Holistic understanding of trimethoprim resistance in Streptococcus pneumoniae using an integrative approach of genome-wide association study, resistance reconstruction, and machine learning.

Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to investigate trimethoprim (TMP) resistance in the key pathogen Streptococcus pneumoniae. We explored a collection of 662 S. pneumoniae genomes by conducting a genome-wide association study (GWAS), followed by functional validation using resistance reconstruction experiments, combined with machine learning (ML) approaches to predict TMP minimum inhibitory concentration (MIC). Our study showed that multiple additive mutations in the folA and sulA loci are responsible for TMP non-susceptibility in S. pneumoniae and can be used as key features to build ML models for digital MIC prediction, reaching an average accuracy within ±1 twofold dilution factor of 86.3%. Our roadmap of in silico analysis-wet-lab validation-diagnostic tool building could be adapted to explore AMR in other combinations of bacteria-antibiotic. IMPORTANCE: In the age of next-generation sequencing (NGS), while data-driven methods such as genome-wide association study (GWAS) and machine learning (ML) excel at finding patterns, functional validation can be challenging due to the high numbers of candidate variants. We designed an integrative approach combining a GWAS on S. pneumoniae clinical isolates, followed by whole-genome transformation coupled with NGS to functionally characterize a large set of GWAS candidates. Our study validated several phenotypic folA mutations beyond the standard Ile100Leu mutation, and showed that the overexpression of the sulA locus produces trimethoprim (TMP) resistance in Streptococcus pneumoniae. These validated loci, when used to build ML models, were found to be the best inputs for predicting TMP minimal inhibitory concentrations. Integrative approaches can bridge the genotype-phenotype gap by biological insights that can be incorporated in ML models for accurate prediction of drug susceptibility.

Systemic Convergent Multitarget Interactions of Plant Polyphenols Revealed by Affinity-Based Protein Profiling of Bone Cells Using C-Glucosidic Vescal(ag)in-Bearing Chemoproteomic Probes.

The ellagitannins vescalagin and vescalin, known as actin-dependent inhibitors of osteoclastic bone resorption, were mounted onto chemical probes to explore their interactions with bone cell proteins by means of affinity-based chemoproteomics and bioinformatics. The chemical reactivity of the pyrogallol units of these polyphenols toward oxidation into electrophilic ortho-quinones was exploited using NaIO4 to promote the covalent capture of target proteins, notably those expressed at lower abundance and those interacting with polyphenols at low-to-moderate levels of affinity. Different assays revealed the multitarget nature of both ellagitannins, with 100-370 statistically significant proteins captured by their corresponding probes. A much higher number of proteins were captured from osteoclasts than from osteoblasts. Bioinformatic analyses unveiled a preference for the capture of proteins having phosphorylated ligands and GTPase regulators and enabled the identification of 33 potential target proteins with systemic relevance to osteoclast differentiation and activity, as well as to the regulation of actin dynamics.

Synthesis of Flavonol-Bearing Probes for Chemoproteomic and Bioinformatic Analyses of Asteraceae Petals in Search of Novel Flavonoid Enzymes.

This study aimed at searching for the enzymes that are responsible for the higher hydroxylation of flavonols serving as UV-honey guides for pollinating insects on the petals of Asteraceae flowers. To achieve this aim, an affinity-based chemical proteomic approach was developed by relying on the use of quercetin-bearing biotinylated probes, which were thus designed and synthesized to selectively and covalently capture relevant flavonoid enzymes. Proteomic and bioinformatic analyses of proteins captured from petal microsomes of two Asteraceae species (Rudbeckia hirta and Tagetes erecta) revealed the presence of two flavonol 6-hydroxylases and several additional not fully characterized proteins as candidates for the identification of novel flavonol 8-hydroxylases, as well as relevant flavonol methyl- and glycosyltransferases. Generally speaking, this substrate-based proteome profiling methodology constitutes a powerful tool for the search for unknown (flavonoid) enzymes in plant protein extracts.

Targeting CAMKK2 and SOC Channels as a Novel Therapeutic Approach for Sensitizing Acute Promyelocytic Leukemia Cells to All-Trans Retinoic Acid.

Calcium ions (Ca2+) play important and diverse roles in the regulation of autophagy, cell death and differentiation. Here, we investigated the impact of Ca2+ in regulating acute promyelocytic leukemia (APL) cell fate in response to the anti-cancer agent all-trans retinoic acid (ATRA). We observed that ATRA promotes calcium entry through store-operated calcium (SOC) channels into acute promyelocytic leukemia (APL) cells. This response is associated with changes in the expression profiles of ORAI1 and STIM1, two proteins involved in SOC channels activation, as well as with a significant upregulation of several key proteins associated to calcium signaling. Moreover, ATRA treatment of APL cells led to a significant activation of calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2) and its downstream effector AMP-activated protein kinase (AMPK), linking Ca2+ signaling to autophagy. Pharmacological inhibition of SOC channels and CAMKK2 enhanced ATRA-induced cell differentiation and death. Altogether, our results unravel an ATRA-elicited signaling pathway that involves SOC channels/CAMKK2 activation, induction of autophagy, inhibition of cellular differentiation and suppression of cell death. We suggest that SOC channels and CAMKK2 may constitute novel drug targets for potentiating the anti-cancer effect of ATRA in APL patients.

TGFß promotes low IL10-producing ILC2 with profibrotic ability involved in skin fibrosis in systemic sclerosis.

OBJECTIVE: Innate lymphoid cells-2 (ILC2) were shown to be involved in the development of lung or hepatic fibrosis. We sought to explore the functional and phenotypic heterogeneity of ILC2 in skin fibrosis within systemic sclerosis (SSc). METHODS: Blood samples and skin biopsies from healthy donor or patients with SSc were analysed by immunostaining techniques. The fibrotic role of sorted ILC2 was studied in vitro on dermal fibroblast and further explored by transcriptomic approach. Finally, the efficacy of a new treatment against fibrosis was assessed with a mouse model of SSc. RESULTS: We found that ILC2 numbers were increased in the skin of patients with SSc and correlated with the extent of skin fibrosis. In SSc skin, KLRG1- ILC2 (natural ILC2) were dominating over KLRG1+ ILC2 (inflammatory ILC2). The cytokine transforming growth factor-ß (TGFß), whose activity is increased in SSc, favoured the expansion of KLRG1- ILC2 simultaneously decreasing their production of interleukin 10 (IL10), which regulates negatively collagen production by dermal fibroblasts. TGFß-stimulated ILC2 also increased myofibroblast differentiation. Thus, human KLRG1- ILC2 had an enhanced profibrotic activity. In a mouse model of SSc, therapeutic intervention-combining pirfenidone with the administration of IL10 was required to reduce the numbers of skin infiltrating ILC2, enhancing their expression of KLRG1 and strongly alleviating skin fibrosis. CONCLUSION: Our results demonstrate a novel role for natural ILC2 and highlight their inter-relationships with TGFß and IL10 in the development of skin fibrosis, thereby opening up new therapeutic approaches in SSc.

Population genomics of apricots unravels domestication history and adaptive events.

Among crop fruit trees, the apricot (Prunus armeniaca) provides an excellent model to study divergence and adaptation processes. Here, we obtain nearly 600 Armeniaca apricot genomes and four high-quality assemblies anchored on genetic maps. Chinese and European apricots form two differentiated gene pools with high genetic diversity, resulting from independent domestication events from distinct wild Central Asian populations, and with subsequent gene flow. A relatively low proportion of the genome is affected by selection. Different genomic regions show footprints of selection in European and Chinese cultivated apricots, despite convergent phenotypic traits, with predicted functions in both groups involved in the perennial life cycle, fruit quality and disease resistance. Selection footprints appear more abundant in European apricots, with a hotspot on chromosome 4, while admixture is more pervasive in Chinese cultivated apricots. Our study provides clues to the biology of selected traits and targets for fruit tree research and breeding.

Novel analytical methods to interpret large sequencing data from small sample sizes.

BACKGROUND: Targeted therapies have greatly improved cancer patient prognosis. For instance, chronic myeloid leukemia is now well treated with imatinib, a tyrosine kinase inhibitor. Around 80% of the patients reach complete remission. However, despite its great efficiency, some patients are resistant to the drug. This heterogeneity in the response might be associated with pharmacokinetic parameters, varying between individuals because of genetic variants. To assess this issue, next-generation sequencing of large panels of genes can be performed from patient samples. However, the common problem in pharmacogenetic studies is the availability of samples, often limited. In the end, large sequencing data are obtained from small sample sizes; therefore, classical statistical analyses cannot be applied to identify interesting targets. To overcome this concern, here, we described original and underused statistical methods to analyze large sequencing data from a restricted number of samples. RESULTS: To evaluate the relevance of our method, 48 genes involved in pharmacokinetics were sequenced by next-generation sequencing from 24 chronic myeloid leukemia patients, either sensitive or resistant to imatinib treatment. Using a graphical representation, from 708 identified polymorphisms, a reduced list of 115 candidates was obtained. Then, by analyzing each gene and the distribution of variant alleles, several candidates were highlighted such as UGT1A9, PTPN22, and ERCC5. These genes were already associated with the transport, the metabolism, and even the sensitivity to imatinib in previous studies. CONCLUSIONS: These relevant tests are great alternatives to inferential statistics not applicable to next-generation sequencing experiments performed on small sample sizes. These approaches permit to reduce the number of targets and find good candidates for further treatment sensitivity studies.

Small RNA-Seq reveals novel miRNAs shaping the transcriptomic identity of rat brain structures.

In the central nervous system (CNS), miRNAs are involved in key functions, such as neurogenesis and synaptic plasticity. Moreover, they are essential to define specific transcriptomes in tissues and cells. However, few studies were performed to determine the miRNome of the different structures of the rat CNS, although a major model in neuroscience. Here, we determined by small RNA-Seq, the miRNome of the olfactory bulb, the hippocampus, the cortex, the striatum, and the spinal cord and showed the expression of 365 known miRNAs and 90 novel miRNAs. Differential expression analysis showed that several miRNAs were specifically enriched/depleted in these CNS structures. Transcriptome analysis by mRNA-Seq and correlation based on miRNA target predictions suggest that the specifically enriched/depleted miRNAs have a strong impact on the transcriptomic identity of the CNS structures. Altogether, these results suggest the critical role played by these enriched/depleted miRNAs, in particular the novel miRNAs, in the functional identities of CNS structures.

Pacific Biosciences Sequencing and IMGT/HighV-QUEST Analysis of Full-Length Single Chain Fragment Variable from an In Vivo Selected Phage-Display Combinatorial Library.

Phage-display selection of immunoglobulin (IG) or antibody single chain Fragment variable (scFv) from combinatorial libraries is widely used for identifying new antibodies for novel targets. Next-generation sequencing (NGS) has recently emerged as a new method for the high throughput characterization of IG and T cell receptor (TR) immune repertoires both in vivo and in vitro. However, challenges remain for the NGS sequencing of scFv from combinatorial libraries owing to the scFv length (>800 bp) and the presence of two variable domains [variable heavy (VH) and variable light (VL) for IG] associated by a peptide linker in a single chain. Here, we show that single-molecule real-time (SMRT) sequencing with the Pacific Biosciences RS II platform allows for the generation of full-length scFv reads obtained from an in vivo selection of scFv-phages in an animal model of atherosclerosis. We first amplified the DNA of the phagemid inserts from scFv-phages eluted from an aortic section at the third round of the in vivo selection. From this amplified DNA, 450,558 reads were obtained from 15 SMRT cells. Highly accurate circular consensus sequences from these reads were generated, filtered by quality and then analyzed by IMGT/HighV-QUEST with the functionality for scFv. Full-length scFv were identified and characterized in 348,659 reads. Full-length scFv sequencing is an absolute requirement for analyzing the associated VH and VL domains enriched during the in vivo panning rounds. In order to further validate the ability of SMRT sequencing to provide high quality, full-length scFv sequences, we tracked the reads of an scFv-phage clone P3 previously identified by biological assays and Sanger sequencing. Sixty P3 reads showed 100% identity with the full-length scFv of 767 bp, 53 of them covering the whole insert of 977 bp, which encompassed the primer sequences. The remaining seven reads were identical over a shortened length of 939 bp that excludes the vicinity of primers at both ends. Interestingly these reads were obtained from each of the 15 SMRT cells. Thus, the SMRT sequencing method and the IMGT/HighV-QUEST functionality for scFv provides a straightforward protocol for characterization of full-length scFv from combinatorial phage libraries.

Composting-Like Conditions Are More Efficient for Enrichment and Diversity of Organisms Containing Cellulase-Encoding Genes than Submerged Cultures.

Cost-effective biofuel production from lignocellulosic biomass depends on efficient degradation of the plant cell wall. One of the major obstacles for the development of a cost-efficient process is the lack of resistance of currently used fungal enzymes to harsh conditions such as high temperature. Adapted, thermophilic microbial communities provide a huge reservoir of potentially interesting lignocellulose-degrading enzymes for improvement of the cellulose hydrolysis step. In order to identify such enzymes, a leaf and wood chip compost was enriched on a mixture of thermo-chemically pretreated wheat straw, poplar and Miscanthus under thermophile conditions, but in two different set-ups. Unexpectedly, metagenome sequencing revealed that incubation of the lignocellulosic substrate with compost as inoculum in a suspension culture resulted in an impoverishment of putative cellulase- and hemicellulase-encoding genes. However, mimicking composting conditions without liquid phase yielded a high number and diversity of glycoside hydrolase genes and an enrichment of genes encoding cellulose binding domains. These identified genes were most closely related to species from Actinobacteria, which seem to constitute important players of lignocellulose degradation under the applied conditions. The study highlights that subtle changes in an enrichment set-up can have an important impact on composition and functions of the microcosm. Composting-like conditions were found to be the most successful method for enrichment in species with high biomass degrading capacity.

Early Medieval Muslim Graves in France: First Archaeological, Anthropological and Palaeogenomic Evidence.

The rapid Arab-Islamic conquest during the early Middle Ages led to major political and cultural changes in the Mediterranean world. Although the early medieval Muslim presence in the Iberian Peninsula is now well documented, based in the evaluation of archeological and historical sources, the Muslim expansion in the area north of the Pyrenees has only been documented so far through textual sources or rare archaeological data. Our study provides the first archaeo-anthropological testimony of the Muslim establishment in South of France through the multidisciplinary analysis of three graves excavated at Nimes. First, we argue in favor of burials that followed Islamic rites and then note the presence of a community practicing Muslim traditions in Nimes. Second, the radiometric dates obtained from all three human skeletons (between the 7th and the 9th centuries AD) echo historical sources documenting an early Muslim presence in southern Gaul (i.e., the first half of 8th century AD). Finally, palaeogenomic analyses conducted on the human remains provide arguments in favor of a North African ancestry of the three individuals, at least considering the paternal lineages. Given all of these data, we propose that the skeletons from the Nimes burials belonged to Berbers integrated into the Umayyad army during the Arab expansion in North Africa. Our discovery not only discusses the first anthropological and genetic data concerning the Muslim occupation of the Visigothic territory of Septimania but also highlights the complexity of the relationship between the two communities during this period.

Aptamer selection by direct microfluidic recovery and surface plasmon resonance evaluation.

A surface plasmon resonance (SPR)-based SELEX approach has been used to raise RNA aptamers against a structured RNA, derived from XBP1 pre-mRNA, that folds as two contiguous hairpins. Thanks to the design of the internal microfluidic cartridge of the instrument, the selection was performed during the dissociation phase of the SPR analysis by recovering the aptamer candidates directly from the target immobilized onto the sensor chip surface. The evaluation of the pools was performed by SPR, simultaneously, during the association phase, each time the amplified and transcribed candidates were injected over the immobilized target. SPR coupled with SELEX from the first to the last round allowed identifying RNA aptamers that formed highly stable loop-loop complexes (KD equal to 8nM) with the hairpin located on the 5' side of the target. High throughput sequencing of two key rounds confirmed the evolution observed by SPR and also revealed the selection of hairpins displaying a loop not fully complementary to the loop of its target. These candidates were selected mainly because they bound 79 times faster to the target than those having a complementary loop. SELEX coupled with SPR is expected to speed up the selection process because selection and evaluation are performed simultaneously.

Genome-wide association links candidate genes to resistance to Plum Pox Virus in apricot (Prunus armeniaca).

In fruit tree species, many important traits have been characterized genetically by using single-family descent mapping in progenies segregating for the traits. However, most mapped loci have not been sufficiently resolved to the individual genes due to insufficient progeny sizes for high resolution mapping and the previous lack of whole-genome sequence resources of the study species. To address this problem for Plum Pox Virus (PPV) candidate resistance gene identification in Prunus species, we implemented a genome-wide association (GWA) approach in apricot. This study exploited the broad genetic diversity of the apricot (Prunus armeniaca) germplasm containing resistance to PPV, next-generation sequence-based genotyping, and the high-quality peach (Prunus persica) genome reference sequence for single nucleotide polymorphism (SNP) identification. The results of this GWA study validated previously reported PPV resistance quantitative trait loci (QTL) intervals, highlighted other potential resistance loci, and resolved each to a limited set of candidate genes for further study. This work substantiates the association genetics approach for resolution of QTL to candidate genes in apricot and suggests that this approach could simplify identification of other candidate genes for other marked trait intervals in this germplasm.

Finishing bacterial genome assemblies with Mix.

MOTIVATION: Among challenges that hamper reaping the benefits of genome assembly are both unfinished assemblies and the ensuing experimental costs. First, numerous software solutions for genome de novo assembly are available, each having its advantages and drawbacks, without clear guidelines as to how to choose among them. Second, these solutions produce draft assemblies that often require a resource intensive finishing phase. METHODS: In this paper we address these two aspects by developing Mix , a tool that mixes two or more draft assemblies, without relying on a reference genome and having the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a set of paths in the extension graph that maximizes the cumulative contig length. RESULTS: We evaluate the performance of Mix on bacterial NGS data from the GAGE-B study and apply it to newly sequenced Mycoplasma genomes. Resulting final assemblies demonstrate a significant improvement in the overall assembly quality. In particular, Mix is consistent by providing better overall quality results even when the choice is guided solely by standard assembly statistics, as is the case for de novo projects. AVAILABILITY: Mix is implemented in Python and is available at https://github.com/cbib/MIX, novel data for our Mycoplasma study is available at http://services.cbib.u-bordeaux2.fr/mix/.

HIV type-1 transmission dynamics in recent seroconverters: relationship with transmission of drug resistance and viral diversity.

BACKGROUND: HIV type-1 (HIV-1) has been shown to be frequently transmitted by acutely infected patients. We investigated the relationship between the dynamics of HIV-1 transmission within recently infected patients, the HIV-1 variability and the transmission of antiretroviral drug resistance. METHODS: We included patients infected between 1996 and 2006, with a plasma sample obtained <18 months after seroconversion and prior to antiretroviral therapy initiation. Reverse transcriptase (RT) and protease sequences were determined by direct population sequencing from plasma samples. Genotypic resistance was interpreted with the Agence Nationale de Recherches sur le SIDA et les Hépatites Virales 2006 algorithm and International AIDS Society-USA list. Phylogenetic analysis (neighbour-joining and maximum likelihood methods) of RT sequences was used to determine the HIV-1 subtype and the interrelationship between sequences. RESULTS: Genotypic resistance was detected in 37/263 (14.1%) patients. Patients were infected by HIV-1 clade B in 222 (84%) cases and with non-B subtypes in 41 (16%). A total of 80 (30.4%) RT sequences were segregated in 24 clusters with bootstrap values >98% for 22 clusters. The frequency of grouping in clusters was higher within B sequences compared with non-B sequences (35.1% versus 4.9%; P<2.10(-4)). Drug-resistant isolates were retrieved in only 3 clusters, but the prevalence of resistance in clustering viruses (10/80, 12.5%) was not different than in isolated sequences. CONCLUSIONS: The segregation into clusters suggested frequent forward transmission events in patients infected with HIV-1 subtype B, including the possibility of transmission of drug-resistant isolates. These findings warrant increasing prevention efforts and serological screening in the at-risk populations.

Genome evolution in yeasts.

Identifying the mechanisms of eukaryotic genome evolution by comparative genomics is often complicated by the multiplicity of events that have taken place throughout the history of individual lineages, leaving only distorted and superimposed traces in the genome of each living organism. The hemiascomycete yeasts, with their compact genomes, similar lifestyle and distinct sexual and physiological properties, provide a unique opportunity to explore such mechanisms. We present here the complete, assembled genome sequences of four yeast species, selected to represent a broad evolutionary range within a single eukaryotic phylum, that after analysis proved to be molecularly as diverse as the entire phylum of chordates. A total of approximately 24,200 novel genes were identified, the translation products of which were classified together with Saccharomyces cerevisiae proteins into about 4,700 families, forming the basis for interspecific comparisons. Analysis of chromosome maps and genome redundancies reveal that the different yeast lineages have evolved through a marked interplay between several distinct molecular mechanisms, including tandem gene repeat formation, segmental duplication, a massive genome duplication and extensive gene loss.

New strategy for the representation and the integration of biomolecular knowledge at a cellular scale.

The combination of sequencing and post-sequencing experimental approaches produces huge collections of data that are highly heterogeneous both in structure and in semantics. We propose a new strategy for the integration of such data. This strategy uses structured sets of sequences as a unified representation of biological information and defines a probabilistic measure of similarity between the sets. Sets can be composed of sequences that are known to have a biological relationship (e.g. proteins involved in a complex or a pathway) or that share similar values for a particular attribute (e.g. expression profile). We have developed a software, BlastSets, which implements this strategy. It exploits a database where the sets derived from diverse biological information can be deposited using a standard XML format. For a given query set, BlastSets returns target sets found in the database whose similarity to the query is statistically significant. The tool allowed us to automatically identify verified relationships between correlated expression profiles and biological pathways using publicly available data for Saccharomyces cerevisiae. It was also used to retrieve the members of a complex (ribosome) based on the mining of expression profiles. These first results validate the relevance of the strategy and demonstrate the promising potential of BlastSets.

IPPRED: server for proteins interactions inference.

SUMMARY: IPPRED is a web based server to infer protein-protein interactions through homology search between candidate proteins and those described as interacting. This simple inference allows to propose or to validate potential interactions. AVAILABILITY: IPPRED is freely available at http://cbi.labri.fr/outils/ippred/.