The Homeo Domain of a Murine Protein Binds 5\u27 to its Own Homeo Box.

Nuclear protein extracts from day 12.5 mouse embryos were used to study protein binding to DNA sequences 5\u27 of the Hox 1.5 homeo box. Embryos of this developmental stage are known to express this gene. DNA binding protein blotting and retardation gel techniques show that murine embryonic nuclear proteins specifically bind a 753-base pair (bp) DNA fragment from the region upstream of the Hox 1.5 homeo box. A fusion protein containing the Hox 1.5 homeo domain constructed in lambda gt11 also binds the same 753-bp DNA fragment. Specific binding of the fusion protein to the upstream DNA fragment shows that the homeo box contains the sequences required for specific protein-DNA interactions, and the 753-bp fragment contains a homeo domain binding site. These results support the hypothesis that murine homeo boxes are DNA binding domains of proteins involved in the regulation of embryonic development

Green Fluorescent Protein in the sea urchin: new experimental approaches to transcriptional regulatory analysis in embryos and larvae

The use of Green Fluorescent Protein (GFP) as a reporter for expression transgenes opens the way to several new experimental strategies for the study of gene regulation in sea urchin development. A GFP coding sequence was associated with three different previously studied cis-regulatory systems, viz those of the SM50 gene, expressed in skeletogenic mesenchyme, the CyIIa gene, expressed in archenteron, skeletogenic and secondary mesenchyme, and the Endo16 gene, expressed in vegetal plate, archenteron and midgut. We demonstrate that the sensitivity with which expression can be detected is equal to or greater than that of whole-mount in situ hybridization applied to detection of CAT mRNA synthesized under the control of the same cis-regulatory systems. However, in addition to the important feature that it can be visualized nondestructively in living embryos, GFP has other advantages. First, it freely diffuses even within fine cytoplasmic cables, and thus reveals connections between cells, which in sea urchin embryos is particularly useful for observations on regulatory systems that operate in the syncytial skeletogenic mesenchyme. Second, GFP expression can be dramatically visualized in postembryonic larval tissues. This brings postembryonic larval developmental processes for the first time within the easy range of gene transfer analyses. Third, GFP permits identification and segregation of embryos in which the clonal incorporation of injected DNA has occurred in any particular desired region of the embryo. Thus, we show explicitly that, as expected, GFP transgenes are incorporated in the same nuclei together with other transgenes with which they are co-injected

Microarray and EST database estimates of mRNA expression levels differ: The protein length versus expression curve for C. elegans

BACKGROUND: Various methods for estimating protein expression levels are known. The level of correlation between these methods is only fair, and systematic biases in each of the methods cannot be ruled out. We here investigate systematic biases in the estimation of gene expression rates from microarray data and from abundance within the Expressed Sequence Tag (EST) database. We suggest that length is a significant factor in biases to measured gene expression rates. As a specific example of the importance of the bias of expression rate with length, we address the following evolutionary question: Does the average C. elegans protein length increase or decrease with expression level? Two different answers to this question have been reported in the literature, one method using expression levels estimated by abundance within the EST database and another using microarrays. We have investigated this issue by constructing the full protein length versus expression curve for C. elegans, using both methods for estimating expression levels. RESULTS: The microarray data show a monotonic decrease of length with expression level, whereas the abundance within the EST database data show a non-monotonic behavior. Furthermore, the ratio of the expression level estimated by the EST database to that measured by microarrays is not constant, but rather systematically biased with gene length. CONCLUSIONS: It is suggested that the length bias may lie primarily in the abundance within the EST database method, being not ameliorated by internal standards as it is in the microarray data, and that this bias should be removed before data interpretation. When this is done, both the microarray and the abundance within the EST database give a monotonic decrease of spliced length with expression level, and the correlation between the EST and microarray data becomes larger. We suggest that standard RNA controls be used to normalize for length bias in any method that measures expression

Correlations in the T Cell Response to Altered Peptide Ligands

The vertebrate immune system is a wonder of modern evolution. Occasionally, however, correlations within the immune system lead to inappropriate recruitment of preexisting T cells against novel viral diseases. We present a random energy theory for the correlations in the naive and memory T cell immune responses. The non-linear susceptibility of the random energy model to structural changes captures the correlations in the immune response to mutated antigens. We show how the sequence-level diversity of the T cell repertoire drives the dynamics of the immune response against mutated viral antigens.Comment: 21 pages; 6 figures; to appear in Physica

A Hierarchical Approach to Protein Molecular Evolution

Biological diversity has evolved despite the essentially infinite complexity of protein sequence space. We present a hierarchical approach to the efficient searching of this space and quantify the evolutionary potential of our approach with Monte Carlo simulations. These simulations demonstrate that non-homologous juxtaposition of encoded structure is the rate-limiting step in the production of new tertiary protein folds. Non-homologous ``swapping'' of low energy secondary structures increased the binding constant of a simulated protein by $\approx10^7$ relative to base substitution alone. Applications of our approach include the generation of new protein folds and modeling the molecular evolution of disease.Comment: 15 pages. 2 figures. LaTeX styl

Library Design in Combinatorial Chemistry by Monte Carlo Methods

Strategies for searching the space of variables in combinatorial chemistry experiments are presented, and a random energy model of combinatorial chemistry experiments is introduced. The search strategies, derived by analogy with the computer modeling technique of Monte Carlo, effectively search the variable space even in combinatorial chemistry experiments of modest size. Efficient implementations of the library design and redesign strategies are feasible with current experimental capabilities.Comment: 5 pages, 3 figure

Parallel Tempering: Theory, Applications, and New Perspectives

We review the history of the parallel tempering simulation method. From its origins in data analysis, the parallel tempering method has become a standard workhorse of physiochemical simulations. We discuss the theory behind the method and its various generalizations. We mention a selected set of the many applications that have become possible with the introduction of parallel tempering and we suggest several promising avenues for future research.Comment: 21 pages, 4 figure

Experimental Rugged Fitness Landscape in Protein Sequence Space

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region