The prion model for [URE3] of yeast: Spontaneous generation and requirements for propagation

The genetic properties of the non-Mendelian element, [URE3], suggest that it is a prion (infectious protein) form of Ure2p, a mediator of nitrogen regulation in Saccharomyces cerevisiae. Into a ure2Δ strain (necessarily lacking [URE3]), we introduced a plasmid overproducing Ure2p. This induced the frequent “spontaneous generation” of [URE3], with properties identical to the original [URE3]. Altering the translational frame only in the prion-inducing domain of URE2 shows that it is Ure2 protein (and not URE2 RNA) that induces appearance of [URE3]. The proteinase K-resistance of Ure2p is unique to [URE3] strains and is not seen in nitrogen regulation of normal strains. The prion-inducing domain of Ure2p (residues 1–65) can propagate [URE3] in the absence of the C-terminal part of the molecule. In contrast, the C-terminal part of Ure2p cannot be converted to the prion (inactive) form without the prion-inducing domain covalently attached. These experiments support the prion model for [URE3] and extend our understanding of its propagation.

Transforming neural computations and representing time

Motifs of neural circuitry seem surprisingly conserved over different areas of neocortex or of paleocortex, while performing quite different sensory processing tasks. This apparent paradox may be resolved by the fact that seemingly different problems in sensory information processing are related by transformations (changes of variables) that convert one problem into another. The same basic algorithm that is appropriate to the recognition of a known odor quality, independent of the strength of the odor, can be used to recognize a vocalization (e.g., a spoken syllable), independent of whether it is spoken quickly or slowly. To convert one problem into the other, a new representation of time sequences is needed. The time that has elapsed since a recent event must be represented in neural activity. The electrophysiological hallmarks of cells that are involved in generating such a representation of time are discussed. The anatomical relationships between olfactory and auditory pathways suggest relevant experiments. The neurophysiological mechanism for the psychophysical logarithmic encoding of time duration would be of direct use for interconverting olfactory and auditory processing problems. Such reuse of old algorithms in new settings and representations is related to the way that evolution develops new biochemistry.

A new Eocene archaeocete (Mammalia, Cetacea) from India and the time of origin of whales

Himalayacetus subathuensis is a new pakicetid archaeocete from the Subathu Formation of northern India. The type dentary has a small mandibular canal indicating a lack of auditory specializations seen in more advanced cetaceans, and it has Pakicetus-like molar teeth suggesting that it fed on fish. Himalayacetus is significant because it is the oldest archaeocete known and because it was found in marine strata associated with a marine fauna. Himalayacetus extends the fossil record of whales about 3.5 million years back in geological time, to the middle part of the early Eocene [≈53.5 million years ago (Ma)]. Oxygen in the tooth-enamel phosphate has an isotopic composition intermediate between values reported for freshwater and marine archaeocetes, indicating that Himalayacetus probably spent some time in both environments. When the temporal range of Archaeoceti is calibrated radiometrically, comparison of likelihoods constrains the time of origin of Archaeoceti and hence Cetacea to about 54–55 Ma (beginning of the Eocene), whereas their divergence from extant Artiodactyla may have been as early as 64–65 Ma (beginning of the Cenozoic).

Diffractive optics-based heterodyne-detected four-wave mixing signals of protein motion: From “protein quakes” to ligand escape for myoglobin

Ligand transport through myoglobin (Mb) has been observed by using optically heterodyne-detected transient grating spectroscopy. Experimental implementation using diffractive optics has provided unprecedented sensitivity for the study of protein motions by enabling the passive phase locking of the four beams that constitute the experiment, and an unambiguous separation of the Real and Imaginary parts of the signal. Ligand photodissociation of carboxymyoglobin (MbCO) induces a sequence of events involving the relaxation of the protein structure to accommodate ligand escape. These motions show up in the Real part of the signal. The ligand (CO) transport process involves an initial, small amplitude, change in volume, reflecting the transit time of the ligand through the protein, followed by a significantly larger volume change with ligand escape to the surrounding water. The latter process is well described by a single exponential process of 725 ± 15 ns at room temperature. The overall dynamics provide a distinctive signature that can be understood in the context of segmental protein fluctuations that aid ligand escape via a few specific cavities, and they suggest the existence of discrete escape pathways.

Brownian dynamics simulations of protein folding: Access to milliseconds time scale and beyond

Protein folding occurs on a time scale ranging from milliseconds to minutes for a majority of proteins. Computer simulation of protein folding, from a random configuration to the native structure, is nontrivial owing to the large disparity between the simulation and folding time scales. As an effort to overcome this limitation, simple models with idealized protein subdomains, e.g., the diffusion–collision model of Karplus and Weaver, have gained some popularity. We present here new results for the folding of a four-helix bundle within the framework of the diffusion–collision model. Even with such simplifying assumptions, a direct application of standard Brownian dynamics methods would consume 10,000 processor-years on current supercomputers. We circumvent this difficulty by invoking a special Brownian dynamics simulation. The method features the calculation of the mean passage time of an event from the flux overpopulation method and the sampling of events that lead to productive collisions even if their probability is extremely small (because of large free-energy barriers that separate them from the higher probability events). Using these developments, we demonstrate that a coarse-grained model of the four-helix bundle can be simulated in several days on current supercomputers. Furthermore, such simulations yield folding times that are in the range of time scales observed in experiments.

Formation of temporal-feature maps by axonal propagation of synaptic learning

Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.