Soil microbiome engineering for sustainable nutrient cycling in tropical agroecosystems using metagenomics and machine learning

Project Abstract

In tropical agroecosystems, soil health and nutrient cycling are critically shaped by the complex interactions among microbial communities, soil physicochemical properties, crop management, and climate variability, yet the functional potential and activity of these microbiomes remain poorly understood at the ecosystem scale. This study integrates metagenomic profiling, shotgun sequencing, and advanced bioinformatics with machine learning to decipher how microbial communities govern nutrient transformations (nitrogen, phosphorus, sulfur, and micronutrients) and to identify leverage points for enhancing soil fertility and crop productivity under sustainable management. We characterize baseline microbial diversity, functional gene repertoires, and metabolic pathways across diverse tropical soils subjected to contrasting agronomic practices (organic amendments, synthetic fertilizers, crop rotations, and residue management) in multiple representative agroecologies. By coupling high-resolution taxonomic and functional annotations with metatranscriptomic and metabolomic data, we reveal active pathways linked to mineralization, immobilization, nitrification/denitrification, phosphorus solubilization, siderophore production, and organic matter decomposition, and how these processes respond to moisture regimes, temperature fluctuations, and soil structure. A novel machine learning framework is developed to predict nutrient fluxes from integrated omics, soil physico-chemical features, and management histories, enabling scenario-based forecasting under climate variability. The model identifies key microbial consortia and keystone genes driving efficient nutrient recycling and resilience to disturbances, and it prioritizes candidate microbial inoculants and agronomic interventions that maximize nutrient use efficiency while minimizing environmental losses. Field validation across long-term trials assesses the transferability of microbial indicators and predictive models to real-world settings, including assessment of greenhouse gas emissions and soil carbon stabilization. We also evaluate the socio-economic dimensions of adopting microbiome-informed practices by estimating cost-benefit trade-offs, adoption barriers, and policy implications for tropical farming communities. The outputs include a publicly accessible database of microbial taxa, functional genes, and associated nutrient pathways, along with an open-source toolkit for microbiome-informed soil management decision-making. This research advances a systems-level understanding of soil microbiome functions in tropical soils, demonstrating how targeted manipulation of microbial networks through informed management can stabilize nutrient cycling, reduce fertilizer dependency, and enhance crop yields under climate change, thereby contributing to sustainable intensification and long-term soil health in tropical agroecosystems.

Project Overview

What This Project Is About

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A straightforward study exploring how tiny organisms in soil influence nutrient availability in tropical farms. It combines modern gene-based techniques with simple data analysis to understand how microbial communities help or hinder plant nutrition.

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The Problem It Addresses

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Tropical soils often lose nutrients quickly, requiring more fertilizers. The project looks at the unseen soil life to find ways to keep nutrients available to crops naturally, reducing inputs and environmental impact.

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Objectives of the Project

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1. Identify key soil microbes linked to nutrient release in tropical soils.
2. Assess how farming practices affect microbial communities.
3. Use simple data tools to link microbes with nutrient levels and crop growth.
4. Suggest farming approaches that support beneficial microbes.

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What You Will Do Step by Step

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1) Learn basic soil sampling and lab-safe handling. 2) Collect soil samples from different tropical farms. 3) Extract microbial DNA and run basic sequencing assays. 4) Compile nutrient measurements and plant growth data. 5) Use beginner-friendly software to identify microbial patterns. 6) Interpret results to connect microbes with nutrient cycling. 7) Propose practical farming tweaks. 8) Prepare a clear report and short presentation.

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Expected Outcome

Clear ideas on which microbes help unlock nutrients, practical farming recommendations, and a simple data story showing how soil life supports crop nutrition.