Description of microcolumnar ensembles in association cortex and their disruption in Alzheimer and Lewy body dementias

The cortex of the brain is organized into clear horizontal layers, laminae, which subserve much of the connectional anatomy of the brain. We hypothesize that there is also a vertical anatomical organization that might subserve local interactions of neuronal functional units, in accord with longstanding electrophysiological observations. We develop and apply a general quantitative method, inspired by analogous methods in condensed matter physics, to examine the anatomical organization of the cortex in human brain. We find, in addition to obvious laminae, anatomical evidence for tightly packed microcolumnar ensembles containing approximately 11 neurons, with a periodicity of about 80 μm. We examine the structural integrity of this new architectural feature in two common dementing illnesses, Alzheimer disease and dementia with Lewy bodies. In Alzheimer disease, there is a dramatic, nearly complete loss of microcolumnar ensemble organization. The relative degree of loss of microcolumnar ensembles is directly proportional to the number of neurofibrillary tangles, but not related to the amount of amyloid-β deposition. In dementia with Lewy bodies, a similar disruption of microcolumnar ensemble architecture occurs despite minimal neuronal loss. These observations show that quantitative analysis of complex cortical architecture can be applied to analyze the anatomical basis of brain disorders.

Dynamics of fluorescence fluctuations in green fluorescent protein observed by fluorescence correlation spectroscopy

We have investigated the pH dependence of the dynamics of conformational fluctuations of green fluorescent protein mutants EGFP (F64L/S65T) and GFP-S65T in small ensembles of molecules in solution by using fluorescence correlation spectroscopy (FCS). FCS utilizes time-resolved measurements of fluctuations in the molecular fluorescence emission for determination of the intrinsic dynamics and thermodynamics of all processes that affect the fluorescence. Fluorescence excitation of a bulk solution of EGFP decreases to zero at low pH (pKa = 5.8) paralleled by a decrease of the absorption at 488 nm and an increase at 400 nm. Protonation of the hydroxyl group of Tyr-66, which is part of the chromophore, induces these changes. When FCS is used the fluctuations in the protonation state of the chromophore are time resolved. The autocorrelation function of fluorescence emission shows contributions from two chemical relaxation processes as well as diffusional concentration fluctuations. The time constant of the fast, pH-dependent chemical process decreases with pH from 300 μs at pH 7 to 45 μs at pH 5, while the time-average fraction of molecules in a nonfluorescent state increases to 80% in the same range. A second, pH-independent, process with a time constant of 340 μs and an associated fraction of 13% nonfluorescent molecules is observed between pH 8 and 11, possibly representing an internal proton transfer process and associated conformational rearrangements. The FCS data provide direct measures of the dynamics and the equilibrium properties of the protonation processes. Thus FCS is a convenient, intrinsically calibrated method for pH measurements in subfemtoliter volumes with nanomolar concentrations of EGFP.

Deciphering a neural code for vision

Deciphering the information that eyes, ears, and other sensory organs transmit to the brain is important for understanding the neural basis of behavior. Recordings from single sensory nerve cells have yielded useful insights, but single neurons generally do not mediate behavior; networks of neurons do. Monitoring the activity of all cells in a neural network of a behaving animal, however, is not yet possible. Taking an alternative approach, we used a realistic cell-based model to compute the ensemble of neural activity generated by one sensory organ, the lateral eye of the horseshoe crab, Limulus polyphemus. We studied how the neural network of this eye encodes natural scenes by presenting to the model movies recorded with a video camera mounted above the eye of an animal that was exploring its underwater habitat. Model predictions were confirmed by simultaneously recording responses from single optic nerve fibers of the same animal. We report here that the eye transmits to the brain robust “neural images” of objects having the size, contrast, and motion of potential mates. The neural code for such objects is not found in ambiguous messages of individual optic nerve fibers but rather in patterns of coherent activity that extend over small ensembles of nerve fibers and are bound together by stimulus motion. Integrative properties of neurons in the first synaptic layer of the brain appear well suited to detecting the patterns of coherent activity. Neural coding by this relatively simple eye helps explain how horseshoe crabs find mates and may lead to a better understanding of how more complex sensory organs process information.

Native protein sequences are close to optimal for their structures

How large is the volume of sequence space that is compatible with a given protein structure? Starting from random sequences, low free energy sequences were generated for 108 protein backbone structures by using a Monte Carlo optimization procedure and a free energy function based primarily on Lennard–Jones packing interactions and the Lazaridis–Karplus implicit solvation model. Remarkably, in the designed sequences 51% of the core residues and 27% of all residues were identical to the amino acids in the corresponding positions in the native sequences. The lowest free energy sequences obtained for ensembles of native-like backbone structures were also similar to the native sequence. Furthermore, both the individual residue frequencies and the covariances between pairs of positions observed in the very large SH3 domain family were recapitulated in core sequences designed for SH3 domain structures. Taken together, these results suggest that the volume of sequence space optimal for a protein structure is surprisingly restricted to a region around the native sequence.

Top-down free-energy minimization on protein potential energy landscapes

The hierarchical properties of potential energy landscapes have been used to gain insight into thermodynamic and kinetic properties of protein ensembles. It also may be possible to use them to direct computational searches for thermodynamically stable macroscopic states, i.e., computational protein folding. To this end, we have developed a top-down search procedure in which conformation space is recursively dissected according to the intrinsic hierarchical structure of a landscape's effective-energy barriers. This procedure generates an inverted tree similar to the disconnectivity graphs generated by local minima-clustering methods, but it fundamentally differs in the manner in which the portion of the tree that is to be computationally explored is selected. A key ingredient is a branch-selection algorithm that takes advantage of statistically predictive properties of the landscape to guide searches down the tree branches that are most likely to lead to the physically relevant macroscopic states. Using the computational folding of a β-hairpin-forming peptide as an example, we show that such predictive properties indeed exist and can be used for structure prediction by free-energy global minimization.

Fluorescence correlation spectroscopy: Diagnostics for sparse molecules

The robust glow of molecular fluorescence renders even sparse molecules detectable and susceptible to analysis for concentration, mobility, chemistry, and photophysics. Correlation spectroscopy, a statistical-physics-based tool, gleans quantitative information from the spontaneously fluctuating fluorescence signals obtained from small molecular ensembles. This analytical power is available for studying molecules present at minuscule concentrations in liquid solutions (less than one nanomolar), or even on the surfaces of living cells at less than one macromolecule per square micrometer. Indeed, routines are becoming common to detect, locate, and examine individual molecules under favorable conditions.

Molecular kinesis in cellular function and plasticity

Intracellular transport and localization of cellular components are essential for the functional organization and plasticity of eukaryotic cells. Although the elucidation of protein transport mechanisms has made impressive progress in recent years, intracellular transport of RNA remains less well understood. The National Academy of Sciences Colloquium on Molecular Kinesis in Cellular Function and Plasticity therefore was devised as an interdisciplinary platform for participants to discuss intracellular molecular transport from a variety of different perspectives. Topics covered at the meeting included RNA metabolism and transport, mechanisms of protein synthesis and localization, the formation of complex interactive protein ensembles, and the relevance of such mechanisms for activity-dependent regulation and synaptic plasticity in neurons. It was the overall objective of the colloquium to generate momentum and cohesion for the emerging research field of molecular kinesis.

Probing the interaction between two single molecules: fluorescence resonance energy transfer between a single donor and a single acceptor.

We extend the sensitivity of fluorescence resonance energy transfer (FRET) to the single molecule level by measuring energy transfer between a single donor fluorophore and a single acceptor fluorophore. Near-field scanning optical microscopy (NSOM) is used to obtain simultaneous dual color images and emission spectra from donor and acceptor fluorophores linked by a short DNA molecule. Photodestruction dynamics of the donor or acceptor are used to determine the presence and efficiency of energy transfer. The classical equations used to measure energy transfer on ensembles of fluorophores are modified for single-molecule measurements. In contrast to ensemble measurements, dynamic events on a molecular scale are observable in single pair FRET measurements because they are not canceled out by random averaging. Monitoring conformational changes, such as rotations and distance changes on a nanometer scale, within single biological macromolecules, may be possible with single pair FRET.