scholarly journals Kocuria Strains from Unique Radon Spring Water from Jachymov Spa

Fermentation ◽  
2022 ◽  
Vol 8 (1) ◽  
pp. 35
Author(s):  
Elizaveta Timkina ◽  
Lucie Drábová ◽  
Andrea Palyzová ◽  
Tomáš Řezanka ◽  
Olga Maťátková ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Free Radicals ◽  
Extreme Environments ◽  
Optimal Growth ◽  
Spring Water ◽  
Extreme Conditions ◽  
Bacterial Isolates ◽  
Temperature Dependent ◽  
Optimal Growth Temperature ◽  
Biotechnological Production

Members of the genus Kocuria are often found in soils contaminated with toxic metals or exposed to high levels of ionizing radiation. The use of classical cultivation technics often leads to the isolation of Kocuria sp. from underground spring waters. These bacterial isolates have to adapt their metabolism to survive in such extreme environments. Four bacterial isolates of the genus Kocuria (Kocuria sp. 101, 208, 301, and 401) were obtained from radon spring water (Jachymov, Czech Republic). These isolates were tested for their ability to withstand stress and extreme conditions. Growth was observed at a temperature range of 10–45 °C with optimal growth temperature between 20 and 30 °C. The content of polyunsaturated fatty acids in all four isolates was proved to be temperature-dependent. The strain Kocuria sp. 301 showed high resistance to all studied extreme conditions (UV radiation, desiccation, and free radicals in medium). The results suggest that isolates from radioactive springs might have developed mechanisms that help them survive under several extreme conditions and could be used in biotechnological production.

scholarly journals Prediction of Optimal Growth Temperature using only Genome Derived Features

2018 ◽  
Author(s):  
David B. Sauer ◽  
Da-Neng Wang
Keyword(s):  
Growth Temperature ◽  
High Throughput Sequencing ◽  
Optimal Growth ◽  
Temperature Dependent ◽  
Optimal Growth Temperature ◽  
Rapid Calculation ◽  
Dependent Activity ◽  
Organism Growth ◽  
Novel Method ◽  
Living Organisms

AbstractOptimal growth temperature is a fundamental characteristic of all living organisms. Knowledge of this temperature is central to the study the organism, the thermal stability and temperature dependent activity of its genes, and the bioprospecting of its genome for thermally adapted proteins. While high throughput sequencing methods have dramatically increased the availability of genomic information, the growth temperatures of the source organisms are often unknown. This limits the study and technological application of these species and their genomes. Here, we present a novel method for the prediction of growth temperatures of prokaryotes using only genomic sequences. By applying the reverse ecology principle that an organism’s genome includes identifiable adaptations to its native environment, we can predict a species’ optimal growth temperature with an accuracy of 4.69 °C root-mean-square error and a correlation coefficient of 0.908. The accuracy can be further improved for specific taxonomic clades or by excluding psychrophiles. This method provides a valuable tool for the rapid calculation of organism growth temperature when only the genome sequence is known.

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 Atlantic salmon require long-chain n-3 fatty acids for optimal growth throughout the seawater period

2016 ◽  
Vol 5 ◽  
Author(s):  
Grethe Rosenlund ◽  
Bente E. Torstensen ◽  
Ingunn Stubhaug ◽  
Nafiha Usman ◽  
Nini H. Sissener
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Atlantic Salmon ◽  
Fold Increase ◽  
Optimal Growth ◽  
Dietary Fatty Acids ◽  
Nutritional Requirement ◽  
Retention Efficiency ◽  
Long Chain

AbstractThe nutritional requirement for n-3 long-chain PUFA in fast-growing Atlantic salmon (Salmo salar) during grow out in the sea is not well documented. Diets were formulated with levels of EPA (20 : 5n-3) and DHA (22 : 6n-3) ranging from 1·3 to 7·4 % of fatty acids (4–24 g/kg feed). Two long-term trials were conducted through the seawater phase, the first at 6 and 12°C, and the second at 12°C. In the first trial, growth at both temperatures was significantly lower in fish fed 1·4 % EPA+DHA of total fatty acids compared with the 5·2 % EPA+DHA group. In the second trial, growth was significantly lower in fish fed 1·3 and 2·7 % compared with 4·4 and 7·4 % EPA + DHA. Fatty acid composition in the fish reflected diet composition, but only after a 7-fold increase in body weight did the fatty acid profile of the fish stabilise according to dietary fatty acids (shown for EPA and DHA). The retention efficiency of DHA increased with decreasing dietary levels, and was 120–190 and 120–200 % in trials 1 and 2, respectively. The retention efficiency of EPA was lower (60–200 %), and values >100 % were only achieved at the lowest dietary levels in both trials. Temperature did not affect fatty acid retention efficiency. These results suggest that Atlantic salmon have a specific requirement for EPA + DHA >2·7 % of fatty acids for optimal long-term growth in seawater, and that short-term growth trials with less weight increase would not show these effects.

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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