scholarly journals A Positive Correlation between Bacterial GC Content and Growth Temperature

2021 ◽  
Author(s):  
En-Ze Hu ◽  
Xin-Ran Lan ◽  
Zhi-Ling Liu ◽  
Jie Gao ◽  
Deng-Ke Niu
Keyword(s):  
High Temperatures ◽  
Growth Temperature ◽  
Gc Content ◽  
Optimal Growth ◽  
Whole Genome ◽  
Genome Sequences ◽  
Optimal Growth Temperature ◽  
Positive Correlations ◽  
Rna Genes ◽  
Gc Contents

Abstract Background: Because GC pairs are more stable than AT pairs, GC-rich genomes were proposed to be more adapted to high temperatures than AT-rich genomes. Previous studies consistently showed positive correlations between growth temperature and the GC contents of structural RNA genes. However, for the whole genome sequences and the silent sites of the codons in protein-coding genes, the relationship between GC content and growth temperature is in a long-lasting debate. Results: With a dataset much larger than previous studies (681 bacteria and 155 archaea), our phylogenetic comparative analyses showed positive correlations between optimal growth temperature and GC content both in bacterial and archaeal structural RNA genes and in bacterial whole genome sequences, chromosomal sequences, plasmid sequences, core genes, and accessory genes. However, in the 155 archaea, we did not observe a significant positive correlation of optimal growth temperature with whole-genome GC content or GC content at four-fold degenerate sites. We randomly drew 155 samples from the 681 bacteria for 1000 rounds. In most cases (> 95%), the positive correlations between optimal growth temperature and genomic GC contents became statistically nonsignificant (P > 0.05). This result suggested that the small sample sizes might account for the lack of positive correlations between growth temperature and genomic GC content in the 155 archaea and the bacterial samples of previous studies. Conclusions: This study explains the previous contradictory observations and ends a long debate. Bacteria growing in high temperatures have higher GC contents. Thermal adaptation is one possible explanation for the positive association. Meanwhile, we should be open to other intricate explanations, including nonadaptive ones.

scholarly journals Significant Correlation between Growth Temperature and Guanine-Cytosine Content in Bacteria

2021 ◽  
Author(s):  
En-Ze Hu ◽  
Xin-Ran Lan ◽  
Zhi-Ling Liu ◽  
Jie Gao ◽  
Deng-Ke Niu
Keyword(s):  
Growth Temperature ◽  
Gc Content ◽  
Optimal Growth ◽  
Small Sample ◽  
Whole Genome ◽  
Genome Sequences ◽  
Optimal Growth Temperature ◽  
Positive Correlations ◽  
Rna Genes ◽  
Genomic Gc Content

AbstractBecause GC pairs are more stable than AT pairs, GC-rich sequences were proposed to be more adapted to high temperatures than AT-rich sequences. Previous studies consistently showed positive correlations between the growth temperature and the GC contents of structural RNA genes. However, for the whole genome sequences and the silent sites of the codons in protein-coding genes, the relationship between GC content and growth temperature is in a long-lasting debate. With a dataset much larger than previous studies (681 bacteria and 155 archaea), our phylogenetic comparative analyses showed positive correlations between optimal growth temperature and GC content exists, both in the structural RNA genes of bacteria and archaea and in bacterial whole genome sequences, chromosomal sequences, plasmid sequences, core genes, and accessory genes. However, in the 155 archaea, we did not observe a significant positive correlation of optimal growth temperature with whole-genome GC content or GC content at four-fold degenerate sites. We randomly drew 155 samples from the 681 bacteria for 1000 rounds. In most cases (> 95%), the positive correlations between optimal growth temperature and genomic GC content became statistically nonsignificant (P > 0.05). This result suggested that the small sample sizes might account for the lack of positive correlations between growth temperature and genomic GC content in the 155 archaea and the bacterial samples of previous studies.

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.

scholarly journals Characteristics of Phomopsis juglandina (Sacc.) Hohn. Associated with Dieback of Walnut in the Climatic Conditions of Southern Romania

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 46
Author(s):  
Cristina Mihaescu ◽  
Daniel Dunea ◽  
Adrian Gheorghe Bășa ◽  
Loredana Neagu Frasin
Keyword(s):  
Growth Temperature ◽  
Potential Evapotranspiration ◽  
Optimal Growth ◽  
Climatic Conditions ◽  
Cultural Characteristics ◽  
Optimal Growth Temperature ◽  
Conidial State ◽  
Optimal Ph

Phomopsis juglandina (Sacc.) Höhn., which is the conidial state of Diaporthe juglandina (Fuckel) Nitschke, and the main pathogen causing the dieback of branches and twigs of walnut was recently detected in many orchards from Romania. The symptomatological, morphological, ultrastructural, and cultural characteristics, as well as the pathogenicity of an isolate of this lignicolous fungus, were described and illustrated. The optimum periods for infection, under the conditions prevailing in Southern Romania, mainly occur in the spring (April) and autumn months (late September-beginning of October). Strong inverse correlations (p < 0.001) were found between potential evapotranspiration and lesion lengths on walnut branches in 2019. The pathogen forms two types of phialospores: alpha and beta; the role of beta phialospores is not well known in pathogenesis. In Vitro, the optimal growth temperature of mycelial hyphae was in the range of 22–26 °C, and the optimal pH is 4.4–7. This pathogen should be monitored continuously due to its potential for damaging infestations of intensive plantations.

The correlation between genomic G + C and optimal growth temperature of prokaryotes is robust: A reply to Marashi and Ghalanbor

2005 ◽  
Vol 330 (2) ◽  
pp. 357-360 ◽  
Author(s):  
Hector Musto ◽  
Hugo Naya ◽  
Alejandro Zavala ◽  
Hector Romero ◽  
Fernando Alvarez-Valin ◽  
...  
Keyword(s):  
Growth Temperature ◽  
Optimal Growth ◽  
Optimal Growth Temperature

Genomic GC level, optimal growth temperature, and genome size in prokaryotes

2006 ◽  
Vol 347 (1) ◽  
pp. 1-3 ◽  
Author(s):  
Héctor Musto ◽  
Hugo Naya ◽  
Alejandro Zavala ◽  
Héctor Romero ◽  
Fernando Alvarez-Valín ◽  
...  
Keyword(s):  
Genome Size ◽  
Growth Temperature ◽  
Optimal Growth ◽  
Optimal Growth Temperature

scholarly journals Building a tRNA thermometer to access the world’s biochemical diversity

2020 ◽  
Author(s):  
Emre Cimen ◽  
Sarah E. Jensen ◽  
Edward S. Buckler
Keyword(s):  
Growth Temperature ◽  
Input Data ◽  
Prediction Models ◽  
Extreme Temperature ◽  
Protein Composition ◽  
Network Models ◽  
Optimal Growth ◽  
Optimal Growth Temperature ◽  
Neural Network Models ◽  
Thermophilic Organism

ABSTRACTBecause ambient temperature affects biochemical reactions, organisms living in extreme temperature conditions adapt protein composition and structure to maintain biochemical functions. While it is not feasible to experimentally determine optimal growth temperature (OGT) for every known microbial species, organisms adapted to different temperatures have measurable differences in DNA, RNA, and protein composition that allow OGT prediction from genome sequence alone. In this study, we built a model using tRNA sequence to predict OGT. We used tRNA sequences from 100 archaea and 683 bacteria species as input to train two Convolutional Neural Network models. The first pairs individual tRNA sequences from different species to predict which comes from a more thermophilic organism, with accuracy ranging from 0.538 to 0.992. The second uses the complete set of tRNAs in a species to predict optimal growth temperature, achieving a maximum r2 of 0.86; comparable with other prediction accuracies in the literature despite a significant reduction in the quantity of input data. This model improves on previous OGT prediction models by providing a model with minimum input data requirements, removing laborious feature extraction and data preprocessing steps, and widening the scope of valid downstream analyses.

scholarly journals Comparative Genomics Reveals the Core Gene Toolbox for the Fungus-Insect Symbiosis

mBio ◽  
2018 ◽  
Vol 9 (3) ◽  
Author(s):  
Yan Wang ◽  
Matt Stata ◽  
Wei Wang ◽  
Jason E. Stajich ◽  
Merlin M. White ◽  
...  
Keyword(s):  
Entomopathogenic Fungi ◽  
Gc Content ◽  
Core Gene ◽  
Whole Genome ◽  
Black Flies ◽  
Genome Sequences ◽  
Free Living ◽  
Genomic Features ◽  
Insect Pathogens ◽  
Insect Gut

ABSTRACTModern genomics has shed light on many entomopathogenic fungi and expanded our knowledge widely; however, little is known about the genomic features of the insect-commensal fungi. Harpellales are obligate commensals living in the digestive tracts of disease-bearing insects (black flies, midges, and mosquitoes). In this study, we produced and annotated whole-genome sequences of nine Harpellales taxa and conducted the first comparative analyses to infer the genomic diversity within the members of the Harpellales. The genomes of the insect gut fungi feature low (26% to 37%) GC content and large genome size variations (25 to 102 Mb). Further comparisons with insect-pathogenic fungi (from both Ascomycota and Zoopagomycota), as well as with free-living relatives (as negative controls), helped to identify a gene toolbox that is essential to the fungus-insect symbiosis. The results not only narrow the genomic scope of fungus-insect interactions from several thousands to eight core players but also distinguish host invasion strategies employed by insect pathogens and commensals. The genomic content suggests that insect commensal fungi rely mostly on adhesion protein anchors that target digestive system, while entomopathogenic fungi have higher numbers of transmembrane helices, signal peptides, and pathogen-host interaction (PHI) genes across the whole genome and enrich genes as well as functional domains to inactivate the host inflammation system and suppress the host defense. Phylogenomic analyses have revealed that genome sizes of Harpellales fungi vary among lineages with an integer-multiple pattern, which implies that ancient genome duplications may have occurred within the gut of insects.IMPORTANCEInsect guts harbor various microbes that are important for host digestion, immune response, and disease dispersal in certain cases. Bacteria, which are among the primary endosymbionts, have been studied extensively. However, fungi, which are also frequently encountered, are poorly known with respect to their biology within the insect guts. To understand the genomic features and related biology, we produced the whole-genome sequences of nine gut commensal fungi from disease-bearing insects (black flies, midges, and mosquitoes). The results show that insect gut fungi tend to have low GC content across their genomes. By comparing these commensals with entomopathogenic and free-living fungi that have available genome sequences, we found a universal core gene toolbox that is unique and thus potentially important for the insect-fungus symbiosis. This comparative work also uncovered different host invasion strategies employed by insect pathogens and commensals, as well as a model system to study ancient fungal genome duplication within the gut of insects.

scholarly journals Building a tRNA thermometer to estimate microbial adaptation to temperature

2020 ◽  
Vol 48 (21) ◽  
pp. 12004-12015
Author(s):  
Emre Cimen ◽  
Sarah E Jensen ◽  
Edward S Buckler
Keyword(s):  
Growth Temperature ◽  
Input Data ◽  
Prediction Models ◽  
Extreme Temperature ◽  
Protein Composition ◽  
Network Models ◽  
Optimal Growth ◽  
Optimal Growth Temperature ◽  
Neural Network Models ◽  
Thermophilic Organism

Abstract Because ambient temperature affects biochemical reactions, organisms living in extreme temperature conditions adapt protein composition and structure to maintain biochemical functions. While it is not feasible to experimentally determine optimal growth temperature (OGT) for every known microbial species, organisms adapted to different temperatures have measurable differences in DNA, RNA and protein composition that allow OGT prediction from genome sequence alone. In this study, we built a ‘tRNA thermometer’ model using tRNA sequence to predict OGT. We used sequences from 100 archaea and 683 bacteria species as input to train two Convolutional Neural Network models. The first pairs individual tRNA sequences from different species to predict which comes from a more thermophilic organism, with accuracy ranging from 0.538 to 0.992. The second uses the complete set of tRNAs in a species to predict optimal growth temperature, achieving a maximum ${r^2}$ of 0.86; comparable with other prediction accuracies in the literature despite a significant reduction in the quantity of input data. This model improves on previous OGT prediction models by providing a model with minimum input data requirements, removing laborious feature extraction and data preprocessing steps and widening the scope of valid downstream analyses.

Elevation of the Heat Resistance of Vegetative Cells and Spores of Clostridium perfringens Type A by Sublethal Heat Shock

1997 ◽  
Vol 60 (8) ◽  
pp. 998-1000 ◽  
Author(s):  
NORMA L. HEREDIA ◽  
GERARDO A. GARCÍA ◽  
RAMIRO LUÉVANOS ◽  
RONALD G. LABBÉ ◽  
J. SANTOS GARCÍA-ALVARADO
Keyword(s):  
Heat Shock ◽  
Heat Resistance ◽  
Clostridium Perfringens ◽  
Growth Temperature ◽  
Optimal Growth ◽  
Shock Treatment ◽  
Heat Shock Treatment ◽  
Optimal Growth Temperature ◽  
Vegetative Cells ◽  
Kinetics Of

The degree of heat resistance conferred on Clostridium perfringens by a heat shock, the kinetics of this development, and its duration were determined. A sublethal heat shock at 55°C for 30 min increased the heat tolerance of vegetative cells at least two- to threefold. The acquired tolerance was maintained for 2 h after the heat shock treatment. Heat shock applied for the first hour of incubation produced spores more tolerant to heat than the spores of the control. Acquired thermotolerance is of importance in the case of this organism because of its inherently high optimal growth temperature.

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