Newly Identified Mycobacterium africanum Lineage 10, Central Africa

Analysis of genome sequencing data from >100,000 genomes of Mycobacterium tuberculosis complex using TB-Annotator software revealed a previously unknown lineage, proposed name L10, in central Africa. Phylogenetic reconstruction suggests L10 could represent a missing link in the evolutionary and geographic migration histories of M. africanum.

Advancements and Challenges in Handwritten Text Recognition: A Comprehensive Survey

Handwritten Text Recognition (HTR) is essential for digitizing historical documents in different kinds of archives. In this study, we introduce a hybrid form archive written in French: the Belfort civil registers of births. The digitization of these historical documents is challenging due to their unique characteristics such as writing style variations, overlapped characters and words, and marginal annotations. The objective of this survey paper is to summarize research on handwritten text documents and provide research directions toward effectively transcribing this French dataset. To achieve this goal, we presented a brief survey of several modern and historical HTR offline systems of different international languages, and the top state-of-the-art contributions reported of the French language specifically. The survey classifies the HTR systems based on techniques employed, datasets used, publication years, and the level of recognition. Furthermore, an analysis of the systems' accuracies is presented, highlighting the best-performing approach. We have also showcased the performance of some HTR commercial systems. In addition, this paper presents a summarization of the HTR datasets that publicly available, especially those identified as benchmark datasets in the International Conference on Document Analysis and Recognition (ICDAR) and the International Conference on Frontiers in Handwriting Recognition (ICFHR) competitions. This paper, therefore, presents updated state-of-the-art research in HTR and highlights new directions in the research field.

The paradoxes of Mycobacterium tuberculosis molecular evolution and consequences for the inference of tuberculosis emergence date

The date of Mycobacterium tuberculosis complex emergence has been the subject of long debates. New studies joining archaeological efforts with sequencing methods raise high hopes for solving whether this emergence is closer to 70,000 or to 6000 years before present. Inferring the date of emergence of this pathogen based on sequence data requires a molecular clock. Several clocks inferred from different types of loci and/or different samples, using both sound reasoning and reliable data, are actually very different, which we refer to as the paradoxes of M. tuberculosis molecular evolution. After having presented these paradoxes, we will remind the limits of the molecular clocks used in the different studies such as the assumption of homogeneous substitution rate. We will then review recent results that shed new light on the characteristics of M. tuberculosis molecular evolution: traces of diverse selection pressures, the impact of host dynamics, etc. We provide some ideas on what to do next to get nearer to a reliable dating of Mycobacterium tuberculosis complex emergence. Among them, the collection of additional remains from ancient tuberculosis seems still essential.

Towards the reconstruction of a global TB history using a new pipeline "TB-Annotator"

Mycobacterium tuberculosis complex (MTBC) has a population structure consisting of 9 human and animal lineages. The genomic diversity within these lineages is a pathogenesis factor that affects virulence, transmissibility, host response, and antibiotic resistance. Hence it is important to develop improved information systems for tracking and understanding the spreading and evolution of genomes. We present results obtained thanks to a new informatics platform for computational biology of MTBC, that uses a convenience sample from public/private SRAs, designated as TB-Annotator. Version 1 was a first interactive graphic-based web tool based on 15,901 representative genomes. Version 2, still interactive, is a more sophisticated database, developed using the Snakemake Workflow Management System (WMS) that allows an unsupervised global and scalable analysis of the content of the USA National Center for Biotechnology Information Short Read Archives database. This platform analyzes nucleotide variants, the presence/absence of genes, known regions of difference and detect new deletions, the insertion sites of mobile genetic elements, and allows phylogenetic trees to be built, imported in a graphical interface and interactively analyzed between the data and the tree. The objective of TB-Annotator is triple: detect recent epidemiological links, reconstruct distant phylogeographical histories as well as perform more complex phenotypic/genotypic Genome-Wide Association Studies (GWAS). In this paper, we compare the various taxonomic SNPs-based labels and hierarchies previously described in recent reference papers for L1, and present a comparative analysis that allows identification of alias and thus provides the basis of a future unifying naming scheme for L1 sublineages. We present a global phylogenetic tree built with RAxML-NG, and one on L2; at the time of writing, we characterized about 200 sublineages, with many new ones; a detail tree for Modern L2 and a hierarchical scheme allowing to facilitate L2 lineage assignment are also presented.

Towards a better understanding of the long-lasting evolutionary history of Mycobacterium tuberculosis

The daily increasing sequencing of Mycobacterium tuberculosis has made it possible to establish an advanced phylogeny of this bacterium. It currently includes 9 lineages mainly affecting humans, completed by animal lineages, which form the Mycobacterium tuberculosis complex. Inherited from various historical approaches, this phylogeny is now based on Single Nucleotide Polymorphisms (SNPs), of which updates are frequently proposed. We present here evidence that the task needs refinements: some lineages have currently suboptimal defining SNPs, and many sublineages still need to be named and characterized. These findings are based on a new tool specifically designed to index the entire existing sequencing data. In this article, we focus on lineages 4.5, 4.7, 6 and 7. We take the opportunity to present some evidence that TB-annotator shows strong relevance, identifying well supported sublineages, as well as good global agreement with previous findings.

Mycobacterium tuberculosis complex drug-resistance, phylogenetics, and evolution in Nigeria: Comparison with Ghana and Cameroon

In this article, we provide an in-depth analysis on the drug-resistance phenotypic characteristics of a cohort of 325 tuberculosis and characterize by Whole Genome Sequencing 24 isolates from Nigeria belonging to L4, L5 and L6. Our results suggest an alarming rate of drug-resistance of the L4.6.2.2 Mycobacterium tuberculosis complex (MTBC) lineage and a high diversity of L5. We compiled these new Sequence Read Archives (SRAs) to previously published ones from available Bioprojects run in Nigeria. We performed RAxML phylogenetic reconstructions of larger samples that include public NCBI SRAs from some neighboring countries (Cameroon, Ghana). To confront phylogenetic reconstruction to metadata, we used a new proprietary database named TB-Annotator. We show that L5 genomes in Northern Nigeria belong to new clades as the ones described until now and allow an update of the taxonomy of L5. In addition, we describe the L4.6.2.2 lineage in Nigeria, Cameroon and Ghana. We provide computations on the likely divergence time of L4.6.2.2 and suggest a new hypothesis concerning its origin. Finally we provide a short overview on M. bovis diversity in Nigeria. This study constitutes a baseline knowledge on the global genomic diversity, phylogeography and phylodynamics of MTBC in Nigeria, as well as on the natural history of this largely ignored but densely populated country of Africa. These results highlight the need of sequencing additional MTBC genomes in Nigeria and more generally in West-Africa, both for public health and for academic reasons. The likelihood of replacement of L5-L6 by L4.6.2.2 isolates, leave potentially little time to gather historical knowledge informative on the ancient history of tuberculosis in West-Africa.

Cross-Layer Federated Learning for Lightweight IoT Intrusion Detection Systems

With the proliferation of IoT devices, ensuring the security and privacy of these devices and their associated data has become a critical challenge. In this paper, we propose a federated sampling and lightweight intrusion-detection system for IoT networks that use K-meansfor sampling network traffic and identifying anomalies in a semi-supervised way. The system is designed to preserve data privacy by performing local clustering on each device and sharing only summary statistics with a central aggregator. The proposed system is particularly suitable for resource-constrained IoT devices such as sensors with limited computational and storage capabilities. We evaluate the system's performance using the publicly available NSL-KDD dataset. Our experiments and simulations demonstrate the effectiveness and efficiency of the proposed intrusion-detection system, highlighting the trade-offs between precision and recall when sharing statistics between workers and the coordinator. Notably, our experiments show that the proposed federated IDS can increase the true-positive rate up to 10% when the workers and the coordinator collaborate.

Comparison of in silico predicted Mycobacterium tuberculosis spoligotypes and lineages from whole genome sequencing data

Bacterial strain-types in the Mycobacterium tuberculosis complex underlie tuberculosis disease, and have been associated with drug resistance, transmissibility, virulence, and host-pathogen interactions. Spoligotyping was developed as a molecular genotyping technique used to determine strain-types, though recent advances in whole genome sequencing (WGS) technology have led to their characterization using SNP-based sub-lineage nomenclature. Notwithstanding, spoligotyping remains an important tool and there is a need to study the congruence between spoligotyping-based and SNP-based sub-lineage assignation. To achieve this, an in silico spoligotype prediction method ("Spolpred2") was developed and integrated into TB-Profiler. Lineage and spoligotype predictions were generated for > 28 k isolates and the overlap between strain-types was characterized. Major spoligotype families detected were Beijing (25.6%), T (18.6%), LAM (13.1%), CAS (9.4%), and EAI (8.3%), and these broadly followed known geographic distributions. Most spoligotypes were perfectly correlated with the main MTBC lineages (L1-L7, plus animal). Conversely, at lower levels of the sub-lineage system, the relationship breaks down, with only 65% of spoligotypes being perfectly associated with a sub-lineage at the second or subsequent levels of the hierarchy. Our work supports the use of spoligotyping (membrane or WGS-based) for low-resolution surveillance, and WGS or SNP-based systems for higher-resolution studies.

Characterization of a Driven Two-Level Quantum System by Supervised Learning

We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to a given target state. For any control protocol, the goal is to find the mapping between the offset and the distance. This mapping is interpolated using a neural network. The estimate is global in the sense that no a priori knowledge is required on the relation to be determined. Different neural network algorithms are tested on a series of data sets. We show that the mapping can be reproduced with very high precision in the direct case when the offset is known, while obstacles appear in the indirect case starting from the distance to the target. We point out the limits of the estimation procedure with respect to the properties of the mapping to be interpolated. We discuss the physical relevance of the different results.

The usefulness of NLP techniques for predicting peaks in firefighter interventions due to rare events

In some countries such as France, the number of operations assisted by firefighters has shown an almost linear increase over the years, contrary to their resource capacity. For this reason, predicting the number of interventions has become a necessity. Initially, time series models were developed with several types of qualitative and quantitative features, including the alert level of the bulletins, to predict the operational load. We realized that interventions related to human activities are quite predictable. However, the recognition of interventions due to rare events such as storms or floods needs more than quantitative meteorological data to be identified, since there are almost always zero cases. Thus, this work proposes the application of natural language processing techniques, namely long short-term memory, convolutional neural networks, FlauBERT, and CamemBERT to extract features from the texts of weather bulletins in order to recognize periods with peak interventions, where the intense workload of firefighters is caused by rare events. Four categories identified as Emergency Person Rescue, Total Person Rescue, interventions related to Heating, and Storm/Flood were our targets for the multilabel classification models developed. The results showed a remarkable accuracy of 80%, 86%, 92%, and 86% for Emergency Rescue People, Total Rescue People, Heating, and Storm/Flood, respectively.

Connection between two historical tuberculosis outbreak sites in Japan, Honshu, by a new ancestral Mycobacterium tuberculosis L2 sublineage

By gathering 680 publicly available Sequence Read Archives from isolates of Mycobacterium tuberculosis complex (MTBC) including 190 belonging to the lineage 2 Beijing , and using an in-house bioinformatical pipeline, the TB-Annotator , that analyses more than 50 000 characters, we describe herein a new L2 sublineage from 20 isolates found in the Tochigi province, (Japan), that we designate as asia ancestral 5 (AAnc5). These isolates harbour a number of specific criteria (42 SNPs) and their intra-cluster pairwise distance suggests historical and not epidemiological transmission. These isolates harbour a mutation in rpoC , and do not fulfil, any of the modern Beijing lineage criteria, nor any of the other ancestral Beijing lineages described so far. Asia ancestral 5 isolates do not possess mutT2 58 and ogt 12 characteristics of modern Beijing , but possess ancestral Beijing SNPs characteristics. By looking into the literature, we found a reference isolate ID381, described in Kobe and Osaka belonging to the ‘G3’ group, sharing 36 out of the 42 specific SNPs found in AAnc5. We also assessed the intermediate position of the asia ancestral 4 (AAnc4) sublineage recently described in Thailand and propose an improved classification of the L2 that now includes AAnc4 and AAnc5. By increasing the recruitment into TB-Annotator to around 3000 genomes (including 642 belonging to L2), we confirmed our results and discovered additional historical ancestral L2 branches that remain to be investigated in more detail. We also present, in addition, some anthropological and historical data from Chinese and Japan history of tuberculosis, as well as from Korea, that could support our results on L2 evolution. This study shows that the reconstruction of the early history of tuberculosis in Asia is likely to reveal complex patterns since its emergence.

Economic burden in non-Hodgkin lymphoma survivors: The French Lymphoma Study Association SIMONAL cross-sectional study

BACKGROUND

No study has focused on the economic burden in non-Hodgkin lymphoma (NHL) survivors, even though this knowledge is essential. This study reports on health care resource use and associated health care costs as well as related factors in a series of 1671 French long-term NHL survivors.

METHODS

Health care costs were measured from the payer perspective. Only direct medical costs (medical consultations, outpatient treatments, hospitalizations, and medical transport) in the past 12 months were included (reference year 2015). Multiple linear regression was used to search for explanatory factors of health care costs.

RESULTS

In total, 1100 survivors (66%) reported having used at least 1 health care resource, and 867 (52%) reported having used at least 1 outpatient treatment. After the authors accounted for missing data, the mean health care cost was estimated at €702 ± €2221. Hospitalizations and outpatient treatments were the main cost drivers. Sensitivity analyses confirmed the robustness of the results. For the 1100 survivors who reported using at least 1 health care resource, the mean health care cost was €1067 ± €2268. Several factors demonstrated statistically significant relationships with health care costs. For instance, cardiovascular disorders increased costs by 66% ± 16%. In contrast, rituximab or autologous stem cell transplantation as initial therapy had no effect on health care costs.

CONCLUSIONS

The consideration of economic constraints in health care is now a reality. This retrospective study reports on a better understanding of health care resource use and associated health care costs as well as related factors. It may help health care professionals in their ongoing efforts to design person-centered health care pathways.

CRISPRbuilder-TB: "CRISPR-builder for tuberculosis". Exhaustive reconstruction of the CRISPR locus in mycobacterium tuberculosis complex using SRA

Mycobacterium tuberculosis complex (MTC) CRISPR locus diversity has long been studied solely investigating the presence/absence of a known set of spacers. Unveiling the genetic mechanisms of its evolution requires a more exhaustive reconstruction in a large amount of representative strains.

In this article, we point out and resolve, with a new pipeline, the problem of CRISPR reconstruction based directly on short read sequences in M. tuberculosis. We first show that the process we set up, that we coin as “CRISPRbuilder-TB” (https://github.com/cguyeux/CRISPRbuilder-TB), allows an efficient reconstruction of simulated or real CRISPRs, even when including complex evolutionary steps like the insertions of mobile elements. Compared to more generalist tools, the whole process is much more precise and robust, and requires only minimal manual investigation. Second, we show that more than 1/3 of the currently complete genomes available for this complex in the public databases contain largely erroneous CRISPR loci. Third, we highlight how both the classical experimental in vitro approach and the basic in silico spoligotyping provided by existing analytic tools miss a whole diversity of this locus in MTC, by not capturing duplications, spacer and direct repeats variants, and IS6110 insertion locations. This description is extended in a second article that describes MTC-CRISPR diversity and suggests general rules for its evolution. This work opens perspectives for an in-depth exploration of M. tuberculosis CRISPR loci diversity and of mechanisms involved in its evolution and its functionality, as well as its adaptation to other CRISPR locus-harboring bacterial species.

In this article, we tackle the bioinformatical issue of the reconstruction of the Mycobacterium tuberculosis complex CRISPR locus using short read sequences without requiring genome assembly. We first show that many complete genomes, as found in public databases and often reconstructed by de novo assemblies, often contain errors on this locus as well as on other repeated sequences. We provide an in-depth description of our new method, designated as ‘CRISPRbuilder-TB’, and we show that our method provides much more exhaustive and reliable information (on DR variants, spacer diversity, global structure) than Crass and CRISPR_detector. The new and unsuspected genomic diversity we detected is described in a companion paper. Scripts are available to adapt the tool to other species.

OSIP1 is a self-assembling DUF3129 protein required to protect fungal cells from toxins and stressors

Secreted proteins are key players in fungal physiology and cell protection against external stressing agents and antifungals. Oak stress-induced protein 1 (OSIP1) is a fungal-specific protein with unknown function. By using Podospora anserina and Phanerochaete chrysosporium as models, we combined both in vivo functional approaches and biophysical characterization of OSIP1 recombinant protein. The P. anserina OSIP1^Δ mutant showed an increased sensitivity to the antifungal caspofungin compared to the wild type. This correlated with the production of a weakened extracellular exopolysaccharide/protein matrix (ECM). Since the recombinant OSIP1 from P. chrysosporium self-assembled as fibers and was capable of gelation, it is likely that OSIP1 is linked to ECM formation that acts as a physical barrier preventing drug toxicity. Moreover, compared to the wild type, the OSIP1^Δ mutant was more sensitive to oak extractives including chaotropic phenols and benzenes. It exhibited a strongly modified secretome pattern and an increased production of proteins associated to the cell-wall integrity signalling pathway, when grown on oak sawdust. This demonstrates that OSIP1 has also an important role in fungal resistance to extractive-induced stress.

Unexpected diversity of CRISPR unveils some evolutionary patterns of repeated sequences in Mycobacterium tuberculosis

BACKGROUND

Diversity of the CRISPR locus of Mycobacterium tuberculosis complex has been studied since 1997 for molecular epidemiology purposes. By targeting solely the 43 spacers present in the two first sequenced genomes (H37Rv and BCG), it gave a biased idea of CRISPR diversity and ignored diversity in the neighbouring cas-genes.

RESULTS

We set up tailored pipelines to explore the diversity of CRISPR-cas locus in Short Reads. We analyzed data from a representative set of 198 clinical isolates as evidenced by well-characterized SNPs. We found a relatively low diversity in terms of spacers: we recovered only the 68 spacers that had been described in 2000. We found no partial or global inversions in the sequences, letting always the Direct Variant Repeats (DVR) in the same order. In contrast, we found an unexpected diversity in the form of: SNPs in spacers and in Direct Repeats, duplications of various length, and insertions at various locations of the IS6110 insertion sequence, as well as blocks of DVR deletions. The diversity was in part specific to lineages. When reconstructing evolutionary steps of the locus, we found no evidence for SNP reversal. DVR deletions were linked to recombination between IS6110 insertions or between Direct Repeats.

CONCLUSION

This work definitively shows that CRISPR locus of M. tuberculosis did not evolve by classical CRISPR adaptation (incorporation of new spacers) since the last most recent common ancestor of virulent lineages. The evolutionary mechanisms that we discovered could be involved in bacterial adaptation but in a way that remains to be identified.

Complex evolutionary history of coffees revealed by full plastid genomes and 28,800 nuclear SNP analyses, with particular emphasis on Coffea canephora (Robusta coffee)

For decades coffees were associated with the genus Coffea. In 2011, the closely related genus Psilanthus was subsumed into Coffea. However, results obtained in 2017-based on 28,800 nuclear SNPs-indicated that there is not substantial phylogenetic support for this incorporation. In addition, a recent study of 16 plastid full-genome sequences highlighted an incongruous placement of Coffea canephora (Robusta coffee) between maternal and nuclear trees. In this study, similar global features of the plastid genomes of Psilanthus and Coffea are observed. In agreement with morphological and physiological traits, the nuclear phylogenetic tree clearly separates Psilanthus from Coffea (with exception to C. rhamnifolia, closer to Psilanthus than to Coffea). In contrast, the maternal molecular tree was incongruent with both morphological and nuclear differentiation, with four main clades observed, two of which include both Psilanthus and Coffea species, and two with either Psilanthus or Coffea species. Interestingly, Coffea and Psilanthus taxa sampled in West and Central Africa are members of the same group. Several mechanisms such as the retention of ancestral polymorphisms due to incomplete lineage sorting, hybridization leading to homoploidy (without chromosome doubling) and alloploidy (for C. arabica) are involved in the evolutionary history of the coffee species. While sharing similar morphological characteristics, the genetic relationships within C. canephora have shown that some populations are well differentiated and genetically isolated. Given the position of its closely-related species, we may also consider C. canephora to be undergoing a long process of speciation with an intermediate step of (sub-)speciation.

Chloroplast genomes of Rubiaceae: Comparative genomics and molecular phylogeny in subfamily Ixoroideae

In Rubiaceae phylogenetics, the number of markers often proved a limitation with authors failing to provide well-supported trees at tribal and generic levels. A robust phylogeny is a prerequisite to study the evolutionary patterns of traits at different taxonomic levels. Advances in next-generation sequencing technologies have revolutionized biology by providing, at reduced cost, huge amounts of data for an increased number of species. Due to their highly conserved structure, generally recombination-free, and mostly uniparental inheritance, chloroplast DNA sequences have long been used as choice markers for plant phylogeny reconstruction. The main objectives of this study are: 1) to gain insight in chloroplast genome evolution in the Rubiaceae (Ixoroideae) through efficient methodology for de novo assembly of plastid genomes; and, 2) to test the efficiency of mining SNPs in the nuclear genome of Ixoroideae based on the use of a coffee reference genome to produce well-supported nuclear trees. We assembled whole chloroplast genome sequences for 27 species of the Rubiaceae subfamily Ixoroideae using next-generation sequences. Analysis of the plastid genome structure reveals a relatively good conservation of gene content and order. Generally, low variation was observed between taxa in the boundary regions with the exception of the inverted repeat at both the large and short single copy junctions for some taxa. An average of 79% of the SNP determined in the Coffea genus are transferable to Ixoroideae, with variation ranging from 35% to 96%. In general, the plastid and the nuclear genome phylogenies are congruent with each other. They are well-resolved with well-supported branches. Generally, the tribes form well-identified clades but the tribe Sherbournieae is shown to be polyphyletic. The results are discussed relative to the methodology used and the chloroplast genome features in Rubiaceae and compared to previous Rubiaceae phylogenies.

Ancestral Reconstruction and Investigations of Genomic Recombination on some Pentapetalae Chloroplasts

In this article, we propose a semi-automated method to rebuild genome ancestors of chloroplasts by taking into account gene duplication. Two methods have been used in order to achieve this work: a naked eye investigation using homemade scripts, whose results are considered as a basis of knowledge, and a dynamic programming based approach similar to Needleman-Wunsch. The latter fundamentally uses the Gestalt pattern matching method of sequence matcher to evaluate the occurrences probability of each gene in the last common ancestor of two given genomes. The two approaches have been applied on chloroplastic genomes from Apiales, Asterales, and Fabids orders, the latter belonging to Pentapetalae group. We found that Apiales species do not undergo indels, while they occur in the Asterales and Fabids orders. A series of experiments was then carried out to extensively verify our findings by comparing the obtained ancestral reconstruction results with the latest released approach called MLGO (Maximum Likelihood for Gene-Order analysis).

panISa: ab initio detection of insertion sequences in bacterial genomes from short read sequence data

Motivation

The advent of next-generation sequencing has boosted the analysis of bacterial genome evolution. Insertion sequence (IS) elements play a key role in prokaryotic genome organization and evolution, but their repetitions in genomes complicate their detection from short-read data.

Results

PanISa is a software pipeline that identifies IS insertions ab initio in bacterial genomes from short-read data. It is a highly sensitive and precise tool based on the detection of read-mapping patterns at the insertion site. PanISa performs better than existing IS detection systems as it is based on a database-free approach. We applied it to a high-risk clone lineage of the pathogenic species Pseudomonas aeruginosa, and report 43 insertions of five different ISs (among which three are new) and a burst of ISPa1635 in a hypermutator isolate.

Availability and implementation

PanISa is implemented in Python and released as an open source software (GPL3) at https://github.com/bvalot/panISa.

Supplementary information

Supplementary data are available at Bioinformatics online.

SpCLUST: Towards a fast and reliable clustering for potentially divergent biological sequences

This paper presents SpCLUST, a new C++ package that takes a list of sequences as input, aligns them with MUSCLE, computes their similarity matrix in parallel and then performs the clustering. SpCLUST extends a previously released software by integrating additional scoring matrices which enables it to cover the clustering of amino-acid sequences. The similarity matrix is now computed in parallel according to the master/slave distributed architecture, using MPI. Performance analysis, realized on two real datasets of 100 nucleotide sequences and 1049 amino-acids ones, show that the resulting library substantially outperforms the original Python package. The proposed package was also intensively evaluated on simulated and real genomic and protein data sets. The clustering results were compared to the most known traditional tools, such as UCLUST, CD-HIT and DNACLUST. The comparison showed that SpCLUST outperforms the other tools when clustering divergent sequences, and contrary to the others, it does not require any user intervention or prior knowledge about the input sequences.

Evaluation of chloroplast genome annotation tools and application to analysis of the evolution of coffee species

Chloroplast sequences are widely used for phylogenetic analysis due to their high degree of conservation in plants. Whole chloroplast genomes can now be readily obtained for plant species using new sequencing methods, giving invaluable data for plant evolution However new annotation methods are required for the efficient analysis of this data to deliver high quality phylogenetic analyses. In this study, the two main tools for chloroplast genome annotation were compared. More consistent detection and annotation of genes were produced with GeSeq when compared to the currently used Dogma. This suggests that the annotation of most of the previously annotated chloroplast genomes should now be updated. GeSeq was applied to species related to coffee, including 16 species of the Coffea and Psilanthus genera to reconstruct the ancestral chloroplast genomes and to evaluate their phylogenetic relationships. Eight genes in the plant chloroplast pan genome (consisting of 92 genes) were always absent in the coffee species analyzed. Notably, the two main cultivated coffee species (i.e. Arabica and Robusta) did not group into the same clade and differ in their pattern of gene evolution. While Arabica coffee (Coffea arabica) belongs to the Coffea genus, Robusta coffee (Coffea canephora) is associated with the Psilanthus genus. A more extensive survey of related species is required to determine if this is a unique attribute of Robusta coffee or a more widespread feature of coffee tree species.

On the reconstruction of the ancestral bacterial genomes in genus Mycobacterium and Brucella

BACKGROUND

To reconstruct the evolution history of DNA sequences, novel models of increasing complexity regarding the number of free parameters taken into account in the sequence evolution, as well as faster and more accurate algorithms, and statistical and computational methods, are needed. More particularly, as the principal forces that have led to major structural changes are genome rearrangements (such as translocations, fusions, and so on), understanding their underlying mechanisms, among other things via the ancestral genome reconstruction, are essential. In this problem, since finding the ancestral genomes that minimize the number of rearrangements in a phylogenetic tree is known to be NP-hard for three or more genomes, heuristics are commonly chosen to obtain approximations of the exact solution. The aim of this work is to show that another path is possible.

RESULTS

Various algorithms and software already deal with the difficult nature of the problem of reconstruction of the ancestral genome, but they do not function with precision, in particular when indels or single nucleotide polymorphisms fall into repeated sequences. In this article, and despite the theoretical NP-hardness of the ancestral reconstruction problem, we show that an exact solution can be found in practice in various cases, encompassing organelles and some bacteria. A practical example proves that an accurate reconstruction, which also allows to highlight homoplasic events, can be obtained. This is illustrated by the reconstruction of ancestral genomes of two bacterial pathogens, belonging in Mycobacterium and Brucella genera.

CONCLUSIONS

By putting together automatically reconstructed ancestral regions with handmade ones for problematic cases, we show that an accurate reconstruction of ancestors of the Brucella genus and of the Mycobacterium tuberculosis complex is possible. By doing so, we are able to investigate the evolutionary history of each pathogen by computing their common ancestors. They can be investigated extensively, by studying the gene content evolution over time, the resistance acquisition, and the impacts of mobile elements on genome plasticity.

Streptomyces Dominate the Soil Under Betula Trees That Have Naturally Colonized a Red Gypsum Landfill

The successful restoration of well-engineered tailings storage facilities is needed to avoid mine tailings problems. This study characterized the bacterial communities from vegetated and non-vegetated soils from a red gypsum landfill resulting from the industrial extraction of titanium. A set of 275 bacteria was isolated from vegetated soil and non-vegetated soil areas and taxonomically characterized using BOX-PCR. The study also evaluated the ability of a subset of 88 isolated bacteria on their ability to produce plant growth promoting (PGP) traits [indoleacetic acid (IAA) production, phosphate solubilization, and siderophore production] and their tolerance to potentially toxic elements (PTEs). Twenty strains were chosen for further analysis to produce inoculum for birch-challenging experiments. Principal component analysis (PCA) showed that the set of pedological parameters (pH, granulometry, carbon, organic matter, and Mg content) alone explained approximately 40% of the differences between the two soils. The highest density of total culturable bacteria was found in the vegetated soil, and it was much higher than that in the non-vegetated soil. The Actinobacteria phyla dominated the culturable soil community (70% in vegetated soil and 95% in non-vegetated soil), while the phyla Firmicutes (including the genus Bacillus) and Bacteroides (including the genera Pedobacter and Olivibacter) were found only in the vegetated soil fraction. Additional genera (Rhizobium, Variovorax, and Ensifer) were found solely in the vegetated soil. The vegetated soil bacteria harbored the most beneficial PGP bacteria with 12% of the isolates showing three or more PGP traits. The strains with higher metal tolerances in our study were Phyllobacterium sp. WR140 (RO1.15), Phyllobacterium sp. WR140 (R01.34), and Streptomyces sp. (R04.15), all isolated from the vegetated soil. Among the isolates tested in challenging experiments, Phyllobacterium (R01.34) and Streptomyces sp. (R05.33) have the greatest potential to act as PGP rhizobacteria and therefore to be used in the biological restoration of tailings dumps.

Comparison of metaheuristics to measure gene effects on phylogenetic supports and topologies

Background

A huge and continuous increase in the number of completely sequenced chloroplast genomes, available for evolutionary and functional studies in plants, has been observed during the past years. Consequently, it appears possible to build large-scale phylogenetic trees of plant species. However, building such a tree that is well-supported can be a difficult task, even when a subset of close plant species is considered. Usually, the difficulty raises from a few core genes disturbing the phylogenetic information, due for example from problems of homoplasy. Fortunately, a reliable phylogenetic tree can be obtained once these problematic genes are identified and removed from the analysis.Therefore, in this paper we address the problem of finding the largest subset of core genomes which allows to build the best supported tree.

Results

As an exhaustive study of all core genes combination is untractable in practice, since the combinatorics of the situation made it computationally infeasible, we investigate three well-known metaheuristics to solve this optimization problem. More precisely, we design and compare distributed approaches using genetic algorithm, particle swarm optimization, and simulated annealing. The latter approach is a new contribution and therefore is described in details, whereas the two former ones have been already studied in previous works. They have been designed de novo in a new platform, and new experiments have been achieved on a larger set of chloroplasts, to compare together these three metaheuristics.

Conclusions

The ways genes affect both tree topology and supports are assessed using statistical tools like Lasso or dummy logistic regression, in an hybrid approach of the genetic algorithm. By doing so, we are able to provide the most supported trees based on the largest subsets of core genes.

A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model

In this article, a new Python package for nucleotide sequences clustering is proposed. This package, freely available on-line, implements a Laplacian eigenmap embedding and a Gaussian Mixture Model for DNA clustering. It takes nucleotide sequences as input, and produces the optimal number of clusters along with a relevant visualization. Despite the fact that we did not optimise the computational speed, our method still performs reasonably well in practice. Our focus was mainly on data analytics and accuracy and as a result, our approach outperforms the state of the art, even in the case of divergent sequences. Furthermore, an a priori knowledge on the number of clusters is not required here. For the sake of illustration, this method is applied on a set of 100 DNA sequences taken from the mitochondrially encoded NADH dehydrogenase 3 (ND3) gene, extracted from a collection of Platyhelminthes and Nematoda species. The resulting clusters are tightly consistent with the phylogenetic tree computed using a maximum likelihood approach on gene alignment. They are coherent too with the NCBI taxonomy. Further test results based on synthesized data are then provided, showing that the proposed approach is better able to recover the clusters than the most widely used software, namely Cd-hit-est and BLASTClust.

Systematic investigations of gene effects on both topologies and supports: An Echinococcus illustration

In this paper, we propose a high performance computing toolbox implementing efficient statistical methods for the study of phylogenies. This toolbox, which implements logit models and LASSO-type penalties, gives a way to better understand, measure, and compare the impact of each gene on a global phylogeny. As an application, we study the Echinococcus phylogeny, which is often considered as a particularly difficult example. Mitochondrial and nuclear genomes (19 coding sequences) of nine Echinococcus species are considered in order to investigate the molecular phylogeny of this genus. First, we check that the 19 gene trees lead to 19 totally different unsupported topologies (a topology is the sister relationship when both branch lengths and supports are ignored in a phylogenetic tree), while using the 19 genes as a whole are not sufficient for estimating the phylogeny. In order to circumvent this issue and understand the impact of the genes, we computed 43,796 trees using combinations ranging from 13 to 19 genes. By doing so, 15 topologies are obtained. Four particular topologies, appearing more robust and frequent, are then selected for more precise investigation. Refining further our statistical analysis, a particularly robust topology is extracted. We also carefully demonstrate the influence of nuclear genes on the likelihood of the phylogeny.

Simulation-based estimation of branching models for LTR retrotransposons

Motivation

LTR retrotransposons are mobile elements that are able, like retroviruses, to copy and move inside eukaryotic genomes. In the present work, we propose a branching model for studying the propagation of LTR retrotransposons in these genomes. This model allows us to take into account both the positions and the degradation level of LTR retrotransposons copies. In our model, the duplication rate is also allowed to vary with the degradation level.

Results

Various functions have been implemented in order to simulate their spread and visualization tools are proposed. Based on these simulation tools, we have developed a first method to evaluate the parameters of this propagation model. We applied this method to the study of the spread of the transposable elements ROO, GYPSY and DM412 on a chromosome of Drosophila melanogaster .

Availability and Implementation

Our proposal has been implemented using Python software. Source code is freely available on the web at https://github.com/SergeMOULIN/retrotransposons-spread .

Contact

serge.moulin@univ-fcomte.fr.

Supplementary information

are available at Bioinformatics online.

A Bregman-proximal point algorithm for robust non-negative matrix factorization with possible missing values and outliers - application to gene expression analysis

Background

Non-Negative Matrix factorization has become an essential tool for feature extraction in a wide spectrum of applications. In the present work, our objective is to extend the applicability of the method to the case of missing and/or corrupted data due to outliers.

Results

An essential property for missing data imputation and detection of outliers is that the uncorrupted data matrix is low rank, i.e. has only a small number of degrees of freedom. We devise a new version of the Bregman proximal idea which preserves nonnegativity and mix it with the Augmented Lagrangian approach for simultaneous reconstruction of the features of interest and detection of the outliers using a sparsity promoting ℓ₁ penality.

Conclusions

An application to the analysis of gene expression data of patients with bladder cancer is finally proposed.

Dendrochemical assessment of mercury releases from a pond and dredged-sediment landfill impacted by a chlor-alkali plant

Although current Hg emissions from industrial activities may be accurately monitored, evidence of past releases to the atmosphere must rely on one or more environmental proxies. We used Hg concentrations in tree cores collected from poplars and willows to investigate the historical changes of Hg emissions from a dredged sediment landfill and compared them to a nearby control location. Our results demonstrated the potential value of using dendrochemistry to record historical Hg emissions from past industrial activities.

Chaos in DNA evolution

In this paper, we explain why the chaotic mutation (CM) model of J. M. Bahi and C. Michel (2008) simulates the genes mutations over time with good accuracy. It is firstly shown that the CM model is a truly chaotic one, as it is defined by Devaney. Then, it is established that mutations occurring in genes mutations have indeed a same chaotic dynamic, thus making relevant the use of chaotic models for genomes evolution. Transposition and inversion dynamics are finally investigated.

Fluoroquinolone Resistance Mechanisms and population structure of Enterobacter cloacae non-susceptible to Ertapenem in North-Eastern France

Fluoroquinolone (FQ) agents are a potential resort to treat infection due to Enterobacteriaceae producing extended spectrum β-lactamase and susceptible to FQ. In a context of increase of non-susceptibility to carbapenems among Enterobacteriaceae, we characterized FQ resistance mechanisms in 75 Enterobacter cloacae isolates non-susceptible to ertapenem in North-Eastern France in 2012 and describe the population structure by pulsed field gel electrophoresis (PFGE) and multi-locus sequence typing (MLST). Among them, 14.7% (12/75) carried a carbapenemase-encoding gene. Except one isolate producing VIM-1, the carbapenemase-producing isolates carried the well-known IncL/M pOXA48a plasmid. Most of the isolates (59/75) harbored at least a FQ-R determinant. qnr genes were predominant (40%, 30/75). The MLST study revealed that E. cloacae isolates’ clonality was wide [24 different sequence types (STs)]. The more widespread STs were ST74, ST101, ST110, ST114, and ST133. Carbapenem MICs were higher for E. cloacae ST74 than for other E. cloacae isolates. Plasmid-mediated quinolone resistance determinants were more often observed in E. cloacae ST74 isolates. These findings showed that (i) pOXA-48a is spreading in North-Eastern France, (ii) qnr is preponderant in E. cloacae, (iii) E. cloacae comprised a large amount of lineages spreading in North-Eastern France, and (iv) FQ as an alternative to β-lactams to treat ertapenem non-susceptible Enterobacteriaceae are compromised.

The study of unfoldable self-avoiding walks — Application to protein structure prediction software

Self-avoiding walks (SAWs) are the source of very difficult problems in probability and enumerative combinatorics. They are of great interest as, for example, they are the basis of protein structure prediction (PSP) in bioinformatics. The authors of this paper have previously shown that, depending on the prediction algorithm, the sets of obtained walk conformations differ: For example, all the SAWs can be generated using stretching-based algorithms whereas only the unfoldable SAWs can be obtained with methods that iteratively fold the straight line. A deeper study of (non-)unfoldable SAWs is presented in this paper. The contribution is first a survey of what is currently known about these sets. In particular, we provide clear definitions of various subsets of SAWs related to pivot moves (unfoldable and non-unfoldable SAWs, etc.) and the first results that we have obtained, theoretically or computationally, on these sets. Then a new theorem on the number of non-unfoldable SAWs is demonstrated. Finally, a list of open questions is provided and the consequences on the PSP problem is proposed.

What It Takes to Be a Pseudomonas aeruginosa? The Core Genome of the Opportunistic Pathogen Updated

Pseudomonas aeruginosa is an opportunistic bacterial pathogen able to thrive in highly diverse ecological niches and to infect compromised patients. Its genome exhibits a mosaic structure composed of a core genome into which accessory genes are inserted en bloc at specific sites. The size and the content of the core genome are open for debate as their estimation depends on the set of genomes considered and the pipeline of gene detection and clustering. Here, we redefined the size and the content of the core genome of P. aeruginosa from fully re-analyzed genomes of 17 reference strains. After the optimization of gene detection and clustering parameters, the core genome was defined at 5,233 orthologs, which represented ~ 88% of the average genome. Extrapolation indicated that our panel was suitable to estimate the core genome that will remain constant even if new genomes are added. The core genome contained resistance determinants to the major antibiotic families as well as most metabolic, respiratory, and virulence genes. Although some virulence genes were accessory, they often related to conserved biological functions. Long-standing prophage elements were subjected to a genetic drift to eventually display a G+C content as higher as that of the core genome. This contrasts with the low G+C content of highly conserved ribosomal genes. The conservation of metabolic and respiratory genes could guarantee the ability of the species to thrive on a variety of carbon sources for energy in aerobiosis and anaerobiosis. Virtually all the strains, of environmental or clinical origin, have the complete toolkit to become resistant to the major antipseudomonal compounds and possess basic pathogenic mechanisms to infect humans. The knowledge of the genes shared by the majority of the P. aeruginosa isolates is a prerequisite for designing effective therapeutics to combat the wide variety of human infections.

Population structure and antimicrobial susceptibility of Pseudomonas aeruginosa from animal infections in France

Background

Pseudomonas aeruginosa is a major human pathogen, which also affects animals. It is thought that P. aeruginosa has a non-clonal epidemic population structure, with distinct isolates found in humans, animals or the environment. However, very little is known about the structure of the P. aeruginosa population from diseased animals. Data on antimicrobial resistance are also scarce.

Results

Thirty-four already registered and 19 new MLST profiles were identified. Interestingly, a few clones were more prevalent, and clones associated to human outbreaks were also detected. Multidrug resistance phenotypes were overall rare.

Conclusion

We highlight the non clonal structure of the population and show a higher prevalence of specific clones, possibly correlating with higher pathogenicity. The low proportion of antimicrobial resistance contrasts with the high resistance rate of human isolates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-015-0324-x) contains supplementary material, which is available to authorized users.

A Complete Security Framework for Wireless Sensor Networks

Wireless sensor networks are often deployed in public or otherwise untrusted and even hostile environments, which prompt a number of security issues. Although security is a necessity in other types of networks, it is much more so in sensor networks due to the resource-constraint, susceptibility to physical capture, and wireless nature. Till now, most of the security approaches proposed for sensor networks present single solution for particular and single problem. Therefore, to address the special security needs of sensor networks as a whole we introduce a security framework. In their framework, the authors emphasize the following areas: (1) secure communication infrastructure, (2) secure scheduling, and (3) a secure data aggregation algorithm. Due to resource constraints, specific strategies are often necessary to preserve the network's lifetime and its quality of service. For instance, to reduce communication costs, data can be aggregated through the network, or nodes can go to sleep mode periodically (nodes scheduling). These strategies must be proven as secure, but protocols used to guarantee this security must be compatible with the resource preservation requirement. To achieve this goal, secure communications in such networks will be defined, together with the notions of secure scheduling and secure aggregation. The concepts of indistinguability, nonmalleability, and message detection resistance will thus be adapted to communications in wireless sensor networks. Finally, some of these security properties will be evaluated in concrete case studies.

Population structure of clinical Pseudomonas aeruginosa from West and Central African countries

BACKGROUND

Pseudomonas aeruginosa (PA) has a non-clonal, epidemic population with a few widely distributed and frequently encountered sequence types (STs) called 'high-risk clusters'. Clinical P. aeruginosa (clinPA) has been studied in all inhabited continents excepted in Africa, where a very few isolates have been analyzed. Here, we characterized a collection of clinPA isolates from four countries of West and Central Africa.

METHODOLOGY

184 non-redundant isolates of clinPA from hospitals of Senegal, Ivory Coast, Nigeria, and Central African Republic were genotyped by MLST. We assessed their resistance level to antibiotics by agar diffusion and identified the extended-spectrum β-lactamases (ESBLs) and metallo-β-lactamases (MBLs) by sequencing. The population structure of the species was determined by a nucleotide-based analysis of the entire PA MLST database and further localized on the phylogenetic tree (i) the sequence types (STs) of the present collection, (ii) the STs by continents, (iii) ESBL- and MBL-producing STs from the MLST database.

PRINCIPAL FINDINGS

We found 80 distinct STs, of which 24 had no relationship with any known STs. 'High-risk' international clonal complexes (CC155, CC244, CC235) were frequently found in West and Central Africa. The five VIM-2-producing isolates belonged to CC233 and CC244. GES-1 and GES-9 enzymes were produced by one CC235 and one ST1469 isolate, respectively. We showed the spread of 'high-risk' international clonal complexes, often described as multidrug-resistant on other continents, with a fully susceptible phenotype. The MBL- and ESBL-producing STs were scattered throughout the phylogenetic tree and our data suggest a poor association between a continent and a specific phylogroup.

CONCLUSIONS

ESBL- and MBL-encoding genes are borne by both successful international clonal complexes and distinct local STs in clinPA of West and Central Africa. Furthermore, our data suggest that the spread of a ST could be either due to its antibiotic resistance or to features independent from the resistance to antibiotics.

Molecular epidemiology of OXA-48-producing Klebsiella pneumoniae in France

We characterized 53 OXA-48-producing Klebsiella pneumoniae (OXA-48-Kp) isolated between 2011 and 2013 in 21 French hospitals. All the isolates were genotyped using MLST and PFGE and the population structure of the species was determined by a nucleotide-based analysis of the entire K. pneumoniae MLST database. Most of the OXA-48-Kp isolates also produced CTX-M-15 and remained susceptible to imipenem and meropenem. The isolates were distributed into 20 STs, of which five were dominant (ST15, ST101, ST147, ST395 and ST405). All the OXA-48-Kp clustered in the major clade of K. pneumoniae KpI.

Neural networks and chaos: construction, evaluation of chaotic networks, and prediction of chaos with multilayer feedforward networks

Many research works deal with chaotic neural networks for various fields of application. Unfortunately, up to now, these networks are usually claimed to be chaotic without any mathematical proof. The purpose of this paper is to establish, based on a rigorous theoretical framework, an equivalence between chaotic iterations according to Devaney and a particular class of neural networks. On the one hand, we show how to build such a network, on the other hand, we provide a method to check if a neural network is a chaotic one. Finally, the ability of classical feedforward multilayer perceptrons to learn sets of data obtained from a dynamical system is regarded. Various boolean functions are iterated on finite states. Iterations of some of them are proven to be chaotic as it is defined by Devaney. In that context, important differences occur in the training process, establishing with various neural networks that chaotic behaviors are far more difficult to learn.