scholarly journals The molecular determinants of thermoadaptation: Methanococcales as a case study

Author(s):  
M Lecocq ◽  
M Groussin ◽  
M Gouy ◽  
C Brochier-Armanet

Abstract Previous reports have shown that environmental temperature impacts proteome evolution in Bacteria and Archaea. However, it is unknown whether thermoadaptation mainly occurs via the sequential accumulation of substitutions, massive horizontal gene transfers, or both. Measuring the real contribution of amino acid substitution to thermoadaptation is challenging, because of confounding environmental and genetic factors (e.g. pH, salinity, genomic G+C content) that also affect proteome evolution. Here, using Methanococcales, a major archaeal lineage, as a study model, we show that optimal growth temperature is the major factor affecting variations in amino acid frequencies of proteomes. By combining phylogenomic and ancestral sequence reconstruction approaches, we disclose a sequential substitutional scheme in which lysine plays a central role by fine tuning the pool of arginine, serine, threonine, glutamine, and asparagine, whose frequencies are strongly correlated with optimal growth temperature. Finally, we show that colonization to new thermal niches is not associated with high amounts of horizontal gene transfers. Altogether, while the acquisition of a few key proteins through horizontal gene transfer may have favoured thermoadaptation in Methanococcales, our findings support sequential amino acid substitutions as the main factor driving thermoadaptation.

FEBS Letters ◽  
2006 ◽  
Vol 580 (6) ◽  
pp. 1672-1676 ◽  
Author(s):  
Liron Klipcan ◽  
Ilya Safro ◽  
Boris Temkin ◽  
Mark Safro

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 46
Author(s):  
Cristina Mihaescu ◽  
Daniel Dunea ◽  
Adrian Gheorghe Bășa ◽  
Loredana Neagu Frasin

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.


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

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

2020 ◽  
Author(s):  
Emre Cimen ◽  
Sarah E. Jensen ◽  
Edward S. Buckler

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.


2020 ◽  
Vol 48 (21) ◽  
pp. 12004-12015
Author(s):  
Emre Cimen ◽  
Sarah E Jensen ◽  
Edward S Buckler

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.


1997 ◽  
Vol 60 (8) ◽  
pp. 998-1000 ◽  
Author(s):  
NORMA L. HEREDIA ◽  
GERARDO A. GARCÍA ◽  
RAMIRO LUÉVANOS ◽  
RONALD G. LABBÉ ◽  
J. SANTOS GARCÍA-ALVARADO

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.


2013 ◽  
Vol 30 (11) ◽  
pp. 2463-2474 ◽  
Author(s):  
Anna G. Green ◽  
Kristen S. Swithers ◽  
Jan F. Gogarten ◽  
Johann Peter Gogarten

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