Quantitative analysis of senile plaques in Alzheimer disease: observation of log-normal size distribution and molecular epidemiology of differences associated with apolipoprotein E genotype and trisomy 21 (Down syndrome).

The discovery that the epsilon 4 allele of the apolipoprotein E (apoE) gene is a putative risk factor for Alzheimer disease (AD) in the general population has highlighted the role of genetic influences in this extremely common and disabling illness. It has long been recognized that another genetic abnormality, trisomy 21 (Down syndrome), is associated with early and severe development of AD neuropathological lesions. It remains a challenge, however, to understand how these facts relate to the pathological changes in the brains of AD patients. We used computerized image analysis to examine the size distribution of one of the characteristic neuropathological lesions in AD, deposits of A beta peptide in senile plaques (SPs). Surprisingly, we find that a log-normal distribution fits the SP size distribution quite well, motivating a porous model of SP morphogenesis. We then analyzed SP size distribution curves in genotypically defined subgroups of AD patients. The data demonstrate that both apoE epsilon 4/AD and trisomy 21/AD lead to increased amyloid deposition, but by apparently different mechanisms. The size distribution curve is shifted toward larger plaques in trisomy 21/AD, probably reflecting increased A beta production. In apoE epsilon 4/AD, the size distribution is unchanged but the number of SP is increased compared to apoE epsilon 3, suggesting increased probability of SP initiation. These results demonstrate that subgroups of AD patients defined on the basis of molecular characteristics have quantitatively different neuropathological phenotypes.

Fluorescence-intensity distribution analysis and its application in biomolecular detection technology

A methodology, fluorescence-intensity distribution analysis, has been developed for confocal microscopy studies in which the fluorescence intensity of a sample with a heterogeneous brightness profile is monitored. An adjustable formula, modeling the spatial brightness distribution, and the technique of generating functions for calculation of theoretical photon count number distributions serve as the two cornerstones of the methodology. The method permits the simultaneous determination of concentrations and specific brightness values of a number of individual fluorescent species in solution. Accordingly, we present an extremely sensitive tool to monitor the interaction of fluorescently labeled molecules or other microparticles with their respective biological counterparts that should find a wide application in life sciences, medicine, and drug discovery. Its potential is demonstrated by studying the hybridization of 5′-(6-carboxytetramethylrhodamine)-labeled and nonlabeled complementary oligonucleotides and the subsequent cleavage of the DNA hybrids by restriction enzymes.

Digging for dead genes: an analysis of the characteristics of the pseudogene population in the Caenorhabditis elegans genome

Pseudogenes are non-functioning copies of genes in genomic DNA, which may either result from reverse transcription from an mRNA transcript (processed pseudogenes) or from gene duplication and subsequent disablement (non-processed pseudogenes). As pseudogenes are apparently ‘dead’, they usually have a variety of obvious disablements (e.g., insertions, deletions, frameshifts and truncations) relative to their functioning homologs. We have derived an initial estimate of the size, distribution and characteristics of the pseudogene population in the Caenorhabditis elegans genome, performing a survey in ‘molecular archaeology’. Corresponding to the 18 576 annotated proteins in the worm (i.e., in Wormpep18), we have found an estimated total of 2168 pseudogenes, about one for every eight genes. Few of these appear to be processed. Details of our pseudogene assignments are available from http://bioinfo.mbb.yale.edu/genome/worm/pseudogene. The population of pseudogenes differs significantly from that of genes in a number of respects: (i) pseudogenes are distributed unevenly across the genome relative to genes, with a disproportionate number on chromosome IV; (ii) the density of pseudogenes is higher on the arms of the chromosomes; (iii) the amino acid composition of pseudogenes is midway between that of genes and (translations of) random intergenic DNA, with enrichment of Phe, Ile, Leu and Lys, and depletion of Asp, Ala, Glu and Gly relative to the worm proteome; and (iv) the most common protein folds and families differ somewhat between genes and pseudogenes—whereas the most common fold found in the worm proteome is the immunoglobulin fold and the most common ‘pseudofold’ is the C-type lectin. In addition, the size of a gene family bears little overall relationship to the size of its corresponding pseudogene complement, indicating a highly dynamic genome. There are in fact a number of families associated with large populations of pseudogenes. For example, one family of seven-transmembrane receptors (represented by gene B0334.7) has one pseudogene for every four genes, and another uncharacterized family (represented by gene B0403.1) is approximately two-thirds pseudogenic. Furthermore, over a hundred apparent pseudogenic fragments do not have any obvious homologs in the worm.