covered in Chapter 8. We discuss the application of these methods for predicting dysregulated or dysfunctional protein complexes, identifying rewiring of interactions within complexes, and in discovery of new disease genes and drug targets. We conclude the book in Chapter 9 by reiterating the diverse applications of protein complex prediction methods and thereby the importance of computational methods in driving this exciting field of research.
1. http://www.nobelprize.org/nobel_prizes/medicine/laureates/1993/
2
Constructing Reliable Protein-Protein Interaction (PPI) Networks
No molecule arising naturally (MAN) is an island, entire of itself.
—John Donne (1573–1631), English poet and cleric (modified [Dunn 2010] from original quote, “No man is an island, entire of itself.”)
The identification of PPIs yields insights into functional relationships between proteins. Over the years, a number of different experimental techniques have been developed to infer PPIs. This inference of PPIs is orthogonal, but also complementary, to experiments inferring genetic interactions; both provide lists of candidate interactions and implicate functional relationships between proteins [Morris et al. 2014].
2.1 High-Throughput Experimental Systems to Infer PPIs
Physical interactions between proteins are inferred using different biochemical, biophysical, and genetic techniques (summarized in Table 2.1). Yeast two-hybrid (Y2H; less commonly, YTH) [Ito et al. 2000, Uetz et al. 2000, Ho et al. 2002] and protein-fragment complement assays [Michnick 2003, Remy and Michnick 2004, Remy et al. 2007] enable identification of direct binary physical interactions between the proteins, whereas co-immunoprecipitation or affinity purification assays [Golemis and Adams 2002, Rigaut et al. 1999, Köcher and Superti-Furga 2007, Dunham et al. 2012] enable pull down of whole protein complexes from which the binary interactions are inferred. Protein-fragment complementation assay (PCA) coupled with biomolecular fluorescence complementation (BIFC) [Grinberg et al. 2004] enables mapping of interaction surfaces of proteins, and is thus a good tool to confirm protein binding. Membrane YTH and mammalian membrane YTH (MaMTH) [Lalonde et al. 2008, Kittanakom et al. 2009, Lalonde et al. 2010, Petschnigg et al. 2014, Yao et al. 2017] enable identification of interactions involving membrane or membrane-bound proteins which are typically difficult to identify using traditional Y2H and AP techniques. Techniques inferring genetic interactions [Brown et al. 2006] enable detection of functional associations or genetic relationships between the proteins (genes), but these associations do not always correspond to physical interactions. Here, we present only an overview of each of the experimental techniques; for a more descriptive survey, the readers are referred to Brückner et al. [2009], Shoemaker and Panchenko [2007], and Snider et al. [2015].
Table 2.1 Experimental techniques for screening protein interactions; these techniques can be employed in a high-throughput manner to screen whole protein libraries for potential interactors
Yeast Two-Hybrid (Y2H) Screening System
Y2H was first described by Fields and Song [1989] and is based on the modularity of binding domains in eukaryotic transcription factors. Eukaryotic transcription factors have at least two distinct domains: (1) the DNA binding domain (BD) which directs binding to a promoter DNA sequence (upstream activating sequence (UAS)); and (2) the transcription activating domain (AD) which activates the transcription of target reporter genes. Splitting the BD and AD domains inactivates transcription, but even indirectly connecting AD and BD can restore transcription resulting in activation of specific reporter genes. Plasmids are engineered to produce a protein product (chimeric or “hybrid”) in which the BD fragment is in-frame fused onto a protein of interest (the bait), while the AD fragment is in-frame fused onto another protein (the prey) (Figure 2.1). The plasmids are then transfected into cells chosen for the screening method, usually from yeast. If the bait and prey proteins interact, the AD and BD domains are indirectly connected, resulting in the activation of reporters within nuclei of cells. Typically, multiple independent yeast colonies are assayed for each combination of plasmids to account for the heterogeneity in protein expression levels and their ability to activate reporter transcription.
This basic Y2H technique has been improved over the years to enable large library screening [Chien et al. 1991, Dufree et al. 1993, Gyuris et al. 1993, Finley and Brent 1994]. Interaction mating is one such protocol that can screen more than one bait against a library of preys, and can save considerable time and materials. In this protocol, the AD- and BD-fused proteins begin in two different haploid yeast strains with opposite mating types. These proteins are brought together by mating, a process in which two haploid cells fuse to form a single diploid cell. The diploids are then tested using conventional reporter activation for possible interactors. Therefore, different bait-expressing strains can be mated with a library of prey-expressing strains, and the resulting diploids can be screened for interactors. It is important to know how many viable diploids have arisen and to determine the false-positive frequency of the detected interactions. True interactors tend to come up in a timeframe specific for each given bait, with false positives clustering at a different timepoint. Multiple yeast colonies are assayed to confirm the interactors.
Figure 2.1 Schematic representation of the yeast two-hybrid protocol to detect interaction between bait and prey proteins. If the bait and prey proteins interact, the DNA binding domain (BD) fused to the bait and the transcription activing domain (AD) fused to the prey are indirectly connected resulting in the activation of the reporter gene. UAS: upstream activating sequence (promoter) of the reporter gene.
Y2H screens have been extensively used to detect protein interactions among yeast proteins, with two of the earliest studies reporting 692 [Uetz et al. 2000] and 841 [Ito et al. 2000] interactions for S. cerevisiae. In the bacteria Helicobacter pylori, one of the first applications of Y2H identified over 1,200 interactions, covering about 47% of the bacterial proteome [Rain et al. 2001]. Applications on fly proceeded on an even greater scale when Giot et al. [2003] identified 10,021 protein interactions involving 4,500 proteins in D. melanogaster. More recently, Vo et al. [2016] used Y2H to map binary interactions in the yeast S. pombe (fission yeast). This network, called FissionNet, consisted of 2,278 interactions covering 4,989 protein-coding genes in S. pombe. The Y2H system has also been applied for humans, with two initial studies [Rual et al. 2005, Stelzl et al. 2005] yielding over 5,000 interactions among human proteins. More recently, Rolland et al. [2014] employed Y2H to characterize nearly 14,000 human interactions.
However, inherent to this type of library screening, the number of detected false-positive interactions is usually high. Among the possible reasons for the generation of false positives is that the experimental compartmentalization (within the nucleus) for bait and prey proteins does not correspond to the natural cellular compartmentalization. Moreover, proteins that are not correctly folded under experimental conditions or are “sticky” may show non-specific interactions. The third source of false positives is the interaction of the preys themselves with reporter proteins, which can turn on the reporter genes. Von Mering et al. [2002] estimated the accuracy of classic Y2H to be less than 10%, with subsequent evaluations suggesting the number of false positives to be between
