scholarly journals A rapid and simple method for assessing and representing genome sequence relatedness

2019 ◽  
Author(s):  
M Briand ◽  
M Bouzid ◽  
G Hunault ◽  
M Legeay ◽  
M Fischer-Le Saux ◽  
...  
Keyword(s):  
Circle Packing ◽  
Bacterial Species ◽  
Genomic Sequences ◽  
Species Delineation ◽  
Genome Sequences ◽  
Simple Method ◽  
Computationally Intensive ◽  
Sequence Relatedness ◽  
User Friendly

AbstractCoherent genomic groups are frequently used as a proxy for bacterial species delineation through computation of overall genome relatedness indices (OGRI). Average nucleotide identity (ANI) is a widely employed method for estimating relatedness between genomic sequences. However, pairwise comparisons of genome sequences based on ANI is relatively computationally intensive and therefore precludes analyses of large datasets composed of thousands of genome sequences.In this work we proposed a workflow to compute and visualize relationships between genomic sequences. A dataset containing more than 3,500 Pseudomonas genome sequences was successfully classified with an alternative OGRI based on k-mer counts in few hours with the same precision as ANI. A new visualization method based on zoomable circle packing was employed for assessing relationships among the 350 groups generated. Amendment of databases with these Pseudomonas groups greatly improved the classification of metagenomic read sets with k-mer-based classifier.The developed workflow was integrated in the user-friendly KI-S tool that is available at the following address:https://iris.angers.inra.fr/galaxypub-cfbp.

scholarly journals Draft Genome Sequences of Four Aeromonas salmonicida subsp. achromogenes Strains, 23051, 23053, 23055, and 23056, Isolated from Senegalese Sole (Solea senegalensis)

2019 ◽  
Vol 8 (33) ◽  
Author(s):  
Antony T. Vincent ◽  
Alain Le Breton ◽  
Alex Bernatchez ◽  
Cynthia Gagné-Thivierge ◽  
Valérie E. Paquet ◽  
...  
Keyword(s):  
Bacterial Species ◽  
Draft Genome ◽  
Aeromonas Salmonicida ◽  
Large Majority ◽  
Genomic Sequences ◽  
Solea Senegalensis ◽  
Senegalese Sole ◽  
Genome Sequences ◽  
Content Type ◽  
Genomic Analyses

The bacterial species Aeromonas salmonicida officially has five subspecies. A large majority of the currently available sequences come from Aeromonas salmonicida subsp. salmonicida, which causes furunculosis in salmonids. We present the genomic sequences of four Aeromonas salmonicida subsp. achromogenes strains. This will help increase the robustness of genomic analyses for this subspecies.

scholarly journals Genome analysis-based reclassification of Pseudomonas fuscovaginae and Pseudomonas shirazica as later heterotypic synonyms of Pseudomonas asplenii and Pseudomonas asiatica, respectively

2020 ◽  
Vol 70 (5) ◽  
pp. 3547-3552 ◽  
Author(s):  
Mari Tohya ◽  
Shin Watanabe ◽  
Tatsuya Tada ◽  
Htay Htay Tin ◽  
Teruo Kirikae
Keyword(s):  
Dna Hybridization ◽  
Type Species ◽  
Bacterial Species ◽  
Taxonomic Status ◽  
Species Delineation ◽  
Genome Sequences ◽  
Content Type ◽  
Link Type ◽  
Type Strains ◽  
Group Species

This study was conducted to clarify the taxonomic status of the species Pseudomonas fuscovaginae and Pseudomonas shirazica . Whole genome sequences for the type strains of P. fuscovaginae and P. shirazica were compared against the closely related type strains of the Pseudomonas putida group and the Pseudomonas fluorescens group species. Average nucleotide identity and digital DNA–DNA hybridization values between P. fuscovaginae LMG 2158T and Pseudomonas asplenii ATCC 23835T were 98.4 and 85.5 %, and between P. shirazica VM14T and Pseudomonas asiatica RYU5T were 99.3 and 95.3 %. These values were greater than recognized thresholds for bacterial species delineation, indicating that they belong to the same genomospecies, respectively. Therefore, P. fuscovaginae and P. shirazica should be reclassified as later heterotypic synonyms of P. asplenii and P. asiatica , respectively.

scholarly journals Tracking the Taxonomy of the GenusBifidobacteriumBased on a Phylogenomic Approach

2017 ◽  
Vol 84 (4) ◽  
Author(s):  
Gabriele Andrea Lugli ◽  
Christian Milani ◽  
Sabrina Duranti ◽  
Leonardo Mancabelli ◽  
Marta Mangifesta ◽  
...  
Keyword(s):  
New Technologies ◽  
Bacterial Species ◽  
Bacterial Genome ◽  
Bacterial Taxonomy ◽  
Genome Sequences ◽  
Content Type ◽  
Complete Bacterial Genome ◽  
Novel Taxa

ABSTRACTFor decades, bacterial taxonomy has been based onin vitromolecular biology techniques and comparison of molecular marker sequences to measure the degree of genetic similarity and deduce phylogenetic relatedness of novel bacterial species to reference microbial taxa. Due to the advent of the genomic era, access to complete bacterial genome contents has become easier, thereby presenting the opportunity to precisely investigate the overall genetic diversity of microorganisms. Here, we describe a high-accuracy phylogenomic approach to assess the taxonomy of members of the genusBifidobacteriumand identify apparent misclassifications in current bifidobacterial taxonomy. The developed method was validated by the classification of seven novel taxa belonging to the genusBifidobacteriumby employing their overall genetic content. The results of this study demonstrate the potential of this whole-genome approach to become the gold standard for phylogenomics-based taxonomic classification of bacteria.IMPORTANCENowadays, next-generation sequencing has given access to genome sequences of the currently known bacterial taxa. The public databases constructed by means of these new technologies allowed comparison of genome sequences between microorganisms, providing information to perform genomic, phylogenomic, and evolutionary analyses. In order to avoid misclassifications in the taxonomy of novel bacterial isolates, new (bifido)bacterial taxons should be validated with a phylogenomic assessment like the approach presented here.

scholarly journals Genome sequences hot and cold: a database of organisms with defined optimal growth temperatures

2021 ◽  
Author(s):  
Karla Helena-Bueno ◽  
Charlotte Rebecca Brown ◽  
Egor Konyk ◽  
Sergey Melnikov
Keyword(s):  
Growth Temperature ◽  
Bacterial Species ◽  
Protein Sequences ◽  
Optimal Growth ◽  
Growth Conditions ◽  
Biological Molecules ◽  
Genomic Sequences ◽  
Genome Sequences ◽  
Optimal Growth Temperature ◽  
Database Interface

Despite the rapidly increasing number of organisms with sequenced genomes, there is no existing resource that simultaneously contains information about genome sequences and the optimal growth conditions for a given species. In the absence of such a resource, we cannot immediately sort genomic sequences by growth conditions, making it difficult to study how organisms and biological molecules adapt to distinct environments. To address this problem, we have created a database called GSHC (Genome Sequences: Hot, Cold, and everything in between). This database, available at http://melnikovlab.com/gshc, brings together information about the genomic sequences and optimal growth temperatures for 25,324 species, including ~89% of the bacterial species with known genome sequences. Using this database, it is now possible to readily compare genomic sequences from thousands of species and correlate variations in genes and genomes with optimal growth temperatures, at the scale of the entire tree of life. The database interface allows users to retrieve protein sequences sorted by optimal growth temperature for their corresponding species, providing a tool to explore how organisms, genomes, and individual proteins and nucleic acids adapt to certain temperatures. We hope that this database will contribute to medicine and biotechnology by helping to create a better understanding of molecular adaptations to heat and cold, leading to new ways to preserve biological samples, engineer useful enzymes, and develop new biological materials and organisms with the desired tolerance to heat and cold.

Clin-mNGS: Automated Pipeline for Pathogen Detection from Clinical Metagenomic Data

2020 ◽  
Vol 15 ◽  
Author(s):  
Akshatha Prasanna ◽  
Vidya Niranjan
Keyword(s):  
Antimicrobial Resistance ◽  
High Performance ◽  
Pathogen Detection ◽  
Bacterial Species ◽  
Workflow Management ◽  
Metagenomic Data ◽  
Antimicrobial Resistance Genes ◽  
Culture Independent ◽  
Automated Pipeline ◽  
User Friendly

Background: Since bacteria are the earliest known organisms, there has been significant interest in their variety and biology, most certainly concerning human health. Recent advances in Metagenomics sequencing (mNGS), a culture-independent sequencing technology have facilitated an accelerated development in clinical microbiology and our understanding of pathogens. Objective: For the implementation of mNGS in routine clinical practice to become feasible, a practical and scalable strategy for the study of mNGS data is essential. This study presents a robust automated pipeline to analyze clinical metagenomic data for pathogen identification and classification. Method: The proposed Clin-mNGS pipeline is an integrated, open-source, scalable, reproducible, and user-friendly framework scripted using the Snakemake workflow management software. The implementation avoids the hassle of manual installation and configuration of the multiple command-line tools and dependencies. The approach directly screens pathogens from clinical raw reads and generates consolidated reports for each sample. Results: The pipeline is demonstrated using publicly available data and is tested on a desktop Linux system and a High-performance cluster. The study compares variability in results from different tools and versions. The versions of the tools are made user modifiable. The pipeline results in quality check, filtered reads, host subtraction, assembled contigs, assembly metrics, relative abundances of bacterial species, antimicrobial resistance genes, plasmid finding, and virulence factors identification. The results obtained from the pipeline are evaluated based on sensitivity and positive predictive value. Conclusion: Clin-mNGS is an automated Snakemake pipeline validated for the analysis of microbial clinical metagenomics reads to perform taxonomic classification and antimicrobial resistance prediction.

A Simple Method for Prediction of Effective Core Area and Index of Refraction of Single-mode Graded Index Fiber in the Low V Region

2014 ◽  
Vol 35 (4) ◽  
Author(s):  
Angshuman Majumdar ◽  
Satabdi Das ◽  
Sankar Gangopadhyay
Keyword(s):  
Refractive Index ◽  
Single Mode ◽  
Index Of Refraction ◽  
Core Area ◽  
Exact Results ◽  
Simple Method ◽  
Graded Index ◽  
Core Areas ◽  
V Region ◽  
User Friendly

AbstractBased on the simple power series formulation of fundamental mode developed by Chebyshev formalism in the low V region, we prescribe analytical expression for effective core area of graded index fiber. Taking step and parabolic index fibers as examples, we estimate the effective core areas as well as effective refractive index for different normalized frequencies (V number) having low values. We also show that our estimations match excellently with the available exact results. The concerned predictions by our method require little computation. Thus, this simple but accurate formalism will be user friendly for the system engineers.

scholarly journals Whole genome characterization of strains belonging to the Ralstonia solanacearum species complex and in silico analysis of TaqMan assays for detection in this heterogenous species complex

2021 ◽  
Author(s):  
Viola Kurm ◽  
Ilse Houwers ◽  
Claudia E. Coipan ◽  
Peter Bonants ◽  
Cees Waalwijk ◽  
...  
Keyword(s):  
Ralstonia Solanacearum ◽  
In Silico ◽  
Species Complex ◽  
Sequence Data ◽  
In Silico Analysis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequences ◽  
Pcr Assays

AbstractIdentification and classification of members of the Ralstonia solanacearum species complex (RSSC) is challenging due to the heterogeneity of this complex. Whole genome sequence data of 225 strains were used to classify strains based on average nucleotide identity (ANI) and multilocus sequence analysis (MLSA). Based on the ANI score (>95%), 191 out of 192(99.5%) RSSC strains could be grouped into the three species R. solanacearum, R. pseudosolanacearum, and R. syzygii, and into the four phylotypes within the RSSC (I,II, III, and IV). R. solanacearum phylotype II could be split in two groups (IIA and IIB), from which IIB clustered in three subgroups (IIBa, IIBb and IIBc). This division by ANI was in accordance with MLSA. The IIB subgroups found by ANI and MLSA also differed in the number of SNPs in the primer and probe sites of various assays. An in-silico analysis of eight TaqMan and 11 conventional PCR assays was performed using the whole genome sequences. Based on this analysis several cases of potential false positives or false negatives can be expected upon the use of these assays for their intended target organisms. Two TaqMan assays and two PCR assays targeting the 16S rDNA sequence should be able to detect all phylotypes of the RSSC. We conclude that the increasing availability of whole genome sequences is not only useful for classification of strains, but also shows potential for selection and evaluation of clade specific nucleic acid-based amplification methods within the RSSC.

scholarly journals Complete Genome Sequences of Two Hydrangea Ringspot Virus Isolates from Japan

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Akira Yusa ◽  
Nozomu Iwabuchi ◽  
Hiroaki Koinuma ◽  
Takuya Keima ◽  
Yutaro Neriya ◽  
...  
Keyword(s):  
Complete Genome ◽  
Rna Virus ◽  
Nucleotide Sequences ◽  
Ringspot Virus ◽  
Genomic Sequences ◽  
Genome Sequences ◽  
Hydrangea Macrophylla ◽  
Hydrangea Ringspot Virus ◽  
Virus Isolates

Hydrangea ringspot virus (HdRSV) is a plant RNA virus, naturally infecting Hydrangea macrophylla . Here, we report the first genomic sequences of two HdRSV isolates from hydrangea plants in Japan. The overall nucleotide sequences of these Japanese isolates were 96.0 to 96.3% identical to those of known European isolates.

scholarly journals Detection & Classification of Cardiac Arrhythmia

2017 ◽  
Vol 6 (1) ◽  
pp. 31
Author(s):  
Chetan M. Jadhav ◽  
V. K. Bairagi
Keyword(s):  
Cardiac Arrhythmia ◽  
Early Stage ◽  
Low Cost ◽  
Simple Method ◽  
Arrhythmia Detection ◽  
Ecg Signals ◽  
Electrocardiogram Signals ◽  
Electrical Impulses ◽  
Very High

<p>The term Arrhythmia refers to any change from the normal sequence in the electrical impulses. It is also treated as abnormal heart rhythms or irregular heartbeats. The rate of growth of Cardiac Arrhythmia disease is very high &amp; its effects can be observed in any age group in society. Arrhythmia detection can be done in many ways but effective &amp; simple method for detection &amp; diagnosis of  Cardiac Arrhythmia is by doing analysis of Electrocardiogram signals from ECG sensors. ECG signal can give us the detail information of heart activities, so we can use ECG signals to detect the rhythm &amp; behaviour of heart beats resulting into detection &amp; diagnosis of Cardiac Arrhythmia. In this paper new &amp; improved methodology for early Detection &amp; Classification of Cardiac Arrhythmia has been proposed. In this paper ECG signals are captured using ECG sensors &amp; this ECG signals are used &amp; processed to get the required data regarding heart beats of the human being &amp; then proposed methodology applies for Detection &amp; Classification of Cardiac Arrhythmia. Detection of Cardiac Arrhythmia using ECG signals allows us for easy &amp; reliable way with low cost solution to diagnose Arrhythmia in its prior early stage.</p>

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