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 (NH4+), we find that the characteristic length scales of nanoporous S-layers elevate the concentration of NH4+ 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 NH4+ availability, with broad implications for comparisons of ecologically distinct populations.

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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).

Author information


  1. Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA

    • Po-Nan Li
  2. SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA

    • Po-Nan Li
    • , Jonathan Herrmann
    • , John R. Bargar
    • , Soichi Wakatsuki
    •  & Henry van den Bedem
  3. Department of Structural Biology, Stanford University, Stanford, CA, 94305, USA

    • Jonathan Herrmann
    • , Frédéric Poitevin
    •  & Soichi Wakatsuki
  4. Department of Earth System Science, Stanford University, Stanford, CA, 94305, USA

    • Bradley B. Tolar
    •  & Christopher A. Francis
  5. Stanford PULSE Institute, SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA

    • Frédéric Poitevin
  6. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA

    • Rasika Ramdasi
    •  & Grant J. Jensen
  7. Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, 98195, USA

    • David A. Stahl
  8. Howard Hughes Medical Institute, California Institute of Technology, Pasadena, CA, 91125, USA

    • Grant J. Jensen
  9. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94158, USA

    • Henry van den Bedem


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Correspondence to Christopher A. Francis or Soichi Wakatsuki or Henry van den Bedem.

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