Bacteriophages are broadly classified into two distinct lifestyles: temperate and virulent. Temperate phages are capable of a latent phase of infection within a host cell (lysogenic cycle), whereas virulent phages directly replicate and lyse host cells upon infection (lytic cycle). Accurate lifestyle identification is critical for determining the role of individual phage species within ecosystems and their effect on host evolution. Here, we present BACPHLIP, a BACterioPHage LIfestyle Predictor. BACPHLIP detects the presence of a set of conserved protein domains within an input genome and uses this data to predict lifestyle via a Random Forest classifier that was trained on a dataset of 634 phage genomes. On an independent test set of 423 phages, BACPHLIP has an accuracy of 98% greatly exceeding that of the previously existing tools (79%). BACPHLIP is freely available on GitHub (https://github.com/adamhockenberry/bacphlip) and the code used to build and test the classifier is provided in a separate repository (https://github.com/adamhockenberry/bacphlip-model-dev) for users wishing to interrogate and re-train the underlying classification model.

BACPHLIP: predicting bacteriophage lifestyle from conserved protein domains.

Enhancing phage therapy through synthetic biology and genome engineering

Background As antibiotic resistance is becoming a major problem nowadays in a treatment of infections, bacteriophages (also known as phages) seem to be an alternative. However, to be used in a therapy, their life cycle should be strictly lytic. With the growing popularity of Next Generation Sequencing (NGS) technology, it is possible to gain such information from the genome sequence. A number of tools are available which help to define phage life cycle. However, there is still no unanimous way to deal with this problem, especially in the absence of well-defined open reading frames. To overcome this limitation, a new tool is definitely needed. Results We developed a novel tool, called PhageAI, that allows to access more than 10 000 publicly available bacteriophages and differentiate between their major types of life cycles: lytic and lysogenic. The tool included life cycle classifier which achieved 98.90% accuracy on a validation set and 97.18% average accuracy on a test set. We adopted nucleotide sequences embedding based on the Word2Vec with Ship-gram model and linear Support Vector Machine with 10-fold cross-validation for supervised classification. PhageAI is free of charge and it is available at https://phage.ai/. PhageAI is a REST web service and available as Python package. Conclusions Machine learning and Natural Language Processing allows to extract information from bacteriophages nucleotide sequences for lifecycle prediction tasks. The PhageAI tool classifies phages into either virulent or temperate with a higher accuracy than any existing methods and shares interactive 3D visualization to help interpreting model classification results.

/pdf/phageai-bacteriophage-life-cycle-recognition-with-machine-2o9lduasnp.pdf

PhageAI - Bacteriophage Life Cycle Recognition with Machine Learning and Natural Language Processing

Multidrug-resistant bacterial infections are becoming increasingly common, with only few last-resort antibiotics such as colistin for clinical therapy. An alternative therapeutic strategy gaining momentum is phage therapy, which has the advantage of not being affected by bacterial resistance to antibiotics. However, a major challenge in phage therapy is the rapid emergence of phage-resistant bacteria. In this work, our main aim was to understand the mechanisms of phage-resistance used by the top priority pathogen Acinetobacter baumannii. We isolated the novel phage Phab24, capable of infecting colistin-sensitive and -resistant strains of A. baumannii. After co-incubating Phab24 with its hosts, we obtained phage-resistant mutants which were characterised on both genotypic and phenotypic levels. Using whole genome sequencing, we identified phage-resistant strains that displayed mutations in genes that alter the architecture of the bacterial envelope at two levels: the capsule and the outer membrane. Using an adsorption assay, we confirmed that phage Phab24 uses the bacterial capsule as its primary receptor, with the outer membrane possibly serving as the secondary receptor. Interestingly, the phage-resistant isolates were less virulent compared to the parental strains in a Galleria mellonella infection model. Most importantly, we observed that phage-resistant bacteria that evolved in the absence of antibiotics exhibited an increased sensitivity to colistin, even though the antibiotic resistance mechanism per se remained unaltered. This increase in antibiotic sensitivity is a direct consequence of the phage-resistance mechanism, and could potentially be exploited in the clinical setting.

Colistin- phage combinations decrease antibiotic resistance in A. baumannii via changes in envelope architecture

Escherichia phage N4 was isolated in 1966 in Italy and has remained a genomic orphan for a long time. It encodes an extremely large virion-associated RNA polymerase unique for bacterial viruses that became characteristic for this group. In recent years, due to new and relatively inexpensive sequencing techniques the number of publicly available phage genome sequences expanded rapidly. This revealed new members of the N4-like phage group, from 33 members in 2015 to 115 N4-like viruses in 2020. Using new technologies and methods for classification, the Bacterial and Archaeal Viruses Subcommittee of the International Committee on Taxonomy of Viruses (ICTV) has moved the classification and taxonomy of bacterial viruses from mere morphological approaches to genomic and proteomic methods. The analysis of 115 N4-like genomes resulted in a huge reassessment of this group and the proposal of a new family “Schitoviridae”, including eight subfamilies and numerous new genera.

https://www.mdpi.com/2079-6382/9/10/663/pdf

From orphan phage to a proposed new family–the diversity of N4-like viruses

Aquaculture is the fastest growing sector of food production worldwide. However, one of the major reasons limiting its effectiveness are infectious diseases among aquatic organisms resulting in vast economic losses. Fighting such infections with chemotherapy is normally used as a rapid and effective treatment. The rise of antibiotic resistance, however, is limiting the efficacy of antibiotics and creates environmental and human safety concerns due to their massive application in the aquatic environment. Bacteriophages are an alternative solution that could be considered in order to protect fish against pathogens while minimizing the side-effects for the environment and humans. Bacteriophages kill bacteria via different mechanisms than antibiotics, and so fit nicely into the ‘novel mode of action’ concept desired for all new antibacterial agents. The bacteriophages were isolated from sewage water and characterized by RFLP, spectrum of specificity, transmission electron microscopy (TEM) and sequencing (WGS). Bioinformatics analysis of genomic data enables an in-depth characterization of phages and the choice of phages. This allows an optimised choice of phage for therapy, excluding those with toxin genes, virulence factor genes, and genes responsible for lysogeny. In this study, we isolated eleven new bacteriophages: seven infecting Aeromonas and four infecting Pseudomonas, which significantly increases the genomic information of Aeromonas and Pseudomonas phages. Bioinformatics analysis of genomic data, assessing the likelihood of these phages to enter the lysogenic cycle with experimental data on their specificity towards large number of bacterial field isolates representing different locations. From 11 newly isolated bacteriophages only 6 (25AhydR2PP, 50AhydR13PP, 60AhydR15PP, 22PfluR64PP, 67PfluR64PP, 71PfluR64PP) have a potential to be used in phage therapy due to confirmed lytic lifestyle and absence of virulence or resistance genes.

/pdf/complete-genome-sequences-of-aeromonas-and-pseudomonas-3wvkanhf57.pdf

Complete genome sequences of Aeromonas and Pseudomonas phages as a supportive tool for development of antibacterial treatment in aquaculture

Swab, quantitative, reverse transcription polymerase chain reaction (RT-qPCR) tests remain the gold standard of diagnostics of SARS-CoV-2 infections. However, these tests are costly and time-consuming, and swabbing limits their throughput. We developed a 3-gene, seminested RT-qPCR test with SYBR green-based detection, optimized for testing pooled saliva samples for high-throughput diagnostics of epidemic-affected populations. The proposed two-tier approach depends on decentralized self-collection of saliva samples, pooling, 1st-tier testing with the mentioned highly sensitive screening test and subsequent 2nd-tier testing of individual samples from positive pools with the in vitro diagnostic (IVD) test. The screening test was able to detect 5 copies of the viral genome in 10 {micro}l of isolated RNA with 50% probability and 18.8 copies with 95% probability and reached Ct values that were highly linearly RNA concentration-dependent. In the side-by-side comparison (testing artificial pooled samples), the screening test attained slightly better results than the commercially available IVD-certified RT-qPCR diagnostic test (100% specificity and 89.8% sensitivity vs. 100% and 73.5%, respectively). Testing of 1475 individual clinical samples pooled in 374 pools of 4 revealed 0.8% false positive pools and no false negative pools. In weekly prophylactic testing of 113 people within 6 months, a two-tier testing approach enabled the detection of 18 infected individuals, including several asymptomatic individuals, with a fraction of the costs of individual RT-PCR testing.

/pdf/rt-qpcr-based-tests-for-sars-cov-2-detection-in-pooled-3hv7cdpl1i.pdf

RT-qPCR-based tests for SARS-CoV-2 detection in pooled saliva samples for massive population screening to monitor epidemics.

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PhageAI - Bacteriophage Life Cycle Recognition with Machine Learning and Natural Language Processing

Complete genome sequences of Aeromonas and Pseudomonas phages as a supportive tool for development of antibacterial treatment in aquaculture

RT-qPCR-based tests for SARS-CoV-2 detection in pooled saliva samples for massive population screening to monitor epidemics.