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2024

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Shanghai Jiaotong University Zhao Liping/Peng Yongde/Zhang Chenhong and other teams cooperated with the latest Cell to develop new research methods for the field.

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Essential to human health, the gut microbiome is a complex adaptive system, similar to a vital organ.To identify the core gut microbes associated with health, the researchers followed the principles of systems biology, where stable relationships imply core components.

On October 7, 2024, Zhao Liping, Peng Yongde, Zhang Chenhong and Shi Yu of Qidong People's Hospital of Shanghai Jiaotong University jointly communicated inCellOnline published the title"A core microbiome signature as an indicator of healthBy analyzing metagenomic datasets from a high-fiber diet that intervened in type 2 diabetes and 26 case-control studies involving 15 diseases, the study identified a set of stably associated genome pairs in a co-abundance network of dietary interventions and disease disturbances.

These genomes form a model of "two competing guilds" (TCGs), with one guild specializing in fiber fermentation and butyrate production and the other characterized by virulence and antibiotic resistance. The random forest model successfully discriminated between cases and controls for multiple diseases and predicted the outcome of immunotherapy by using these genomes.In summary, the guild-based approach is genome-specific, database-independent, and focused on interactions. It identifies a core microbiome feature as an overall health indicator and potential common target for health enhancement.

 

Similar to a vital organ, the gut microbiota plays a key role in the host's health, influencing a range of processes from nutrient metabolism to immune function and behavior.Advances in high-throughput sequencing technology have extensively characterized this complex ecosystem, revealing detailed insights into its composition and function. However, traditional analysis methods, such as taxonomy-based and gene-centric methods, often produce inconsistent results. For example, in different studies, taxa like Lactobacillus or the phyla clonorum have been positively, negatively, or not associated with diseases such as obesity or diabetes, A new methodological framework is urgently needed to identify key microbiome members as biomarkers for health maintenance and disease management.

Traditional methods often rely on low-resolution features, such as taxonomic labels, which fail to identify subtle genetic and functional changes within the same taxon in a microbial community.To improve the resolution of microbial analysis, researchers advocate the use of high-quality metagenomic assembly genomes (HQMAGs) assembled from scratch. HQMAGs achieve near-line level resolution by employing an average nucleotide identification (ANI) differentiation threshold of 1%-significantly better than the typical 5%-6% used for species definition. In addition, to facilitate database-independent tracking of microbial entities in various studies and samples, the researchers assigned a universally unique identifier (UUID) to each HQMAG. This strategy includes new or understudied microorganisms in the analysis and enhances data comparison and integration between different projects by using these UUIDs as genomic markers. HQMAGs provide a deeper understanding of the function of health-related microorganisms by analyzing all genes in the genomic context, and can even perform functional analysis of unannotated genes.This strategic improvement in microbial genomic analysis lays the foundation for more precise identification and understanding of microbial roles in health and disease.

In addition, traditional analysis methods tend to focus on the differential analysis of a single feature, while ignoring the complex interactions between microorganisms.This approach ignores the fact that the gut microbiota is an illustration of a complex adaptive system (CAS) characterized by components or factors that interact in a dynamic and non-linear manner. These interactions lead to system-level emergent properties that cannot be predicted from the behavior of individual agents alone. Within this microbiota CAS, microbes form structural modules known as "guilds" that underpin the emerging properties of the gut ecosystem that support host health. Members of the same guild may come from different taxonomic backgrounds and exhibit co-rich behaviors. The researchers used HQMAG's co-abundance analysis to describe a guild-level organization based on interactions between microbes, clarifying "who works with whom" in this complex ecosystem ". Through this perspective, each guild is associated with human clinical parameters, providing insights into their impact on health and disease, embodying the CAS principle that "the whole is greater than the sum of its parts.
Using this innovative approach, researchers have elucidated the microbiota associated with diseases such as obesity, type 2 diabetes (T2D), diabetic nephropathy, diabetic neuropathy, and coronavirus disease 2019 (COVID-19).These studies highlight the critical role of microbial interactions in the dynamics of microbiome function and their broader impact on host health. Therefore, this study uses a guild-based framework that emphasizes genome specificity, database independence, and interaction-focused analysis. This approach has changed the way we look at microbial entities-from thinking of them as separate units to exploring their complex patterns of interaction. This perspective is crucial for exploring the system-level functions of the gut microbiome and understanding their impact on host health. This fundamental understanding guides us in exploring how these complex microbial networks influence overall health outcomes.
Utilizing a guild-based approach, this study focuses on stable interactions to identify health-related microbial entities.Inspired by the principles of systems biology, where stable interactions imply core system components, the researchers hypothesized that stable related genome pairs under different conditions may be core members of health-related guilds, which may be influenced by evolutionary forces due to their key role in human health. By constructing a co-abundance network of individual HQMAGs under different environmental disturbances (including dietary interventions and differences in health status), a group of stably related core HQMAGs were found.

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