Microbiological interactions with cold plasma

There is a diverse range of microbiological challenges facing the food, healthcare and clinical sectors. The increasing and pervasive resistance to broad‐spectrum antibiotics and health‐related concerns with many biocidal agents drives research for novel and complementary antimicrobial approaches. Biofilms display increased mechanical and antimicrobial stability and are the subject of extensive research. Cold plasmas (CP) have rapidly evolved as a technology for microbial decontamination, wound healing and cancer treatment, owing to the chemical and bio‐active radicals generated known collectively as reactive oxygen and nitrogen species. This review outlines the basics of CP technology and discusses the interactions with a range of microbiological targets. Advances in mechanistic insights are presented and applications to food and clinical issues are discussed. The possibility of tailoring CP to control specific microbiological challenges is apparent. This review focuses on microbiological issues in relation to food‐ and healthcare‐associated human infections, the role of CP in their elimination and the current status of plasma mechanisms of action.     

Consolidated ethanol production from Jerusalem artichoke tubers at elevated temperature by <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> engineered with inulinase expression through cell surface display

Ethanol fermentation from Jerusalem artichoke tubers was performed at elevated temperatures by the consolidated bioprocessing strategy using Saccharomyces cerevisiae MK01 expressing inulinase through cell surface display. No significant difference was observed in yeast growth when temperature was controlled at 38 and 40 °C, respectively, but inulinase activity with yeast cells was substantially enhanced at 40 °C. As a result, enzymatic hydrolysis of inulin was facilitated and ethanol production was improved with 89.3 g/L ethanol produced within 72 h from 198.2 g/L total inulin sugars consumed. Similar results were also observed in ethanol production from Jerusalem artichoke tubers with 85.2 g/L ethanol produced within 72 h from 185.7 g/L total sugars consumed. On the other hand, capital investment on cooling facilities and energy consumption for running the facilities would be saved, since regular cooling water instead of chill water could be used to cool down the fermentation system.     

Frequency of a natural truncated allele of <Emphasis Type="Italic">MdMLO19</Emphasis> in the germplasm of <Emphasis Type="Italic">Malus domestica</Emphasis>

Podosphaera leucotricha is the causal agent of powdery mildew (PM) in apple. To reduce the amount of fungicides required to control this pathogen, the development of resistant apple cultivars should become a priority. Resistance to PM was achieved in various crops by knocking out specific members of the MLO gene family that are responsible for PM susceptibility (S-genes). In apple, the knockdown of MdMLO19 resulted in PM resistance. However, since gene silencing technologies such as RNAi are perceived unfavorably in Europe, a different approach that exploits this type of resistance is needed. This work evaluates the presence of non-functional naturally occurring alleles of MdMLO19 in apple germplasm. The screening of the re-sequencing data of 63 apple individuals led to the identification of 627 single nucleotide polymorphisms (SNPs) in five MLO genes (MdMLO5, MdMLO7, MdMLO11, MdMLO18, and MdMLO19), 127 of which were located in exons. The T-1201 insertion of a single nucleotide in MdMLO19 caused the formation of an early stop codon, resulting in a truncated protein lacking 185 amino acids, including the calmodulin-binding domain. The presence of the insertion was evaluated in 115 individuals. It was heterozygous in 64 and homozygous in 25. Twelve of the 25 individuals carrying the insertion in homozygosity were susceptible to PM. After barley, pea, cucumber, and tomato, apple would be the fifth species for which a natural non-functional mlo allele has been found.     

Practical application of genomic selection in a doubled-haploid winter wheat breeding program

Crop improvement is a long-term, expensive institutional endeavor. Genomic selection (GS), which uses single nucleotide polymorphism (SNP) information to estimate genomic breeding values, has proven efficient to increasing genetic gain by accelerating the breeding process in animal breeding programs. As for crop improvement, with few exceptions, GS applicability remains in the evaluation of algorithm performance. In this study, we examined factors related to GS applicability in line development stage for grain yield using a hard red winter wheat (Triticum aestivum L.) doubled-haploid population. The performance of GS was evaluated in two consecutive years to predict grain yield. In general, the semi-parametric reproducing kernel Hilbert space prediction algorithm outperformed parametric genomic best linear unbiased prediction. For both parametric and semi-parametric algorithms, an upward bias in predictability was apparent in within-year cross-validation, suggesting the prerequisite of cross-year validation for a more reliable prediction. Adjusting the training population’s phenotype for genotype by environment effect had a positive impact on GS model’s predictive ability. Possibly due to marker redundancy, a selected subset of SNPs at an absolute pairwise correlation coefficient threshold value of 0.4 produced comparable results and reduced the computational burden of considering the full SNP set. Finally, in the context of an ongoing breeding and selection effort, the present study has provided a measure of confidence based on the deviation of line selection from GS results, supporting the implementation of GS in wheat variety development.     

Osmotic stress decreases complexity underlying the electrophysiological dynamic in soybean

• Studies on plant electrophysiology are mostly focused on specific traits of single cells. Inspired by the complexity of the signalling network in plants, and by analogy with neurons in human brains, we sought evidence of high complexity in the electrical dynamics of plant signalling and a likely relationship with environmental cues.
• An EEG‐like standard protocol was adopted for high‐resolution measurements of the electrical signal in Glycine max seedlings. The signals were continuously recorded in the same plants before and after osmotic stimuli with a ?2 MPa mannitol solution. Non‐linear time series analyses methods were used as follows: auto‐correlation and cross‐correlation function, power spectra density function, and complexity of the time series estimated as Approximate Entropy (ApEn).
• Using Approximate Entropy analysis we found that the level of temporal complexity of the electrical signals was affected by the environmental conditions, decreasing when the plant was subjected to a low osmotic potential. Electrical spikes observed only after stimuli followed a power law distribution, which is indicative of scale invariance.
• Our results suggest that changes in complexity of the electrical signals could be associated with water stress conditions in plants. We hypothesised that the power law distribution of the spikes could be explained by a self‐organised critical state (SOC) after osmotic stress.

     

Phylogenetic analysis of the genus <Emphasis Type="Italic">Argia</Emphasis> Rambur, 1842 (Odonata: Coenagrionidae), based on morphological characters of larvae and mitochondrial DNA sequences

The study of the evolutionary interrelationships among the species encompassed in the Neotropical genus Argia (Zygoptera: Coenagrionidae) has been neglected. The goal of this study is to infer the phylogenetic relationships among 36 species of Argia Rambur, 1842, using complementary data sets (i.e., larval morphology and mitochondrial DNA). The morphological data set comprises 76% of the larvae currently described for this genus and includes 97 morphological characters. From those, 47 characters have not been previously used in taxonomic studies involving dragonflies’ larvae. This is the first cladistic study based on larvae morphology for species within the suborder Zygoptera. Data partitions were analyzed individually, as well as total evidence, using parsimony and Bayesian inference as criteria for optimal-tree selection. The results support the monophyly of the North American species of Argia. This genus can be identified by the combination of eight synapomorphies, four of which are exclusively found in Argia. According to the optimal trees, the individual data sets (i.e., morphology and DNA sequences) have a high level of homoplasy, resulting in soft polytomies and low support for several nodes. The specific relationships of the terminal units differ between the phylogenies; nonetheless, there is historical congruence among them. Within Argia, five clades were consistently recovered. Most of those clades have been identified, at least in part, in previous phylogenetic and taxonomic studies. Indubitably, the morphological characters from larvae have historical signal useful for cladistic and taxonomic inference. Therefore, it should be a priority to pay more attention to this source of characters.