Dual-mode of insulin action controls GLUT4 vesicle exocytosis.

Insulin stimulates translocation of GLUT4 storage vesicles (GSVs) to the surface of adipocytes, but precisely where insulin acts is controversial. Here we quantify the size, dynamics, and frequency of single vesicle exocytosis in 3T3-L1 adipocytes. We use a new GSV reporter, VAMP2-pHluorin, and bypass insulin signaling by disrupting the GLUT4-retention protein TUG. Remarkably, in unstimulated TUG-depleted cells, the exocytic rate is similar to that in insulin-stimulated control cells. In TUG-depleted cells, insulin triggers a transient, twofold burst of exocytosis. Surprisingly, insulin promotes fusion pore expansion, blocked by acute perturbation of phospholipase D, which reflects both properties intrinsic to the mobilized vesicles and a novel regulatory site at the fusion pore itself. Prolonged stimulation causes cargo to switch from approximately 60 nm GSVs to larger exocytic vesicles characteristic of endosomes. Our results support a model whereby insulin promotes exocytic flux primarily by releasing an intracellular brake, but also by accelerating plasma membrane fusion and switching vesicle traffic between two distinct circuits.

3-D reconstruction of microtubules from multi-angle total internal reflection fluorescence microscopy using Bayesian framework.

Total internal reflection fluorescence (TIRF) microscopy excites a thin evanescent field which theoretically decays exponentially. Each TIRF image is actually the projection of a 3-D volume and hence cannot alone produce an accurate localization of structures in the z-dimension, however, it provides greatly improved axial resolution for biological samples. Multiple angle-TIRF microscopy allows controlled variation of the incident angle of the illuminating laser beam, thus generating a set of images of different penetration depths with the potential to reconstruct the 3-D volume of the sample. With the ultimate goal to quantify important biological parameters of microtubules, we present a method to reconstruct 3-D position and orientation of microtubules based on multi-angle TIRF data, as well as experimental calibration of the actual decay function of the evanescent field at each angle. We validate our method using computer simulations, by creating a phantom simulating the curvilinear characteristics of microtubules and project the artificially constructed volume into a set of TIRF image for different penetration depth. The reconstructed depth information for the phantom data is shown to be accurate and robust to noise. We apply our method to microtubule TIRF images of PtK(2) cells in vivo. By comparing microtubule curvatures of the reconstruction results and several electron microscopy (EM) images of vertically sliced sample of microtubules, we find that the curvature statistics of our reconstruction agree well with the ground truth (EM data). Quantifying the distribution of microtubule curvature reveals an interesting discovery that microtubules can buckle and form local bendings of considerably small radius of curvature which is also visually spotted on the EM images, while microtubule bendings on a larger scale generally have a much larger radius and cannot bear the stress of a large curvature. The presented method has the potential to provide a reliable tool for 3-D reconstruction and tracking of microtubules.

Tiling array data analysis: a multiscale approach using wavelets.

BACKGROUND: Tiling array data is hard to interpret due to noise. The wavelet transformation is a widely used technique in signal processing for elucidating the true signal from noisy data. Consequently, we attempted to denoise representative tiling array datasets for ChIP-chip experiments using wavelets. In doing this, we used specific wavelet basis functions, Coiflets, since their triangular shape closely resembles the expected profiles of true ChIP-chip peaks. RESULTS: In our wavelet-transformed data, we observed that noise tends to be confined to small scales while the useful signal-of-interest spans multiple large scales. We were also able to show that wavelet coefficients due to non-specific cross-hybridization follow a log-normal distribution, and we used this fact in developing a thresholding procedure. In particular, wavelets allow one to set an unambiguous, absolute threshold, which has been hard to define in ChIP-chip experiments. One can set this threshold by requiring a similar confidence level at different length-scales of the transformed signal. We applied our algorithm to a number of representative ChIP-chip data sets, including those of Pol II and histone modifications, which have a diverse distribution of length-scales of biochemical activity, including some broad peaks. CONCLUSIONS: Finally, we benchmarked our method in comparison to other approaches for scoring ChIP-chip data using spike-ins on the ENCODE Nimblegen tiling array. This comparison demonstrated excellent performance, with wavelets getting the best overall score.

Estimation of 3D geometry of microtubules using multi-angle total internal reflection fluorescence microscopy.

With the ultimate goal to quantify important biological parameters of microtubules, we present a method to estimate the 3D positions of microtubules from multi-angle TIRF data based on the calibrated decay profiles for each angle. Total Internal Reflection Fluorescence (TIRF) Microscopy images are actually projections of 3D volumes and hence cannot alone produce an accurate localization of structures in the z-dimension, however, they provide greatly improved axial resolution for biological samples. Multiple angle-TIRF microscopy allows controlled variation of the incident angle of the illuminating laser beam, thus generating a set of images of different penetration depths with the potential to estimate the 3D volume of the sample. Our approach incorporates prior information about intensity and geometric smoothness. We validate our method using computer simulated phantom data and test its robustness to noise. We apply our method to TIRF images of microtubules in PTK2 cells and compare the distribution of the microtubule curvatures with electron microscopy (EM) images.

Robust-linear-model normalization to reduce technical variability in functional protein microarrays.

Protein microarrays are similar to DNA microarrays; both enabling the parallel interrogation of thousands of probes immobilized on a surface. Consequently, they have benefited from technologies previously developed for DNA microarrays. However, assumptions for the analysis of DNA microarrays do not always translate to protein arrays, especially in the case of normalization. Hence, we have developed an experimental and computational framework to assess normalization procedures for protein microarrays. Specifically, we profiled two sera with markedly different autoantibody compositions. To analyze intra- and interarray variability, we compared a set of control proteins across subarrays and the corresponding spots across multiple arrays, respectively. To estimate the degree to which the normalization could help reveal true biological separability, we tested the difference in the signal between the sera relative to the variability within replicates. Next, by mixing the sera in different proportions (titrations), we correlated the reactivity of proteins with serum concentration. Finally, we analyzed the effect of normalization procedures on the list of reactive proteins. We compared global and quantile normalization, techniques that have traditionally been employed for DNA microarrays, with a novel normalization approach based on a robust linear model (RLM) making explicit use of control proteins. We show that RLM normalization is able to reduce both intra- and interarray technical variability while maintaining biological differences. Moreover, in titration experiments, RLM normalization enhances the correlation of protein signals with serum concentration. Conversely, while quantile and global normalization can reduce interarray technical variability, neither is as effective as RLM normalization in maintaining biological differences. Most importantly, both introduce artifacts that distort the signals and affect the correct identification of reactive proteins, impairing their use for biomarker discovery. Hence, we show RLM normalization is better suited to protein arrays than approaches used for DNA microarrays.

Chimeric receptor mRNA transfection as a tool to generate antineoplastic lymphocytes.

mRNA transfection is a useful approach for temporal cell reprogramming with minimal risk of transgene-mediated mutagenesis. We applied this to redirect lymphocyte cytotoxicity toward malignant cells. Using the chimeric immune receptor (CIR) constructs anti-CD19 CIR and 8H9 CIR, we achieved uniform expression of CIRs on virtually the entire population of lymphocytes. We reprogrammed CD3+ CD8+, CD3+ CD4+, and natural killer (NK ) cells toward autologous and allogeneic targets such as B cells, Daudi lymphoma, primary melanoma, breast ductal carcinoma, breast adenocarcinoma, and rhabdomyosarcoma. The reprogramming procedure is fast. Although most of the experiments were performed on lymphocytes obtained after 7-day activation, only 1-day activation of T cells with anti-CD3, anti-CD28 antibodies, and interleukin-2 is sufficient to develop both lymphocyte cytotoxicity and competence for mRNA transfer. The entire procedure, which includes lymphocyte activation and reprogramming, can be completed in 2 days. The efficiency of mRNA-modified human T cells was tested in a murine xenograft model. Human CD3+CD8+ lymphocytes expressing anti-CD19 CIR mRNA inhibited Daudi lymphoma growth in NOD=SCID mice. These results demonstrate that a mixed population of cytotoxic lymphocytes, including T cells together with NK cells, can be quickly and simultaneously reprogrammed by mRNA against autologous malignancies. With relatively minor modifications the described method of lymphocyte reprogramming can be scaled up for cancer therapy.

A genomic analysis of RNA polymerase II modification and chromatin architecture related to 3' end RNA polyadenylation.

Genomic analyses have been applied extensively to analyze the process of transcription initiation in mammalian cells, but less to transcript 3' end formation and transcription termination. We used a novel approach to prepare 3' end fragments from polyadenylated RNA, and mapped the position of the poly(A) addition site using oligonucleotide arrays tiling 1% of the human genome. This approach revealed more 3' ends than had been annotated. The distribution of these ends relative to RNA polymerase II (PolII) and di- and trimethylated lysine 4 and lysine 36 of histone H3 was compared. A substantial fraction of unannotated 3' ends of RNA are intronic and antisense to the embedding gene. Poly(A) ends of annotated messages lie on average 2 kb upstream of the end of PolII binding (termination). Near the termination sites, and in some internal sites, unphosphorylated and C-terminal domain (CTD) serine 2 phosphorylated PolII (POLR2A) accumulate, suggesting pausing of the polymerase and perhaps dephosphorylation prior to release. Lysine 36 trimethylation occurs across transcribed genes, sometimes alternating with stretches of DNA in which lysine 36 dimethylation is more prominent. Lysine 36 methylation decreases at or near the site of polyadenylation, sometimes disappearing before disappearance of phosphorylated RNA PolII or release of PolII from DNA. Our results suggest that transcription termination loss of histone 3 lysine 36 methylation and later release of RNA polymerase. The latter is often associated with polymerase pausing. Overall, our study reveals extensive sites of poly(A) addition and provides insights into the events that occur during 3' end formation.

Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets.

The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols, and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated.