Nature’s AI shows NIH cuts could have reshaped microbiome research
A recent Nature article leverages a machine-learning algorithm to simulate NIH grant cut decisions by the Trump administration. In this article, CMFI Board Member Ruth Ley—whose research would have been directly affected according to the simulation—assesses the findings. Similar cuts to NIH funding in 2014 would also have affected the Human Microbiome Project, in which she was involved. This would have fundamentally changed the course of microbiome research. Ruth Ley highlights that without the Human Microbiome Project’s foundational grant, which underpinned data standards, analysis pipelines, and open sharing in the field, microbiome research might not exist as it does today.
“It’s our whole field! Dammit,” she says. “That particular grant was a big multicentre thing, but it had amazing trickle-down effects […] .”1
The Nature Index’s editorial team used a novel machine-learning approach to model the hypothetical impact of the NIH cuts made in 2014. By training an algorithm on the cuts made and decades of NIH grant and publication data, they predicted which awards would have been lost and how scientific output would have shifted. This bot-driven analysis allowed the authors to show, at unprecedented scale, how funding decisions ripple through research fields and shape scientific progress.
1Nienaber V, Leeming J. What research might be lost after the NIH's cuts? Nature trained a bot to find out. Nature. 2025 Sep 24. doi: 10.1038/d41586-025-02748-8. Epub ahead of print. PMID: 40993423.
Prof. Ruth Ley, PhD
Max Planck Institute for Biology Tübingen
Managing Director
Department of Microbiome Science
Leon Kokkoliadis
Public Relations Management
Tel: +49 7071 29-74707 / +49 152 346 79 269
leon.kokkoliadis@uni-tuebingen.de
Springer Nature