The genomic basis of the Streptococcus thermophilus health-promoting properties.

BACKGROUND: Streptococcus thermophilus is a Gram-positive bacterium widely used as starter in the dairy industry as well as in many traditional fermented products. In addition to its technological importance, it has also gained interest in recent years as beneficial bacterium due to human health-promoting functionalities. The objective of this study was to inventory the main health-promoting properties of S. thermophilus and to study their intra-species diversity at the genomic and genetic level within a collection of representative strains. RESULTS: In this study various health-related functions were analyzed at the genome level from 79 genome sequences of strains isolated over a long time period from diverse products and different geographic locations. While some functions are widely conserved among isolates (e.g., degradation of lactose, folate production) suggesting their central physiological and ecological role for the species, others including the tagatose-6-phosphate pathway involved in the catabolism of galactose, and the production of bioactive peptides and gamma-aminobutyric acid are strain-specific. Most of these strain-specific health-promoting properties seems to have been acquired via horizontal gene transfer events. The genetic basis for the phenotypic diversity between strains for some health related traits have also been investigated. For instance, substitutions in the galK promoter region correlate with the ability of some strains to catabolize galactose via the Leloir pathway. Finally, the low occurrence in S. thermophilus genomes of genes coding for biogenic amine production and antibiotic resistance is also a contributing factor to its safety status. CONCLUSIONS: The natural intra-species diversity of S. thermophilus, therefore, represents an interesting source for innovation in the field of fermented products enriched for healthy components that can be exploited to improve human health. A better knowledge of the health-promoting properties and their genomic and genetic diversity within the species may facilitate the selection and application of strains for specific biotechnological and human health-promoting purpose. Moreover, by pointing out that a substantial part of its functional potential still defies us, our work opens the way to uncover additional health-related functions through the intra-species diversity exploration of S. thermophilus by comparative genomics approaches.

De novo clustering of long reads by gene from transcriptomics data.

Long-read sequencing currently provides sequences of several thousand base pairs. It is therefore possible to obtain complete transcripts, offering an unprecedented vision of the cellular transcriptome. However the literature lacks tools for de novo clustering of such data, in particular for Oxford Nanopore Technologies reads, because of the inherent high error rate compared to short reads. Our goal is to process reads from whole transcriptome sequencing data accurately and without a reference genome in order to reliably group reads coming from the same gene. This de novo approach is therefore particularly suitable for non-model species, but can also serve as a useful pre-processing step to improve read mapping. Our contribution both proposes a new algorithm adapted to clustering of reads by gene and a practical and free access tool that allows to scale the complete processing of eukaryotic transcriptomes. We sequenced a mouse RNA sample using the MinION device. This dataset is used to compare our solution to other algorithms used in the context of biological clustering. We demonstrate that it is the best approach for transcriptomics long reads. When a reference is available to enable mapping, we show that it stands as an alternative method that predicts complementary clusters.

Formalizing and enriching phenotype signatures using Boolean networks.

In order to predict the behavior of a biological system, one common approach is to perform a simulation on a dynamic model. Boolean networks allow to analyze the qualitative aspects of the model by identifying its steady states and attractors. Each of them, when possible, is associated with a phenotype which conveys a biological interpretation. Phenotypes are characterized by their signatures, provided by domain experts. The number of steady states tends to increase with the network size and the number of simulation conditions, which makes the biological interpretation difficult. As a first step, we explore the use of Formal Concept Analysis as a symbolic bi-clustering technics to classify and sort the steady states of a Boolean network according to biological signatures based on the hierarchy of the roles the network components play in the phenotypes. FCA generates a lattice structure describing the dependencies between proteins in the signature and steady-states of the Boolean network. We use this lattice (i) to enrich the biological signatures according to the dependencies carried by the network dynamics, (ii) to identify variants to the phenotypes and (iii) to characterize hybrid phenotypes. We applied our approach on a T helper lymphocyte (Th) differentiation network with a set of signatures corresponding to the sub-types of Th. Our method generated the same classification as a manual analysis performed by experts in the field, and was also able to work under extended simulation conditions. This led to the identification and prediction of a new hybrid sub-type later confirmed by the literature.

Fully in vitro iterative construction of a 24 kb-long artificial DNA sequence to store digital information.

In the absence of a DNA template, the ab initio production of long double-stranded DNA molecules of predefined sequences is particularly challenging. The DNA synthesis step remains a bottleneck for many applications such as functional assessment of ancestral genes, analysis of alternative splicing or DNA-based data storage. In this report we propose a fully in vitro protocol to generate very long double-stranded DNA molecules starting from commercially available short DNA blocks in less than 3 days using Golden Gate assembly. This innovative application allowed us to streamline the process to produce a 24 kb-long DNA molecule storing part of the Declaration of the Rights of Man and of the Citizen of 1789 . The DNA molecule produced can be readily cloned into a suitable host/vector system for amplification and selection.

Evaluation of an electronic nose for the early detection of organic overload of anaerobic digesters.

This study aimed at analysing the utilization of an electronic nose (e-nose) to serve as a specific monitoring tool for anaerobic digestion process, especially for detecting organic overload. An array of non specific metal oxide semiconductor gas sensors were used to detect process faults due to organic overload events in twelve 1.8-L anaerobic semi-continuous reactors. Three different load strategies were followed: (1) a cautious organic load (1.3 gVS L(-1) day(-1)); (2) an increasing load strategy (1.3-5.3 gVS L(-1) day(-1)) and (3) a cautious organic load with load pulses of up to 12 gVS L(-1) day(-1). A first monitoring campaign was conducted with three different substrates: sucrose, maize oil and a mix of sucrose/oil during 60 days. The second campaign was run with dry sugar beet pulp for 45 days. Hotelling's T(2) value and upper control limit to a reference set of digesters fed with a cautious OLR (1.3 gVS L(-1) day(-1)) was used as indirect state variable of the reactors. Overload situations were identified by the e-nose apparatus with Hotelling's T(2) values at least four times higher in magnitude than the upper control limit of 23.7. These results confirmed that the e-nose technology appeared promising for online detection of process imbalances in the domain of anaerobic digestion.

Finding and Characterizing Repeats in Plant Genomes.

Plant genomes contain a particularly high proportion of repeated structures of various types. This chapter proposes a guided tour of the available software that can help biologists to scan automatically for these repeats in sequence data or check hypothetical models intended to characterize their structures. Since transposable elements (TEs) are a major source of repeats in plants, many methods have been used or developed for this broad class of sequences. They are representative of the range of tools available for other classes of repeats and we have provided two sections on this topic (for the analysis of genomes or directly of sequenced reads), as well as a selection of the main existing software. It may be hard to keep up with the profusion of proposals in this dynamic field and the rest of the chapter is devoted to the foundations of an efficient search for repeats and more complex patterns. We first introduce the key concepts of the art of indexing and mapping or querying sequences. We end the chapter with the more prospective issue of building models of repeat families. We present the Machine Learning approach first, seeking to build predictors automatically for some families of ET, from a set of sequences known to belong to this family. A second approach, the linguistic (or syntactic) approach, allows biologists to describe themselves and check the validity of models of their favorite repeat family.

Apple polyphenoloxidase inactivation during heating in the presence of ascorbic acid and chlorogenic acid.

It was recently reported that during osmotic dehydration of ascorbic acid (AA)-treated apple cubes, losses in AA and phenolics could partly arise from enzymatic oxidation, provided polyphenoloxidase (PPO) was still active under the processing conditions. To determine the impact of dehydration temperatures on PPO action, as well as chemical and enzymatic oxidation reactions, apple PPO inactivation alone or with AA (1mM) and/or chlorogenic acid (CG, 3mM), as well as AA and CG levels evolution, during heating of the model solutions at 45 and 60°C were investigated. At pH 3.8, PPO was still functional, keeping 61 and 4% residual activity after 2h of heating at 45 and 60°C, respectively. The combined treatment of heating and AA was more effective in reducing PPO activity, while incubation at 60°C with AA and CG minimised the losses of PPO activity. CG remained stable during heating, even in the presence of AA which, in turn, was more affected by heating. Thus, during heating, provided PPO remained active with enough available O2 in the model systems, CG oxidation and coupled oxidoreduction with AA could readily develop.

Sequencing DNA with nanopores: Troubles and biases.

Oxford Nanopore Technologies' (ONT) long read sequencers offer access to longer DNA fragments than previous sequencer generations, at the cost of a higher error rate. While many papers have studied read correction methods, few have addressed the detailed characterization of observed errors, a task complicated by frequent changes in chemistry and software in ONT technology. The MinION sequencer is now more stable and this paper proposes an up-to-date view of its error landscape, using the most mature flowcell and basecaller. We studied Nanopore sequencing error biases on both bacterial and human DNA reads. We found that, although Nanopore sequencing is expected not to suffer from GC bias, it is a crucial parameter with respect to errors. In particular, low-GC reads have fewer errors than high-GC reads (about 6% and 8% respectively). The error profile for homopolymeric regions or regions with short repeats, the source of about half of all sequencing errors, also depends on the GC rate and mainly shows deletions, although there are some reads with long insertions. Another interesting finding is that the quality measure, although over-estimated, offers valuable information to predict the error rate as well as the abundance of reads. We supplemented this study with an analysis of a rapeseed RNA read set and shown a higher level of errors with a higher level of deletion in these data. Finally, we have implemented an open source pipeline for long-term monitoring of the error profile, which enables users to easily compute various analysis presented in this work, including for future developments of the sequencing device. Overall, we hope this work will provide a basis for the design of better error-correction methods.

Identification of isolated or mixed strains from long reads: a challenge met on Streptococcus thermophilus using a MinION sequencer.

This study aimed to provide efficient recognition of bacterial strains on personal computers from MinION (Nanopore) long read data. Thanks to the fall in sequencing costs, the identification of bacteria can now proceed by whole genome sequencing. MinION is a fast, but highly error-prone sequencing device and it is a challenge to successfully identify the strain content of unknown simple or complex microbial samples. It is heavily constrained by memory management and fast access to the read and genome fragments. Our strategy involves three steps: indexing of known genomic sequences for a given or several bacterial species; a request process to assign a read to a strain by matching it to the closest reference genomes; and a final step looking for a minimum set of strains that best explains the observed reads. We have applied our method, called ORI, on 77 strains of Streptococcus thermophilus. We worked on several genomic distances and obtained a detailed classification of the strains, together with a criterion that allows merging of what we termed 'sibling' strains, only separated by a few mutations. Overall, isolated strains can be safely recognized from MinION data. For mixtures of several non-sibling strains, results depend on strain abundance.

ModuleOrganizer: detecting modules in families of transposable elements.

BACKGROUND: Most known eukaryotic genomes contain mobile copied elements called transposable elements. In some species, these elements account for the majority of the genome sequence. They have been subject to many mutations and other genomic events (copies, deletions, captures) during transposition. The identification of these transformations remains a difficult issue. The study of families of transposable elements is generally founded on a multiple alignment of their sequences, a critical step that is adapted to transposons containing mostly localized nucleotide mutations. Many transposons that have lost their protein-coding capacity have undergone more complex rearrangements, needing the development of more complex methods in order to characterize the architecture of sequence variations. RESULTS: In this study, we introduce the concept of a transposable element module, a flexible motif present in at least two sequences of a family of transposable elements and built on a succession of maximal repeats. The paper proposes an assembly method working on a set of exact maximal repeats of a set of sequences to create such modules. It results in a graphical view of sequences segmented into modules, a representation that allows a flexible analysis of the transformations that have occurred between them. We have chosen as a demonstration data set in depth analysis of the transposable element Foldback in Drosophila melanogaster. Comparison with multiple alignment methods shows that our method is more sensitive for highly variable sequences. The study of this family and the two other families AtREP21 and SIDER2 reveals new copies of very different sizes and various combinations of modules which show the potential of our method. CONCLUSIONS: ModuleOrganizer is available on the Genouest bioinformatics center at http://moduleorganizer.genouest.org.

Bioinformatic prediction, deep sequencing of microRNAs and expression analysis during phenotypic plasticity in the pea aphid, Acyrthosiphon pisum.

BACKGROUND: Post-transcriptional regulation in eukaryotes can be operated through microRNA (miRNAs) mediated gene silencing. MiRNAs are small (18-25 nucleotides) non-coding RNAs that play crucial role in regulation of gene expression in eukaryotes. In insects, miRNAs have been shown to be involved in multiple mechanisms such as embryonic development, tissue differentiation, metamorphosis or circadian rhythm. Insect miRNAs have been identified in different species belonging to five orders: Coleoptera, Diptera, Hymenoptera, Lepidoptera and Orthoptera. RESULTS: We developed high throughput Solexa sequencing and bioinformatic analyses of the genome of the pea aphid Acyrthosiphon pisum in order to identify the first miRNAs from a hemipteran insect. By combining these methods we identified 149 miRNAs including 55 conserved and 94 new miRNAs. Moreover, we investigated the regulation of these miRNAs in different alternative morphs of the pea aphid by analysing the expression of miRNAs across the switch of reproduction mode. Pea aphid microRNA sequences have been posted to miRBase: http://microrna.sanger.ac.uk/sequences/. CONCLUSIONS: Our study has identified candidates as putative regulators involved in reproductive polyphenism in aphids and opens new avenues for further functional analyses.

CRISPI: a CRISPR interactive database.

SUMMARY: The CRISPR genomic structures (Clustered Regularly Interspaced Short Palindromic Repeats) form a family of repeats that is largely present in archaea and frequent in bacteria. On the basis of a formal model of CRISPR using very few parameters, a systematic study of all their occurrences in all available genomes of Archaea and Bacteria has been carried out. This has resulted in a relational database, CRISPI, which also includes a complete repertory of associated CRISPR-associated genes (CAS). A user-friendly web interface with many graphical tools and functions allows users to extract results, find CRISPR in personal sequences or calculate sequence similarity with spacers. AVAILABILITY: CRISPI free access at http://crispi.genouest.org CONTACT: croussea@irisa.fr; jnicolas@irisa.fr

Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift.

Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover. This phenomenon, here formally defined as "metabolic pathway drift," is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a methodological approach to formalize the logical reasoning necessary to infer reactions and molecular structures, abstracting molecular transformations based on previous biochemical knowledge.

Model-based identification of Helitrons results in a new classification of their families in Arabidopsis thaliana.

Helitrons are a class of prolific transposable elements in the Arabidopsis thaliana genome. Although 37 families were identified after the recent discovery of Helitrons, no systematic classification is available because of the high variability of helitronic sequences. Since transposition proteins are assumed to interact with Helitron termini, a Helitron model was formalized based on terminus characterization in order to carry out an exhaustive analysis of all possible combinations of the pairs of termini present. This combinatorics approach resulted in the discovery of a number of new Helitron elements corresponding to termini associations from distinct previously-described Helitron families. The occurrence matrix of termini combinations yielded a structure that revealed clusters of Helitron families.

Domain organization within repeated DNA sequences: application to the study of a family of transposable elements.

MOTIVATION: The analysis of repeated elements in genomes is a fascinating domain of research that is lacking relevant tools for transposable elements (TEs), the most complex ones. The dynamics of TEs, which provides the main mechanism of mutation in some genomes, is an essential component of genome evolution. In this study we introduce a new concept of domain, a segmentation unit useful for describing the architecture of different copies of TEs. Our method extracts occurrences of a terminus-defined family of TEs, aligns the sequences, finds the domains in the alignment and searches the distribution of each domain in sequences. After a classification step relative to the presence or the absence of domains, the method results in a graphical view of sequences segmented into domains. RESULTS: Analysis of the new non-autonomous TE AtREP21 in the model plant Arabidopsis thaliana reveals copies of very different sizes and various combinations of domains which show the potential of our method. AVAILABILITY: DomainOrganizer web page is available at www.irisa.fr/symbiose/DomainOrganizer/.

Inhibition of polyphenoloxidase activity by mixtures of heated cysteine derivatives with carbonyl compounds.

It had previously been shown that soluble Maillard reaction products (MRP) made from thiol compounds and glucose or fructose contained powerful inhibitors of various fruit and vegetable polyphenoloxidase (PPO) activity. In MRP from cysteine and glucose, the amount of hydroxymethylfurfural (HMF) formed increased with the increase in glucose concentration (0-1 M), particularly under acidic (pH 2) conditions. Using model mixtures containing a preheated cysteine-derived compound and a carbonyl component, especially HMF, furfural and benzaldehyde, we showed that the neoformed compounds produced exhibited a stronger inhibitory potency toward PPO activity of eggplant, apple, and mushroom than former MRP. Optimal reaction conditions for the formation of inhibitory compounds when HMF reacted with preheated cysteine were investigated. It was found that a reactants molar ratio of 1:1 and a reaction time exceeding 1 h were the most efficient reaction conditions to generate inhibitory compounds. The stability of the newly formed products, evaluated during storage, showed that their inhibitory potency was globally kept at 4, 21, and 37 degrees C for 72 h but was unstable when stored at -20 degrees C and lost when exposed to UV radiations for 24 h.

Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks.

BACKGROUND: The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving access to a global view of cell functioning. The analysis of metabolic networks may be carried out by simply considering the architecture of the reaction network or by taking into account the stoichiometry of reactions. In both approaches, this analysis is generally centered on the outcome of the network and considers all metabolic compounds to be equivalent in this respect. As in the case of genes and reactions, about which the concept of essentiality has been developed, it seems, however, that some metabolites play crucial roles in system responses, due to the cell structure or the internal wiring of the metabolic network. RESULTS: We propose a classification of metabolic compounds according to their capacity to influence the activation of targeted functions (generally the growth phenotype) in a cell. We generalize the concept of essentiality to metabolites and introduce the concept of the phenotypic essential metabolite (PEM) which influences the growth phenotype according to sustainability, producibility or optimal-efficiency criteria. We have developed and made available a tool, Conquests, which implements a method combining graph-based and flux-based analysis, two approaches that are usually considered separately. The identification of PEMs is made effective by using a logical programming approach. CONCLUSION: The exhaustive study of phenotypic essential metabolites in six genome-scale metabolic models suggests that the combination and the comparison of graph, stoichiometry and optimal flux-based criteria allows some features of the metabolic network functionality to be deciphered by focusing on a small number of compounds. By considering the best combination of both graph-based and flux-based techniques, the Conquests python package advocates for a broader use of these compounds both to facilitate network curation and to promote a precise understanding of metabolic phenotype.

Browsing repeats in genomes: Pygram and an application to non-coding region analysis.

BACKGROUND: A large number of studies on genome sequences have revealed the major role played by repeated sequences in the structure, function, dynamics and evolution of genomes. In-depth repeat analysis requires specialized methods, including visualization techniques, to achieve optimum exploratory power. RESULTS: This article presents Pygram, a new visualization application for investigating the organization of repeated sequences in complete genome sequences. The application projects data from a repeat index file on the analysed sequences, and by combining this principle with a query system, is capable of locating repeated sequences with specific properties. In short, Pygram provides an efficient, graphical browser for studying repeats. Implementation of the complete configuration is illustrated in an analysis of CRISPR structures in Archaea genomes and the detection of horizontal transfer between Archaea and Viruses. CONCLUSION: By proposing a new visualization environment to analyse repeated sequences, this application aims to increase the efficiency of laboratories involved in investigating repeat organization in single genomes or across several genomes.

Use of experimental design methodology to prepare Maillard reaction products from glucose and cysteine inhibitors of polyphenol oxidase from eggplant (Solanum melongena).

Polyphenol oxidase (PPO) from eggplant was extracted and partially purified by a two-step fractionation-precipitation using ammonium sulfate and phenylsepharose hydrophobic interaction chromatography. The eggplant PPO extract was characterized concerning its kinetic properties. Optimal conditions to obtain Maillard reaction products (MRPs) with a maximal inhibitory potency (IP) toward PPO activity were determined using the surface response methodology and a four-factor and five-level experimental design. The MRPs were prepared from cysteine (0.25 M) and glucose (0-1 M), at several initial pH values (2-6) and at differing heating times (3-19 h) and temperatures (95-115 degrees C). The maximal IP was obtained after heating a model system of glucose/cysteine (1/0.25 M) at pH 2 for 3 h 20 min at 115 degrees C. The soluble part of this MRP, called MRP(IPmax), was a noncompetitive inhibitor toward eggplant PPO. The IP of MRP(IPmax) on PPO activity was very potent as compared to that displayed by benzoic, p-coumaric, and t-cinnamic acids, as well as sorbic acid and 4-hexylresorcinol. The activity of preincubated PPO at 0 degrees C with MRP(IPmax) was only slightly restored after dialysis or gel filtration.

Finding and Characterizing Repeats in Plant Genomes.

Plant genomes contain a particularly high proportion of repeated structures of various types. This chapter proposes a guided tour of available software that can help biologists to look for these repeats and check some hypothetical models intended to characterize their structures. Since transposable elements are a major source of repeats in plants, many methods have been used or developed for this large class of sequences. They are representative of the range of tools available for other classes of repeats and we have provided a whole section on this topic as well as a selection of the main existing software. In order to better understand how they work and how repeats may be efficiently found in genomes, it is necessary to look at the technical issues involved in the large-scale search of these structures. Indeed, it may be hard to keep up with the profusion of proposals in this dynamic field and the rest of the chapter is devoted to the foundations of the search for repeats and more complex patterns. The second section introduces the key concepts that are useful for understanding the current state of the art in playing with words, applied to genomic sequences. This can be seen as the first stage of a very general approach called linguistic analysis that is interested in the analysis of natural or artificial texts. Words, the lexical level, correspond to simple repeated entities in texts or strings. In fact, biologists need to represent more complex entities where a repeat family is built on more abstract structures, including direct or inverted small repeats, motifs, composition constraints as well as ordering and distance constraints between these elementary blocks. In terms of linguistics, this corresponds to the syntactic level of a language. The last section introduces concepts and practical tools that can be used to reach this syntactic level in biological sequence analysis.