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.     

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.