Seesandra V. Rajagopala

Evolutionarily conserved herpesviral protein interaction networks.

Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV) and Kaposis sarcoma-associated herpesvirus (KSHV). In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1), murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H), and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species.

MPIDB: the microbial protein interaction database

Summary: The microbial protein interaction database (MPIDB) aims to collect and provide all known physical microbial interactions. Currently, 22 530 experimentally determined interactions among proteins of 191 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 24 060 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 8150 additional evidences based on interaction conservation, co-purification and 3D domain contacts (iPfam, 3did). Availability: http://www.jcvi.org/mpidb/ Contact: jgoll@jcvi.org

The binary protein-protein interaction landscape of Escherichia coli

Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (∼70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, which approximately doubles the number of known binary PPIs in E. coli. Integration of binary PPI and genetic-interaction data revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that we could map in multiprotein complexes were informative regarding internal topology of complexes and indicated that interactions in complexes are substantially more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily important model microbe.

Exhaustive benchmarking of the yeast two-hybrid system

To the Editor: In a recent paper, Braun et al.1 compared the ability of five different methods to detect well-known protein-protein interactions (PPIs). The remarkable outcome of this study was that each of the tested methods detected a different subset of interactions with no single method detecting more than 36% of the tested gold-standard interactions (Fig. 1). Use of all five methods was required to find 62 of 92 interactions (67.4%), whereas individual methods detected only 28.8 out of 92 interactions on average (31.3%). Here we report a similar result when using multiple variants of the yeast two-hybrid (Y2H) system instead of multiple different methods. We have shown that different two-hybrid systems detect markedly different subsets of interactions in the same interactome2,3. Therefore we determined whether the five different methods used by Braun et al.1 could be entirely replaced by variants of the Y2H system. This would have the benefit that only one method needs to be established, and the results of the variants are directly comparable. The set of protein pairs of Braun et al.1 provides a perfect benchmark for such a comparison. We cloned the human positive reference set (PRS) and the random reference set (RRS) from Braun et al.1 (92 protein pairs each) into the following yeast two-hybrid bait-prey vectors: pGBGT7g-pGADCg, pGBGT7g-pGADT7g, pDEST32-pDEST22, pGBKCg-pGADT7g and pGBKCg-pGADCg2,3 (Supplementary Data). In addition to each vector pair, we tested each protein both as activation (prey) and DNA-binding domain fusion (bait), including C-terminal fusions in pGBKCg and pGADCg. This way, we tested each protein pair in ten different configurations (Fig. 1 and Supplementary Table 1).

The protein network of bacterial motility

Motility is achieved in most bacterial species by the flagellar apparatus. It consists of dozens of different proteins with thousands of individual subunits. The published literature about bacterial chemotaxis and flagella documented 51 protein–protein interactions (PPIs) so far. We have screened whole genome two‐hybrid arrays of Treponema pallidum and Campylobacter jejuni for PPIs involving known flagellar proteins and recovered 176 and 140 high‐confidence interactions involving 110 and 133 proteins, respectively. To explore the biological relevance of these interactions, we tested an Escherichia coli gene deletion array for motility defects (using swarming assays) and found 159 gene deletion strains to have reduced or no motility. Comparing our interaction data with motility phenotypes from E. coli, Bacillus subtilis, and Helicobacter pylori, we found 23 hitherto uncharacterized proteins involved in motility. Integration of phylogenetic information with our interaction and phenotyping data reveals a conserved core of motility proteins, which appear to have recruited many additional species‐specific components over time. Our interaction data also predict 18 110 interactions for 64 flagellated bacteria.

The binary protein interactome of Treponema pallidum--the syphilis spirochete.

Protein interaction networks shed light on the global organization of proteomes but can also place individual proteins into a functional context. If we know the function of bacterial proteins we will be able to understand how these species have adapted to diverse environments including many extreme habitats. Here we present the protein interaction network for the syphilis spirochete Treponema pallidum which encodes 1,039 proteins, 726 (or 70%) of which interact via 3,649 interactions as revealed by systematic yeast two-hybrid screens. A high-confidence subset of 991 interactions links 576 proteins. To derive further biological insights from our data, we constructed an integrated network of proteins involved in DNA metabolism. Combining our data with additional evidences, we provide improved annotations for at least 18 proteins (including TP0004, TP0050, and TP0183 which are suggested to be involved in DNA metabolism). We estimate that this “minimal” bacterium contains on the order of 3,000 protein interactions. Profiles of functional interconnections indicate that bacterial proteins interact more promiscuously than eukaryotic proteins, reflecting the non-compartmentalized structure of the bacterial cell. Using our high-confidence interactions, we also predict 417,329 homologous interactions (“interologs”) for 372 completely sequenced genomes and provide evidence that at least one third of them can be experimentally confirmed.

Transcriptional activators in yeast

Eukaryotic transcription activation domains (ADs) are not well defined on the proteome scale. We systematicallly tested ∼6000 yeast proteins for transcriptional activity using a yeast one-hybrid system and identified 451 transcriptional activators. We then determined their transcription activation strength using fusions to the Gal4 DNA-binding domain and a His3 reporter gene which contained a promoter with a Gal4-binding site. Among the 132 strongest activators 32 are known transcription factors while another 35 have no known function. Although zinc fingers, helix–loop–helix domains and several other domains are highly overrepresented among the activators, only few contain characterized ADs. We also found some striking correlations: the stronger the activation activity, the more acidic, glutamine-rich, proline-rich or asparagine-rich the activators were. About 29% of the activators have been found previously to specifically interact with the transcription machinery, while 10% are known to be components of transcription regulatory complexes. Based on their transcriptional activity, localization and interaction patterns, at least six previously uncharacterized proteins are suggested to be bona fide transcriptional regulators (namely YFL049W, YJR070C, YDR520C, YGL066W/Sgf73, YKR064W and YCR082W/Ahc2).

The Escherichia coli K-12 ORFeome: a resource for comparative molecular microbiology

BackgroundSystems biology and functional genomics require genome-wide datasets and resources. Complete sets of cloned open reading frames (ORFs) have been made for about a dozen bacterial species and allow researchers to express and study complete proteomes in a high-throughput fashion.ResultsWe have constructed an open reading frame (ORFeome) collection of 3974 or 94% of the known Escherichia coli K-12 ORFs in Gateway® entry vector pENTR/Zeo. The collection has been used for protein expression and protein interaction studies. For example, we have compared interactions among YgjD, YjeE and YeaZ proteins in E. coli, Streptococcus pneumoniae, and Staphylococcus aureus. We also compare this ORFeome with other Gateway-compatible bacterial ORFeomes and show its utility for comparative functional genomics.ConclusionsThe E. coli ORFeome provides a useful resource for functional genomics and other areas of protein research in a highly flexible format. Our comparison with other ORFeomes makes comparative analyses straighforward and facilitates direct comparisons of many proteins across many genomes.

Benchmarking yeast two-hybrid systems using the interactions of bacterial motility proteins

Yeast two‐hybrid screens often produce vastly non‐overlapping interaction data when the screens are conducted in different laboratories, or use different vectors, strains, or reporter genes. Here we investigate the underlying reasons for such inconsistencies and compare the effect of seven different vectors and their yeast two‐hybrid interactions. Genome‐wide array screens with 49 motility‐related baits from Treponema pallidum yielded 77 and 165 interactions with bait vectors pLP‐GBKT7 and pAS1‐LP, respectively, including 21 overlapping interactions. In addition, 90 motility‐related proteins from Escherichia coli were tested in all pairwise combinations and yielded 140 interactions when tested with pGBKT7g/pGADT7g vectors but only 47 when tested with pDEST32/pDEST22. We discuss the factors that determine these effects, including copy number, the nature of the fusion protein, and species‐specific differences that explain non‐conserved interactions among species. The pDEST22/pDEST32 vectors produce a higher fraction of interactions that are conserved and that are biologically relevant when compared with the pGBKT7/pGADT7‐related vectors, but the latter appear to be more sensitive and thus detect more interactions overall.

Novel Conserved Assembly Factor of the Bacterial Flagellum

TP0658 (FliW) and its orthologs, conserved proteins of unknown function in Treponema pallidum and other species, interact with a C-terminal region of flagellin (FlaB1-3 in T. pallidum; FliC in most other species). Mutants of orthologs in Bacillus subtilis and Campylobacter jejuni (yviF, CJ1075) showed strongly reduced motility. TP0658 stabilizes flagellin in a way similar to FliS, suggesting that TP0658 is a conserved assembly factor for the bacterial flagellum.