intracellular oxidative stress, then permeabilizes the plasma membrane of sensitive filamentous fungus Neurospora crassa and yeast. Transcriptomics reveals plasma membrane homeostasis and oxidative metabolism genes as key players in the response of fungi to chitosan. A lipase and a monosaccharide transporter, both inner plasma membrane proteins, and a glutathione transferase are main chitosan targets in N. crassa. Biocontrol fungi such as Pochonia chlamydosporia have a low content of polyunsaturated free fatty acids in their plasma membranes and are resistant to chitosan. Genome sequencing of P. chlamydosporia reveals a wide gene machinery to degrade and assimilate chitosan. Chitosan increases P. chlamydosporia sporulation and enhances parasitism of plant parasitic nematodes by the fungus. Omics studies allow understanding the mode of action of chitosan and help its development as an antifungal and gene modulator.

From omics and etics to policy and ethics: regulating evolution

A commentary on ELSI 2.0forgenomicsandsociety by Kaye,J.,Meslin,E.,Knoppers,B.,Juengst, E., Deschênes,M.,Cambon-Thomsen,A., etal. (2012). Science336, 673–674. doi: http://dx.doi.org/10.1126/science.1218015

Integrated Omics for the global mapping of biomolecules in LDL

Circulating low density lipoproteins (LDL) are thought to play a crucial role in the onset and development of atherosclerosis, though the detailed molecular mechanisms responsible for their biological effects remain controversial. The complexity of biomolecules (lipids, glycans and protein) and structural features (isoforms and chemical modifications) found in LDL particles hampers the complete understanding of the mechanism underlying its atherogenicity. For this reason the screening of LDL for features discriminative of a particular pathology in search of biomarkers is of high importance. Three major biomolecule classes (lipids, protein and glycans) in LDL particles were screened using mass spectrometry coupled to liquid chromatography. Dual-polarity screening resulted in good lipidome coverage, identifying over 300 lipid species from 12 lipid sub-classes. Multivariate analysis was used to investigate potential discriminators in the individual lipid sub-classes for different study groups (age, gender, pathology). Additionally, the high protein sequence coverage of ApoB-100 routinely achieved (≥70%) assisted in the search for protein modifications correlating to aging and pathology. The large size and complexity of the datasets required the use of chemometric methods (Partial Least Square-Discriminant Analysis, PLS-DA) for their analysis and for the identification of ions that discriminate between study groups. The peptide profile from enzymatically digested ApoB-100 can be correlated with the high structural complexity of lipids associated with ApoB-100 using exploratory data analysis. In addition, using targeted scanning modes, glycosylation sites within neutral and acidic sugar residues in ApoB-100 are also being explored. Together or individually, knowledge of the profiles and modifications of the major biomolecules in LDL particles will contribute towards an in-depth understanding, will help to map the structural features that contribute to the atherogenicity of LDL, and may allow identification of reliable, pathology-specific biomarkers. This research was supported by a Marie Curie Intra-European Fellowship within the 7th European Community Framework Program (IEF 255076). Work of A. Rudnitskaya was supported by Portuguese Science and Technology Foundation, through the European Social Fund (ESF) and "Programa Operacional Potencial Humano - POPH".

Using a bespoke 'Omics' approach to devise a flexible new way to control Fusarium in wheat.

2016

Challenges and Opportunities of Machine Learning for Clinical and Omics Data

Clinical and omics data are a promising field of application for machine learning techniques even though these methods are not yet systematically adopted in healthcare institutions. Despite artificial intelligence has proved successful in terms of prediction of pathologies or identification of their causes, the systematic adoption of these techniques still presents challenging issues due to the peculiarities of the analysed data. The aim of this thesis is to apply machine learning algorithms to both clinical and omics data sets in order to predict a patient's state of health and get better insights on the possible causes of the analysed diseases. In doing so, many of the arising issues when working with medical data will be discussed while possible solutions will be proposed to make machine learning provide feasible results and possibly become an effective and reliable support tool for healthcare systems.

Integrating omics in prion diseases as a model to explore the strain paradigm in neurodegenerative diseases

This project aims at deepening the understanding of the molecular basis of the phenotypic heterogeneity of prion diseases. Prion diseases represent the first and clearest example of “protein misfolding diseases”, that are all the neurodegenerative diseases caused by the accumulation of misfolded proteins in the central nervous system. In the field of protein misfolding diseases, the term “strain” describes the heterogeneity observed among the same disease in the clinical and pathologic progression, biochemical features of the aggregated protein, conformational memory and pattern of lesions. In this work, the two most common strains of Creutzfeldt-Jakob Disease (CJD), named MM1 and VV2, were analyzed. This thesis investigates the strain paradigm with the production of new multi omic data, and, on such data, appropriate computational analysis combining bioinformatics, data science and statistical approaches was performed. In this work, genomic and transcriptomic profiling allowed an improved characterization of the molecular features of the two most common strains of CJD, identifying multiple possible genetic contributors to the disease and finding several shared impaired pathways between the VV2 strain and Parkinson Disease. On the epigenomic level, the tridimensional chromatin folding in peripheral immune cells of CJD patients at onset and of healthy controls was investigated with Hi-C. While being the first application of this very advanced technology in prion diseases and one of the first in general in neurobiology, this work found a significant and diffuse loss of genomic interactions in immune cells of CJD patients at disease onset, particularly in the PRNP locus, suggesting a possible impairment of chromatin conformation in the disease. The results of this project represent a novelty in the state of the art in this field, both from a biomedical and technological point of view.

Cancer omics strategies for personalized treatments

The Consensus Molecular Subtypes (CMSs) classification stratifies colorectal cancer (CRC) into four well-defined molecular subgroups, providing incredible support to personalized medicine. Indeed, the huge inter-patient heterogeneity observed in CRC makes it difficult to define a therapeutic strategy from which every patient can benefit. Unfortunately, so far really few targetable biomarkers are known in the CRC setting, leading to an urgent need for new targeted therapies. Here we performed a bioinformatic meta-analysis over a cohort of 1700 CMS-stratified CRC patients, identifying a negative correlation between high levels of anaplastic lymphoma kinase (ALK) expression and relapse-free survival, exclusively in the CMS1 subtype. No correlation with ALK expression was pointed out in the other three subgroups. The association of ALK with CMS1 led to generate the hypothesis that ALK pharmacological inhibition may elicit therapeutic potential in this subgroup. Thus, we tested ALK inhibitors and an ALK-directed ADC on several CRC in vitro models, stratified according to the CMS classification as well as on CRC patient-derived organoids and mice. ALK interception strongly inhibited CMS1-cells, organoids, and tumor proliferation and was responsible for the dampening of ALK activation along with the downstream. Mechanistically, we found that CMS1 cells display several mRNA copies of both ALK and ALKAL2 ligand, suggesting a role for ALK abundance in the differential response to its inhibition. Collectively, these findings support the hypothesis that ALK may represent an attractive target for CMS1 colorectal cancer therapy.