Cellular receptors usually contain a designated sensory domain that recognizes the signal. Per/Arnt/Sim (PAS) domains are ubiquitous sensors in thousands of species ranging from bacteria to humans. Although PAS domains were described as intracellular sensors, recent structural studies revealed PAS-like domains in extracytoplasmic regions in several transmembrane receptors. However, these structurally defined extracellular PAS-like domains do not match sequence-derived PAS domain models, and thus their distribution across the genomic landscape remains largely unknown. Here we show that structurally defined extracellular PAS-like domains belong to the Cache superfamily, which is homologous to, but distinct from the PAS superfamily. Our newly built computational models enabled identification of Cache domains in tens of thousands of signal transduction proteins including those from important pathogens and model organisms. Furthermore, we show that Cache domains comprise the dominant mode of extracellular sensing in prokaryotes.

Bacterial chemosensory arrays are composed of extended networks of chemoreceptors (also known as methyl-accepting chemotaxis proteins, MCPs), the histidine kinase CheA, and the adaptor protein CheW. Models of these arrays have been developed from cryoelectron microscopy, crystal structures of binary and ternary complexes, NMR spectroscopy, mutational data and biochemical studies. A new 3.2 Å resolution crystal structure of a T. maritima MCP protein interaction region in complex with the CheA kinase-regulatory module (P4–P5) and adaptor protein CheW provides sufficient detail to define residue contacts at the interfaces formed among the three proteins. As in a previous 4.5 Å resolution structure, CheA-P5 and CheW interact through conserved hydrophobic surfaces at the ends of their β-barrels to from pseudo six-fold symmetric rings in which the two proteins alternate around the circumference. The interface between P5 subdomain 1 and CheW subdomain 2 was anticipated from previous studies, whereas the related interface between CheW subdomain 1 and P5 subdomain 2 has only been observed in these ring assemblies. The receptor forms an unexpected structure in that the helical hairpin tip of each subunit has “unzipped” into a continuous α-helix; four such helices associate into a bundle and the tetramers bridge adjacent P5-CheW rings in the lattice through interactions with both P5 and CheW. P5 and CheW each bind a receptor helix with a groove of conserved hydrophobic residues between subdomains 1 and 2. P5 binds the receptor helix N-terminal to the tip region (lower site), whereas CheW binds the same helix with inverted polarity near the bundle end (upper site). Sequence comparisons among different evolutionary classes of chemotaxis proteins show that the binding partners undergo correlated changes at key residue positions that involve the lower site. Such evolutionary analyses argue that both CheW and P5 bind to the receptor tip at overlapping positions. Computational genomics further reveal that two distinct CheW proteins in Thermotogae utilize the analogous recognition motifs to couple different receptor classes to the same CheA kinase. Important residues for function previously identified by mutagenesis, chemical modification and biophysical approaches also map to these same interfaces. Thus, although the native CheW-receptor interaction is not observed in the present crystal structure, the bioinformatics and previous data predict key features of this interface. The companion study of the P5-receptor interface in native arrays (Piasta et al. (2013) Biochemistry; Companion paper) shows that, despite the non-native receptor fold in the present crystal structure, the local helix-in-groove contacts of the crystallographic P5-receptor interaction are present in native arrays and are essential for receptor regulation of kinase activity.

In contrast to , a model organism for chemotaxis that has 5 chemoreceptors and a single chemosensory pathway, PAO1 has a much more complex chemosensory network, which consists of 26 chemoreceptors feeding into four chemosensory pathways. While several chemoreceptors were rigorously linked to specific pathways in a series of experimental studies, for most of them this information is not available. Thus, we addressed the problem computationally. Protein-protein interaction network prediction, coexpression data mining, and phylogenetic profiling all produced incomplete and uncertain assignments of chemoreceptors to pathways. However, comparative sequence analysis specifically targeting chemoreceptor regions involved in pathway interactions revealed conserved sequence patterns that enabled us to unambiguously link all 26 chemoreceptors to four pathways. Placing computational evidence in the context of experimental data allowed us to conclude that three chemosensory pathways in utilize one chemoreceptor per pathway, whereas the fourth pathway, which is the main system controlling chemotaxis, utilizes the other 23 chemoreceptors. Our results show that while only a very few amino acid positions in receptors, kinases, and adaptors determine their pathway specificity, assigning receptors to pathways computationally is possible. This requires substantial knowledge about interacting partners on a molecular level and focusing comparative sequence analysis on the pathway-specific regions. This general principle should be applicable to resolving many other receptor-pathway interactions.