Whole genome transcription profiling of Anaplasma phagocytophilum in human and tick host cells by tiling array analysis

Nelson, Curtis M.; Herron, Michael J.; Felsheim, Roderick F.; Schloeder, Brian R.; Grindle, Suzanne M.; Chavez, Adela Oliva; Kurtti, Timothy J.; Munderloh, Ulrike G.
January 2008
BMC Genomics;2008, Vol. 9, Special section p1
Academic Journal
Background: Anaplasma phagocytophilum (Ap) is an obligate intracellular bacterium and the agent of human granulocytic anaplasmosis, an emerging tick-borne disease. Ap alternately infects ticks and mammals and a variety of cell types within each. Understanding the biology behind such versatile cellular parasitism may be derived through the use of tiling microarrays to establish high resolution, genome-wide transcription profiles of the organism as it infects cell lines representative of its life cycle (tick; ISE6) and pathogenesis (human; HL-60 and HMEC-1). Results: Detailed, host cell specific transcriptional behavior was revealed. There was extensive differential Ap gene transcription between the tick (ISE6) and the human (HL-60 and HMEC-1) cell lines, with far fewer differentially transcribed genes between the human cell lines, and all disproportionately represented by membrane or surface proteins. There were Ap genes exclusively transcribed in each cell line, apparent human- and tick-specific operons and paralogs, and anti-sense transcripts that suggest novel expression regulation processes. Seven virB2 paralogs (of the bacterial type IV secretion system) showed human or tick cell dependent transcription. Previously unrecognized genes and coding sequences were identified, as were the expressed p44/msp2 (major surface proteins) paralogs (of 114 total), through elevated signal produced to the unique hypervariable region of each - 2/114 in HL-60, 3/114 in HMEC-1, and none in ISE6. Conclusion: Using these methods, whole genome transcription profiles can likely be generated for Ap, as well as other obligate intracellular organisms, in any host cells and for all stages of the cell infection process. Visual representation of comprehensive transcription data alongside an annotated map of the genome renders complex transcription into discernable patterns.


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