Whole genome functional analysis identifies novel components required for mitotic spindle integrity in human cells.

Background: The mitotic spindle is a complex mechanical apparatus required for accurate segregation of sister chromosomes during mitosis. We designed a genetic screen using automated microscopy to discover factors essential for mitotic progression. Using a RNA interference library of 49,164 double-stranded RNAs targeting 23,835 human genes, we performed a loss of function screen to look for small interfering RNAs that arrest cells in metaphase.

A novel microarray approach reveals new tissue-specific signatures of known and predicted mammalian microRNAs.

Microarrays to examine the global expression levels of microRNAs (miRNAs) in a systematic in-parallel manner have become important tools to help unravel the functions of miRNAs and to understand their roles in RNA-based regulation and their implications in human diseases. We have established a novel miRNA-specific microarray platform that enables the simultaneous expression analysis of both known and predicted miRNAs obtained from human or mouse origin. Chemically modified 2'-O-(2-methoxyethyl)-(MOE) oligoribonucleotide probes were arrayed onto Evanescent Resonance (ER) microchips by robotic spotting.

Genome-wide functional analysis of human cell-cycle regulators.

Human cells have evolved complex signaling networks to coordinate the cell cycle. A detailed understanding of the global regulation of this fundamental process requires comprehensive identification of the genes and pathways involved in the various stages of cell-cycle progression. To this end, we report a genome-wide analysis of the human cell cycle, cell size, and proliferation by targeting >95% of the protein-coding genes in the human genome using small interfering RNAs (siRNAs).

Design of a genome-wide siRNA library using an artificial neural network.

The largest gene knock-down experiments performed to date have used multiple short interfering/short hairpin (si/sh)RNAs per gene. To overcome this burden for design of a genome-wide siRNA library, we used the Stuttgart Neural Net Simulator to train algorithms on a data set of 2,182 randomly selected siRNAs targeted to 34 mRNA species, assayed through a high-throughput fluorescent reporter gene system. The algorithm, (BIOPREDsi), reliably predicted activity of 249 siRNAs of an independent test set (Pearson coefficient r = 0.

Post-translational modification detection using metastable ions in reflector matrix-assisted laser desorption/ionization-time of flight mass spectrometry.

In addition to protein identification, characterization of post-translational modifications (PTMs) is an essential task in proteomics. PTMs represent the major reason for the variety of protein isoforms and they can influence protein structure and function. Upon matrix-assisted laser desorption/ionization (MALDI) most post-translationally modified peptides form a fraction of labile molecular ions, which lose PTM-specific residues only after acceleration.