scholarly journals Reconstruction of Ancestral 16S rRNA Reveals Mutation Bias in the Evolution of Optimal Growth Temperature in the Thermotogae Phylum

2013 ◽  
Vol 30 (11) ◽  
pp. 2463-2474 ◽  
Author(s):  
Anna G. Green ◽  
Kristen S. Swithers ◽  
Jan F. Gogarten ◽  
Johann Peter Gogarten
Keyword(s):  
16S Rrna ◽  
Growth Temperature ◽  
Optimal Growth ◽  
Optimal Growth Temperature ◽  
Mutation Bias

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 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.

Optimal growth temperature for the isolation of Plesiomonas shigelloides, using various selective and differential agars

1991 ◽  
Vol 37 (10) ◽  
pp. 800-802 ◽  
Author(s):  
Anwarul Huq ◽  
Anwari Akhtar ◽  
M. A. R. Chowdhury ◽  
David A. Sack
Keyword(s):  
Growth Temperature ◽  
Optimal Growth ◽  
Growth Conditions ◽  
Aeromonas Species ◽  
Growth Media ◽  
Optimal Growth Temperature ◽  
Environmental Waters ◽  
Temperature Growth ◽  
Plesiomonas Shigelloides ◽  
Incubation Temperatures

The growth characteristics of known strains of Plesiomonas shigelloides were compared with those of Aeromonas species (the major competing species in environmental waters) on plesiomonas differential agar, inositol brilliant green bile salt, and modified salmonella–shigella agar at incubation temperatures of 37, 42, and 44 °C. Using local isolates from clinical and environmental sources, optimal growth conditions, as determined by colony counts and the colony characteristics, plesiomonas differential agar proved to be ideal when incubated at 44 °C. Contrary to earlier recommendations for 48 h incubation, the colonies could be recognized readily after an incubation of 24 h. Key words: Plesiomonas, growth temperature, growth media.

Phaeotheca dimorphospora sp.nov.: description et caractéristiques culturales

1994 ◽  
Vol 72 (6) ◽  
pp. 808-817 ◽  
Author(s):  
Pierre DesRochers ◽  
G. B. Ouellette
Keyword(s):  
Growth Rate ◽  
Growth Temperature ◽  
Type Species ◽  
Optimal Growth ◽  
Outer Wall ◽  
Dutch Elm Disease ◽  
Optimal Growth Temperature ◽  
Ophiostoma Ulmi ◽  
Mother Cells

An unknown fungus isolated from an elm branch and inhibitory against Ophiostoma ulmi in vitro is described as Phaeotheca dimorphospora sp.nov. This dematiaceous deuteromycete propagates by endoconidia released after exfoliation of chlamydospore outer wall, as in mother cells of the type species Phaeotheca fissurella. However, P. dimorphospora differs from the type species by producing hyaline secondary ameroconidia between the endoconidial masses. Other ameroconidia, similar to the secondary ameroconidia, are produced through the chlamydospore outer wall. The optimal growth temperature of P. dimorphospora is 23 °C, whereas it is 15.5 °C for the type species. On media containing a high dextrose concentration (30 g ∙ L−1), colonies of P. dimorphospora are gray and crustose and grow slowly, at least initially. Conversely, on media with a low dextrose concentration (5 or 10 g ∙ L−1) colonies have a faster growth rate and appear whitish or ivory and fluffy. Key words: Phaeotheca dimorphospora, diagnosis, inhibition, Ophiostoma ulmi, Dutch elm disease.

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