Crop output is directly impacted by infections, with fungi as the major plant pathogens, making accurate diagnosis of these threats crucial. Developing technology and multidisciplinary approaches are turning to genomic analyses in addition to traditional culture methods in diagnostics of fungal plant pathogens. The metagenomic next-generation sequencing (mNGS) method is preferred for genotyping identification of organisms, identification at the species level, illumination of metabolic pathways, and determination of microbiota. Moreover, the data obtained so far show that this new approach is promising as an emerging new trend in fungal disease detection. Another approach covered by mNGS technologies, known as metabarcoding, enables use of specific markers specific to a genetic region and allows for genotypic identification by facilitating the sequencing of certain regions. Although the core concept of mNGS remains constant across applications, the specific sequencing methods and bioinformatics tools used to analyze the data differ. In this review, we focus on how mNGS technology, including metabarcoding, is applied for detecting fungal pathogens and its promising developments for the future.

In this study, we aimed to synthesize silver nanoparticles (AgNPs) using leaf, root, and stem extracts of Phaseolus vulgaris L. (Yunus-90) and elucidate their antifungal activities. In this regard, the prepared AgNPs have been characterized by using UV-vis, FT-IR, TEM, SEM, and DLS techniques. Then, the antifungal activity of both synthesized and commercially purchased AgNPs was investigated via (i) agar well diffusion, (ii) fungal colony morphotype diversity, (iii) inhibition of hyphae and (iv) minimum inhibition concentration (MIC) analyses against Colletotrichum sp., Fusarium oxysporum, Fusarium acuminatum, Fusarium tricinctum, Fusarium graminearum, Fusarium incarnatum, Rhizoctonia solani, Sclerotinia sclerotiorum, and Alternaria alternata. The AgNPs derived from the leaf extract displayed significantly higher levels of antifungal activity relative to the AgNPs prepared from the root and stem extracts. The commercial AgNPs also displayed lower antifungal activity than their green equivalents synthesized in this research, and even a low (~50 μg/mL) concentration of synthesized AgNPs was found to be effective in suppressing the growth of Fusarium tricinctum and Colletotrichum sp.

Crop output is directly impacted by plant infections (with fungi as the major pathogen), making accurate diagnosis of these threats crucial. Developing technology and multidisciplinary approaches are turning to genomic analyses in addition to traditional culture methods in diagnosing fungal plant diseases. The metagenomic next-generation sequencing (mNGS) method is preferred for genotyping identification of organisms, identification at the species level, illumination of metabolic pathways, and determination of microbiota. Moreover, the data obtained so far show that this new approach shows promise as an emerging new trend in fungal disease detection. Another approach covered by mNGS technologies, known as metabarcoding, enables use of specific markers specific to a genetic region and allows for genotypic identification by facilitating the sequencing of certain regions. Although the core concept of mNGS remains constant across applications, the specific sequencing methods and bioinformatics tools used to analyze the data do differ. In this review, we focus on how mNGS technology, including metabarcoding, is applied in fungal pathogenesis and its promising developments for the future.

Nanoteknoloji, kullanım alanı her geçen gün artan bir fenomen haline gelmiştir. Nanopartikülerin kullanımı gittikçe yaygınlaşmakta ve önem kazanmaktadır. Nanopartiküller, özellikle tarımsal bilimlerde, yüksek kullanım potansiyeline sahiptir. Bitkilerin böcek ilaçlarına, herbisitlere ve patojenlerine karşı korunmasında önemli rol oynarlar. Ayrıca, bitki sinyalizasyonuda önemli görevler üstlenebilir veya nanosensör olarak kullanılabilirler. geleceğin teknolojisi olarak değerlendirilen, yeşil nanobiyoteknoloji çevre dostu ve sürdürülebilir olması açısından çok sık tercih edilmektedir. Biz bu çalışmada nanopartiküllerin tarımsal bilimlerdeki kullanım alanlarına odaklanıyor ve nanopartiküllerin önemini vurgulamayı amaçlıyoruz.

Mammillaria elongata is a species of Cactaceae family, native to central Mexico. In Turkey, it is grown as cultivated plant. The succulent plants have pink and red fruits. In this study, we investigated the protein content, sugar content, anti-bacterial and anti-fungal effect in fruit extract. According to the results, in the fruit with a total wet weight of 0.252 g 15.5215 mg protein was found with Lowry method. Besides, the extract contains high amounts of reducing sugar such as glucose. Bacterial growth (Escherichia coli and Pseudomonas aeruginosa on bloody agar) and fungal colonization (Fusarium oxysporum, Rhizoctonia solani, Sclerotinia sclerotiorum on PDA) were not affected by plant extract. However, in all control media, that contain only plant extract, pink colored organism growth was observed. After DNA ısolation and 18S rRNA PCR from this organism, its species name determined as Rhodotorula glutinis according to % 100 sequence similarity.

Hyperemesis gravidarum (HEG) is a pregnancy complication characterized by severe nausea, vomiting more than four times a day and dehydration, especially occurring in the first trimester of pregnancy. In recent years it has been shown that the intestinal bacterial microbiome profile may be associated with a wide range of diseases. The aim of this study was to determine whether the intestinal bacterial microbiome profiles differ between pregnant women diagnosed with hyperemesis gravidarum (HEG) and those with healthy pregnancies. Fresh stool samples were collected from 15 pregnant women diagnosed with HEG and 14 healthy pregnant women who did not have any complaints in the first trimester. After DNA isolation from the samples, 16S rRNA gene-based microbial profiling was performed with next-generation sequencing. The 16S rRNA V3-V4 region was sequenced with paired-end reads (2×250 base pair) on the Illumina MiSeq platform. The average sequence number for each sample was similar (HEG= ~2.54 million, control= ~1.48 million; p> 0.05). After quality filtering, reads obtained from all samples were analyzed by rarefaction at equal depth. Alpha diversity measures were found to be significantly higher in the HEG group compared to the control group (Shannon, ACE, and Chao1 indices; p< 0.05 for all). In the beta diversity analysis, it was observed that the gut microbiome compositions of the two groups were separated; In the Principal Coordinates Analysis plot, the groups were clearly clustered and the group difference was found to be statistically significant by PERMANOVA test (p< 0.01). Significant differences were also found in the comparisons at the taxonomic level. At the class level, the relative abundance of Clostridia was significantly higher in the HEG group (p< 0.05), while the class Bacilli was dominant in the control group (p< 0.05). At the family level, the abundances of Lachnospiraceae and Prevotellaceae were found to be significantly higher in the HEG group than in the control group (p< 0.05). In contrast, at the family level, the rates of Enterobacteriaceae and at the genus level, the rates of Escherichia-Shigella were found to be significantly higher in the control group (p< 0.05). Some bacterial taxa detected only in the HEG group samples were also noteworthy: Collinsella, Blautia, and Dialister genera, which are only found in the intestines of patients with HEG, were not detected in the control group. In conclusion, these findings reveal that there are significant differences between the intestinal microbiome profiles of pregnant women with HEG and healthy pregnant women. The high microbial diversity observed in the HEG group and changes in certain bacterial groups suggest that processes related to lipid and carbohydrate metabolism may play a role in the pathogenesis of HEG. In the future, the clinical significance and possible therapeutic targets of these differences can be evaluated with more comprehensive studies aiming at clarifying causality.