Large-scale analysis of Drosophila core promoter function using synthetic promoters.

The core promoter plays a central role in setting metazoan gene expression levels, but how exactly it "computes" expression remains poorly understood. To dissect its function, we carried out a comprehensive structure-function analysis in Drosophila. First, we performed a genome-wide bioinformatic analysis, providing an improved picture of the sequence motifs architecture. We then measured synthetic promoters' activities of ~3,000 mutational variants with and without an external stimulus (hormonal activation), at large scale and with high accuracy using robotics and a dual luciferase reporter assay. We observed a strong impact on activity of the different types of mutations, including knockout of individual sequence motifs and motif combinations, variations of motif strength, nucleosome positioning, and flanking sequences. A linear combination of the individual motif features largely accounts for the combinatorial effects on core promoter activity. These findings shed new light on the quantitative assessment of gene expression in metazoans.

Sensitive Automated Measurement of Histone-DNA Affinities in Nucleosomes.

The DNA of eukaryotes is wrapped around histone octamers to form nucleosomes. Although it is well established that the DNA sequence significantly influences nucleosome formation, its precise contribution has remained controversial, partially owing to the lack of quantitative affinity data. Here, we present a method to measure DNA-histone binding free energies at medium throughput and with high sensitivity. Competitive nucleosome formation is achieved through automation, and a modified epifluorescence microscope is used to rapidly and accurately measure the fractions of bound/unbound DNA based on fluorescence anisotropy. The procedure allows us to obtain full titration curves with high reproducibility. We applied this technique to measure the histone-DNA affinities for 47 DNA sequences and analyzed how the affinities correlate with relevant DNA sequence features. We found that the GC content has a significant impact on nucleosome-forming preferences, but 10 bp dinucleotide periodicities and the presence of poly(dA:dT) stretches do not.

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy.

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing approaches suffer from significant limitations, we have developed a new method for determining TF-DNA binding affinities with high sensitivity on a large scale. The assay relies on the established fluorescence anisotropy (FA) principle but introduces important technical improvements. First, we measure a full FA competitive titration curve in a single well by incorporating TF and a fluorescently labeled reference DNA in a porous agarose gel matrix. Unlabeled DNA oligomer is loaded on the top as a competitor and, through diffusion, forms a spatio-temporal gradient. The resulting FA gradient is then read out using a customized epifluorescence microscope setup. This improved setup greatly increases the sensitivity of FA signal detection, allowing both weak and strong binding to be reliably quantified, even for molecules of similar molecular weights. In this fashion, we can measure one titration curve per well of a multi-well plate, and through a fitting procedure, we can extract both the absolute dissociation constant (KD) and active protein concentration. By testing all single-point mutation variants of a given consensus binding sequence, we can survey the entire binding specificity landscape of a TF, typically on a single plate. The resulting position weight matrices (PWMs) outperform those derived from other methods in predicting in vivo TF occupancy. Here, we present a detailed guide for implementing HiP-FA on a conventional automated fluorescent microscope and the data analysis pipeline.

Author Correction: True equilibrium measurement of transcription factor-DNA binding affinities using automated polarization microscopy.

In the original version of this Article, equation three contained a sign error whereby the term RT was added when it should have been subtracted. This has now been corrected in the PDF and HTML versions of the Article.

True equilibrium measurement of transcription factor-DNA binding affinities using automated polarization microscopy.

The complex patterns of gene expression in metazoans are controlled by selective binding of transcription factors (TFs) to regulatory DNA. To improve the quantitative understanding of this process, we have developed a novel method that uses fluorescence anisotropy measurements in a controlled delivery system to determine TF-DNA binding energies in solution with high sensitivity and throughput. Owing to its large dynamic range, the method, named high performance fluorescence anisotropy (HiP-FA), allows for reliable quantification of both weak and strong binding; binding specificities are calculated on the basis of equilibrium constant measurements for mutational DNA variants. We determine the binding preference landscapes for 26 TFs and measure high absolute affinities, but mostly lower binding specificities than reported by other methods. The revised binding preferences give rise to improved predictions of in vivo TF occupancy and enhancer expression. Our approach provides a powerful new tool for the systems-biological analysis of gene regulation.

Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation.

In-depth MS-based proteomics has necessitated fractionation of either proteins or peptides or both, often requiring considerable analysis time. Here we employ long liquid chromatography runs with high resolution coupled to an instrument with fast sequencing speed to investigate how much of the proteome is directly accessible to liquid chromatography-tandem MS characterization without any prefractionation steps. Triplicate single-run analyses identified 2990 yeast proteins, 68% of the total measured in a comprehensive yeast proteome. Among them, we covered the enzymes of the glycolysis and gluconeogenesis pathway targeted in a recent multiple reaction monitoring study. In a mammalian cell line, we identified 5376 proteins in a triplicate run, including representatives of 173 out of 200 KEGG metabolic and signaling pathways. Remarkably, the majority of proteins could be detected in the samples at sub-femtomole amounts and many in the low attomole range, in agreement with absolute abundance estimation done in previous works (Picotti et al. Cell, 138, 795-806, 2009). Our results imply an unexpectedly large dynamic range of the MS signal and sensitivity for liquid chromatography-tandem MS alone. With further development, single-run analysis has the potential to radically simplify many proteomic studies while maintaining a systems-wide view of the proteome.

Quantitative proteomics combined with BAC TransgeneOmics reveals in vivo protein interactions.

Protein interactions are involved in all cellular processes. Their efficient and reliable characterization is therefore essential for understanding biological mechanisms. In this study, we show that combining bacterial artificial chromosome (BAC) TransgeneOmics with quantitative interaction proteomics, which we call quantitative BAC-green fluorescent protein interactomics (QUBIC), allows specific and highly sensitive detection of interactions using rapid, generic, and quantitative procedures with minimal material. We applied this approach to identify known and novel components of well-studied complexes such as the anaphase-promoting complex. Furthermore, we demonstrate second generation interaction proteomics by incorporating directed mutational transgene modification and drug perturbation into QUBIC. These methods identified domain/isoform-specific interactors of pericentrin- and phosphorylation-specific interactors of TACC3, which are necessary for its recruitment to mitotic spindles. The scalability, simplicity, cost effectiveness, and sensitivity of this method provide a basis for its general use in small-scale experiments and in mapping the human protein interactome.