scholarly journals The Sinorhizobium fredii HH103 Genome: A Comparative Analysis With S. fredii Strains Differing in Their Symbiotic Behavior With Soybean

2015 ◽  
Vol 28 (7) ◽  
pp. 811-824 ◽  
Author(s):  
José-María Vinardell ◽  
Sebastián Acosta-Jurado ◽  
Susanne Zehner ◽  
Michael Göttfert ◽  
Anke Becker ◽  
...  
Keyword(s):  
Core Genome ◽  
Comparative Genomic ◽  
Secretion Systems ◽  
Sinorhizobium Fredii ◽  
The Core ◽  
Sensing Systems ◽  
Plot Analysis ◽  
Genomic Analyses ◽  
Surface Polysaccharide ◽  
Protein Secretion Systems

Sinorhizobium fredii HH103 is a fast-growing rhizobial strain infecting a broad range of legumes including both American and Asiatic soybeans. In this work, we present the sequencing and annotation of the HH103 genome (7.25 Mb), consisting of one chromosome and six plasmids and representing the structurally most complex sinorhizobial genome sequenced so far. Comparative genomic analyses of S. fredii HH103 with strains USDA257 and NGR234 showed that the core genome of these three strains contains 4,212 genes (61.7% of the HH103 genes). Synteny plot analysis revealed that the much larger chromosome of USDA257 (6.48 Mb) is colinear to the HH103 (4.3 Mb) and NGR324 chromosomes (3.9 Mb). An additional region of the USDA257 chromosome of about 2 Mb displays similarity to plasmid pSfHH103e. Remarkable differences exist between HH103 and NGR234 concerning nod genes, flavonoid effect on surface polysaccharide production, and quorum-sensing systems. Furthermore a number of protein secretion systems have been found. Two genes coding for putative type III–secreted effectors not previously described in S. fredii, nopI and gunA, have been located on the HH103 genome. These differences could be important to understand the different symbiotic behavior of S. fredii strains HH103, USDA257, and NGR234 with soybean.

scholarly journals CoreCruncher: Fast and Robust Construction of Core Genomes in Large Prokaryotic Data Sets

2020 ◽  
Author(s):  
Connor D Harris ◽  
Ellis L Torrance ◽  
Kasie Raymann ◽  
Louis-Marie Bobay
Keyword(s):  
Core Genome ◽  
Genomic Data ◽  
Data Sets ◽  
The Core ◽  
Genomic Analyses ◽  
Massive Accumulation ◽  
Genome Comparisons

Abstract The core genome represents the set of genes shared by all, or nearly all, strains of a given population or species of prokaryotes. Inferring the core genome is integral to many genomic analyses, however, most methods rely on the comparison of all the pairs of genomes; a step that is becoming increasingly difficult given the massive accumulation of genomic data. Here, we present CoreCruncher; a program that robustly and rapidly constructs core genomes across hundreds or thousands of genomes. CoreCruncher does not compute all pairwise genome comparisons and uses a heuristic based on the distributions of identity scores to classify sequences as orthologs or paralogs/xenologs. Although it is much faster than current methods, our results indicate that our approach is more conservative than other tools and less sensitive to the presence of paralogs and xenologs. CoreCruncher is freely available from: https://github.com/lbobay/CoreCruncher. CoreCruncher is written in Python 3.7 and can also run on Python 2.7 without modification. It requires the python library Numpy and either Usearch or Blast. Certain options require the programs muscle or mafft.

scholarly journals Global genomic similarity and core genome sequence diversity of the Streptococcus genus as a toolkit to identify closely related bacterial species in complex environments.

2018 ◽  
Author(s):  
Hugo R Barajas de la Torre ◽  
Miguel Romero ◽  
Shamayim Martínez-Sánchez ◽  
Luis D Alcaraz
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Core Genome ◽  
Comparative Genomic ◽  
Rrna Gene ◽  
Gene Phylogeny ◽  
The Core ◽  
Sequence Identity ◽  
Core Proteins ◽  
Genomic Similarity

Background. Comparative genomics between closely related bacterial strains can distinguish important features determining pathogenesis, antibiotic resistance, and phylogenetic structure. The Streptococcus genus is relevant to public health and food safety and it is well-represented (>100 genomes) in databases of publicly available databases. Streptococci are cosmopolitan, with multiple sources of isolation, from humans to dairy products. The Streptococcus genus has been classified by morphology, serotypes, 16S rRNA gene, and Multi Locus Sequence Types (MLST). The Genomic Similarity Score (GSS) is proposed as a tool to quantify genome level relatedness between species of Streptococcus. The Streptococcus core genome can be used to assess strain specific abundances in metagenomic sequences. Methods. A 16S rRNA gene phylogeny was calculated for 108 strains, belonging to 16 Streptococcus species and compared to a dendrogram using GSS pairwise distances for the same genomes. The core and pan-genome were calculated for these 108 genomes. The core genome sequences were analyzed and used as a resource to discriminate homologous fragment reads from closely related strains in metagenomic samples. Results. A total of 404 proteins are shared by all 108 Streptococcus genomes, which is the core genome. The pairwise amino acid identity values of the core proteins for all the compared strains and outgroups are reported. Lower sequence identity variation (90-100%) is predominantly found in core clusters containing ribosomal and translation-related proteins. For 48 core proteins (11.8%) no functional assignment could be made and those proteins have larger sequence identity variations than other core proteins. The sequence identity of the core genome diminishes as GSS score between species decreases. The GSS dendrogram recovers most of the clades in the 16S rRNA gene phylogeny while distinguishing between 16S polytomies (unresolved nodes). Finally, the core genome was used to distinguish between closely related species within human oral metagenomes. Discussion. The Streptococcus genus provides a benchmark dataset for comparative genomic studies due to the breath depth of genomic coverage. Comparing metagenomic shotgun fragment reads to the core genome using rapid alignment tools allows species-specific abundance estimates in metagenomic samples. Understanding of genomic variability and strains relatedness is the goal of tools like GSS, which make use of both pairwise shared core and pan-genomic homologous shared sequences for its calculation.

scholarly journals Global genomic similarity and core genome sequence diversity of the Streptococcus genus as a toolkit to identify closely related bacterial species in complex environments

PeerJ ◽  
2019 ◽  
Vol 6 ◽  
pp. e6233 ◽  
Author(s):  
Hugo R. Barajas ◽  
Miguel F. Romero ◽  
Shamayim Martínez-Sánchez ◽  
Luis D. Alcaraz
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Core Genome ◽  
Bacterial Species ◽  
Genomic Diversity ◽  
Comparative Genomic ◽  
Rrna Gene ◽  
Gene Phylogeny ◽  
The Core ◽  
Core Proteins

Background The Streptococcus genus is relevant to both public health and food safety because of its ability to cause pathogenic infections. It is well-represented (>100 genomes) in publicly available databases. Streptococci are ubiquitous, with multiple sources of isolation, from human pathogens to dairy products. The Streptococcus genus has traditionally been classified by morphology, serum types, the 16S ribosomal RNA (rRNA) gene, and multi-locus sequence types subject to in-depth comparative genomic analysis. Methods Core and pan-genomes described the genomic diversity of 108 strains belonging to 16 Streptococcus species. The core genome nucleotide diversity was calculated and compared to phylogenomic distances within the genus Streptococcus. The core genome was also used as a resource to recruit metagenomic fragment reads from streptococci dominated environments. A conventional 16S rRNA gene phylogeny reconstruction was used as a reference to compare the resulting dendrograms of average nucleotide identity (ANI) and genome similarity score (GSS) dendrograms. Results The core genome, in this work, consists of 404 proteins that are shared by all 108 Streptococcus. The average identity of the pairwise compared core proteins decreases proportionally to GSS lower scores, across species. The GSS dendrogram recovers most of the clades in the 16S rRNA gene phylogeny while distinguishing between 16S polytomies (unresolved nodes). The GSS is a distance metric that can reflect evolutionary history comparing orthologous proteins. Additionally, GSS resulted in the most useful metric for genus and species comparisons, where ANI metrics failed due to false positives when comparing different species. Discussion Understanding of genomic variability and species relatedness is the goal of tools like GSS, which makes use of the maximum pairwise shared orthologous sequences for its calculation. It allows for long evolutionary distances (above species) to be included because of the use of amino acid alignment scores, rather than nucleotides, and normalizing by positive matches. Newly sequenced species and strains could be easily placed into GSS dendrograms to infer overall genomic relatedness. The GSS is not restricted to ubiquitous conservancy of gene features; thus, it reflects the mosaic-structure and dynamism of gene acquisition and loss in bacterial genomes.

scholarly journals Phylogenomic and Molecular Demarcation of the Core Members of the PolyphyleticPasteurellaceaeGeneraActinobacillus,Haemophilus, andPasteurella

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Sohail Naushad ◽  
Mobolaji Adeolu ◽  
Nisha Goel ◽  
Bijendra Khadka ◽  
Aqeel Al-Dahwi ◽  
...  
Keyword(s):  
Phylogenetic Trees ◽  
Phylogenetic Analyses ◽  
Sensu Stricto ◽  
The Other ◽  
Comparative Genomic ◽  
Molecular Signatures ◽  
The Core ◽  
Conserved Signature Indels ◽  
Genomic Analyses ◽  
Large Clusters

The generaActinobacillus, Haemophilus,andPasteurellaexhibit extensive polyphyletic branching in phylogenetic trees and do not represent coherent clusters of species. In this study, we have utilized molecular signatures identified through comparative genomic analyses in conjunction with genome based and multilocus sequence based phylogenetic analyses to clarify the phylogenetic and taxonomic boundary of these genera. We have identified large clusters ofActinobacillus, Haemophilus,andPasteurellaspecies which represent the “sensu stricto” members of these genera. We have identified 3, 7, and 6 conserved signature indels (CSIs), which are specifically shared bysensu strictomembers ofActinobacillus, Haemophilus,andPasteurella, respectively. We have also identified two different sets of CSIs that are unique characteristics of the pathogen containing generaAggregatibacterandMannheimia, respectively. It is now possible to demarcate the generaActinobacillus sensu stricto, Haemophilus sensu stricto,andPasteurella sensu strictoon the basis of discrete molecular signatures. The other members of the generaActinobacillus, Haemophilus,andPasteurellathat do not fall within the “sensu stricto” clades and do not contain these molecular signatures should be reclassified as other genera. The CSIs identified here also provide useful diagnostic targets for the identification of current and novel members of the indicated genera.

scholarly journals Insights into the Evolution of Spermatogenesis-Related Ubiquitin–Proteasome System Genes in Abdominal Testicular Laurasiatherians

Genes ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1780
Author(s):  
Xiaoyue Ding ◽  
Li Cao ◽  
Yu Zheng ◽  
Xu Zhou ◽  
Xiaofang He ◽  
...  
Keyword(s):  
Sperm Cell ◽  
Rapid Evolution ◽  
Ubiquitin Proteasome System ◽  
Comparative Genomic ◽  
Functional Assays ◽  
The Core ◽  
Genomic Analyses ◽  
Ubiquitin Proteasome ◽  
Normal Spermatogenesis ◽  
Functional Analyses

During embryonic development in mammals, the testicles generally descend into the scrotum, making the testicular temperature 2–4 °C lower than the core temperature via heat exchange and clearance, and thus more beneficial for normal spermatogenesis. Failure to descend, known as cryptorchidism, carries a series of risks such as infertility and testicular cancer. However, some mammals have evolved abdominal testes while maintaining healthy reproduction. To explore the underlying molecular mechanism, we conducted comparative genomic analyses and functional assays on the spermatogenesis-related ubiquitin–proteasome system (UPS) genes essential to sperm formation in representative laurasiatherians. Here, positive selection and rapid evolution of spermatogenesis-related UPS genes were identified in the abdominal testicular laurasiatherians. Moreover, potential convergent amino acids were found between distantly related species with similar abdominal testicles and functional analyses showed RNF8 (V437I) in abdominal testicular species (437I) has a stronger ubiquitination ability, which suggests that the mammals with abdominal testes might exhibit enhanced sperm cell histone clearance to maintain sperm formation. This evidence implies that, in response to “cryptorchidism injury”, spermatogenesis-related UPS genes in the abdominal testicular species might have undergone adaptive evolution to stabilize sperm formation. Thus, our study could provide some novel insights into the reproductive adaptation in abdominal testicular mammals.

scholarly journals Genomic analysis of the type VI secretion systems in Pseudomonas spp.: novel clusters and putative effectors uncovered

Microbiology ◽  
2011 ◽  
Vol 157 (6) ◽  
pp. 1726-1739 ◽  
Author(s):  
Matthieu Barret ◽  
Frank Egan ◽  
Emilie Fargier ◽  
John P. Morrissey ◽  
Fergal O’Gara
Keyword(s):  
Meta Analysis ◽  
Genomic Analysis ◽  
Pseudomonas Stutzeri ◽  
Comparative Genomic ◽  
Secretion Systems ◽  
Genomic Context ◽  
Type Vi Secretion ◽  
Multiple Protein ◽  
Multiple Strains ◽  
Protein Secretion Systems

Bacteria encode multiple protein secretion systems that are crucial for interaction with the environment and with hosts. In recent years, attention has focused on type VI secretion systems (T6SSs), which are specialized transporters widely encoded in Proteobacteria. The myriad of processes associated with these secretion systems could be explained by subclasses of T6SS, each involved in specialized functions. To assess diversity and predict function associated with different T6SSs, comparative genomic analysis of 34 Pseudomonas genomes was performed. This identified 70 T6SSs, with at least one locus in every strain, except for Pseudomonas stutzeri A1501. By comparing 11 core genes of the T6SS, it was possible to identify five main Pseudomonas phylogenetic clusters, with strains typically carrying T6SSs from more than one clade. In addition, most strains encode additional vgrG and hcp genes, which encode extracellular structural components of the secretion apparatus. Using a combination of phylogenetic and meta-analysis of transcriptome datasets it was possible to associate specific subsets of VgrG and Hcp proteins with each Pseudomonas T6SS clade. Moreover, a closer examination of the genomic context of vgrG genes in multiple strains highlights a number of additional genes associated with these regions. It is proposed that these genes may play a role in secretion or alternatively could be new T6S effectors.

scholarly journals Comparative Genomics and CAZyme Genome Repertoires of Marine Zobellia amurskyensis KMM 3526T and Zobellia laminariae KMM 3676T

Marine Drugs ◽  
2019 ◽  
Vol 17 (12) ◽  
pp. 661 ◽  
Author(s):  
Nadezhda Chernysheva ◽  
Evgeniya Bystritskaya ◽  
Anna Stenkova ◽  
Ilya Golovkin ◽  
Olga Nedashkovskaya ◽  
...  
Keyword(s):  
Comparative Genomics ◽  
Core Genome ◽  
Genomic Analysis ◽  
Comparative Genomic Analysis ◽  
Active Enzyme ◽  
Comparative Genomic ◽  
The Core ◽  
Pan Genome ◽  
Carbohydrate Active Enzyme ◽  
Pharmaceutical Industries

We obtained two novel draft genomes of type Zobellia strains with estimated genome sizes of 5.14 Mb for Z. amurskyensis KMM 3526Т and 5.16 Mb for Z. laminariae KMM 3676Т. Comparative genomic analysis has been carried out between obtained and known genomes of Zobellia representatives. The pan-genome of Zobellia genus is composed of 4853 orthologous clusters and the core genome was estimated at 2963 clusters. The genus CAZome was represented by 775 GHs classified into 62 families, 297 GTs of 16 families, 100 PLs of 13 families, 112 CEs of 13 families, 186 CBMs of 18 families and 42 AAs of six families. A closer inspection of the carbohydrate-active enzyme (CAZyme) genomic repertoires revealed members of new putative subfamilies of GH16 and GH117, which can be biotechnologically promising for production of oligosaccharides and rare monomers with different bioactivities. We analyzed AA3s, among them putative FAD-dependent glycoside oxidoreductases (FAD-GOs) being of particular interest as promising biocatalysts for glycoside deglycosylation in food and pharmaceutical industries.

scholarly journals Comprehensive genome analysis of a pangolin-associated Paraburkholderia fungorum provides new insights into its secretion systems and virulence

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9733
Author(s):  
Ka Yun Tan ◽  
Avirup Dutta ◽  
Tze King Tan ◽  
Ranjeev Hari ◽  
Rofina Y. Othman ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Phylogenetic Analysis ◽  
Core Genome ◽  
Virulence Genes ◽  
Secretion Systems ◽  
Gram Negative ◽  
The Core ◽  
Physiological Processes ◽  
Number Of Genes ◽  
Different Types

Background Paraburkholderia fungorum (P. fungorum) is a Gram-negative environmental species that has been commonly used as a beneficial microorganism in agriculture as an agent for biocontrol and bioremediation. Its use in agriculture is controversial as many people believe that it could harm human health; however, there is no clear evidence to support. Methodology The pangolin P. fungorum (pangolin Pf) genome has a genomic size of approximately 7.7 Mbps with N50 of 69,666 bps. Our study showed that pangolin Pf is a Paraburkholderia fungorum supported by evidence from the core genome SNP-based phylogenetic analysis and the ANI analysis. Functional analysis has shown that the presence of a considerably large number of genes related to stress response, virulence, disease, and defence. Interestingly, we identified different types of secretion systems in the genome of pangolin Pf, which are highly specialized and responsible for a bacterium’s response to its environment and in physiological processes such as survival, adhesion, and adaptation. The pangolin Pf also shared some common virulence genes with the known pathogenic member of the Burkholderiales. These genes play important roles in adhesion, motility, and invasion. Conclusion This study may provide better insights into the functions, secretion systems and virulence of this pangolin-associated bacterial strain. The addition of this genome sequence is also important for future comparative analysis and functional work of P. fungorum.

scholarly journals Global genomic similarity and core genome sequence diversity of the Streptococcus genus as a toolkit to identify closely related bacterial species in complex environments.

2018 ◽  
Author(s):  
Hugo R Barajas de la Torre ◽  
Miguel Romero ◽  
Shamayim Martínez-Sánchez ◽  
Luis D Alcaraz
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Core Genome ◽  
Comparative Genomic ◽  
Rrna Gene ◽  
Gene Phylogeny ◽  
The Core ◽  
Sequence Identity ◽  
Core Proteins ◽  
Genomic Similarity

Background. Comparative genomics between closely related bacterial strains can distinguish important features determining pathogenesis, antibiotic resistance, and phylogenetic structure. The Streptococcus genus is relevant to public health and food safety and it is well-represented (>100 genomes) in databases of publicly available databases. Streptococci are cosmopolitan, with multiple sources of isolation, from humans to dairy products. The Streptococcus genus has been classified by morphology, serotypes, 16S rRNA gene, and Multi Locus Sequence Types (MLST). The Genomic Similarity Score (GSS) is proposed as a tool to quantify genome level relatedness between species of Streptococcus. The Streptococcus core genome can be used to assess strain specific abundances in metagenomic sequences. Methods. A 16S rRNA gene phylogeny was calculated for 108 strains, belonging to 16 Streptococcus species and compared to a dendrogram using GSS pairwise distances for the same genomes. The core and pan-genome were calculated for these 108 genomes. The core genome sequences were analyzed and used as a resource to discriminate homologous fragment reads from closely related strains in metagenomic samples. Results. A total of 404 proteins are shared by all 108 Streptococcus genomes, which is the core genome. The pairwise amino acid identity values of the core proteins for all the compared strains and outgroups are reported. Lower sequence identity variation (90-100%) is predominantly found in core clusters containing ribosomal and translation-related proteins. For 48 core proteins (11.8%) no functional assignment could be made and those proteins have larger sequence identity variations than other core proteins. The sequence identity of the core genome diminishes as GSS score between species decreases. The GSS dendrogram recovers most of the clades in the 16S rRNA gene phylogeny while distinguishing between 16S polytomies (unresolved nodes). Finally, the core genome was used to distinguish between closely related species within human oral metagenomes. Discussion. The Streptococcus genus provides a benchmark dataset for comparative genomic studies due to the breath depth of genomic coverage. Comparing metagenomic shotgun fragment reads to the core genome using rapid alignment tools allows species-specific abundance estimates in metagenomic samples. Understanding of genomic variability and strains relatedness is the goal of tools like GSS, which make use of both pairwise shared core and pan-genomic homologous shared sequences for its calculation.

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