Bioinformatics Analysis of The Rhizosphere Microbiota of Dangshan Su Pear in Different Soil Types

Bio-Organic Fertilizer Promotes Pear Yield by Shaping the Rhizosphere Microbiome Composition and Functions

Bio-organic fertilizers (BOF) containing both organic amendments and beneficial microorganisms have been consistently shown to improve soils fertility and yield. However, the exact mechanisms which link amendments and yields remain disputed, and the complexity of bio-organic fertilizers may work in parallel in several ways. BOF may directly improve yield by replenishing soil nutrients or introducing beneficial microbial genes or indirectly by altering the soil microbiome to enrich native beneficial microorganisms. In this work, we aim to disentangle the relative contributions of direct and indirect effects on pear yield. We treated pear trees with either chemical fertilizer or organic fertilizer with/without the plant-beneficial bacterium Bacillus velezensis SQR9. We then assessed, in detail, soil physicochemical and biological properties (metagenome sequencing) as well as pear yield. We then evaluated the relative importance of direct and indirect effects of soil amendments on pear yield. Both organic treatments increased plant yield by up to 20%, with the addition of bacteria tripling the increase driven by organic fertilizer alone. This increase could be linked to alterations in soil physicochemical properties, bacterial community function, and metabolism. Supplementation of organic fertilizer SQR9 increased rhizosphere microbiome richness and functional diversity. Fertilizer-sensitive microbes and functions responded as whole guilds. Pear yield was most positively associated with the Mitsuaria- and Actinoplanes-dominated ecological clusters and with gene clusters involved in ion transport and secondary metabolite biosynthesis. Together, these results suggested that bio-organic fertilizers mainly act indirectly on plant yield by creating soil chemical properties which promote a plant-beneficial microbiome. IMPORTANCE Bio-organic fertilization is a widely used, eco-friendly, sustainable approach to increasing plant productivity in the agriculture and fruit industries. However, it remains unclear whether the promotion of fruit productivity is related to specific changes in microbial inoculants, the resident microbiome, and/or the physicochemical properties of rhizosphere soils. We found that bio-organic fertilizers alter soil chemical properties, thus manipulating specific microbial taxa and functions within the rhizosphere microbiome of pear plants to promote yield. Our work unveils the ecological mechanisms which underlie the beneficial impacts of bio-organic fertilizers on yield promotion in fruit orchards, which may help in the design of more efficient biofertilizers to promote sustainable fruit production.

MILNP: Plant lncRNA-miRNA Interaction Prediction Based on Improved Linear Neighborhood Similarity and Label Propagation

Knowledge of the interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) is the basis of understanding various biological activities and designing new drugs. Previous computational methods for predicting lncRNA-miRNA interactions lacked for plants, and they suffer from various limitations that affect the prediction accuracy and their applicability. Research on plant lncRNA-miRNA interactions is still in its infancy. In this paper, we propose an accurate predictor, MILNP, for predicting plant lncRNA-miRNA interactions based on improved linear neighborhood similarity measurement and linear neighborhood propagation algorithm. Specifically, we propose a novel similarity measure based on linear neighborhood similarity from multiple similarity profiles of lncRNAs and miRNAs and derive more precise neighborhood ranges so as to escape the limits of the existing methods. We then simultaneously update the lncRNA-miRNA interactions predicted from both similarity matrices based on label propagation. We comprehensively evaluate MILNP on the latest plant lncRNA-miRNA interaction benchmark datasets. The results demonstrate the superior performance of MILNP than the most up-to-date methods. What's more, MILNP can be leveraged for isolated plant lncRNAs (or miRNAs). Case studies suggest that MILNP can identify novel plant lncRNA-miRNA interactions, which are confirmed by classical tools. The implementation is available on https://github.com/HerSwain/gra/tree/MILNP.

Dysbiosis of Gut Microbiota in Patients With Acute Myocardial Infarction

Acute myocardial infarction (AMI) continues as the main cause of morbidity and mortality worldwide. Interestingly, emerging evidence highlights the role of gut microbiota in regulating the pathogenesis of coronary heart disease, but few studies have systematically assessed the alterations and influence of gut microbiota in AMI patients. As one approach to address this deficiency, in this study the composition of fecal microflora was determined from Chinese AMI patients and links between gut microflora and clinical features and functional pathways of AMI were assessed. Fecal samples from 30 AMI patients and 30 healthy controls were collected to identify the gut microbiota composition and the alterations using bacterial 16S rRNA gene sequencing. We found that gut microflora in AMI patients contained a lower abundance of the phylum Firmicutes and a slightly higher abundance of the phylum Bacteroidetes compared to the healthy controls. Chao1 (P = 0.0472) and PD-whole-tree (P = 0.0426) indices were significantly lower in the AMI versus control group. The AMI group was characterized by higher levels of the genera Megasphaera, Butyricimonas, Acidaminococcus, and Desulfovibrio, and lower levels of Tyzzerella 3, Dialister, [Eubacterium] ventriosum group, Pseudobutyrivibrio, and Lachnospiraceae ND3007 group as compared to that in the healthy controls (P < 0.05). The common metabolites of these genera are mostly short-chain fatty acids, which reveals that the gut flora is most likely to affect the occurrence and development of AMI through the short-chain fatty acid pathway. In addition, our results provide the first evidence revealing remarkable differences in fecal microflora among subgroups of AMI patients, including the STEMI vs. NSTEMI, IRA-LAD vs. IRA-Non-LAD and Multiple (≥2 coronary stenosis) vs. Single coronary stenosis groups. Several gut microflora were also correlated with clinically significant characteristics of AMI patients, including LVEDD, LVEF, serum TnI and NT-proBNP, Syntax score, counts of leukocytes, neutrophils and monocytes, and fasting serum glucose levels. Taken together, the data generated enables the prediction of several functional pathways as based on the fecal microfloral composition of AMI patients. Such information may enhance our comprehension of AMI pathogenesis.

A comprehensive review for gut microbes: technologies, interventions, metabolites and diseases

Gut microbes have attracted much more attentions in the recent decade since their essential roles in the development of metabolic diseases, cancer and neurological diseases. Considerable evidence indicates that the metabolism of gut microbes exert influences on intestinal homeostasis and human diseases. Here, we first reviewed two mainstream sequencing technologies involving 16s rRNA sequencing and metagenomic sequencing for gut microbes, and data analysis methods assessing alpha and beta diversity. Next, we introduced some observational studies reflecting that many factors, such as lifestyle and intake of diets, drugs, contribute to gut microbes' quantity and diversity. Then, metabolites produced by gut microbes were presented to understand that gut microbes exert on host homeostasis in the intestinal epithelium and immune system. Finally, we focused on the molecular mechanism of gut microbes on the occurrence and development of several common diseases. In-depth knowledge of the relationship among interventions, gut microbes and diseases might provide new insights in to disease prevention and treatment.