We previously described network analyses of cell culture data to define interactions between host and pathogen and identified mitochondrial fatty acid oxidation enzymes that are predicted to function as central points for connecting and controlling metabolic pathways and as such, key targets in HCV-associated metabolic reprogramming [2
]. In fact, dys-regulations in mitochondrial function are evidenced by wide-spread perturbation of related proteins across every HCV model system we have studied [2
]. Thus, the modeling efforts reported here leveraged these data to further investigate whether the parameters used in our prior in vitro
modeling activities (abundance filter of 0, correspondence filter of 4, and correlation filter of 0.9) were the best to help identify new targets. Indeed, our previous study did not examine whether the use of a network topology approach could identify important targets any better than a standard approach such as considering highly differentially regulated proteins. Additionally, though we previously showed that this approach was valuable in cell culture studies it also remained unclear how it would perform on data from very different kinds of samples, such as those from liver biopsies of HCV-positive patients.
In the current study we build upon our previous findings to determine if there are other topological metrics (for example clustering coefficient and closeness) that identify targets in these networks, to define the parameters for network construction that provide the best target identification, and to characterize the relationship between networks derived from the cell culture data and those derived from data from patient biopsies. Our results indicate that the method of network construction has a significant impact on the results obtained. We found that betweenness was the most effective metric for defining important targets in our network but that other topological metrics (degree, clustering coefficient and closeness) could also discriminate targets to a statistically significant extent. From previous work examining the properties of topological bottlenecks in networks inferred from global transcriptomics data we have postulated that bottlenecks may represent mediators of transitions between states of the system [1
], and therefore represent critical points of control for the disease process. We have speculated that this is because bottlenecks link functional modules that represent groups of genes or proteins coexpressed under similar conditions. The transition between modules may represent state changes in the system, and the position of bottlenecks makes them candidates for regulators of these transitions. Our finding that degree was also a good predictor of importance in the system reiterates previous findings in other undirected biological networks [23
], though the primary contribution to importance we found to be betweenness, similar to findings in regulatory networks. Our findings here are consistent with the idea that bottlenecks in coabundance networks represent transitions between functional modules, and show that bottlenecks and hubs from proteomics-based networks may have similar properties as those from transcriptomics-based networks.
We note that modeling activities involving integrated genomic-proteomic analyses is an important area of research aimed at understanding the differences between co-expression at the transcript and protein level. However, our initial modeling efforts centered on the utilization of proteomic and metabolomic data indicating a temporal regulation of cellular metabolic homeostasis that was not detected by the accompanying gene expression profiles. Indeed our prior in vitro
studies were unique in part because they described a previously un-identified role for post-transcriptional regulatory mechanisms in the metabolic rerouting that was observed [2
]. For this reason, the scope of the current manuscript has focused on extending our analyses specifically to comparison with in vivo
protein co-expression networks.
Upon optimization of network construction, subsequent comparative analyses revealed that topologically-defined bottleneck proteins in the cell culture-derived network were generally more differentially regulated in patients with advanced fibrosis than their non-bottleneck counterparts. Interestingly, this was not observed when comparing differential abundance alone between the two datasets, indicating that topological analysis may identify more clinically relevant targets from cell culture studies than relative expression. It is important to note that we previously identified a subset of proteins that showed strongly conserved patterns of differential abundance [2
] between the cell culture and liver biopsy samples. In the current analysis we show that as an overall measure, differential abundance does not correlate well between the two data sets. Additionally, bottlenecks in the cell culture network were more likely to be bottlenecks in the clinical network. This shows that our approach can identify proteins of interest based on cell culture studies that are important in human disease and that these proteins would not be identified by examining differential abundance alone. Importantly, these findings point to the limitations of identifying/prioritizing pathogen-host targets based solely on highly differential regulation, a common approach to the identification of targets for further investigation.
Throughout this study we refer to target proteins as proteins that are important for HCV replication and/or fibrosis development. Some of these proteins have been defined using two-hybrid screens [11
], but our working hypothesis is that there are proteins that are important for replication that have not been previously defined. These are proteins that may or may not be direct interaction partners with HCV proteins but could contribute to metabolic or signaling pathways necessary for HCV replication and/or liver disease progression. We previously proposed an important role for temporal regulation of mitochondrial fatty acid oxidation and energy production in HCV infection and liver disease progression. Briefly, we described early increases in mitochondrial fatty acid oxidation that contribute to the creation of a "pro-viral" environment immediately preceding the subsequent increase in viral replication observed in vitro
]. This was eventually followed by a decline in fatty acid oxidation that accompanied the appearance of a cytopathic effect in vitro
and liver disease progression in vivo
]. The down-regulation of mitochondrial fatty acid oxidation would favor an increase in hepatocellular lipid content (for example, steatosis), a common occurrence in HCV, and histological feature observed among 4 of 6 patients with advanced fibrosis in our in vivo
]. The conservation of protein abundance changes associated with pathogenesis in vitro
(e.g. cytopathic effect) and liver disease progression in vivo
, and the corresponding mitochondrial bottlenecks reported here, including DCI, raises the interesting prospect that these proteins play an important role in the viral life cycle and pathogenesis.
Our previous findings and those described in the current study prompted us to further explore the predicted influence of HCV-associated disruptions in mitochondrial fatty acid oxidation, including consideration of whether these perturbations would be reflected by disease-related patterns detected in blood. From a clinical perspective, biomarker discovery efforts in body fluids represent an attractive alternative to tissue samples owing to the relative ease and less invasive nature of collection and the large volumes that normally can be obtained. We have observed the accumulation of both substrates for enoyl-CoA isomerase activity (e.g. DCI) as well as dicarboxylic acids well known to reflect alternative fatty acid catabolism through ω-oxidation pathways, findings consistent with our predictions regarding an important role for DCI, the essential link between saturated and unsaturated β-oxidation, in the impaired mitochondrial fatty acid catabolism occurring during HCV-associated liver disease progression [28
]. Thus, the identification of disease-related fatty acid patterns in the blood of patients with HCV-associated liver disease progression provides a potentially useful noninvasive diagnostic link to the previously described alterations in hepatic mitochondrial fatty acid oxidation occurring during HCV infection and pathogenesis. Importantly, we have unequivocally validated a biologically relevant role for DCI in the HCV life cycle using a combination of gene silencing and pharmacologic inhibition approaches [2
]. In summary, our data from multiple model systems and clinically relevant physiologic compartments provide evidence confirming our original modeling predictions regarding a requirement for DCI in the HCV life cycle [7
] and demonstrate a physiologically relevant association of temporal declines in fatty acid oxidation that coincide with pathogenesis in vitro
and in vivo
. Taken together, we believe these data provide proof of principle for the utility of integrated in vitro/in vivo
modeling efforts to identify key host targets of HCV infection and pathogenesis.
The biological interpretation of the remaining top 10% bottlenecks, 4 out of 5 of which are mitochondrial proteins with links to fatty acid oxidation and energy production, was predicated on the wealth of data described for the representative example DCI as highlighted above together with the growing literature on the important role of altered mitochondrial function in HCV infection and pathogenesis (for an excellent review on the interactions between HCV and mitochondria we recommend [29
]). Among the additional bottlenecks identified was glutathione-S-transferase kappa 1 (GSTK1), a protein that localizes to the mitochondria and peroxisome and has pleiotropic functions including glutathione conjugation, peroxidase, and disulphide-bond-forming oxidoreductase activities [30
]. Interestingly, GSTK1 has recently been shown to play an important role in the oligomeric assembly and secretion of adiponectin, a cytokine that stimulates fatty acid oxidation through interaction with the hepatic receptor AdipoR2 and subsequent activation of peroxisome proliferator-activated receptor (PPAR)-alpha [31
]. HCV-associated targeting of GSTK1 and DCI may serve to provide multiple control points for modulating catabolic flux of fatty acids during metabolic reprogramming. GSTK1 may promote further cross-talk between metabolic signaling and biochemical pathways by modulating the folding and assembly of oligomeric proteins directly involved in lipid synthesis and/or catabolism, including the trimeric DCI protein. A similar role in the folding of lipid metabolism enzymes has been suggested in Caenorhabditis elegans
where GSTK1 silencing was associated with a decline in the biosynthesis of the monounsaturated fatty acid cis
-vaccenic acid [33
]. It is worth noting that the differential abundance of cis
-vaccenic acid was observed to impact lipid droplet remodeling under pathogenic conditions of defective peroxisomal β-oxidation in C. elegans
]. Taken together, these findings suggest interesting new avenues of research aimed at exploring the interplay between GSTK1 and DCI during metabolic reprogramming and the lipid remodeling events predicted to provide important constituents in the various structural entities supporting the HCV life cycle, including the lipid droplet and membranous replicase compartments.
Among the other bottlenecks detected in our analyses was mitofilin, also known as mitochondrial inner membrane protein (IMMT). Mitofilin is a protein localized to the inner mitochondrial membrane whose presence is essential for tubular cristae formation and the increased surface-to-volume ratio of the inner membrane that occurs during increased metabolic output [35
]. While the molecular basis for these alterations in mitochondrial cristae morphology are not well understood, mitofilin depletion has been shown to induce aberrant structural changes in the inner membrane that are associated with abrogation of ATP production despite increased flux of fatty acid substrates through the β-oxidation pathway thus, suggesting an adverse impact on the oxidative phosphorylation machinery that resides in the inner membrane [35
]. We suspect that the putative HCV targeting of mitofilin reflects a coordinated effort to maximize energy production in support of the significant macromolecular biosynthesis necessary for viral growth [2
]. Consistent with this idea we further identified ATP5B, the major catalytic subunit of F1 ATP synthase, as a conserved bottleneck in our studies. A similarly important pro-viral role for ATP5B has recently been reported for herpes simplex virus-1 (HSV-1) [36
]. In a series of elegant experiments aimed at exploring the effect of host microRNAs on HSV-1 replication, Zheng et al
, identified a point of cross talk between host cell and virus that results in the progressive induction of host cell miR-101 levels that is accompanied by concomitant declines in ATP5B expression and HSV-1 replication [36
]. The interplay between virus and the miR-101/ATP5B regulatory network suggests a potential link between modulation of this host defense mechanism and the establishment of long-term HSV-1 latency [36
]. This latter point is of particular interest as we and others have proposed a similar role for modulation of fatty acid oxidation and energy production in the establishment of persistent HCV and measles virus infection [2
It is important to note that our intent is not to provide a network representation that is faithful to the underlying true network of interactions in the cell, but rather to use topology in these simply defined association networks to identify target proteins for further experimental investigation. The networks generated using this approach are based on correlation of protein abundance over many different observations (time points in the cell culture data and patients in the clinical data). As such they represent the information flow in the system. For example, closely coordinated proteins are close together in the networks, while those with little or no coordination are far apart. It is likely that this organization allows use of topology to query the network for more important proteins, since bottlenecks in particular represent points constriction in information flow in the system [23
]. In a fashion analogous to that for DCI, additional conserved bottleneck proteins represent particularly attractive targets for further investigation of their functional significance during HCV infection and liver disease progression. In this regard, recent efforts to link these findings with clinical protein profiling studies of serial liver biopsies obtained from HCV-positive liver transplant recipients revealed a statistically significant up-regulation of the protein bottleneck GSTK1 in patients who developed severe liver injury [28
]. Importantly, the increased abundance of GSTK1 occurred prior to histologic evidence of fibrosis. Collectively, these findings merit further investigation to understand the functional, regulatory and/or prognostic significance of this protein bottleneck during HCV-associated liver disease progression.
In summary, the results presented in this study show that a network approach to consideration of global proteomics data is a powerful way to identify important target proteins and to elucidate potential mechanisms of pathogenesis. Previous results in yeast [23
], fruit fly and worm [39
], pathogenic bacteria [40
], cyanobacteria [42
], mouse macrophages [43
], mouse blood [44
] and human cell culture [2
] support the notion that our approach is generally applicable, though these have been focused on analysis of coexpression networks from transcriptomics. We have recently published on the network analysis of proteomics data from Salmonella
under infectious-like conditions, and have found that these networks show a similar kind of enrichment of bottlenecks in proteins important to the system [45
]. In the current work we fully characterize the application of this approach to protein co-abundance networks showing that it works very well to identify important nodes in the network. In this study we show that topological betweenness provides the best identification of important target proteins, but that other topological measures can also be used to identify targets. Importantly, we show that this approach can be applied successfully to global proteomic data derived from liver biopsies of HCV-positive fibrosis patients. Key findings of the study were validated in a patient cohort by metabolic profiling in serum [28
]. Interestingly, the topology of cell culture networks provides better insight into important proteins in the liver biopsy data than does differential regulation, showing that it is a viable alternative or complement to standard analysis methods. Our approach represents a generally applicable method for using global proteomics data as a systems biology tool that goes beyond differential abundance of individual proteins. The finding that other metrics could also identify targets suggests that combining network metrics in some way may provide improved discrimination over the individual measures. Our initial results using a simple mean, geometric mean, or minimum of protein rank from each of the four metrics revealed that the results were not improved (data not shown). We are currently investigating more sophisticated methods for integrating multiple topological measures to improve our results.