Extreme dimensions - how big (or small) can tailed phages be?

Overcoming donor variability and risks associated with fecal microbiota transplants through bacteriophage-mediated treatments

BACKGROUND

Fecal microbiota transplantation (FMT) and fecal virome transplantation (FVT, sterile filtrated donor feces) have been effective in treating recurrent Clostridioides difficile infections, possibly through bacteriophage-mediated modulation of the gut microbiome. However, challenges like donor variability, costly screening, coupled with concerns over pathogen transfer (incl. eukaryotic viruses) with FMT or FVT hinder their wider clinical application in treating less acute diseases.

METHODS

To overcome these challenges, we developed methods to broaden FVT's clinical application while maintaining efficacy and increasing safety. Specifically, we employed the following approaches: (1) chemostat-fermentation to reproduce the bacteriophage FVT donor component and remove eukaryotic viruses (FVT-ChP), (2) solvent-detergent treatment to inactivate enveloped viruses (FVT-SDT), and (3) pyronin-Y treatment to inhibit RNA virus replication (FVT-PyT). We assessed the efficacy of these processed FVTs in a C. difficile infection mouse model and compared them with untreated FVT (FVT-UnT), FMT, and saline.

RESULTS

FVT-SDT, FVT-UnT, and FVT-ChP reduced the incidence of mice reaching the humane endpoint (0/8, 2/7, and 3/8, respectively) compared to FMT, FVT-PyT, and saline (5/8, 7/8, and 5/7, respectively) and significantly reduced the load of colonizing C. difficile cells and associated toxin A/B levels. There was a potential elimination of C. difficile colonization, with seven out of eight mice treated with FVT-SDT testing negative with qPCR. In contrast, all other treatments exhibited the continued presence of C. difficile. Moreover, the results were supported by changes in the gut microbiome profiles, cecal cytokine levels, and histopathological findings. Assessment of viral engraftment following FMT/FVT treatment and host-phage correlations analysis suggested that transfer of phages likely were an important contributing factor associated with treatment efficacy.

CONCLUSIONS

This proof-of-concept study shows that specific modifications of FVT hold promise in addressing challenges related to donor variability and infection risks. Two strategies lead to treatments significantly limiting C. difficile colonization in mice, with solvent/detergent treatment and chemostat propagation of donor phages emerging as promising approaches. Video Abstract.

Acinetobacter baumannii satellite phage Aci01-2-Phanie depends on a helper myophage for its multiplication

We report the discovery of a satellite-helper phage system with a novel type of dependence on a tail donor. The Acinetobacter baumannii satellite podovirus Aci01-2-Phanie (short name Phanie) uses a phage phi29-like DNA replication and packaging mode. Its linear 11,885 bp dsDNA genome bears 171 bp inverted terminal repeats (ITR). Phanie is related to phage DU-PP-III from Pectobacterium and to members of the Astrithrvirus from Salmonella enterica. Together, they form a new clade of phages with 27% to 30% identity over the whole genome. Detailed 3D protein structure prediction and mass spectrometry analyses demonstrate that Phanie encodes its capsid structural genes and genes necessary to form a short tail. However, our study reveals that Phanie virions are non-infectious unless they associate with the contractile tail of an unrelated phage, Aci01-1, to produce chimeric myoviruses. Following the coinfection of Phanie with myovirus Aci01-1, hybrid viral particles composed of Phanie capsids and Aci01-1 contractile tails are assembled together with Phanie and Aci01-1 particles.IMPORTANCEThere are few reported cases of satellite-helper phage interactions but many more may be yet undiscovered. Here we describe a new mode of satellite phage dependence on a helper phage. Phanie, like phage phi29, replicates its linear dsDNA by a protein primed-mechanism and protects it inside podovirus-like particles. However, these particles are defective, requiring the acquisition of the tail from a myovirus helper for production of infectious virions. The formation of chimeras between a phi29-like podovirus and a helper contractile tail reveals an unexpected association between very different bacterial viruses.

pyCapsid: identifying dominant dynamics and quasi-rigid mechanical units in protein shells

SUMMARY

pyCapsid is a Python package developed to facilitate the characterization of the dynamics and quasi-rigid mechanical units of protein shells and other protein complexes. The package was developed in response to the rapid increase of high-resolution structures, particularly capsids of viruses, requiring multiscale biophysical analyses. Given a protein shell, pyCapsid generates the collective vibrations of its amino-acid residues, identifies quasi-rigid mechanical regions associated with the disassembly of the structure, and maps the results back to the input proteins for interpretation. pyCapsid summarizes the main results in a report that includes publication-quality figures.

AVAILABILITY AND IMPLEMENTATION

pyCapsid's source code is available under MIT License on GitHub. It is compatible with Python 3.8-3.10 and has been deployed in two leading Python package-management systems, PIP and Conda. Installation instructions and tutorials are available in the online documentation and in the pyCapsid's YouTube playlist. In addition, a cloud-based implementation of pyCapsid is available as a Google Colab notebook. pyCapsid Colab does not require installation and generates the same report and outputs as the installable version. Users can post issues regarding pyCapsid in the repository's issues section.

Choice of Ultrafilter Affects Recovery Rate of Bacteriophages

Studies into the viral fraction of complex microbial communities, like in the mammalian gut, have recently garnered much interest. Yet there is still no standardized protocol for extracting viruses from such samples, and the protocols that exist employ procedures that skew the viral community of the sample one way or another. The first step of the extraction pipeline often consists of the basic filtering of macromolecules and bacteria, yet even this affects the viruses in a strain-specific manner. In this study, we investigate a protocol for viral extraction based on ultrafiltration and how the choice of ultrafilter might influence the extracted viral community. Clinical samples (feces, vaginal swabs, and tracheal suction samples) were spiked with a mock community of known phages (T4, c2, Φ6, Φ29, Φx174, and Φ2972), filtered, and quantified using spot and plaque assays to estimate the loss in recovery. The enveloped Φ6 phage is especially severely affected by the choice of filter, but also tailed phages such as T4 and c2 have a reduced infectivity after ultrafiltration. We conclude that the pore size of ultrafilters may affect the recovery of phages in a strain- and sample-dependent manner, suggesting the need for greater thought when selecting filters for virus extraction.

Predicting the capsid architecture of phages from metagenomic data

Tailed phages are viruses that infect bacteria and are the most abundant biological entities on Earth. Their ecological, evolutionary, and biogeochemical roles in the planet stem from their genomic diversity. Known tailed phage genomes range from 10 to 735 kilobase pairs thanks to the size variability of the protective protein capsids that store them. However, the role of tailed phage capsids’ diversity in ecosystems is unclear. A fundamental gap is the difficulty of associating genomic information with viral capsids in the environment. To address this problem, here, we introduce a computational approach to predict the capsid architecture (T-number) of tailed phages using the sequence of a single gene—the major capsid protein. This approach relies on an allometric model that relates the genome length and capsid architecture of tailed phages. This allometric model was applied to isolated phage genomes to generate a library that associated major capsid proteins and putative capsid architectures. This library was used to train machine learning methods, and the most computationally scalable model investigated (random forest) was applied to human gut metagenomes. Compared to isolated phages, the analysis of gut data reveals a large abundance of mid-sized (T = 7) capsids, as expected, followed by a relatively large frequency of jumbo-like tailed phage capsids (T ≥ 25) and small capsids (T = 4) that have been under-sampled. We discussed how to increase the method’s accuracy and how to extend the approach to other viruses. The computational pipeline introduced here opens the doors to monitor the ongoing evolution and selection of viral capsids across ecosystems.