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Published October 2018 | Supplemental Material
Journal Article Open

Nutrient transport suggests an evolutionary basis for charged archaeal surface layer proteins

Abstract

Surface layers (S-layers) are two-dimensional, proteinaceous, porous lattices that form the outermost cell envelope component of virtually all archaea and many bacteria. Despite exceptional sequence diversity, S-layer proteins (SLPs) share important characteristics such as their ability to form crystalline sheets punctuated with nano-scale pores, and their propensity for charged amino acids, leading to acidic or basic isoelectric points. However, the precise function of S-layers, or the role of charged SLPs and how they relate to cellular metabolism is unknown. Nano-scale lattices affect the diffusion behavior of low-concentration solutes, even if they are significantly smaller than the pore size. Here, we offer a rationale for charged S-layer proteins in the context of the structural evolution of S-layers. Using the ammonia-oxidizing archaea (AOA) as a model for S-layer geometry, and a 2D electrodiffusion reaction computational framework to simulate diffusion and consumption of the charged solute ammonium (NH_4^+), we find that the characteristic length scales of nanoporous S-layers elevate the concentration of NH_4^+ in the pseudo-periplasmic space. Our simulations suggest an evolutionary, mechanistic basis for S-layer charge and shed light on the unique ability of some AOA to oxidize ammonia in environments with nanomolar NH_4^+ availability, with broad implications for comparisons of ecologically distinct populations.

Additional Information

© 2018 International Society for Microbial Ecology. Received: 30 November 2017; Revised: 11 April 2018; Accepted: 14 April 2018; Published online 13 June 2018. This work was partially supported by the US Department of Energy, Laboratory Directed Research and Development under contract No. DE-AC02-76SF00515. JH was supported by the National Science Foundation Graduate Research Fellowship Program (NSF-GRFP), as well as the US Department of Energy Office of Science Graduate Student Research Program (DOE-SCGSR). FP acknowledges support from the National Institutes of Health (NIH), grant No. R35GM122543. DAS was funded in part by the United States National Science Foundation Grants MCB-092074 and OCE-1046017. HvdB acknowledges support from the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) program. Computations were performed at the Stanford Research Computing Center. Glycosylation analysis by mass spectrometry was possible with assistance from C Adams and R Lieb (Stanford University Mass Spectrometry). The authors declare that they have no conflict of interest.

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