Virus Engineering: ORACLE reveals a bright future to fight bacteria
A new way to alter the genome of bacteriophages helps produce large libraries of variants, allowing these bacteria-killing viruses to be designed to target species harmful to human health.
- Department of Bioengineering and Therapeutic Sciences, UCSF, United States
- Quantitative Biosciences Institute, UCSF, United States
Antibiotics are usually quite effective at killing bacteria that cause disease, but they often end up eliminating huge swaths of microorganisms beneficial to health . Limiting this collateral damage by solely targeting pathogenic bacteria remains challenging, as only slight differences separate harmful and beneficial bacterial species.
An alternative treatment to chemical antibiotics could be to harness viruses called bacteriophages (or phages), which have evolved to recognize and prey on highly specific strains of bacteria (Abedon et al., 2011). Yet engineering phages to target harmful bacterial species requires scalable genetic tools that can precisely alter the genomes of these viruses. Now, in eLife, Srivatsan Raman and colleagues at University of Wisconsin-Madison – including Phil Huss as first author – report a new method that can create thousands of mutations in a host-specifying phage protein, showing how these changes alter which bacteria the virus can target (Huss et al., 2021).
Before this study, most protein engineering tools that ‘tweaked’ the genome of a bacteriophage to create desirable traits relied on either rational or directed evolution methods (Favor et al., 2020; Yehl et al., 2019). In rational approaches, the detailed knowledge of the three-dimensional structure of a protein – and its associated function – helps to guide mutations that will lead to desired properties. Directed evolution approaches, in contrast, bypass the need for such detailed understanding as they involve making random mutations which are then filtered for beneficial effects through multiple rounds of selection. However, these methods tend to only sample a small proportion of possible mutations.
Another approach to identify beneficial genetic variation is deep mutational scanning (DMS for short), where every single amino acid in a protein is changed to all other amino acids to see how it affects the function of a protein. This creates both a mechanistic structure-function understanding of the protein, and a starting point for protein engineering. DMS guided-methods are becoming widely used in protein engineering to develop better antibodies, enzymes and virus-based gene delivery systems (Adams et al., 2016; Ogden et al., 2019; Romero et al., 2015). Until the work by Huss et al., however, DMS approaches in bacteriophages were limited by a lack of methods to build sizeable and comprehensive mutational libraries in bacteriophage genomes.
To address this problem, the team developed the ORACLE method (short for Optimized Recombination Accumulation and Library Expression), a new phage genome engineering approach which creates large and unbiased mutational libraries of a phage gene. ORACLE can produce complete libraries of thousands of mutations, enabling DMS-based approaches in phages. The approach was used to create a library of mutant bacteriophages that each carried a single amino acid mutation in the tip of their receptor binding protein (known as RBD), the structure the viruses use to recognize their target species.
Massively parallel DNA sequencing was then applied to assess which mutant bacteriophages multiplied after being exposed to various strains of bacteria, revealing how each amino acid mutation in the RBD tip contributed to host specificity. In particular, changes in amino acids exposed to the surface and in contact with the host gave rise to phage variants highly specific to different bacterial strains.
Additional experiments further showcased this remarkable specificity, and the power of ORACLE. In particular, the phage library obtained through the DMS approach was tested on bacterial strains that carried on their surface slightly modified versions of the sugar molecules (or lipopolysaccharide) recognized by the viruses. This allowed Huss et al. to find phage variants whose ability to infect their prey depended on the type of lipopolysaccharides present on the bacteria. Finally, the team demonstrated the potential therapeutic utility of this approach, selecting for and characterizing RBD tip mutations that made phages target a strain of bacteria which causes urinary tract infections. This work by Huss et al. demonstrates how DMS-based approaches can help to understand the basic principles underlying bacteriophage specificity, and dramatically improve their ability to prey on pathogenic bacteria.
New functions often emerge when multiple genetic changes accumulate and interact, creating larger (or smaller) effects on protein function than would be expected from the sum of individual mutations. DMS experiments alone are ill suited to examine those interactions, as it is impractical to make all double, triple, and other higher-order mutations. However, machine-learning models trained on DMS datasets can help to explore these higher order interactions and to predict useful multi-mutational variants. This approach was applied, for instance, to help turn a small virus into a tool to deliver genes of interest to specific mammalian cells (Ogden et al., 2019). Such DMS-trained models could be employed for bacteriophages in order to expand or specify the host range beyond what is possible with single mutations alone.
A lack of genetic tools and the sheer number of bacteriophage species have turned these viruses into the understudied dark matter of the viral universe. Ongoing ‘metagenomic’ studies that sample the genetic material of phages in the natural world are revealing many strains whose biology is unknown, and which carry massively diverse sequences (Jordan et al., 2014). ORACLE is unlocking new ways to characterize bacteriophages, paving the way to one day harness these sequences to understand and engineer the microbial world within and around us.
References
Article and author information
Author details
Willow Coyote-Maestas
Publication history
- Version of Record published: April 15, 2021 (version 1)
Copyright
© 2021, Coyote-Maestas and Fraser
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,637
- views
-
- 118
- downloads
-
- 0
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Virus Engineering: ORACLE reveals a bright future to fight bacteria
eLife 10:e68277.
https://doi.org/10.7554/eLife.68277
Further reading
-
- Biochemistry and Chemical Biology
- Structural Biology and Molecular Biophysics
The mechanism underlying the preferential and cooperative binding of cofilin and the expansion of clusters toward the pointed-end side of actin filaments remains poorly understood. To address this, we conducted a principal component analysis based on available filamentous actin (F-actin) and C-actin (cofilins were excluded from cofilactin) structures and compared to monomeric G-actin. The results strongly suggest that C-actin, rather than F-ADP-actin, represented the favourable structure for binding preference of cofilin. High-speed atomic force microscopy explored that the shortened bare half helix adjacent to the cofilin clusters on the pointed end side included fewer actin protomers than normal helices. The mean axial distance (MAD) between two adjacent actin protomers along the same long-pitch strand within shortened bare half helices was longer (5.0–6.3 nm) than the MAD within typical helices (4.3–5.6 nm). The inhibition of torsional motion during helical twisting, achieved through stronger attachment to the lipid membrane, led to more pronounced inhibition of cofilin binding and cluster formation than the presence of inorganic phosphate (Pi) in solution. F-ADP-actin exhibited more naturally supertwisted half helices than F-ADP.Pi-actin, explaining how Pi inhibits cofilin binding to F-actin with variable helical twists. We propose that protomers within the shorter bare helical twists, either influenced by thermal fluctuation or induced allosterically by cofilin clusters, exhibit characteristics of C-actin-like structures with an elongated MAD, leading to preferential and cooperative binding of cofilin.
-
- Biochemistry and Chemical Biology
Protein kinases act as central molecular switches in the control of cellular functions. Alterations in the regulation and function of protein kinases may provoke diseases including cancer. In this study we investigate the conformational states of such disease-associated kinases using the high sensitivity of the kinase conformation (KinCon) reporter system. We first track BRAF kinase activity conformational changes upon melanoma drug binding. Second, we also use the KinCon reporter technology to examine the impact of regulatory protein interactions on LKB1 kinase tumor suppressor functions. Third, we explore the conformational dynamics of RIP kinases in response to TNF pathway activation and small molecule interactions. Finally, we show that CDK4/6 interactions with regulatory proteins alter conformations which remain unaffected in the presence of clinically applied inhibitors. Apart from its predictive value, the KinCon technology helps to identify cellular factors that impact drug efficacies. The understanding of the structural dynamics of full-length protein kinases when interacting with small molecule inhibitors or regulatory proteins is crucial for designing more effective therapeutic strategies.
