An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples.

BACKGROUND: Clinical bronchoalveolar lavage fluid (BALF) samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, mass spectrometry (MS)-based proteomic analysis of BALF is challenged by the dynamic range of protein abundance, and potential for interfering contaminants. A robust, MS-based proteomics compatible sample preparation workflow for BALF samples, including those of small and large volume, would be useful for many researchers. RESULTS: We have developed a workflow that combines high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, that is compatible with either qualitative or quantitative MS-based proteomic analysis. The workflow includes a value-added collection of endogenous peptides for peptidomic analysis of BALF samples, if desired, as well as amenability to offline semi-preparative or microscale fractionation of complex peptide mixtures prior to LC-MS/MS analysis, for increased depth of analysis. We demonstrate the effectiveness of this workflow on BALF samples collected from COPD patients, including for smaller sample volumes of 1-5 mL that are commonly available from the clinic. We also demonstrate the repeatability of the workflow as an indicator of its utility for quantitative proteomic studies. CONCLUSIONS: Overall, our described workflow consistently provided high quality proteins and tryptic peptides for MS analysis. It should enable researchers to apply MS-based proteomics to a wide-variety of studies focused on BALF clinical specimens.

Long noncoding RNA Hoxb3os is dysregulated in autosomal dominant polycystic kidney disease and regulates mTOR signaling.

Autosomal dominant polycystic kidney disease (ADPKD) is a debilitating disease that is characterized by the accumulation of numerous fluid-filled cysts in the kidney. ADPKD is primarily caused by mutations in two genes, PKD1 and PKD2 Long noncoding RNAs (lncRNA), defined by a length >200 nucleotides and absence of a long ORF, have recently emerged as epigenetic regulators of development and disease; however, their involvement in PKD has not been explored previously. Here, we performed deep RNA-Seq to identify lncRNAs that are dysregulated in two orthologous mouse models of ADPKD (kidney-specific Pkd1 and Pkd2 mutant mice). We identified a kidney-specific, evolutionarily conserved lncRNA called Hoxb3os that was down-regulated in cystic kidneys from Pkd1 and Pkd2 mutant mice. The human ortholog HOXB3-AS1 was down-regulated in cystic kidneys from ADPKD patients. Hoxb3os was highly expressed in renal tubules in adult WT mice, whereas its expression was lost in the cyst epithelium of mutant mice. To investigate the function of Hoxb3os, we utilized CRISPR/Cas9 to knock out its expression in mIMCD3 cells. Deletion of Hoxb3os resulted in increased phosphorylation of mTOR and its downstream targets, including p70 S6 kinase, ribosomal protein S6, and the translation repressor 4E-BP1. Consistent with activation of mTORC1 signaling, Hoxb3os mutant cells displayed increased mitochondrial respiration. The Hoxb3os mutant phenotype was partially rescued upon re-expression of Hoxb3os in knockout cells. These findings identify Hoxb3os as a novel lncRNA that is down-regulated in ADPKD and regulates mTOR signaling and mitochondrial respiration.

Parameter extraction from fabricated silicon photonic devices.

Three sets of devices were simulated, designed, and laid out for fabrication in the EuroPractice shuttle program and then measured in-house after fabrication. A combination of analytical and numerical modeling is used to extract the dispersion curves that define the effective index of refraction as a function of wavelength for three different classes of silicon photonic devices, namely, micro-ring resonators, racetrack resonators, and directional couplers. The results of this phenomenological study are made plausible by the linearity of the extracted dispersion curves with wavelength over the wavelength regime of interest (S and C bands) and the use of the determined effective indices to reconstruct the measured transmission as a function of wavelength curves in close agreement with experiment. The extracted effective indices can be used to place limits on the actual fabricated values of waveguide widths, thicknesses, radii of curvature, and coupling gaps.

Process variation in silicon photonic devices.

An array of passive silicon-on-insulator optical devices is laid out in repeating patterns on four foundry-fabricated wafers. The physical and optical characterization of these microrings, racetrack resonators, and directional couplers are found to exhibit significant variation in optical response. A device-heating experiment carried out on a number of different devices demonstrates that thermal effects are independent of the device's location on the wafer. An analysis of the variation of the optical responses of the room-temperature devices is used to determine the process variation. We find that if we form successive arrays of the values of a quantity of interest (the peak wavelength of a transfer function) at a single device at some point on the wafer, and then increase the size of the array by including the values of the devices at ever greater distances from the original, then the variance of the values of the successive arrays increases linearly with the linear extent of the sample. That is, the process variation exhibits "random walk" pattern with spatial extent. We express the process variation in units of variance per length and find that our measured values agree with others in the literature; that is, the process variation is approximately 1 nm2/cm.

Network Analysis to Identify Multi-Omic Correlations in the Lower Airways of Children With Cystic Fibrosis.

The leading cause of morbidity and mortality in cystic fibrosis (CF) is progressive lung disease secondary to chronic airway infection and inflammation; however, what drives CF airway infection and inflammation is not well understood. By providing a physiological snapshot of the airway, metabolomics can provide insight into these processes. Linking metabolomic data with microbiome data and phenotypic measures can reveal complex relationships between metabolites, lower airway bacterial communities, and disease outcomes. In this study, we characterize the airway metabolome in bronchoalveolar lavage fluid (BALF) samples from persons with CF (PWCF) and disease control (DC) subjects and use multi-omic network analysis to identify correlations with the airway microbiome. The Biocrates targeted liquid chromatography mass spectrometry (LC-MS) platform was used to measure 409 metabolomic features in BALF obtained during clinically indicated bronchoscopy. Total bacterial load (TBL) was measured using quantitative polymerase chain reaction (qPCR). The Qiagen EZ1 Advanced automated extraction platform was used to extract DNA, and bacterial profiling was performed using 16S sequencing. Differences in metabolomic features across disease groups were assessed univariately using Wilcoxon rank sum tests, and Random forest (RF) was used to identify features that discriminated across the groups. Features were compared to TBL and markers of inflammation, including white blood cell count (WBC) and percent neutrophils. Sparse supervised canonical correlation network analysis (SsCCNet) was used to assess multi-omic correlations. The CF metabolome was characterized by increased amino acids and decreased acylcarnitines. Amino acids and acylcarnitines were also among the features most strongly correlated with inflammation and bacterial burden. RF identified strong metabolomic predictors of CF status, including L-methionine-S-oxide. SsCCNet identified correlations between the metabolome and the microbiome, including correlations between a traditional CF pathogen, Staphylococcus, a group of nontraditional taxa, including Prevotella, and a subnetwork of specific metabolomic markers. In conclusion, our work identified metabolomic characteristics unique to the CF airway and uncovered multi-omic correlations that merit additional study.

Early diagnosis of oral cavity cancers.

Dentists, primary care physicians, and otolaryngologists should continue to perform complete oral cavity examinations and should be aware of high-risk populations for oral cavity carcinomas. Oral cavity carcinoma is the sixth most common cancer and is often detected in later stages. By using the modalities of physical examination, brush biopsies, vital staining, and spectral analysis, it is hoped that more cancers will be detected at an early stage, decreasing the morbidity and mortality of oral cavity tumors.

Slow light structures in dye-doped polymer waveguides.

We present a simple and consistent technique for fabricating slow light structures in dye-doped polymer waveguides using the process of irreversible photobleaching. The slow light structures are moiré gratings. The gratings are holographically written into channel waveguides photobleached in side-chained PMMA/DR1 films. The films are annealed during the photobleaching process in order to remove stresses in the films generated during the photobleaching process. These stresses have been observed to cause distortion and cracking of the film surface. The slowing factor for the moiré gratings is calculated from the reflectance spectrum of the waveguides using the Hilbert transform. Moiré gratings with slowing factors between 1.6 and 2.6 are demonstrated.

Wavelength dependence of irreversible photobleaching of dye-doped polymer waveguide materials.

We report the irreversible bleaching characteristics of 4-(dicyanomethylene)-2-methyl-6-(p-dimethyl aminostyryl)-4H-pyran (DCM) doped into perfluorocyclobutene (PFCB) and a new material known as DH-6 doped into amorphous polycarbonate (APC) by a monochromatic bleaching source. The wavelength dependent rate constants for the irreversible bleaching process are found, and the experimental bleaching characteristics are compared to the theoretical bleaching characteristics determined from a kinetic model of the bleaching process.