m-CAFEs SFA — Microbial Community Analysis & Functional Evaluation in Soils

About m-CAFEs

Toward a Predictive Science of Soil Microbiomes

m-CAFEs is a multi-institutional Science Focus Area studying how microbes around plant roots assemble, interact, and function. Our team combines next-generation biotechnologies — including CRISPR-Cas and bacteriophage tools — with AI/ML models and unique laboratory ecosystems to understand soil microbial communities at unprecedented resolution.

By learning how genes and metabolites direct community assembly, we are building the foundation for a new kind of predictive microbiome science — one that can improve the growth of bioenergy crops like sorghum, advance the DOE Genesis Mission, and develop transformantive microbiome biotechnologies.

Our Science

Four Integrated Research Areas

m-CAFEs research advances along four connected research areas, each contributing to a unified goal: to understand, predict, design, and support microbial communities that matter for DOE missions.

Research Area 01

Developing New Biotechnologies

We build next-generation tools — CRISPR-Cas systems and phage-based approaches — to study how genes, molecules, and microbes shape soil community function in their environment.

Primary PIsDoudna, Barrangou, Banfield, Deutschbauer, Mukhopadhyay

Research Area 02

Understanding Microbial Community Assembly

We use large-scale characterization to learn how microbes interact and assemble around plant roots.

Primary PIsDeutschbauer, Northen, Chakraborty, Doudna, Hill-Maini

Research Area 03 Genesis Mission

AI/ML Modeling

We use laboratory ecosystems to develop AI/ML models that learn from automated experiments and predict how microbial communities assemble and respond to perturbations.

Primary PIsSegrè, Wang, Hill-Maini, Northen

Research Area 04

Rhizosphere Engineering for Sorghum

We apply these tools to sorghum, a key bioenergy crop, to understand and support how root microbiomes contribute to plant productivity in real-world conditions.

Primary PIsEudes, Zhalnina, Northen, Chakraborty, Mukhopadhyay, Barrangou, Doudna, Banfield

Experimental Platforms

A Scalable, Controlled Laboratory Ecosystem Toolkit

EcoFAB

Bench-scale fabricated ecosystem devices for reproducible plant-microbiome studies, distributed as community kits.

EcoPOD

Meter-scale contained ecosystems extending m-CAFEs science to more complex soil environments.

EcoBOT

Automated robotic imaging and sampling system enabling high-throughput experiments integrated with AI/ML.

BioEPIC

LBNL's new facility offering one-of-a-kind capabilities for soil-microbe-plant research.

Science Highlights

Recent Discoveries

Selected peer-reviewed findings from our team — illustrating progress across our four research areas and contributions to DOE BER's mission.

2026

Reduced methane emissions in transgenic rice genotypes are associated with altered rhizosphere microbial hydrogen cycling

Shi et al., Nature Communications, 10.1038/s41467-026-68640-9

2026

Phage-mediated delivery of CRISPR payloads

Beckley et al., Current Opinion in Microbiology, 10.1016/j.mib.2025.102704

2025

A miniature CRISPR–Cas10 enzyme confers immunity by inhibitory signalling

Doherty et al., Nature, 10.1038/s41586-025-09569-9

2025

Bacterial fitness for plant colonization is influenced by plant growth substrate

Torres et al., New Phytologist, 10.1111/nph.70617

2025

Biophysical metabolic modeling of complex bacterial colony morphology

Dukovski et al., Cell Systems, 10.1016/j.cels.2025.101352

2025

Breaking the reproducibility barrier with standardized protocols for plant-microbiome research

Novak et al., PLOS Biology, 10.1371/journal.pbio.3003358

2025

CRISPRi-ART enables functional genomics of diverse bacteriophages using RNA-binding dCas13d

Adler et al., Nature Microbiology, 10.1038/s41564-025-01935-7

2025

EcoBOT: an AI/ML enabled automated phenotyping capability for model plants

Andeer et al., Frontiers in Plant Science, 10.3389/fpls.2025.1633557

2025

Generating functional plasmid origins with OriGen

Irvine et al., Nucleic Acids Research, 10.1093/nar/gkaf1198

Team

Principal Investigators

The m-CAFEs team brings together 12 leading researchers across 6 institutions, combining deep expertise in microbial genetics, phage biology, plant biology, metabolomics, AI/ML, and environmental microbiology.

Trent Northen

LBNL

Lab Research Manager

Metabolomics, EcoFABs, plant-microbe interactions

Adam Deutschbauer

LBNL

Technical Co-Manager

High-throughput functional genomics

Jennifer Doudna

UCB / LBNL

Co-PI

CRISPR-Cas biology, genome editing

Jillian Banfield

UCB / LBNL

Co-PI

Geomicrobiology, metagenomics

Rodolphe Barrangou

NC State University

Co-PI

CRISPR-Cas systems, bacterial genetics

Romy Chakraborty

LBNL

Co-PI

Molecular ecology, biogeochemistry

Aymerick Eudes

LBNL

Co-PI

Plant physiology, metabolic engineering, JBEI

Vayu Hill-Maini

Stanford University

Co-PI

AI/ML, computational biology

Aindrila Mukhopadhyay

LBNL

Co-PI

Microbial transport, signaling, stress response

Daniel Segrè

Boston University

Co-PI

Computational models of microbial communities

Mingxun Wang

UC Riverside

Co-PI

Omics computation, metabolomics bioinformatics

Kateryna Zhalnina

LBNL

Co-PI

Soil and rhizosphere microbiology

Partner Institutions

Lawrence Berkeley National Laboratory UC Berkeley NC State University Stanford University UC Riverside Boston University

Program Management

The m-CAFEs SFA is led by Trent Northen (Laboratory Research Manager) and Adam Deutschbauer (Technical Co-Manager). High-level project management support is provided by Caitlin Chiang and Suzanne Kosina.

External Collaborations

m-CAFEs collaborates with the three SFAs co-located in BioEPIC — Watershed, ENIGMA, and Belowground Biogeochemistry — and with a number of external collaborators including other National Laboratories, Universities, Industry, Science Focus Area Projects, and Bioenergy Research Centers.