Progress in predicting bacteriophage host ranges by intelligent computing

Abstract:

The prediction of bacteriophage host ranges is of great significance for the basic research and clinical application of bacteriophages. The conventional biological experimental methods are limited by the poor culturability of bacteriophages and strict cultivation conditions. The availability of massive genome or metagenome sequencing data provides the sequence signature of bacteriophages and bacteria. Therefore, intelligent computing serves as a feasible way to predict bacteriophage host ranges. This paper systematically reviews the studies about intelligent computing-based prediction of bacteriophage host ranges. Starting from the process of bacteriophage infecting bacteria, we describe the feature source and biological rationality of prediction models, analyze the typical intelligent models and their prediction principles, and list all the reference datasets, real-world datasets, and evaluation indicators. The review aims to improve the understanding on the mechanism of bacteriophages in invading bacterial hosts and promote the usage of bacteriophages as antibiotic substitutes in biological therapy.

Key words:microbiome;bacteriophage-host interactions;prediction model;intelligent computing;machine learning;neural network