Using RNA-Sequencing Data to Examine Tissue-Specific Garlic Microbiomes

Exploring Tomato Fruit Viromes through Transcriptome Data Analysis

This study delves into the complex landscape of viral infections in tomatoes (Solanum lycopersicum) using available transcriptome data. We conducted a virome analysis, revealing 219 viral contigs linked to four distinct viruses: tomato chlorosis virus (ToCV), southern tomato virus (STV), tomato yellow leaf curl virus (TYLCV), and cucumber mosaic virus (CMV). Among these, ToCV predominated in contig count, followed by STV, TYLCV, and CMV. A notable finding was the prevalence of coinfections, emphasizing the concurrent presence of multiple viruses in tomato plants. Despite generally low viral levels in fruit transcriptomes, STV emerged as the primary virus based on viral read count. We delved deeper into viral abundance and the contributions of RNA segments to replication. While initially focused on studying the impact of sound treatment on tomato fruit transcriptomes, the unexpected viral presence underscores the importance of considering viruses in plant research. Geographical variations in virome communities hint at potential forensic applications. Phylogenetic analysis provided insights into viral origins and genetic diversity, enhancing our understanding of the Korean tomato virome. In conclusion, this study advances our knowledge of the tomato virome, stressing the need for robust pest control in greenhouse-grown tomatoes and offering insights into virus management and crop protection.

Temperature, Salinity and Garlic Additive Shape the Microbial Community during Traditional Beetroot Fermentation Process

Plant-based traditional fermented products are attracting a lot of interest in global markets. An example of them is beetroot leaven, which is valued for its high bioactive compound content. The variety of production recipes and the spontaneous nature of red beet fermentation favor its high diversity. This study aimed to analyze the impact of external factors-temperature, brine salinity, and garlic dose-on the beetroot fermentation and bacterial metapopulation responsible for this process. The research results confirmed the significant influence of the selected and analyzed factors in shaping the leaven physicochemical profile including organic acid profile and betalain content. Analysis of bacterial populations proved the crucial importance of the first 48 h of the fermentation process in establishing a stable metapopulation structure and confirmed that this is a targeted process driven by the effect of the analyzed factors. Lactobacillaceae, Enterobacteriaceae, and Leuconostocaceae were observed to be the core microbiome families of the fermented red beet. Regardless of the impact of the tested factors, the leaven maintained the status of a promising source of probiotic bacteria. The results of this research may be helpful in the development of the regional food sector and in improving the quality and safety of traditionally fermented products such as beetroot leaven.

In Silico Virome Analysis of Chinese Narcissus Transcriptomes Reveals Diverse Virus Species and Genetic Diversity at Different Flower Development Stages

Viromes of Chinese narcissus flowers were explored using transcriptome data from 20 samples collected at different flower development stages. Quality controlled raw data underwent de novo assembly, resulting in 5893 viral contigs that matched the seven virus species. The most abundant viruses were narcissus common latent virus (NCLV), narcissus yellow stripe virus (NYSV), and narcissus mottling-associated virus (NMaV). As flower development stages advanced, white tepal plants showed an increase in the proportion of viral reads, while the variation in viral proportion among yellow tepal plants was relatively small. Narcissus degeneration virus (NDV) dominated the white tepal samples, whereas NDV and NYSV prevailed in the yellow tepal samples. Potyviruses, particularly NDV, are the primary infectious viruses. De novo assembly generated viral contigs for five viruses, yielding complete genomes for NCLV, NDV, narcissus late season yellow virus (NLSYV), and NYSV. Phylogenetic analysis revealed genetic diversity, with distinct NCLV, NMaV, NDV, NLSYV, and NYSV groups. This study provides valuable insights into the viromes and genetic diversity of viruses in Chinese narcissus flowers.

Uncovering the special microbiota associated with occurrence and progression of gastric cancer by using RNA-sequencing

Gastric cancer (GC) has been identified as the third deadly cancer in the world. Accumulating researches suggest a potential role of microorganisms in tumorigenesis. However, the composition of microbiota in GC tissues is not clear and it changes throughout the different stages of GC remain mostly elusive. Our study integrated RNA-Seq data of 727 samples derived from gastric tissues across four datasets and revealed its microbial composition. In order to remove the false positive results, core taxa were defined and characterized. Based on it, we analyzed the influence of biological factors on its composition. The pan-microbiome of gastric tissues was estimated to be over than 1400 genera. Seventeen core genera were identified. Among them, Helicobacter, Lysobacter were significantly enriched in normal tissues, while Pseudomonas was enriched in tumor tissues. Interestingly, Acinetobacter, Pasteurella, Streptomyces, Chlamydia, and Lysobacter, showed a significant increase trend during tumor development and formed strong intra/inter-correlations among them or with other genera. Furthermore, we found that tumor stage played an important role in altering the microbial composition of GC tissues. This study provides support for the in-depth study of tumor microbiome, and the specific microbiome excavated provides a possibility for the subsequent identification of potential biomarkers for GC.

Establishment and Validation of a New Analysis Strategy for the Study of Plant Endophytic Microorganisms

Amplicon sequencing of bacterial or fungal marker sequences is currently the main method for the study of endophytic microorganisms in plants. However, it cannot obtain all types of microorganisms, including bacteria, fungi, protozoa, etc., in samples, nor compare the relative content between endophytic microorganisms and plants and between different types of endophytes. Therefore, it is necessary to develop a better analysis strategy for endophytic microorganism investigation. In this study, a new analysis strategy was developed to obtain endophytic microbiome information from plant transcriptome data. Results showed that the new strategy can obtain the composition of microbial communities and the relative content between plants and endophytic microorganisms, and between different types of endophytic microorganisms from the plant transcriptome data. Compared with the amplicon sequencing method, more endophytic microorganisms and relative content information can be obtained with the new strategy, which can greatly broaden the research scope and save the experimental cost. Furthermore, the advantages and effectiveness of the new strategy were verified with different analysis of the microbial composition, correlation analysis, inoculant content test, and repeatability test.