Kocuria Strains from Unique Radon Spring Water from Jachymov Spa

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.

Genome sequences hot and cold: a database of organisms with defined optimal growth temperatures

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.

A Positive Correlation between Bacterial GC Content and Growth Temperature

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.

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

Because 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.

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

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 molecular determinants of thermoadaptation: Methanococcales as a case study

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.

Building a tRNA thermometer to estimate microbial adaptation to temperature

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.

Diploid Potato Germplasm with Resistance to Dickeya solani

Potato growers suffer losses due to potato soft rot and blackleg caused by pectinolytic bacteria of different species. These bacteria cause yield loss during cultivation and storage, and can be transmitted to the next generations through seed tubers. The prevalence of Pectobacterium atrosepticum has decreased over the last 20 years in Europe in favour of Dickeya solani and P. carotovorum subsp. brasiliense. Twenty-six diploid interspecific Solanum hybrids, previously selected for tuber resistance to P. atrosepticum, were screened for resistance to a highly aggressive D. solani strain in terms of tuber and blackleg reaction. The bacterial strain used for inoculation was characterised by a relatively high optimal growth temperature in vitro, ranging from 33 to 35 °C. Twenty-four diploid clones did not differ in terms of tuber reaction to inoculation with this strain of bacteria in comparison with the clone USA 249, which is the somatic hybrid of S. brevidens (+) S. tuberosum with proven resistance to Pectobacterium. Seventeen clones performed significantly better in terms of blackleg resistance than the resistant potato cultivar Glada. Eleven of the selected diploids produced unreduced gametes, which allows their use in improving the resistance of tetraploid potatoes to diseases caused by bacteria of both Pectobacterium and Dickeya.

The hemoglobin Gly16β1Asp polymorphism in turbot (Scophthalmus maximus) is differentially distributed across European populations

Turbot is an important flatfish widely distributed along the European coasts, whose fishery is centered in the North Sea. The commercial value of the species has boosted a successful aquaculture sector in Europe and China. Body growth is the main target of turbot breeding programs and is also a key trait related to local adaptation to temperature and salinity. Differences in growth rate and optimal growth temperature in turbot have been shown to be associated with a hemoglobin polymorphism reported more than 50 years ago. Here, we identified a Gly16Asp amino acid substitution in the β1 globin subunit by searching for genetic variation in the five functional globin genes within the whole annotated turbot genome. We predicted increased stability of the turbot hemoglobin by the replacement of the conserved Gly with the negative charged Asp residue that is consistent with the higher rate of αβ dimer assembly in the human J-Baltimore Gly16β->Asp mutant than in normal HbA. The turbot Hbβ1-Gly16 variant dominated in the northern populations examined, particularly in the Baltic Sea, while the Asp allele showed elevated frequencies in southern populations and was the prevalent variant in the Adriatic Sea. Body weight did not associate with the Hbβ1 genotypes at farming conditions (i.e., high oxygen levels, feeding ad libitum) after analyzing 90 fish with high growth dispersal from nine turbot families. Nevertheless, all data at hand suggest that the turbot hemoglobin polymorphism has an adaptive significance in the variable wild conditions regarding temperature and oxygen availability.