ArticlemSystems2021
Retooling Microbiome Engineering for a Sustainable Future.
Article in mSystems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Antimicrobial peptides: An important link in the game theory between plants and pathogens.Journal of advanced research · 2026Review
- A mathematical framework to correct for compositionality in microbiome data sets.Applied and environmental microbiology · 2026Article
- Productive chaos and precision engineering: decoupling discovery from manufacturing to revolutionize plant-inspired therapeutics.Frontiers in plant science · 2026Article
- Carbohydrate-active enzyme architectures reflect distinct fungal and bacterial strategies for lignocellulose conversion to volatile fatty acids.ISME communications · 2026Article
- Engineering nitrogen-fixing microbiomes with waste-derived carbon sources: toward circular and resilient biofertilizer solution.Frontiers in microbiology · 2025Article
- Global WWTP Microbiome-based Integrative Information Platform: From experience to intelligence.Environmental science and ecotechnology · 2024Review
- Microbiome modulation in inflammatory diseases: Progress to microbiome genetic engineering.Cancer cell international · 2023Review
- Integrating a tailored recurrent neural network with Bayesian experimental design to optimize microbial community functions.PLoS computational biology · 2023Article
- Engineering microbial consortia with rationally designed cellular interactions.Current opinion in biotechnology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbial communities (microbiomes) have been harnessed in biotechnology applications such as wastewater treatment and bioremediation for over a century. Traditionally, engineering approaches have focused on shaping the environment to steer microbiome function versus direct manipulation of the microbiome's metabolic network. While these selection-based approaches have proven to be invaluable for guiding bioprocess engineering, they do not enable the precise manipulation and control of microbiomes required for unlocking their full potential. Over the past 2 decades, systems biology has revolutionized our understanding of the metabolic networks driving microbiome processes, and more recently genetic engineering tools have started to emerge for nonmodel microorganisms and microbiomes. In this commentary, I discuss how systems biology approaches are being used to generate actionable understanding of microbiome functions in engineered ecosystems. I also highlight how integrating synthetic biology, automation, and machine learning can accelerate microbiome engineering to meet the sustainability challenges of the future.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.