Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features

Novel pelagiphage isolate Polarivirus skadi is a polar specialist that dominates SAR11-associated bacteriophage communities at high latitudes

The SAR11 clade are the most abundant members of surface marine bacterioplankton and a critical component of global biogeochemical cycles. Similarly, pelagiphages that infect SAR11 are ubiquitous and highly abundant in the oceans. Pelagiphages are predicted to shape SAR11 community structures and increase carbon turnover throughout the oceans. Yet, ecological drivers of host and niche specificity of pelagiphage populations are poorly understood. Here we report the global distribution of a novel pelagiphage called "Polarivirus skadi", which is the sole representative of a novel genus. P. skadi was isolated from the Western English Channel using a cold-water ecotype of SAR11 as bait. P. skadi is closely related to the globally dominant pelagiphage HTVC010P. Along with other HTVC010P-type viruses, P. skadi belongs to a distinct viral family within the order Caudovirales, for which we propose the name Ubiqueviridae. Metagenomic read recruitment identified P. skadi as one of the most abundant pelagiphages on Earth. P. skadi is a polar specialist, replacing HTVC010P at high latitudes. Experimental evaluation of P. skadi host range against cold- and warm-water SAR11 ecotypes supported cold-water specialism. Relative abundance of P. skadi in marine metagenomes correlated negatively with temperature, and positively with nutrients, available oxygen, and chlorophyll concentrations. In contrast, relative abundance of HTVC010P correlated negatively with oxygen and positively with salinity, with no significant correlation to temperature. The majority of other pelagiphages were scarce in most marine provinces, with a few representatives constrained to discrete ecological niches. Our results suggest that pelagiphage populations persist within a global viral seed bank, with environmental parameters and host availability selecting for a few ecotypes that dominate ocean viromes.

Identification of Phage Receptor-Binding Protein Sequences with Hidden Markov Models and an Extreme Gradient Boosting Classifier

Receptor-binding proteins (RBPs) of bacteriophages initiate the infection of their corresponding bacterial host and act as the primary determinant for host specificity. The ever-increasing amount of sequence data enables the development of predictive models for the automated identification of RBP sequences. However, the development of such models is challenged by the inconsistent or missing annotation of many phage proteins. Recently developed tools have started to bridge this gap but are not specifically focused on RBP sequences, for which many different annotations are available. We have developed two parallel approaches to alleviate the complex identification of RBP sequences in phage genomic data. The first combines known RBP-related hidden Markov models (HMMs) from the Pfam database with custom-built HMMs to identify phage RBPs based on protein domains. The second approach consists of training an extreme gradient boosting classifier that can accurately discriminate between RBPs and other phage proteins. We explained how these complementary approaches can reinforce each other in identifying RBP sequences. In addition, we benchmarked our methods against the recently developed PhANNs tool. Our best performing model reached a precision-recall area-under-the-curve of 93.8% and outperformed PhANNs on an independent test set, reaching an F1-score of 84.0% compared to 69.8%.

The Use of Bacteriophages in Biotechnology and Recent Insights into Proteomics

Phages have certain features, such as their ability to form protein-protein interactions, that make them good candidates for use in a variety of beneficial applications, such as in human or animal health, industry, food science, food safety, and agriculture. It is essential to identify and characterize the proteins produced by particular phages in order to use these viruses in a variety of functional processes, such as bacterial detection, as vehicles for drug delivery, in vaccine development, and to combat multidrug resistant bacterial infections. Furthermore, phages can also play a major role in the design of a variety of cheap and stable sensors as well as in diagnostic assays that can either specifically identify specific compounds or detect bacteria. This article reviews recently developed phage-based techniques, such as the use of recombinant tempered phages, phage display and phage amplification-based detection. It also encompasses the application of phages as capture elements, biosensors and bioreceptors, with a special emphasis on novel bacteriophage-based mass spectrometry (MS) applications.

Treating Bacterial Infections with Bacteriophage-Based Enzybiotics: In Vitro, In Vivo and Clinical Application

Over the past few decades, we have witnessed a surge around the world in the emergence of antibiotic-resistant bacteria. This global health threat arose mainly due to the overuse and misuse of antibiotics as well as a relative lack of new drug classes in development pipelines. Innovative antibacterial therapeutics and strategies are, therefore, in grave need. For the last twenty years, antimicrobial enzymes encoded by bacteriophages, viruses that can lyse and kill bacteria, have gained tremendous interest. There are two classes of these phage-derived enzymes, referred to also as enzybiotics: peptidoglycan hydrolases (lysins), which degrade the bacterial peptidoglycan layer, and polysaccharide depolymerases, which target extracellular or surface polysaccharides, i.e., bacterial capsules, slime layers, biofilm matrix, or lipopolysaccharides. Their features include distinctive modes of action, high efficiency, pathogen specificity, diversity in structure and activity, low possibility of bacterial resistance development, and no observed cross-resistance with currently used antibiotics. Additionally, and unlike antibiotics, enzybiotics can target metabolically inactive persister cells. These phage-derived enzymes have been tested in various animal models to combat both Gram-positive and Gram-negative bacteria, and in recent years peptidoglycan hydrolases have entered clinical trials. Here, we review the testing and clinical use of these enzymes.

Predicting bacteriophage hosts based on sequences of annotated receptor-binding proteins

Nowadays, bacteriophages are increasingly considered as an alternative treatment for a variety of bacterial infections in cases where classical antibiotics have become ineffective. However, characterizing the host specificity of phages remains a labor- and time-intensive process. In order to alleviate this burden, we have developed a new machine-learning-based pipeline to predict bacteriophage hosts based on annotated receptor-binding protein (RBP) sequence data. We focus on predicting bacterial hosts from the ESKAPE group, Escherichia coli, Salmonella enterica and Clostridium difficile. We compare the performance of our predictive model with that of the widely used Basic Local Alignment Search Tool (BLAST). Our best-performing predictive model reaches Precision-Recall Area Under the Curve (PR-AUC) scores between 73.6 and 93.8% for different levels of sequence similarity in the collected data. Our model reaches a performance comparable to that of BLASTp when sequence similarity in the data is high and starts outperforming BLASTp when sequence similarity drops below 75%. Therefore, our machine learning methods can be especially useful in settings in which sequence similarity to other known sequences is low. Predicting the hosts of novel metagenomic RBP sequences could extend our toolbox to tune the host spectrum of phages or phage tail-like bacteriocins by swapping RBPs.