Biology subjects

Segall, A.

Publications and source records attributed to Segall, A..

5 recordsLinked to original sources

bioRxiv2025

Small uncultured viral-like entities redraw the origin of viruses and cellular compartments

The HK97-fold is an ancient, conserved protein structure that forms protein shells. It is the building block of capsids that protect the genome of viruses in the Duplodnaviria realm, infecting organisms across all domains of life. It is also the building block of encapsulins, compartments that confine biochemical reactions in prokaryotes. Recent genomic studies have hypothesized that encapsulins evolved from HK97-fold viruses. However, this evolutionary pathway is challenging to justify biophysically because HK97-fold viruses form larger and more complex protein shells than encapsulins. We addressed this paradox by searching for smaller and simpler HK97-fold viral capsids across ecosystems. The investigation yielded a well-defined group of viral entities, which encode HK97-fold proteins displaying molecular similarities with encapsulins and lacking portal and tail genes. The structural phylogenetic analysis of HK97-fold entities revealed bidirectional evolutionary transitions between encapsulins and HK97-fold viruses. An evolutionary mechanism responsible for such transitions was proposed based on the presence of lysogeny-associated genes in the viral entities and the structural and molecular parallels between encapsulins and procapsids, the immature state of viral capsids before genome packaging. We concluded that procapsids are akin to the common HK97-fold protein shell ancestor and might still facilitate transitions between modern viruses and encapsulins. The potential genomic and biochemical functions of HK97-fold procapsids make them an ideal candidate model for the early evolution of life and might require a revision of the role of viral capsids in the biosphere.

bioinformatics↗

bioRxiv2024

Sphae: An automated toolkit for predicting phage therapy candidates from sequencing data

MotivationPhage therapy is a viable alternative for treating bacterial infections amidst the escalating threat of antimicrobial resistance. However, the therapeutic success of phage therapy depends on selecting safe and effective phage candidates. While experimental methods focus on isolating phages and determining their lifecycle and host range, comprehensive genomic screening is critical to identify markers that indicate potential risks, such as toxins, antimicrobial resistance, or temperate lifecycle traits. These analyses are often labor-intensive and time-consuming, limiting the rapid deployment of phage in clinical settings. ResultsWe developed Sphae, an automated bioinformatics pipeline designed to streamline therapeutic potential of a phage in under ten minutes. Using Snakemake workflow manager, Sphae integrates tools for quality control, assembly, genome assessment, and annotation tailored specifically for phage biology. Sphae automates the detection of key genomic markers, including virulence factors, antimicrobial resistance genes, and lysogeny indicators like integrase, recombinase, and transposase, which could preclude therapeutic use. Benchmarked on 65 phage sequences, 28 phage samples showed therapeutic potential, 8 failed during assembly due to low sequencing depth, 22 samples included prophage or virulent markers, and the remaining 23 samples included multiple phage genomes per sample. This workflow outputs a comprehensive report, enabling rapid assessment of phage safety and suitability for phage therapy under these criteria. Sphae is scalable, portable, facilitating efficient deployment across most high-performance computing (HPC) and cloud platforms, expediting the genomic evaluation process. AvailabilitySphae is source code and freely available at https://github.com/linsalrob/sphae, with installation supported on Conda, PyPi, Docker containers.

bioinformatics↗

bioRxiv2023

Novel crAssphage isolates exhibit conserved gene order and purifying selection of the host specificity protein

Bacteroides, the prominent bacteria in the human gut, play a crucial role in degrading complex polysaccharides. Their abundance is influenced by phages belonging to the Crassvirales order. Despite identifying over 600 Crassvirales genomes computationally, only few have been successfully isolated. Continued efforts in isolation of more Crassvirales genomes can provide insights into phage-host-evolution and infection mechanisms. We focused on wastewater samples, as potential sources of phages infecting various Bacteroides hosts. Sequencing, assembly, and characterization of isolated phages revealed 14 complete genomes belonging to three novel Crassvirales species infecting Bacteroides cellulosilyticus WH2. These species, Kehishuvirus sp. tikkala strain Bc01, Kolpuevirus sp. frurule strain Bc03, and Rudgehvirus jaberico strain Bc11, spanned two families, and three genera, displaying a broad range of virion productions. Upon testing all successfully cultured Crassvirales species and their respective bacterial hosts, we discovered that they do not exhibit co-evolutionary patterns with their bacterial hosts. Furthermore, we observed variations in gene similarity, with greater shared similarity observed within genera. However, despite belonging to different genera, the three novel species shared a unique structural gene that encodes the tail spike protein. When investigating the relationship between this gene and host interaction, we discovered evidence of purifying selection, indicating its functional importance. Moreover, our analysis demonstrated that this tail spike protein binds to the TonB-dependent receptors present on the bacterial host surface. Combining these observations, our findings provide insights into phage-host interactions and present three Crassvirales species as an ideal system for controlled infectivity experiments on one of the most dominant members of the human enteric virome. Impact statementBacteriophages play a crucial role in shaping microbial communities within the human gut. Among the most dominant bacteriophages in the human gut microbiome are Crassvirales phages, which infect Bacteroides. Despite being widely distributed, only a few Crassvirales genomes have been isolated, leading to a limited understanding of their biology, ecology, and evolution. This study isolated and characterized three novel Crassvirales genomes belonging to two different families, and three genera, but infecting one bacterial host, Bacteroides cellulosilyticus WH2. Notably, the observation confirmed the phages are not co-evolving with their bacterial hosts, rather have a shared ability to exploit similar features in their bacterial host. Additionally, the identification of a critical viral protein undergoing purifying selection and interacting with the bacterial receptors opens doors to targeted therapies against bacterial infections. Given Bacteroides role in polysaccharide degradation in the human gut, our findings advance our understanding of the phage-host interactions and could have important implications for the development of phage-based therapies. These discoveries may hold implications for improving gut health and metabolism to support overall well-being. Data summaryThe genomes used in this research are available on Sequence Read Archive (SRA) within the project, PRJNA737576. Bacteroides cellulosilyticus WH2, Kehishuvirus sp. tikkala strain Bc01, Kolpuevirus sp. frurule strain Bc03, and Rudgehvirus jaberico strain Bc11 are all available on GenBank with accessions NZ_CP072251.1 (B. cellulosilyticus WH2), QQ198717 (Bc01), QQ198718 (Bc03), and QQ198719 (Bc11), and we are working on making the strains available through ATCC. The 3D protein structures for the three Crassvirales genomes are available to download at doi.org/10.25451/flinders.21946034.

bioinformatics↗

bioRxiv2020

PhANNs, a fast and accurate tool and web server to classify phage structural proteins

For any given bacteriophage genome or phage sequences in metagenomic data sets, we are unable to assign a function to 50-90% of genes. Structural protein-encoding genes constitute a large fraction of the average phage genome and are among the most divergent and difficult-to-identify genes using homology-based methods. To understand the functions encoded by phages, their contributions to their environments, and to help gauge their utility as potential phage therapy agents, we have developed a new approach to classify phage ORFs into ten major classes of structural proteins or into an "other" category. The resulting tool is named PhANNs (Phage Artificial Neural Networks). We built a database of 538,213 manually curated phage protein sequences that we split into eleven subsets (10 for cross-validation, one for testing) using a novel clustering method that ensures there are no homologous proteins between sets yet maintains the maximum sequence diversity for training. An Artificial Neural Network ensemble trained on features extracted from those sets reached a test F1-score of 0.875 and test accuracy of 86.2%. PhANNs can rapidly classify proteins into one of the ten classes, and non-phage proteins are classified as "other", providing a new approach for functional annotation of phage proteins. PhANNs is open source and can be run from our web server or installed locally. Author SummaryBacteriophages (phages, viruses that infect bacteria) are the most abundant biological entity on Earth. They outnumber bacteria by a factor of ten. As phages are very different within them and from bacteria, and we have comparatively few phage genes in our database, we are unable to assign function to 50%-90% of phage genes. In this work, we developed PhANNs, a machine learning tool that can classify a phage gene as one of ten structural roles, or "other". This approach does not require a similar gene to be known.

bioinformatics↗

bioRxiv2017

Prophage genomics reveals patterns in phage genome organization and replication

Temperate phage genomes are highly variable mosaic collections of genes that infect a bacterial host, integrate into the hosts genome or replicate as low copy number plasmids, and are regulated to switch from the lysogenic to lytic cycles to generate new virions and escape their host. Genomes from most Bacterial phyla contain at least one or more prophages. We updated our PhiSpy algorithm to improve detection of prophages and to provide a web-based framework for PhiSpy. We have used this algorithm to identify 36,488 prophage regions from 11,941 bacterial genomes, including almost 600 prophages with no known homology to any proteins. Transfer RNA genes were abundant in the prophages, many of which alleviate the limits of translation efficiency due to host codon bias and presumably enable phages to surpass the normal capacity of the hosts translation machinery. We identified integrase genes in 15,765 prophages (43% of the prophages). The integrase was routinely located at either end of the integrated phage genome, and was used to orient and align prophage genomes to reveal their underlying organization. The conserved genome alignments of phages recapitulate early, middle, and late gene order in transcriptional control of phage genes, and demonstrate that gene order, presumably selected by transcription timing and/or coordination among functional modules has been stably conserved throughout phage evolution.

biochemistry↗