Background: Next-generation sequencing (NGS) approaches have revolutionized gut microbiome research and can provide strain-level resolution, but these techniques have limitations in that they are only semi-quantitative, suffer from high detection limits, and generate data that is compositional. The present study aimed to systematically compare quantitative PCR (qPCR) and droplet digital PCR (ddPCR) for the absolute quantification of Limosilactobacillus reuteri strains in human fecal samples and to develop an optimized protocol for the absolute quantification of bacterial strains in fecal samples.
Results: Using strain-specific PCR primers for L. reuteri 17938, ddPCR showed slightly better reproducibility, but qPCR was almost as reproducible and showed comparable sensitivity (limit of detection [LOD] around 104 cells/g feces) and linearity (R2 > 0.98) when kit-based DNA isolation methods were used. qPCR further had a wider dynamic range and is cheaper and faster. Based on these findings, we conclude that qPCR has advantages over ddPCR for the absolute quantification of bacterial strains in fecal samples. We provide an optimized and easy-to-follow step-by-step protocol for the design of strain-specific qPCR assays, starting from primer design from genome sequences to the calibration of the PCR system. Validation of this protocol to design PCR assays for two L. reuteri strains, PB-W1 and DSM 20016 T, resulted in a highly accurate qPCR with a detection limit in spiked fecal samples of around 103 cells/g feces. Applying our strain-specific qPCR assays to fecal samples collected from human subjects who received live L. reuteri PB-W1 or DSM 20016 T during a human trial demonstrated a highly accurate quantification and sensitive detection of these two strains, with a much lower LOD and a broader dynamic range compared to NGS approaches (16S rRNA gene sequencing and whole metagenome sequencing).
Conclusions: Based on our analyses, we consider qPCR with kit-based DNA extraction approaches the best approach to accurately quantify gut bacteria at the strain level in fecal samples. The provided step-by-step protocol will allow scientists to design highly sensitive strain-specific PCR systems for the accurate quantification of bacterial strains of not only L. reuteri but also other bacterial taxa in a broad range of applications and sample types. Video Abstract.
Background: To adapt to constantly changing environments, ancient gymnosperms have coevolved with diverse endophytic fungi that are essential for the fitness and adaptability of the plant host. However, the effect of sex on plant-endophyte interactions in response to environmental stressors remains unknown. RNA-seq integrated with ITS analysis was applied to reveal the potential mechanisms underlying the sex-specific responses of Taxus mairei to ultraviolet (UV)-B radiation.
Results: Enrichment analysis suggested that sex influenced the expression of several genes related to the oxidation-reduction system, which might play potential roles in sex-mediated responses to UV-B radiations. ITS-seq analysis clarified the effects of UV-B radiation and sex on the composition of endophytic fungal communities. Sex influenced various secondary metabolic pathways, thereby providing chemicals for T. mairei host to produce attractants and/or inhibitors to filter microbial taxa. Analysis of fungal biomarkers suggested that UV-B radiation reduced the effect of sex on fungal communities. Moreover, Guignardia isolate #1 was purified to investigate the role of endophytic fungi in sex-mediated responses to UV-B radiation. Inoculation with spores produced by isolate #1 significantly altered various oxidation-reduction systems of the host by regulating the expression of APX2, GST7 NCED1, ZE1, CS1, and CM1.
Conclusion: These results revealed the roles of endophytic fungi in sex-mediated responses to UV-B radiation and provided novel insights into the sex-specific responses of Taxus trees to environmental stressors. Video Abstract.
Background: Microbial anaerobic metabolism is a key driver of biogeochemical cycles, influencing ecosystem function and health of both natural and engineered environments. However, the temporal dynamics of the intricate interactions between microorganisms and the organic metabolites are still poorly understood. Leveraging metagenomic and metabolomic approaches, we unveiled the principles governing microbial metabolism during a 96-day anaerobic bioreactor experiment.
Results: During the turnover and assembly of metabolites, homogeneous selection was predominant, peaking at 84.05% on day 12. Consistent dynamic coordination between microbes and metabolites was observed regarding their composition and assembly processes. Our findings suggested that microbes drove deterministic metabolite turnover, leading to consistent molecular conversions across parallel reactors. Moreover, due to the more favorable thermodynamics of N-containing organic biotransformations, microbes preferentially carried out sequential degradations from N-containing to S-containing compounds. Similarly, the metabolic strategy of C18 lipid-like molecules could switch from synthesis to degradation due to nutrient exhaustion and thermodynamical disadvantage. This indicated that community biotransformation thermodynamics emerged as a key regulator of both catabolic and synthetic metabolisms, shaping metabolic strategy shifts at the community level. Furthermore, the co-occurrence network of microbes-metabolites was structured around microbial metabolic functions centered on methanogenesis, with CH4 as a network hub, connecting with 62.15% of total nodes as 1st and 2nd neighbors. Microbes aggregate molecules with different molecular traits and are modularized depending on their metabolic abilities. They established increasingly positive relationships with high-molecular-weight molecules, facilitating resource acquisition and energy utilization. This metabolic complementarity and substance exchange further underscored the cooperative nature of microbial interactions.
Conclusions: All results revealed three key rules governing microbial anaerobic degradation. These rules indicate that microbes adapt to environmental conditions according to their community-level metabolic trade-offs and synergistic metabolic functions, further driving the deterministic dynamics of molecular composition. This research offers valuable insights for enhancing the prediction and regulation of microbial activities and carbon flow in anaerobic environments. Video Abstract.
Background: Plant-associated microorganisms can be found in various plant niches and collectively comprise the plant microbiome. The plant microbiome assemblages have been extensively studied, primarily in model species. However, a deep understanding of the microbiome assembly associated with plant health is still needed. Ginger rhizome rot has been variously attributed to multiple individual causal agents. Due to its global relevance, we used ginger and rhizome rot as a model to elucidate the metabolome-driven microbiome assembly associated with plant health.
Results: Our study thoroughly examined the biodiversity of soilborne and endophytic microbiota in healthy and diseased ginger plants, highlighting the impact of bacterial and fungal microbes on plant health and the specific metabolites contributing to a healthy microbial community. Metabarcoding allowed for an in-depth analysis of the associated microbial community. Dominant genera represented each microbial taxon at the niche level. According to linear discriminant analysis effect size, bacterial species belonging to Sphingomonas, Quadrisphaera, Methylobacterium-Methylorubrum, Bacillus, as well as the fungal genera Pseudaleuria, Lophotrichus, Pseudogymnoascus, Gymnoascus, Mortierella, and Eleutherascus were associated with plant health. Bacterial dysbiosis related to rhizome rot was due to the relative enrichment of Pectobacterium, Alcaligenes, Klebsiella, and Enterobacter. Similarly, an imbalance in the fungal community was caused by the enrichment of Gibellulopsis, Pyxidiophorales, and Plectosphaerella. Untargeted metabolomics analysis revealed several metabolites that drive microbiome assembly closely related to plant health in diverse microbial niches. At the same time, 6-({[3,4-dihydroxy-4-(hydroxymethyl)oxolan-2-yl]oxy}methyl)oxane-2,3,4,5-tetrol was present at the level of the entire healthy ginger plant. Lipids and lipid-like molecules were the most significant proportion of highly abundant metabolites associated with ginger plant health versus rhizome rot disease.
Conclusions: Our research significantly improves our understanding of metabolome-driven microbiome structure to address crop protection impacts. The microbiome assembly rather than a particular microbe's occurrence drove ginger plant health. Most microbial species and metabolites have yet to be previously identified in ginger plants. The indigenous microbial communities and metabolites described can support future strategies to induce plant disease resistance. They provide a foundation for further exploring pathogens, biocontrol agents, and plant growth promoters associated with economically important crops. Video Abstract.