bioRxiv Science⌕ Search

Biology subjects

Antony-Babu, S.

Publications and source records attributed to Antony-Babu, S..

4 recordsLinked to original sources

Microbiome differentiation between micro-sympatric maize and teosinte reveals domestication-driven functional erosion of the microbiome across plant compartments

IntroductionCrop domestication has fundamentally transformed plant phenotypes through artificial selection, yet the consequences of domestication for plant-associated microbial communities across the plant-soil continuum remain poorly understood. Gap StatementWhile recent studies suggest that domestication impacts microbiome structures, the magnitude, mechanisms, and functional implications of such impacts have not been systematically quantified using controlled experimental designs that eliminate environmental confounding factors. AimTo characterize and quantify the effects of crop domestication on microbial community structure and function by comparing maize (Zea mays subsp. mays) and its wild ancestor Balsas teosinte (Zea mays subsp. parviglumis) across multiple plant compartments in an unmanipulated field setting in Mexico, maizes domestication center. MethodologyWe applied a micro-sympatric design in a natural setting to compare microbial communities between maize and Balsas teosinte across five plant compartments: bulk soil, rhizosphere, mucilage, leaves, and seeds. Full-length 16S rRNA gene sequencing was used for taxonomic characterization, Functional Annotation of Prokaryotic Taxa (FAPROTAX) and PICRUSt 2.0 were used to predict functional profiles, and network analysis was used to assess functional connectivity. ResultsCompartment identity explained 72.2% of variation in community structure, with consistent host effects across all niches (9.0%). Teosinte maintained significantly higher microbial diversity than maize across all compartments, with pronounced differences in seeds (32.0 {+/-} 1.9 vs 9.3 {+/-} 1.8 species, P < 0.01) and rhizosphere (60.3 {+/-} 5.8 vs 33.8 {+/-} 10.4 species, P < 0.01). Eighty-nine percent of predicted metabolic functions showed significant changes associated with domestication, with teosinte exhibiting enhanced nitrogen fixation (0.89 {+/-} 0.07 vs 0.44 {+/-} 0.04 in maize mucilage), siderophore production, and pathogen suppression. Network analysis revealed functional fragmentation in maize, with reduced connections (80 to 49) and lower clustering coefficients (0.62 {+/-} 0.03 vs 0.25 {+/-} 0.02, P < 0.001). ConclusionBalsas teosinte domestication fundamentally eroded microbial diversity and functional capacity in maize leading to a "domestication gap" that encompasses taxonomic loss, functional simplification, and network fragmentation, and replaced mutualistic plant-microbe partnerships with simplified microbial assemblages that may compromise crop resilience vis-a-vis a changing climate. Impact statementUnderstanding how plants select their microbial partners is crucial for enhancing agricultural productivity yet distinguishing between environmental and host genetic effects on microbiome assemblage remains challenging. Our study provides compelling evidence for host-driven microbiome assembly by comparing ancestral Balsas teosinte with derived maize growing in a common farm field in Mexico, eliminating environmental variation and experimental manipulation as confounding factors. By characterizing bacterial communities across different plant compartments, from soil to seed, we showed that each hosts genotype shaped divergent microbiome compositions despite growing in common environmental conditions. This research represents a significant step forward in understanding plant-microbe co-evolution during crop domestication and has three key implications. First, it suggests that microbiome traits were likely selected in conjunction with plant (host) traits during domestication and post-domestication selection. Second, it identifies specific bacterial communities that could be targeted for improving crop productivity and resilience. And third, it provides a methodological framework for studying host-microbe interactions in other crop-wild ancestor pairs. Our findings are particularly relevant for developing microbiome-based agricultural technologies and conservation strategies for beneficial plant-microbe interactions for deployment in traditional and modern farming systems. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

microbiology↗

Machine Learning-Guided Synthetic Microbial Communities Enable Functional and Sustainable Degradation of Persistent Environmental Pollutants

Persistent environmental pollutants demand the use of diverse microbial metabolic capabilities for effective degradation. While naturally occurring consortia or single strains often fall short in efficiency, synthetic microbial communities (SynComs) hold greater promise for enhanced degradation. To address this challenge, we developed GENIA (Genomically and Environmentally Networked Intelligent Assemblies), a genome-informed and machine learning-guided framework for the rational design of SynComs capable of multi-pollutant degradation under simulated environmental conditions. Using a microfluidic high-throughput cultivation platform, 2,155 bacterial strains were isolated from xenobiotic-enriched environments and screened for pollutant-specific growth. Whole-genome sequencing and functional annotation of 45 prioritized strains revealed metabolic traits associated with the potential degradation of challenging persistent environmental pollutants as proof of concept, i.e., lignin oxidation, atrazine dechlorination, and PFAS defluorination. These genomic profiles were encoded into spline-based graph representations and integrated within the GENIA pipeline, which combines graph neural networks, pathway complementarity modeling, and functional redundancy minimization to predict optimal community assemblies. The resulting nine-member community--comprising Pantoea dispersa, Atlantibacter hermannii, Pseudomonas fulva, Paenibacillus polymyxa, Bacillus cabrialesii, Micrococcus luteus, Bacillus pseudomycoides, Bacillus licheniformis, and Pseudomonas pergaminensis--was predicted to exhibit broad catabolic capacity and minimal intra-community competition. Kinetic experiments in minimal medium demonstrated simultaneous multi-pollutant degradation: lignin (91.6% removal by day 5), atrazine (91.4% removal by day 3), and PFOS (93.1% removal within seven days), representing a 2-4-fold improvement over existing approaches. GENIA establishes a scalable and generalizable framework that integrates systems-level genomics, phenotypic screening, and predictive modeling to engineer ecologically coherent microbial consortia with application to complex environmental bioremediation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/677392v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@1beee39org.highwire.dtl.DTLVardef@a0a1corg.highwire.dtl.DTLVardef@11ddc4aorg.highwire.dtl.DTLVardef@169ba57_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Characterization of Differences of Seed Endophytic Microbiome in Conventional and Organic Rice by Amplicon-based Sequencing and Culturing Methods

The seed serves as the primary source of microbial inoculum for plant microbiota, playing a crucial role in establishing microbial populations in plants across subsequent generations, ultimately impacting plant growth and its overall health. Cropping conditions, especially farming practices, can influence the composition and functionality of the seed microbiome. Very little is known about the differences in seed microbiome between organic and conventional production systems. In this study, we characterized the endophytic microbial populations in seeds of rice grown under organic and conventional management practices through culture-dependent and independent analyses. The V4 region of 16S rRNA was used for bacterial taxa identification, and the ITS1 region was used in the identification of fungal taxa. Our results revealed significantly higher Shannon and Simpson indices for bacterial diversity in the conventional farming system whereas the fungal diversity was higher for observed, Shannon, and Simpson indices in the organic farming system. The cultivable endophytic bacteria were isolated and identified by the full-length 16S rRNA gene. There was no difference in culturable endophytic bacterial isolates in rice seeds grown under both conventional and organic farming systems. Among 33 unique isolates tested in vitro, three bacteria Bacillus sp. ST24, Burkholderia sp. OR5, and Pantoea sp. ST25, showed antagonistic activities against Marasmius graminum, Rhizoctonia solani AG4, and R. solani AG11, the fungal pathogens causing rice seedling blight. IMPORTANCEIn this paper, we studied the differences in the endophytic microbial composition of rice seeds grown in conventional and organic farming systems. Our results demonstrate a greater bacterial diversity in conventional farming, while organic farming showcases a higher fungal diversity. Additionally, our research reveals the ability of seed bacterial endophytes to inhibit the growth of three fungal pathogens responsible for causing seedling blight in rice. This study provides valuable insights into the potential use of beneficial seed microbial endophytes for developing a novel microbiome-based strategy in the management rice diseases. Such an approach has the potential to enhance overall plant health and improve crop productivity.

microbiology↗

Core bacteria associated with hyphosphere of Fusarium oxysporum f. sp. niveum over spatial and temporal differences.

BackgroundBacteria and fungi co-inhabit the soil microbiome in dynamic interactions. In the rhizosphere, fungi and bacteria have been studied to synergistically colonize soil as beneficial or as antagonists to form a pathobiome. These variations of soil bacterial community from pathogen and nonpathogen form of FOSC have been researched, however the bacterial community within the hyphosphere has yet to be studied thoroughly for direct pathogen interkingdom interactions. This study used 16S rRNA gene sequencing and a to decipher the bacteriome diversity associated with the hyphosphere of three isolates of Fusarium oxysporum f. sp. niveum race 2 (FON2) with temporal and spatial differences. ResultsOur results show a core microbiome that is shared among the three isolates regardless of the differences of spatial and temporal differences. The core hyphosphere community visualized as a ternary plot was made up 15 OTUs which were associated with all three FON2. Although a few operational taxonomic units (OTUs) were significantly correlated with a particular isolate of FON2, reported in the LDA (p<0.05), these OTUs were still present as part of the core in all isolates. Co-occurrence analysis and correlation plot identified a negative correlation among most of the microbiota which may indicate a positive correlation to the FON2 that is not tested. ConclusionsThe study indicates a core microbiota associated with FON2 regardless of the isolates temporal and spatial differences. Through our results we provide insights into the microbe-microbe dynamic of the pathogens success and its ability to recruit a core pathobiome. Our research promotes the concept of pathogens not being lone invaders but recruits from the established host microbiome to form a pathobiome.

microbiology↗