Biostatistical prediction of genes essential for growth of Anaplasma phagocytophilum in a human promyelocytic cell line using a random transposon mutant library.

Abstract

Anaplasma phagocytophilum (Ap), agent of human anaplasmosis, is an intracellular bacterium that causes the second most common tick-borne illness in North America. To address the lack of a genetic system for these pathogens, we used random Himar1 transposon mutagenesis to generate a library of Ap mutants capable of replicating in human promyelocytes (HL-60 cells). Illumina sequencing identified 1195 non-randomly distributed insertions. As the density of mutants was non-saturating, genes without insertions were either essential for Ap, or spared randomly. To resolve this question, we applied a biostatistical method for prediction of essential genes. Since the chances that a transposon was inserted into genomic TA dinucleotide sites should be the same for all loci, we used a Markov chain Monte Carlo model to estimate the probability that a non-mutated gene was essential for Ap. Predicted essential genes included those coding for structural ribosomal proteins, enzymes involved in metabolism, components of the type IV secretion system, antioxidant defense molecules and hypothetical proteins. We have used an in silico post-genomic approach to predict genes with high probability of being essential for replication of Ap in HL-60 cells. These results will help target genes to investigate their role in the pathogenesis of human anaplasmosis.