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The periplasmic chaperone network ensures the biogenesis of bacterial outer membrane proteins (OMPs) and has recently been identified as a promising target for antibiotics. SurA is the most important member of this network, both due to its genetic interaction with the β-barrel assembly machinery complex as well as its ability to prevent unfolded OMP (uOMP) aggregation. Using only binding energy, the mechanism by which SurA carries out these two functions is not well-understood. Here, we use a combination of photo-crosslinking, mass spectrometry, solution scattering, and molecular modeling techniques to elucidate the key structural features that define how SurA solubilizes uOMPs. Our experimental data support a model in which SurA binds uOMPs in a groove formed between the core and P1 domains. This binding event results in a drastic expansion of the rest of the uOMP, which has many biological implications. Using these experimental data as restraints, we adopted an integrative modeling approach to create a sparse ensemble of models of a SurA•uOMP complex. We validated key structural features of the SurA•uOMP ensemble using independent scattering and chemical crosslinking data. Our data suggest that SurA utilizes three distinct binding modes to interact with uOMPs and that more than one SurA can bind a uOMP at a time. This work demonstrates that SurA operates in a distinct fashion compared to other chaperones in the OMP biogenesis network.

SurA is thought to be the most important periplasmic chaperone for outer membrane protein (OMP) biogenesis. Its structure is composed of a core region and two peptidylprolyl isomerase domains, termed P1 and P2, connected by flexible linkers. As such these three independent folding units are able to adopt a number of distinct spatial positions with respect to each other. The conformational dynamics of these domains are thought to be functionally important yet are largely unresolved. Here we address this question of the conformational ensemble using sedimentation equilibrium, small‐angle neutron scattering, and folding titrations. This combination of orthogonal methods converges on a SurA population that is monomeric at physiological concentrations. The conformation that dominates this population has the P1 and core domains docked to one another, for example, “P1‐closed” and the P2 domain extended in solution. We discovered that the distribution of domain orientations is defined by modest and favorable interactions between the core domain and either the P1 or the P2 domains. These two peptidylprolyl domains compete with each other for core‐binding but are thermodynamically uncoupled. This arrangement implies two novel insights. Firstly, an open conformation must exist to facilitate P1 and P2 exchange on the core, indicating that the open client‐binding conformation is populated at low levels even in the absence of client unfolded OMPs. Secondly, competition between P1 and P2 binding paradoxically occludes the client binding site on the core, which may serve to preserve the reservoir of binding‐competent apo‐SurA in the periplasm.

Shifting baselines in the Arctic atmosphere‐sea ice‐ocean system have significant potential to alter biogeochemical cycling and ecosystem dynamics. In particular, the impact of increased open water duration on lower trophic level productivity and biological CO₂sequestration is poorly understood. Using high‐resolution observations of surface seawater dissolved O₂/Ar andpCO₂collected in the Pacific Arctic in October 2011 and 2012, we evaluate spatial variability in biological metabolic status (autotrophy vs heterotrophy) as constrained by O₂/Ar saturation (∆O₂/Ar) as well as the relationship between net biological production and the sea‐air gradient ofpCO₂(∆pCO₂). We find a robust relationship between∆pCO₂and∆O₂/Ar(correlation coefficient of −0.74 and −0.61 for 2011 and 2012, respectively), which suggests that biological production in the late open water season is an important determinant of the air‐sea CO₂gradient at a timeframe of maximal ocean uptake for CO₂in this region. Patchiness in biological production as indicated by∆O₂/Arsuggests spatially variable nutrient supply mechanisms supporting late season growth amidst a generally strongly stratified and nutrient‐limited condition.