Jonathan Miller

Novel MicroRNA Candidates and miRNA-mRNA Pairs in Embryonic Stem (ES) Cells

Background MicroRNAs (miRNAs: a class of short non-coding RNAs) are emerging as important agents of post transcriptional gene regulation and integral components of gene networks. MiRNAs have been strongly linked to stem cells, which have a remarkable dual role in development. They can either continuously replenish themselves (self-renewal), or differentiate into cells that execute a limited number of specific actions (pluripotence). Methodology/Principal Findings In order to identify novel miRNAs from narrow windows of development we carried out an in silico search for micro-conserved elements (MCE) in adult tissue progenitor transcript sequences. A plethora of previously unknown miRNA candidates were revealed including 545 small RNAs that are enriched in embryonic stem (ES) cells over adult cells. Approximately 20% of these novel candidates are down-regulated in ES (Dicer −/−) ES cells that are impaired in miRNA maturation. The ES-enriched miRNA candidates exhibit distinct and opposite expression trends from mmu-mirs (an abundant class in adult tissues) during retinoic acid (RA)-induced ES cell differentiation. Significant perturbation of trends is found in both miRNAs and novel candidates in ES (GCNF −/−) cells, which display loss of repression of pluripotence genes upon differentiation. Conclusion/Significance Combining expression profile information with miRNA target prediction, we identified miRNA-mRNA pairs that correlate with ES cell pluripotence and differentiation. Perturbation of these pairs in the ES (GCNF −/−) mutant suggests a role for miRNAs in the core regulatory networks underlying ES cell self-renewal, pluripotence and differentiation.

MicroRNA target detection and analysis for genes related to breast cancer using MDLcompress

We describe initial results of miRNA sequence analysis with the optimal symbol compression ratio (OSCR) algorithm and recast this grammar inference algorithm as an improved minimum description length (MDL) learning tool: MDLcompress. We apply this tool to explore the relationship between miRNAs, single nucleotide polymorphisms (SNPs), and breast cancer. Our new algorithm outperforms other grammar-based coding methods, such as DNA Sequitur, while retaining a two-part code that highlights biologically significant phrases. The deep recursion of MDLcompress, together with its explicit two-part coding, enables it to identify biologically meaningful sequence without needlessly restrictive priors. The ability to quantify cost in bits for phrases in the MDL model allows prediction of regions where SNPs may have the most impact on biological activity. MDLcompress improves on our previous algorithm in execution time through an innovative data structure, and in specificity of motif detection (compression) through improved heuristics. An MDLcompress analysis of 144 over expressed genes from the breast cancer cell line BT474 has identified novel motifs, including potential microRNA (miRNA) binding sites that are candidates for experimental validation.

Vesicle-like biomechanics governs important aspects of nuclear geometry in fission yeast.

It has long been known that during the closed mitosis of many unicellular eukaryotes, including the fission yeast (Schizosaccharomyces pombe), the nuclear envelope remains intact while the nucleus undergoes a remarkable sequence of shape transformations driven by elongation of an intranuclear mitotic spindle whose ends are capped by spindle pole bodies embedded in the nuclear envelope. However, the mechanical basis of these normal cell cycle transformations, and abnormal nuclear shapes caused by intranuclear elongation of microtubules lacking spindle pole bodies, remain unknown. Although there are models describing the shapes of lipid vesicles deformed by elongation of microtubule bundles, there are no models describing normal or abnormal shape changes in the nucleus. We describe here a novel biophysical model of interphase nuclear geometry in fission yeast that accounts for critical aspects of the mechanics of the fission yeast nucleus, including the biophysical properties of lipid bilayers, forces exerted on the nuclear envelope by elongating microtubules, and access to a lipid reservoir, essential for the large increase in nuclear surface area during the cell cycle. We present experimental confirmation of the novel and non-trivial geometries predicted by our model, which has no free parameters. We also use the model to provide insight into the mechanical basis of previously described defects in nuclear division, including abnormal nuclear shapes and loss of nuclear envelope integrity. The model predicts that (i) despite differences in structure and composition, fission yeast nuclei and vesicles with fluid lipid bilayers have common mechanical properties; (ii) the S. pombe nucleus is not lined with any structure with shear resistance, comparable to the nuclear lamina of higher eukaryotes. We validate the model and its predictions by analyzing wild type cells in which ned1 gene overexpression causes elongation of an intranuclear microtubule bundle that deforms the nucleus of interphase cells.