
An interdisciplinary team of Rice University researchers has uncovered previously unknown relationships between bacteriophages — viruses that infect bacteria — and their bacterial hosts, offering a powerful new tool for next-generation microbiome engineering.
Published in Nature Communications, the study utilizes a Rice-developed RNA-based barcoding system that allows scientists to identify which bacteria receive genetic material from bacteriophages (also known as phages) in complex microbial environments. The approach enabled researchers to uncover a previously unreported group of bacterial hosts for the well-studied bacteriophage P1 and examine how subtle changes in viral structure influence which microbes a phage can target.
“Phages are everywhere, and they play an enormous role in shaping microbial communities and moving genes between bacteria,” said corresponding author Lauren Stadler, associate professor of civil and environmental engineering. “But identifying which phages interact with which hosts in real-world microbial communities has been a long-standing challenge. This work gives us a scalable way to directly observe those interactions.”
Phages are the most abundant biological entities on Earth, outnumbering all other forms of life. They influence microbial ecosystems by killing bacteria, altering their metabolism and transferring genes between organisms. Scientists are increasingly interested in harnessing phages as alternatives to antibiotics and as tools for engineering microbiomes, but traditional techniques for understanding which bacteria a phage can infect often require bacteria to be cultured in the laboratory, are labor-intensive or cannot distinguish between viruses merely attaching to cells and successfully transferring DNA.
To overcome these limitations, the Rice team, which also included James Chappell, associate professor of biosciences, and Jonathan Silberg, the Stewart Memorial Professor of BioSciences, among others, adapted their synthetic biology platform known as RNA-addressable modification. Originally developed to track gene transfer through bacterial conjugation, the system uses an engineered ribozyme (an RNA strand capable of catalyzing specific biochemical reactions) that inserts a unique “barcode” into a bacterium’s 16S ribosomal RNA after receiving DNA from a phage. Researchers can then identify the recipient organism through targeted RNA sequencing.
“Instead of trying to isolate every interaction individually, we let the phage leave a molecular signature behind in the cells it reaches,” Stadler said. “That gives us a sensitive, high-throughput way to map host range directly within microbial communities.”
The researchers incorporated the barcoding system into bacteriophage P1, a virus known to transfer DNA among enteric bacteria (microorganisms that reside primarily in the intestinal tracts of humans and animals) and thought to contribute to the spread of antibiotic resistance genes. They then tested the approach in laboratory-grown microbial communities and in wastewater collected from a Houston-area treatment plant.
The wastewater experiments produced an even more surprising discovery. Among the organisms receiving genetic material from P1 were members of the order Aeromonadales, including Aeromonas hydrophila, a common wastewater bacterium that had never before been identified as a P1 host.
“Finding a completely new host group in a complex environmental sample demonstrates the power of this approach,” Stadler said. “There are likely many important phage-host relationships that remain hidden simply because we haven’t had the tools to observe them easily and without laborious methods.”
The team also used the technology to investigate how different viral tail fibers — protein structures phages use to recognize and attach to bacteria — influence host range. By engineering phage-derived particles with alternative tail fibers and applying the RNA barcoding system, the researchers showed that each tail fiber targeted a distinct set of microbes within wastewater communities.
“These experiments allowed us to see how relatively small genetic changes in a phage can dramatically alter which bacteria it interacts with,” Stadler said. “That information is incredibly valuable for designing phages with specific functions, whether the goal is delivering beneficial genes or selectively eliminating harmful bacteria.”
In the future, this method could accelerate efforts to develop engineered phages for medicine, environmental remediation and industrial biotechnology. Because the approach relies on common molecular biology techniques such as amplicon sequencing rather than labor-intensive culturing methods, it could also enable large-scale studies of viral ecology across diverse microbiomes.
Source – Rice University
An interdisciplinary team of Rice University researchers has uncovered previously unknown relationships between bacteriophages — viruses that infect bacteria — and their bacterial hosts, offering a powerful new tool for next-generation microbiome engineering.
Published in Nature Communications, the study utilizes a Rice-developed RNA-based barcoding system that allows scientists to identify which bacteria receive genetic material from bacteriophages (also known as phages) in complex microbial environments. The approach enabled researchers to uncover a previously unreported group of bacterial hosts for the well-studied bacteriophage P1 and examine how subtle changes in viral structure influence which microbes a phage can target.
Phages are the most abundant biological entities on Earth, outnumbering all other forms of life. They influence microbial ecosystems by killing bacteria, altering their metabolism and transferring genes between organisms. Scientists are increasingly interested in harnessing phages as alternatives to antibiotics and as tools for engineering microbiomes, but traditional techniques for understanding which bacteria a phage can infect often require bacteria to be cultured in the laboratory, are labor-intensive or cannot distinguish between viruses merely attaching to cells and successfully transferring DNA.
To overcome these limitations, the Rice team, which also included James Chappell, associate professor of biosciences, and Jonathan Silberg, the Stewart Memorial Professor of BioSciences, among others, adapted their synthetic biology platform known as RNA-addressable modification. Originally developed to track gene transfer through bacterial conjugation, the system uses an engineered ribozyme (an RNA strand capable of catalyzing specific biochemical reactions) that inserts a unique “barcode” into a bacterium’s 16S ribosomal RNA after receiving DNA from a phage. Researchers can then identify the recipient organism through targeted RNA sequencing.
The researchers incorporated the barcoding system into bacteriophage P1, a virus known to transfer DNA among enteric bacteria (microorganisms that reside primarily in the intestinal tracts of humans and animals) and thought to contribute to the spread of antibiotic resistance genes. They then tested the approach in laboratory-grown microbial communities and in wastewater collected from a Houston-area treatment plant.
The wastewater experiments produced an even more surprising discovery. Among the organisms receiving genetic material from P1 were members of the order Aeromonadales, including Aeromonas hydrophila, a common wastewater bacterium that had never before been identified as a P1 host.
The team also used the technology to investigate how different viral tail fibers — protein structures phages use to recognize and attach to bacteria — influence host range. By engineering phage-derived particles with alternative tail fibers and applying the RNA barcoding system, the researchers showed that each tail fiber targeted a distinct set of microbes within wastewater communities.
In the future, this method could accelerate efforts to develop engineered phages for medicine, environmental remediation and industrial biotechnology. Because the approach relies on common molecular biology techniques such as amplicon sequencing rather than labor-intensive culturing methods, it could also enable large-scale studies of viral ecology across diverse microbiomes.
Source – Rice University
LaTurner ZW, Dysart MJ, Schwartz SK, Zeng E, Chappell J, Silberg JJ, Stadler LB. (2026) Cross-order detection of bacteriophage transduction in microbial communities using RNA barcoding. Nature Communications 17(1):4308. [article]
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An interdisciplinary team of Rice University researchers has uncovered previously unknown relationships between bacteriophages — viruses that infect bacteria — and their bacterial hosts, offering a powerful new tool for next-generation microbiome engineering.
Published in Nature Communications, the study utilizes a Rice-developed RNA-based barcoding system that allows scientists to identify which bacteria receive genetic material from bacteriophages (also known as phages) in complex microbial environments. The approach enabled researchers to uncover a previously unreported group of bacterial hosts for the well-studied bacteriophage P1 and examine how subtle changes in viral structure influence which microbes a phage can target.
Phages are the most abundant biological entities on Earth, outnumbering all other forms of life. They influence microbial ecosystems by killing bacteria, altering their metabolism and transferring genes between organisms. Scientists are increasingly interested in harnessing phages as alternatives to antibiotics and as tools for engineering microbiomes, but traditional techniques for understanding which bacteria a phage can infect often require bacteria to be cultured in the laboratory, are labor-intensive or cannot distinguish between viruses merely attaching to cells and successfully transferring DNA.
To overcome these limitations, the Rice team, which also included James Chappell, associate professor of biosciences, and Jonathan Silberg, the Stewart Memorial Professor of BioSciences, among others, adapted their synthetic biology platform known as RNA-addressable modification. Originally developed to track gene transfer through bacterial conjugation, the system uses an engineered ribozyme (an RNA strand capable of catalyzing specific biochemical reactions) that inserts a unique “barcode” into a bacterium’s 16S ribosomal RNA after receiving DNA from a phage. Researchers can then identify the recipient organism through targeted RNA sequencing.
The researchers incorporated the barcoding system into bacteriophage P1, a virus known to transfer DNA among enteric bacteria (microorganisms that reside primarily in the intestinal tracts of humans and animals) and thought to contribute to the spread of antibiotic resistance genes. They then tested the approach in laboratory-grown microbial communities and in wastewater collected from a Houston-area treatment plant.
The wastewater experiments produced an even more surprising discovery. Among the organisms receiving genetic material from P1 were members of the order Aeromonadales, including Aeromonas hydrophila, a common wastewater bacterium that had never before been identified as a P1 host.
The team also used the technology to investigate how different viral tail fibers — protein structures phages use to recognize and attach to bacteria — influence host range. By engineering phage-derived particles with alternative tail fibers and applying the RNA barcoding system, the researchers showed that each tail fiber targeted a distinct set of microbes within wastewater communities.
In the future, this method could accelerate efforts to develop engineered phages for medicine, environmental remediation and industrial biotechnology. Because the approach relies on common molecular biology techniques such as amplicon sequencing rather than labor-intensive culturing methods, it could also enable large-scale studies of viral ecology across diverse microbiomes.
Source – Rice University
LaTurner ZW, Dysart MJ, Schwartz SK, Zeng E, Chappell J, Silberg JJ, Stadler LB. (2026) Cross-order detection of bacteriophage transduction in microbial communities using RNA barcoding. Nature Communications 17(1):4308. [article]
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Scientists identify the neuroblastoma cells that signal poor outcomes
Novel biosensor uses DNA ‘barcodes’ to uncover disease signals in cells
CellART extracts single-cell information from high-resolution spatial transcriptomics
Cell2space restores spatial context to single-cell RNA sequencing data
Urine test may improve bladder cancer diagnosis and guide treatment decisions
DeCoRE – a computational method to resolve RNA structural heterogeneity from RNA structure probing data by direct RNA sequencing
Tracing 700 million years of cell evolution
How should biological replicates be handled in long-read RNA sequencing?
RNA-Seq reveals a new way the developing heart controls its growth
The Human RNome Project Consortium seeks to publish first-ever complete sequence of the body’s RNA
scFlowReport brings multiple single-cell RNA sequencing analyses into one workflow
Long-read RNA sequencing reveals how neurons choose alternative RNA endings
DeOPUS improves cell-type estimates from bulk RNA sequencing
ResolVI improves accuracy in spatial transcriptomics analysis
RNA sequencing reveals transcriptional allele differences in prostate cancer stem cells
Unmasking “zombie cells” in aging tissue with an AI-powered barcode
Single-cell TimeLapse-seq reveals MTA is an essential retrotransposon
RNA variant imaging for cancer diagnosis
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