Transporter ProP of Escherichia coli mediates the cellular accumulation of organic zwitterions in response to increased extracellular osmolality. We compared and characterized the osmoregulation of ProP activity in cells and proteoliposomes to define the osmotic shift-induced cellular change(s) to which ProP responds. ProP-(His)(6) activity in cells and proteoliposomes was correlated with medium osmolality, not osmotic shift, turgor pressure, or membrane strain. Both K(M) and V(max) for proline uptake via ProP-(His)(6) increased with increasing medium osmolality, as would be expected if osmolality controls the proportions of transporter with inactive and active conformations. The osmolality yielding half-maximal ProP-(His)(6) activity was higher in proteoliposomes than in cells. The osmolality response of ProP is also attenuated in bacteria lacking soluble protein ProQ. Indeed, the catalytic constant (k(cat)) for ProP-(His)(6) in proteoliposomes approximated that of ProP in intact bacteria lacking ProQ. Thus, the proteoliposome system may replicate a primary osmosensory response that can be further amplified by ProQ. ProP-(His)(6) is designated as an osmosensor because its activity is dependent on the osmolality, but not the composition, of the assay medium to which the cell surface is exposed. In contrast, ProP-(His)(6) activity was dependent on both the osmolality and the composition of the lumen in osmolyte-loaded proteoliposomes. For proteoliposomes containing inorganic salts, glucose, or poly(ethylene glycol) 503, transporter activity correlated with total lumenal cation concentration. In contrast, for proteoliposomes loaded with larger poly(ethylene glycol)s, the osmolality, the lumenal cation concentration, and the lumenal ionic strength at half-maximal transporter activity decreased systematically with poly(ethylene glycol) radius of gyration (range 0.8-1.8 nm). These data suggest that ProP-(His)(6) responds to osmotically induced changes in both cytoplasmic K(+) levels and the concentration of cytoplasmic macromolecules.

Transporter ProP of Escherichia coli is an osmosensor and an osmoprotectant transporter. Previous results suggest that medium osmolality determines the proportions of ProP in active and inactive conformations. A cysteine-less (Cys-less) variant was created and characterized as a basis for structural and functional analyses based on site-directed Cys substitution and chemical labeling of ProP. Parameters describing the osmosensory and osmoprotectant transport activities of Cys-less ProP-(His)(6) variants were examined, including the threshold for osmotic activation and the absolute transporter activity at high osmolality (in both cells and proteoliposomes), the dependence of K(M) and V(max) for proline uptake on osmolality, and the rate constant for transporter activation in response to an osmotic upshift (in cells only). Variant ProP-(His)(6)-C112A-C133A-C264V-C367A (designated ProP) retained similar activities to ProP-(His)(6) in both cells and proteoliposomes. The bulky Val residue was favored over Ala or Ser at position 264, whereas Val strongly impaired function when placed at position 367, highlighting the importance of residues at those positions for osmosensing. In the ProP* background, variants with a single Cys residue at positions 112, 133, 241, 264, 293, or 367 retained full function. The native Cys at positions 112, 133, 264, and 367, predicted to be within transmembrane segments of ProP, were poorly reactive with membrane-impermeant thiol reagents. The reactivities of Cys at positions 241 and 293 were consistent with exposure of those residues on the cytoplasmic and periplasmic surfaces of the cytoplasmic membrane, respectively. These observations are consistent with the topology and orientation of ProP predicted by hydropathy analysis.

Neural field theory insights are used to derive effective brain connectivity matrices from the functional connectivity matrix defined by activity covariances. The symmetric case is exactly solved for a resting state system driven by white noise, in which strengths of connections, often termed effective connectivities, are inferred from functional data; these include strengths of connections that are underestimated or not detected by anatomical imaging. Proximity to criticality is calculated and found to be consistent with estimates obtainable from other methods. Links between anatomical, effective, and functional connectivity and resting state activity are quantified, with applicability to other complex networks. Proof-of-principle results are illustrated using published experimental data on anatomical connectivity and resting state functional connectivity. In particular, it is shown that functional connection matrices can be used to uncover the existence and strength of connections that are missed from anatomical connection matrices, including interhemispheric connections that are difficult to track with techniques such as diffusion spectrum imaging.