Using machine learning to predict protein-protein interactions between a zombie ant fungus and its carpenter ant host.

Parasitic fungi produce proteins that modulate virulence, alter host physiology, and trigger host responses. These proteins, classified as a type of "effector," often act via protein-protein interactions (PPIs). The fungal parasite Ophiocordyceps camponoti-floridani (zombie ant fungus) manipulates Camponotus floridanus (carpenter ant) behavior to promote transmission. The most striking aspect of this behavioral change is a summit disease phenotype where infected hosts ascend and attach to an elevated position. Plausibly, interspecific PPIs drive aspects of Ophiocordyceps infection and host manipulation. Machine learning PPI predictions offer high-throughput methods to produce mechanistic hypotheses on how this behavioral manipulation occurs. Using D-SCRIPT to predict host-parasite PPIs, we found ca. 6000 interactions involving 2083 host proteins and 129 parasite proteins, which are encoded by genes upregulated during manipulated behavior. We identified multiple overrepresentations of functional annotations among these proteins. The strongest signals in the host highlighted neuromodulatory G-protein coupled receptors and oxidation-reduction processes. We also detected Camponotus structural and gene-regulatory proteins. In the parasite, we found enrichment of Ophiocordyceps proteases and frequent involvement of novel small secreted proteins with unknown functions. From these results, we provide new hypotheses on potential parasite effectors and host targets underlying zombie ant behavioral manipulation.

Genetic Underpinnings of Host Manipulation by Ophiocordyceps as Revealed by Comparative Transcriptomics.

Ant-infecting Ophiocordyceps fungi are globally distributed, host manipulating, specialist parasites that drive aberrant behaviors in infected ants, at a lethal cost to the host. An apparent increase in activity and wandering behaviors precedes a final summiting and biting behavior onto vegetation, which positions the manipulated ant in a site beneficial for fungal growth and transmission. We investigated the genetic underpinnings of host manipulation by: (i) producing a high-quality hybrid assembly and annotation of the Ophiocordyceps camponoti-floridani genome, (ii) conducting laboratory infections coupled with RNAseq of O. camponoti-floridani and its host, Camponotus floridanus, and (iii) comparing these data to RNAseq data of Ophiocordyceps kimflemingiae and Camponotus castaneus as a powerful method to identify gene expression patterns that suggest shared behavioral manipulation mechanisms across Ophiocordyceps-ant species interactions. We propose differentially expressed genes tied to ant neurobiology, odor response, circadian rhythms, and foraging behavior may result by activity of putative fungal effectors such as enterotoxins, aflatrem, and mechanisms disrupting feeding behaviors in the ant.

Daily rhythms and enrichment patterns in the transcriptome of the behavior-manipulating parasite Ophiocordyceps kimflemingiae.

Various parasite-host interactions that involve adaptive manipulation of host behavior display time-of-day synchronization of certain events. One example is the manipulated biting behavior observed in Carpenter ants infected with Ophiocordyceps unilateralis sensu lato. We hypothesized that biological clocks play an important role in this and other parasite-host interactions. In order to identify candidate molecular clock components, we used two general strategies: bioinformatics and transcriptional profiling. The bioinformatics approach was used to identify putative homologs of known clock genes. For transcriptional profiling, RNA-Seq was performed on 48 h time courses of Ophiocordyceps kimflemingiae (a recently named species of the O. unilateralis complex), whose genome has recently been sequenced. Fungal blastospores were entrained in liquid media under 24 h light-dark (LD) cycles and were harvested at 4 h intervals either under LD or continuous darkness. Of all O. kimflemingiae genes, 5.3% had rhythmic mRNAs under these conditions (JTK Cycle, ≤ 0.057 statistical cutoff). Our data further indicates that a significant number of transcription factors have a peaked activity during the light phase (day time). The expression levels of a significant number of secreted enzymes, proteases, toxins and small bioactive compounds peaked during the dark phase or subjective night. These findings support a model whereby this fungal parasite uses its biological clock for phase-specific activity. We further suggest that this may be a general mechanism involved in parasite-host interactions.