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.

How to sequence and annotate insect mitochondrial genomes for systematic and comparative genomics research

Over the past decade the mitochondrial (mt) genome has become the most widely used genomic resource available for systematic entomology. While the availability of other types of ‘–omics’ data – in particular transcriptomes – is increasing rapidly, mt genomes are still vastly cheaper to sequence and are far less demanding of high quality templates. Furthermore, almost all other ‘–omics’ approaches also sequence the mt genome, and so it can form a bridge between legacy and contemporary datasets. Mitochondrial genomes have now been sequenced for all insect orders, and in many instances representatives of each major lineage within orders (suborders, series or superfamilies depending on the group). They have also been applied to systematic questions at all taxonomic scales from resolving interordinal relationships (e.g. Cameron et al., 2009; Wan et al., 2012; Wang et al., 2012), through many intraordinal (e.g. Dowton et al., 2009; Timmermans et al., 2010; Zhao et al. 2013a) and family-level studies (e.g. Nelson et al., 2012; Zhao et al., 2013b) to population/biogeographic studies (e.g. Ma et al., 2012). Methodological issues around the use of mt genomes in insect phylogenetic analyses and the empirical results found to date have recently been reviewed by Cameron (2014), yet the technical aspects of sequencing and annotating mt genomes were not covered. Most papers which generate new mt genome report their methods in a simplified form which can be difficult to replicate without specific knowledge of the field. Published studies utilize a sufficiently wide range of approaches, usually without justification for the one chosen, that confusion about commonly used jargon such as ‘long PCR’ and ‘primer walking’ could be a serious barrier to entry. Furthermore, sequenced mt genomes have been annotated (gene locations defined) to wildly varying standards and improving data quality through consistent annotation procedures will benefit all downstream users of these datasets. The aims of this review are therefore to: 1. Describe in detail the various sequencing methods used on insect mt genomes; 2. Explore the strengths/weakness of different approaches; 3. Outline the procedures and software used for insect mt genome annotation, and; 4. Highlight quality control steps used for new annotations, and to improve the re-annotation of previously sequenced mt genomes used in systematic or comparative research.

Facing Hymenoptera venom allergy: from natural to recombinant allergens

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

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.

Filling in gaps of Drosophila melanogaster urate degradation metabolic pathway using metabolomics approaches: towards the core metabolome of the fruit fly

The primary goal of systems biology is to integrate complex omics data, and data obtained from traditional experimental studies in order to provide a holistic understanding of organismal function. One way of achieving this aim is to generate genome-scale metabolic models (GEMs), which contain information on all metabolites, enzyme-coding genes, and biochemical reactions in a biological system. Drosophila melanogaster GEM has not been reconstructed to date. Constraint-free genome-wide metabolic model of the fruit fly has been reconstructed in our lab, identifying gaps, where no enzyme was identified and metabolites were either only produced or consume. The main focus of the work presented in this thesis was to develop a pipeline for efficient gap filling using metabolomics approaches combined with standard reverse genetics methods, using 5-hydroxyisourate hydrolase (5-HIUH) as an example. 5-HIUH plays a role in urate degradation pathway. Inability to degrade urate can lead to inborn errors of metabolism (IEMs) in humans, including hyperuricemia. Based on sequence analysis Drosophila CG30016 gene was hypothesised to encode 5- HIUH. CG30016 knockout flies were examined to identify Malpighian tubules phenotype, and shortened lifespan might reflect kidney disorders in hyperuricemia in humans. Moreover, LC-MS analysis of mutant tubules revealed that CG30016 is involved in purine metabolism, and specifically urate degradation pathway. However, the exact role of the gene has not been identified, and the complete method for gap filling has not been developed. Nevertheless, thanks to the work presented here, we are a step closer towards the development of a gap-filling pipeline in Drosophila melanogaster GEM. Importantly, the areas that require further optimisation were identified and are the focus of future research. Moreover, LC-MS analysis confirmed that tubules rather than the whole fly were more suitable for metabolomics analysis of purine metabolism. Previously, Dow/Davies lab has generated the most complete tissue-specific transcriptomic atlas for Drosophila – FlyAtlas.org, which provides data on gene expression across multiple tissues of adult fly and larva. FlyAtlas revealed that transcripts of many genes are enriched in specific Drosophila tissues, and that it is possible to deduce the functions of individual tissues within the fly. Based on FlyAtlas data, it has become clear that the fly (like other metazoan species) must be considered as a set of tissues, each 2 with its own distinct transcriptional and functional profile. Moreover, it revealed that for about 30% of the genome, reverse genetic methods (i.e. mutation in an unknown gene followed by observation of phenotype) are only useful if specific tissues are investigated. Based on the FlyAtlas findings, we aimed to build a primary tissue-specific metabolome of the fruit fly, in order to establish whether different Drosophila tissues have different metabolomes and if they correspond to tissue-specific transcriptome of the fruit fly (FlyAtlas.org). Different fly tissues have been dissected and their metabolome elucidated using LC-MS. The results confirmed that tissue metabolomes differ significantly from each other and from the whole fly, and that some of these differences can be correlated to the tissue function. The results illustrate the need to study individual tissues as well as the whole organism. It is clear that some metabolites that play an important role in a given tissue might not be detected in the whole fly sample because their abundance is much lower in comparison to other metabolites present in all tissues, which prevent the detection of the tissue-specific compound.