A methodology for detecting the orthology signal in a PPI network at a functional complex level.

BACKGROUND: Stable evolutionary signal has been observed in a yeast protein-protein interaction (PPI) network. These finding suggests more connected regions of a PPI network to be potential mediators of evolutionary information. Because more connected regions of PPI networks contain functional complexes, we are motivated to exploit the orthology relation for identifying complexes that can be clearly attributed to such evolutionary signal. RESULTS: We proposed a computational methodology for detecting the orthology signal present in a PPI network at a functional complex level. Specifically, we examined highly functionally coherent putative protein complexes as detected by a clustering technique in the complete yeast PPI network, in the yeast sub-network which spans only ortholog proteins as determined by a given second organism, and in yeast sub-networks induced by a set of proteins randomly selected. We proposed a filtering technique for extracting orthology-driven clusters with unique functionalities, that is, neither enriched by clusters identified using the complete yeast PPI network nor identified using random sampling. Moreover, we extracted functional categories that can be clearly attributed to the presence of evolutionary signal as described by these clusters. CONCLUSIONS: Application of the proposed methodology to the yeast PPI network indicated that evolutionary information at a functional complex level can be retrieved from the structure of the network. In particular, we detected protein complexes whose functionality could be uniquely attributed to the evolutionary signal. Moreover, we identified functions that are over-represented in these complexes due the evolutionary signal.

Composite survival index to compare virulence changes in azole-resistant Aspergillus fumigatus clinical isolates.

Understanding resistance to antifungal agents in Aspergillus fumigatus is of increasing importance for the treatment of invasive infections in immunocompromised patients. Although a number of molecular resistance mechanisms are described in detail, the potential accompanying virulence changes and impact on clinical outcome have had little attention. We developed a new measure of survival, the composite survival index (CSI) to use as a measure of the virulence properties of A. fumigatus. Using a novel mathematical model we found a strong correlation between the in vitro growth characteristics and virulence in vivo expressed as CSI. Our model elucidates how three critical parameters (the lag phase (τ), decay constant (λ), and growth rate (ν)) interact with each other resulting in a CSI that correlated with virulence. Hence, strains with a long lag phase and high decay constant were less virulent in a murine model of invasive aspergillosis, whereas high virulence for isolates with a high CSI was associated in vitro with rapid growth and short lag phases. Resistant isolates with cyp51A mutations, which account for the majority of azole resistant aspergillosis cases, did not show a lower virulence compared to azole-susceptible isolates. In contrast, the CSI index revealed that a non-cyp51A-mediated resistance mechanism was associated with a dramatic decrease in CSI. Because of its predictive value, the mathematical model developed may serve to explore strain characteristics in vitro to predict virulence in vivo and significantly reduce the number of experimental animals required in such studies. The proposed measure of survival, the CSI can be used more in a general form in survival studies to explore optimal treatment options.