In situ characterization of the mTORC1 during adipogenesis of human adult stem cells on chip.

Mammalian target of rapamycin (mTOR) is a central kinase integrating nutrient, energy, and metabolite signals. The kinase forms two distinct complexes: mTORC1 and mTORC2. mTORC1 plays an essential but undefined regulatory function for regeneration of adipose tissue. Analysis of mTOR in general is hampered by the complexity of regulatory mechanisms, including protein interactions and/or phosphorylation, in an ever-changing cellular microenvironment. Here, we developed a microfluidic large-scale integration chip platform for culturing and differentiating human adipose-derived stem cells (hASCs) in 128 separated microchambers under standardized nutrient conditions over 3 wk. The progression of the stem cell differentiation was measured by determining the lipid accumulation rates in hASC cultures. For in situ protein analytics, we developed a multiplex in situ proximity ligation assay (mPLA) that can detect mTOR in its two complexes selectively in single cells and implemented it on the same chip. With this combined technology, it was possible to reveal that the mTORC1 is regulated in its abundance, phosphorylation state, and localization in coordination with lysosomes during adipogenesis. High-content image analysis and parameterization of the in situ PLA signals in over 1 million cells cultured on four individual chips showed that mTORC1 and lysosomes are temporally and spatially coordinated but not in its composition during adipogenesis.

Structural Characterization of Serum N-Glycans by Methylamidation, Fluorescent Labeling, and Analysis by Microchip Electrophoresis.

To characterize the structures of N-glycans derived from human serum, we report a strategy that combines microchip electrophoresis, standard addition, enzymatic digestion, and matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). We compared (i) electrophoretic mobilities of known N-glycans from well-characterized (standard) glycoproteins through standard addition, (ii) the electrophoretic mobilities of N-glycans with their molecular weights determined by MALDI-MS, and (iii) electrophoretic profiles of N-glycans enzymatically treated with fucosidase. The key step to identify the sialylated N-glycans was to quantitatively neutralize the negative charge on both α2,3- and α2,6-linked sialic acids by covalent derivatization with methylamine. Both neutralized and nonsialylated N-glycans from these samples were then reacted with 8-aminopyrene-1,3,6-trisulfonic acid (APTS) to provide a fluorescent label and a triple-negative charge, separated by microchip electrophoresis, and detected by laser-induced fluorescence. The methylamidation step leads to a 24% increase in the peak capacity of the separation and direct correlation of electrophoretic and MALDI-MS results. In total, 37 unique N-glycan structures were assigned to 52 different peaks recorded in the electropherograms of the serum samples. This strategy ensures the needed separation efficiency and detectability, easily resolves linkage and positional glycan isomers, and is highly reproducible.

Microchip electrophoresis at elevated temperatures and high separation field strengths.

We report free-solution microchip electrophoresis performed at elevated temperatures and high separation field strengths. We used microfluidic devices with 11 cm long separation channels to conduct separations at temperatures between 22 (ambient) and 45°C and field strengths from 100 to 1000 V/cm. To evaluate separation performance, N-glycans were used as a model system and labeled with 8-aminopyrene-1,3,6-trisulfonic acid to impart charge for electrophoresis and render them fluorescent. Typically, increased diffusivity at higher temperatures leads to increased axial dispersion and poor separation performance; however, we demonstrate that sufficiently high separation field strengths offset the impact of increased diffusivity in order to maintain separation efficiency. Efficiencies for these free-solution separations are the same at temperatures of 25, 35, and 45°C with separation field strengths ≥ 500 V/cm.

Comparative profiling of N-glycans isolated from serum samples of ovarian cancer patients and analyzed by microchip electrophoresis.

Ovarian cancer is the fifth leading cause of cancer-related mortalities for women in the United States and the most lethal gynecological cancer. Aberrant glycosylation has been linked to several human diseases, including ovarian cancer, and accurate measurement of changes in glycosylation may provide relevant diagnostic and prognostic information. In this work, we used microchip electrophoresis coupled with laser-induced fluorescence detection to determine quantitative differences among the N-glycan profiles of control individuals and late-stage recurrent ovarian cancer patients prior to and after an experimental drug treatment that combined docetaxel and imatinib mesylate. N-Glycans were enzymatically released from 5-µL aliquots of serum samples, labeled with the anionic fluorescent tag, 8-aminopyrene-1,3,6-trisulfonic acid, and analyzed on microfluidic devices. A 22-cm long separation channel, operated at 1250 V/cm, generated analysis times less than 100 s, separation efficiencies up to 8 × 10(5) plates (3.6 × 10(6) plates/m), and migration time reproducibilities better than 0.1% relative standard deviation after peak alignment. Principal component analysis (PCA) and analysis of variance (ANOVA) tests showed significant differences between the control and both pre- and post-treatment cancer samples and subtle differences between the pre- and post-treatment cancer samples. Area-under-the-curve (AUC) values from receiver operating characteristics (ROC) tests were used to evaluate the diagnostic merit of N-glycan peaks, and specific N-glycan peaks used in combination provided AUCs > 0.90 (highly accurate test) when the control and pretreatment cancer samples and control and post-treatment samples were compared.

Improved mass defect model for theoretical tryptic peptides.

Improvements in the mass accuracy and resolution of mass spectrometers have greatly aided mass spectrometry-based proteomics in profiling complex biological mixtures. With the use of innovative bioinformatics approaches, high mass accuracy and resolution information can be used for filtering chemical noise in mass spectral data. Using our recent algorithmic developments, we have generated the mass distributions of all theoretical tryptic peptides composed of 20 natural amino acids and with masses limited to 3.5 kDa. Peptide masses are distributed discretely, with well-defined peak clusters separated by empty or sparsely populated trough regions. Accurate models for peak centers and widths can be used to filter peptide signals from chemical noise. We modeled mass defects, the difference between monoisotopic and nominal masses, and peak centers and widths in the peptide mass distributions. We found that peak widths encompassing 95% of all peptide sequences are substantially smaller than previously thought. The result has implications for filtering out larger stretches of the mass axis. Mass defects of peptides exhibit an oscillatory behavior which is damped at high mass values. The periodicity of the oscillations is about 14 Da which is the most common difference between the masses of the 20 natural amino acids. To determine the effects of amino acid modifications on our findings, we examined the mass distributions of peptides composed of the 20 natural amino acids, oxidized Met, and phosphorylated Ser, Thr, and Tyr. We found that extension of the amino acid set by modifications increases the 95% peak width. Mass defects decrease, reflecting the fact that the average mass defect of natural amino acids is larger than that of oxidized Met. We propose that a new model for mass defects and peak widths of peptides may improve peptide identifications by filtering chemical noise in mass spectral data.

N-glycan profiling by microchip electrophoresis to differentiate disease states related to esophageal adenocarcinoma.

We report analysis of N-glycans derived from disease-free individuals and patients with Barrett's esophagus, high-grade dysplasia, and esophageal adenocarcinoma by microchip electrophoresis with laser-induced fluorescence detection. Serum samples in 10 µL aliquots are enzymatically treated to cleave the N-glycans that are subsequently reacted with 8-aminopyrene-1,3,6-trisulfonic acid to add charge and a fluorescent label. Separations at 1250 V/cm and over 22 cm yielded efficiencies up to 700,000 plates for the N-glycans and analysis times under 100 s. Principal component analysis (PCA) and analysis of variance (ANOVA) tests of the peak areas and migration times are used to evaluate N-glycan profiles from native and desialylated samples and determine differences among the four sample groups. With microchip electrophoresis, we are able to distinguish the three patient groups from each other and from disease-free individuals.

Examining troughs in the mass distribution of all theoretically possible tryptic peptides.

This work describes the mass distribution of all theoretically possibly tryptic peptides made of 20 amino acids, up to the mass of 3 kDa, with resolution of 0.001 Da. We characterize regions between the peaks of the distribution, including gaps (forbidden zones) and low-populated areas (quiet zones). We show how the gaps shrink over the mass range and when they completely disappear. We demonstrate that peptide compositions in quiet zones are less diverse than those in the peaks of the distribution and that by eliminating certain types of unrealistic compositions the gaps in the distribution may be increased. The mass distribution is generated using a parallel implementation of a recursive procedure that enumerates all amino acid compositions. It allows us to enumerate all compositions of tryptic peptides below 3 kDa in 48 min using a computer cluster with 12 Intel Xeon X5650 CPUs (72 cores). The results of this work can be used to facilitate protein identification and mass defect labeling in mass spectrometry-based proteomics experiments.

Nanofluidic devices with two pores in series for resistive-pulse sensing of single virus capsids.

We report fabrication and characterization of nanochannel devices with two nanopores in series for resistive-pulse sensing of hepatitis B virus (HBV) capsids. The nanochannel and two pores are patterned by electron beam lithography between two microchannels and etched by reactive ion etching. The two nanopores are 50-nm wide, 50-nm deep, and 40-nm long and are spaced 2.0-µm apart. The nanochannel that brackets the two pores is 20× wider (1 µm) to reduce the electrical resistance adjacent to the two pores and to ensure the current returns to its baseline value between resistive-pulse events. Average pulse amplitudes differ by <2% between the two pores and demonstrate that the fabrication technique is able to produce pores with nearly identical geometries. Because the two nanopores in series sense single particles at two discrete locations, particle properties, e.g., electrophoretic mobility, are determined from the pore-to-pore transit time.

Microchip electrophoresis of N-glycans on serpentine separation channels with asymmetrically tapered turns.

We designed and fabricated microfluidic devices with serpentine separation channels and asymmetrically tapered turns, thus allowing high efficiency separations and minimizing band broadening associated with the "racetrack" effect. We evaluated the performance of these devices by measuring the variation in separation efficiency with separation length, electric field strength, taper ratio of the turns, and number of turns. N-Glycans derived from ribonuclease B and labeled with 8-aminopyrene-1,3,6-trisulfonic acid were electrophoretically separated on serpentine channels with separation lengths of 11, 18, 22, and 36 cm at electric field strengths from 750 to 1750 V/cm. Separations on the 36-cm channel produced plate numbers up to 940,000 with an analysis time under 3.1 min, whereas separations on the 22-cm channel had a shorter analysis time (less than 1.25 min), still with respectable efficiencies (up to 600,000 plates). Turn-induced dispersion was minimized with taper ratios 2 and 3, whereas having two or four 180° turns along with the separation length did not impact the overall efficiency. The developed device was used to analyze native and desialylated N-glycans derived from the blood serum of an ovarian cancer patient and a disease-free individual. Separation efficiencies similar to that achieved with the model glycans from ribonuclease B were attained for these biological samples.

Non-Markovian noise mediated through anomalous diffusion within ion channels.

It is evident from a wide range of experimental findings that ion channel gating is inherently stochastic. The issue of "memory effects" (diffusional retardation due to local changes in water viscosity) in ionic flow has been recently addressed using Brownian dynamics simulations. The results presented indicate such memory effects are negligible, unless the diffusional barrier is much higher than that of free solute. In this paper using differential stochastic methods we conclude that the Markovian property of exponential dwell times gives rise to a high barrier, resulting in diffusional memory effects that cannot be ignored in determining ionic flow through channels. We have addressed this question using a generalized Langevin equation that contains a combination of Markovian and non-Markovian processes with different time scales. This approach afforded the development of an algorithm that describes an oscillatory ionic diffusional sequence. The resulting oscillatory function behavior, with exponential decay, was obtained at the weak non-Markovian limit with two distinct time scales corresponding to the processes of ionic diffusion and drift. This will be analyzed further in future studies using molecular dynamics simulations. We propose that the rise of time scales and memory effects is related to differences of shear viscosity in the cytoplasm and extracellular matrix.

Generalized Linear and Mixed Models for Label-Free Shotgun Proteomics.

Label-free shotgun proteomics holds great promise, and has already had some great successes in pinpointing which proteins are up or down regulated in certain disease states. However, there are still some pressing issues concerning the statistical analysis of label-free shotgun proteomics, and this field has not enjoyed as much dedication of statistical research towards it as microarray research has. Here we reapply previously used statistical methods, the QSpec and quasi-Poisson, as well as apply the negative binomial distribution to both a control data set and a data set with known differential expression to determine the successes and failure of each of the three methods.

Probabilistic polynomial dynamical systems for reverse engineering of gene regulatory networks.

Elucidating the structure and/or dynamics of gene regulatory networks from experimental data is a major goal of systems biology. Stochastic models have the potential to absorb noise, account for un-certainty, and help avoid data overfitting. Within the frame work of probabilistic polynomial dynamical systems, we present an algorithm for the reverse engineering of any gene regulatory network as a discrete, probabilistic polynomial dynamical system. The resulting stochastic model is assembled from all minimal models in the model space and the probability assignment is based on partitioning the model space according to the likeliness with which a minimal model explains the observed data. We used this method to identify stochastic models for two published synthetic network models. In both cases, the generated model retains the key features of the original model and compares favorably to the resulting models from other algorithms.