Selten, G. | bioRxiv Science

bioRxiv2025

Bacillus: driver of functional states in synthetic plant root bacterial communities

Plant roots release root exudates to attract microbes that form root communities, which in turn promote plant health and growth. Root community assembly arises from millions of interactions between microbes and the plant, leading to robust and stable microbial networks. To manage the complexity of natural root microbiomes for research purposes, scientists have developed reductionist approaches using synthetic microbial inocula, known as SynComs. In recent years, an increasing number of studies employed SynComs to investigate root microbiome assembly and dynamics under various conditions or with specific plant mutants. These studies have identified bacterial traits linked to root competence, but if and how these traits shape root microbiome dynamics across conditions is not well understood. To explore whether bacterial trait selection follows recurrent patterns, we conducted a meta-analysis of nine SynCom studies involving plant roots. Surprisingly, we observed that root communities frequently assemble into two distinct functional states. Further analysis revealed that these states are characterized by differences in the abundance of Bacilli. We propose that these Bacilli-associated functional states are driven by microbial interactions such as quorum sensing and biofilm formation. Additionally, we show that host activities, including root exudation and immune responses, influence the functional state of the root microbiome. Whether natural root communities also organize into distinct functional states remains unclear, but the implications could be significant. Functional diversification within root communities may influence the success and effectiveness of plant-beneficial bioinoculants, particularly Bacilli-based inoculants. To optimize microbiome-driven plant benefits, a deeper understanding of the mechanisms underlying functional state differentiation in root microbiomes is needed.

microbiology↗

bioRxiv2025

SyFi: generating and using sequence fingerprints to distinguish SynCom isolates

The plant root microbiome is a complex community shaped by interactions among bacteria, the plant host, and the environment. Synthetic community (SynCom) experiments help disentangle these interactions by inoculating host plants with a representative set of culturable microbial isolates from the natural root microbiome. Studying these simplified communities provides valuable insights into microbiome assembly and function. However, as SynComs become increasingly complex to better represent natural communities, bioinformatics challenges arise. Specifically, accurately identifying, and quantifying SynCom members based on, for example, 16S rRNA amplicon sequencing becomes more difficult due to the high similarity of the target amplicon, limiting downstream interpretations. Here, we present SynCom Fingerprinting (SyFi), a bioinformatics workflow designed to improve the resolution and accuracy of SynCom member identification. SyFi consists of three modules: the first module constructs a genomic fingerprint for each SynCom member based on its genome sequence, accounting for both copy number and sequence variation in the target gene. The second module then extracts a specific region from this genomic fingerprint to create a secondary fingerprint focused on the target amplicon. The third module uses these fingerprints as a reference to perform pseudoalignment-based quantification of SynCom member abundance from amplicon sequencing reads. We demonstrate that SyFi outperforms standard amplicon analysis by leveraging natural intragenomic variation, enabling more precise differentiation of closely related SynCom members. As a result, SyFi enhances the reliability of microbiome experiments using complex SynComs, which more accurately reflect natural communities. This improved resolution is essential for advancing our understanding of the root microbiome and its impact on plant health and productivity in agricultural and ecological settings. SyFi is available at https://github.com/adriangeerre/SyFi. Impact statementSyFi represents a significant advancement in microbiome research by enhancing the accuracy and resolution of synthetic community (SynCom) member identification. By leveraging natural intragenomic variation, SyFi improves the differentiation of closely related microbial strains, addressing a key challenge in amplicon-based sequencing analysis. This increased precision allows researchers to more reliably track microbial dynamics in complex SynCom experiments, leading to deeper insights into microbiome assembly, function, and host-microbe interactions. As a result, SyFi strengthens the interpretability of microbiome studies, ultimately contributing to a better understanding of plant health and productivity in both agricultural and ecological contexts. Data SummaryThe data reported in this article have been deposited in the National Center for Biotechnology Information Short Read Archive BioProject database. SyFi fingerprint generation was run on a collection of 737 human gut-derived bacterial genomes from Forster et al. (2019) (Genomic read data deposited in the ENA under project numbers ERP105624 and ERP012217) and 447 Arabidopsis-derived bacterial genomes (Selten et al., 2024b) (NCBI Project numbers PRJNA1138681, PRJNA1139421 (Genomes), and PRJNA1131834 (Genomic reads)). A list of the closed genomes used for SyFi validation can be found at https://github.com/adriangeerre/SyFi. Subsequently, SyFi was validated on a complex SynCom dataset by pseudoaligning 16S rRNA V3-V4 and V5-V7 amplicon reads (PRJNA1191388) to SyFi-generated fingerprints and comparing this to shotgun metagenomics-sequenced dataset of the same samples in Selten et al. (2024a) (PRJNA1131994). This complex SynCom dataset included the inoculation of the 447 bacterial isolates on Arabidopsis, Barley, and Lotus roots.

genomics↗

bioRxiv2024

Functional capacities drive recruitment of bacteria into plant root microbiota

Host-associated microbiota follow predictable assembly patterns but show significant variation at the bacterial isolate level depending on the host and environmental context. This variability poses challenges for studying, predicting, and engineering microbiomes. Here we examined how Arabidopsis, Barley, and Lotus plants recruit specific bacteria from highly complex synthetic communities (SynComs) composed of hundreds of bacterial isolates originating from these plants when grown in natural soil. We discovered that, despite their taxonomic diversity, bacteria enriched by these three plant species encode largely overlapping functions. A set of 266 functions common among all host-associated communities was identified at the foundation of the microbiotas functional potential. Analysis of the differences observed between root-associated communities revealed that functions recruited by Arabidopsis and Barley were primarily driven by the SynCom composition, while Lotus selected fewer isolates but with more diverse functionalities, akin to a Swiss army knife strategy. We analysed the variation at the functional level and found this can be explained by the combined functions of bacteria at the family level. Additionally, across major taxa, the isolates covering a broader range of their familys functional diversity achieved higher relative abundance in the root communities. Our work sheds light on key functions and principles guiding the recruitment of bacterial isolates into root microbiota, offering valuable insights for microbiome engineering and inoculant discovery at a previously inaccessible taxonomic level.

plant biology↗