Validation of membrane protein topology models by oxidative labeling and mass spectrometry

Computer-assisted topology predictions are widely used to build low-resolution structural models of integral membrane proteins (IMPs). Experimental validation of these models by traditional methods is labor intensive and requires modifications that might alter the IMP native conformation. This work employs oxidative labeling coupled with mass spectrometry (MS) as a validation tool for computer-generated topology models. ·OH exposure introduces oxidative modifications in solvent-accessible regions, whereas buried segments (e.g., transmembrane helices) are non-oxidizable. The Escherichia coli protein WaaL (O-antigen ligase) is predicted to have 12 transmembrane helices and a large extramembrane domain (Pérez et al., Mol. Microbiol. 2008, 70, 1424). Tryptic digestion and LC-MS/MS were used to map the oxidative labeling behavior of WaaL. Met and Cys exhibit high intrinsic reactivities with ·OH, making them sensitive probes for solvent accessibility assays. Overall, the oxidation pattern of these residues is consistent with the originally proposed WaaL topology. One residue (M151), however, undergoes partial oxidation despite being predicted to reside within a transmembrane helix. Using an improved computer algorithm, a slightly modified topology model was generated that places M151 closer to the membrane interface. On the basis of the labeling data, it is concluded that the refined model more accurately reflects the actual topology of WaaL. We propose that the combination of oxidative labeling and MS represents a useful strategy for assessing the accuracy of IMP topology predictions, supplementing data obtained in traditional biochemical assays. In the future, it might be possible to incorporate oxidative labeling data directly as constraints in topology prediction algorithms.

Testing the channel-based model of duration perception

The channel-based model of duration perception postulates the existence of neural mechanisms that respond selectively to a narrow range of stimulus durations centred on their preferred duration (Heron et al Proceedings of the Royal Society B 279 690–698). In principle the channel-based model could
explain recent reports of adaptation-induced, visual duration compression effects (Johnston et al Current Biology 16 472–479; Curran and Benton Cognition 122 252–257); from this perspective duration compression is a consequence of the adapting stimuli being presented for a longer duration than the test stimuli. In the current experiment observers adapted to a sequence of moving random dot patterns at the same retinal position, each 340ms in duration and separated by a variable (500–1000ms) interval. Following adaptation observers judged the duration of a 600ms test stimulus at the same location. The test stimulus moved in the same, or opposite, direction as the adaptor. Contrary to the channel-based
model’s prediction, test stimulus duration appeared compressed, rather than expanded, when it moved in the same direction as the adaptor. That test stimulus duration was not distorted when moving in the opposite direction further suggests that visual timing mechanisms are influenced by additional neural processing associated with the stimulus being timed.

Sum-Rate and Power Scaling of Massive MIMO Systems with Channel Aging

This paper investigates the achievable sum-rate of massive multiple-input multiple-output (MIMO) systems in the presence of channel aging. For the uplink, by assuming that the base station (BS) deploys maximum ratio combining (MRC) or zero-forcing (ZF) receivers, we present tight closed-form lower bounds on the achievable sum-rate for both receivers with aged channel state information (CSI). In addition, the benefit of implementing channel prediction methods on the sum-rate is examined, and closed-form sum rate lower bounds are derived. Moreover, the impact of channel aging and channel prediction on the power scaling law is characterized. Extension to the downlink scenario and multi-cell scenario are also considered. It is found that, for a system with/without channel prediction, the transmit power of each user can be scaled down at most by 1= p M (where M is the number of BS antennas), which indicates that aged CSI does not degrade the power scaling law, and channel prediction does not enhance the power scaling law; instead, these phenomena affect the achievable sum-rate by degrading or enhancing the effective signal to interference and noise ratio, respectively.