Reproducible mass spectrometry data processing and compound annotation in MZmine 3.

Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.

Synthesis of silicon carbide in a matrix of graphite-like carbon prepared via carbonization of rigid-rod polyimide Langmuir-Blodgett films on silicon substrate.

Silicon carbide (SiC) is a wide-band gap semiconductor that exceeds other semiconducting materials (except diamond) in electrical, mechanical, chemical, and radiation stability. In this paper, we report a novel approach to fabrication of SiC nano films on a Si substrate, which is based on the endotaxial growth of a SiC crystalline phase in a graphite-like carbon (GLC) matrix. GLC films were formed by carbonization of rigid rod polyimide (PI) Langmuir-Blodgett (LB) films on a Si substrate at 1000 °C in vacuum. After rapid thermal annealing of GLC films at 1100 °C and 1200 °C, new types of heterostructures SiC(10 nm)/GLC(20 nm)/Si(111) and SiC(20 nm)/GLC(15 nm)/SiC(10 nm)/Si(111) were obtained. The SiC top layer was formed due to the Si-containing gas phase present above the surface of GLC film. An advantage of the proposed method of endotaxy is that the SiC crystalline phase is formed within the volume of the GLC film of a thickness predetermined by using PI LB films with different numbers of monolayers for carbonization. This approach allows growing SiC layers close to the 2D state, which is promising for optoelectronics, photovoltaics, spintronics.

NeuroWRAP: integrating, validating, and sharing neurodata analysis workflows.

Multiphoton calcium imaging is one of the most powerful tools in modern neuroscience. However, multiphoton data require significant pre-processing of images and post-processing of extracted signals. As a result, many algorithms and pipelines have been developed for the analysis of multiphoton data, particularly two-photon imaging data. Most current studies use one of several algorithms and pipelines that are published and publicly available, and add customized upstream and downstream analysis elements to fit the needs of individual researchers. The vast differences in algorithm choices, parameter settings, pipeline composition, and data sources combine to make collaboration difficult, and raise questions about the reproducibility and robustness of experimental results. We present our solution, called NeuroWRAP (www.neurowrap.org), which is a tool that wraps multiple published algorithms together, and enables integration of custom algorithms. It enables development of collaborative, shareable custom workflows and reproducible data analysis for multiphoton calcium imaging data enabling easy collaboration between researchers. NeuroWRAP implements an approach to evaluate the sensitivity and robustness of the configured pipelines. When this sensitivity analysis is applied to a crucial step of image analysis, cell segmentation, we find a substantial difference between two popular workflows, CaImAn and Suite2p. NeuroWRAP harnesses this difference by introducing consensus analysis, utilizing two workflows in conjunction to significantly increase the trustworthiness and robustness of cell segmentation results.

Memory-Efficient Searching of Gas-Chromatography Mass Spectra Accelerated by Prescreening.

The number of metabolomics studies and spectral libraries for compound annotation (i.e., assigning possible compound identities to a fragmentation spectrum) has been growing steadily in recent years. Accompanying this growth is the number of mass spectra available for searching through those libraries. As the size of spectral libraries grows, accurate and fast compound annotation becomes more challenging. We herein report a prescreening algorithm that was developed to address the speed of spectral search under the constraint of low memory requirements. This prescreening has been incorporated into the Automated Data Analysis Pipeline Spectral Knowledgebase (ADAP-KDB) and can be applied to compound annotation by searching other spectral libraries as well. Performance of the prescreening algorithm was evaluated for different sets of parameters and compared to the original ADAP-KDB spectral search and the MSSearch software. The comparison has demonstrated that the new algorithm is about four-times faster than the original when searching for low-resolution mass spectra, and about as fast as the original when searching for high-resolution mass spectra. However, the new algorithm is still slower than MSSearch due to the relational database design of the former. The new search workflow can be tried out at the ADAP-KDB web portal.

ADAP-KDB: A Spectral Knowledgebase for Tracking and Prioritizing Unknown GC-MS Spectra in the NIH's Metabolomics Data Repository.

We report the development of a spectral knowledgebase named ADAP-KDB for tracking and prioritizing unknown gas chromatography-mass spectrometry (GC-MS) spectra in the NIH's Metabolomics Data Repository-a national and international repository for metabolomics data. ADAP-KDB consists of two parts. One part is a computational workflow that preprocesses raw mass spectrometry data and derives consensus mass spectra. The other part is a web portal for users to browse the consensus spectra and match query spectra against them. For each consensus spectrum, the Gini-Simpson diversity index and the p-value from χ2 goodness-of-fit test are calculated to measure its statistical significance, which enables prioritization of unknown mass spectra for subsequent costly compound identification.

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data.

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

Metabolomics Data Preprocessing Using ADAP and MZmine 2.

The informatics pipeline for making sense of untargeted LC-MS or GC-MS data starts with preprocessing the raw data. Results from data preprocessing undergo statistical analysis and subsequently mapped to metabolic pathways for placing untargeted metabolomics data in the biological context. ADAP is a suite of computational algorithms that has been developed specifically for preprocessing LC-MS and GC-MS data. It consists of two separate computational workflows that extract compound-relevant information from raw LC-MS and GC-MS data, respectively. Computational steps include construction of extracted ion chromatograms, detection of chromatographic peaks, spectral deconvolution, and alignment. The two workflows have been incorporated into the cross-platform and graphical MZmine 2 framework and ADAP-specific graphical user interfaces have been developed for using ADAP with ease. This chapter summarizes the algorithmic principles underlying key steps in the two workflows and illustrates how to apply ADAP to preprocess LC-MS and GC-MS data.

Submucosal Tunneling Muscle Biopsy for Esophageal Motility Disorders: A Case Report.

Submucosal tunneling endoscopic technique can be useful in obtaining esophageal muscle specimens in patients with esophageal motility disorders. Here, we describe the case of a patient with systemic sclerosis. Histological verification of the esophageal involvement in the pathological process was required for the treatment. There were no intra- and post- operational complications.

ADAP-GC 4.0: Application of Clustering-Assisted Multivariate Curve Resolution to Spectral Deconvolution of Gas Chromatography-Mass Spectrometry Metabolomics Data.

We report a multivariate curve resolution (MCR)-based spectral deconvolution workflow for untargeted gas chromatography-mass spectrometry metabolomics. As an essential step in preprocessing such data, spectral deconvolution computationally separates ions that are in the same mass spectrum but belong to coeluting compounds that are not resolved completely by chromatography. As a result of this computational separation, spectral deconvolution produces pure fragmentation mass spectra. Traditionally, spectral deconvolution has been achieved by using a model peak approach. We describe the fundamental differences between the model peak-based and the MCR-based spectral deconvolution and report ADAP-GC 4.0 that employs the latter approach while overcoming the associated computational complexity. ADAP-GC 4.0 has been evaluated using GC-TOF data sets from a 27-standards mixture at different dilutions and urine with the mixture spiked in, and GC Orbitrap data sets from mixtures of different standards. It produced the average matching scores 960, 959, and 926 respectively. Moreover, its performance has been compared against MS-DIAL, eRah, and ADAP-GC 3.2, and ADAP-GC 4.0 demonstrated a higher number of matched compounds and up to 6% increase of the average matching score.

Global analysis and Decay Associated Images (DAI) derived from Fluorescence Lifetime Imaging Microscopy (FLIM).

The extraction of fluorophore lifetimes in a biological sample provides useful information about the probe environment that is not readily available from fluorescence intensity alone. Cell membrane potential, pH, concentration of oxygen ([O2]), calcium ([Ca2+]), NADH and other ions and metabolites are all regularly measured by lifetime-based techniques. These measurements provide invaluable knowledge about cell homeostasis, metabolism and communication with the cell environment. Fluorescence lifetime imaging microscopy (FLIM) produces spatial maps with time-correlated single-photon counting (TCSPC) histograms collected and analyzed at each pixel, but traditional TCSPC analysis is often hampered by the low number of photons that can reasonably be collected while maintaining high spatial resolution. More important, traditional analysis fails to employ the spatial linkages within the image. Here, we present a different approach, where we work under the assumption that mixtures of a global set of lifetimes (often only 2 or 3) can describe the entire image. We determine these lifetime components by globally fitting precise decays aggregated over large spatial regions of interest, and then we perform a pixel-by-pixel calculation of decay amplitudes (via simple linear algebra applied to coarser time-windows). This yields accurate amplitude images (Decay Associate Images, DAI) that contain stoichiometric information about the underlying mixtures while retaining single pixel resolution. We collected FLIM data of dye mixtures and bacteria expressing fluorescent proteins with a two-photon microscope system equipped with a commercial single-photon counting card, and we used these data to benchmark the gDAI program.

ADAP-GC 3.2: Graphical Software Tool for Efficient Spectral Deconvolution of Gas Chromatography-High-Resolution Mass Spectrometry Metabolomics Data.

ADAP-GC is an automated computational workflow for extracting metabolite information from raw, untargeted gas chromatography-mass spectrometry metabolomics data. Deconvolution of coeluting analytes is a critical step in the workflow, and the underlying algorithm is able to extract fragmentation mass spectra of coeluting analytes with high accuracy. However, its latest version ADAP-GC 3.0 was not user-friendly. To make ADAP-GC easier to use, we have developed ADAP-GC 3.2 and describe here the improvements on three aspects. First, all of the algorithms in ADAP-GC 3.0 written in R have been replaced by their analogues in Java and incorporated into MZmine 2 to make the workflow user-friendly. Second, the clustering algorithm DBSCAN has replaced the original hierarchical clustering to allow faster spectral deconvolution. Finally, algorithms originally developed for constructing extracted ion chromatograms (EICs) and detecting EIC peaks from LC-MS data are incorporated into the ADAP-GC workflow, allowing the latter to process high mass resolution data. Performance of ADAP-GC 3.2 has been evaluated using unit mass resolution data from standard-mixture and urine samples. The identification and quantitation results were compared with those produced by ADAP-GC 3.0, AMDIS, AnalyzerPro, and ChromaTOF. Identification results for high mass resolution data derived from standard-mixture samples are presented as well.

Multiscale BerEp4 molecular imaging of microtumor phantoms: toward theranostics for basal cell carcinoma.

Basal cell carcinoma (BCC), the most common cancer in humans, appears macroscopically and microscopically similar to many other skin lesions, which makes differential diagnosis difficult. We are developing an approach for quantitative molecular imaging of BerEP4, a transmembrane biomarker for BCC, with the goal of increasing the precision and accuracy of diagnosis. This pilot study was conducted to assess the affinity and selectivity of BerEp4 antibody and assess its possible use in designing theranostic probes for BCC. We provide evidence that our photon-counting fluorescence macrodetection system can recover specific signal increases from a film/pellet phantom. Additionally, we show that a two-photon excited fluorescence /backscatter confocal microscopy system can image BerEP4 antibody/antigen complex on the surface of BerEP4-expressing cancer cells in three dimensions. Based on the initial results, BerEP4 seems to be a promising biomarker for molecular imaging of BCC. To prepare BerEP4 for eventual theranostic use, we examined the feasibility of a combined macro-/micro-optical approach to imaging BCC with various histologies. These optical methods, endowed with the ability to monitor treatment in real time, may open an opportunity for noninvasive diagnosis, treatments, and follow-up.

Compact non-contact total emission detection for in vivo multiphoton excitation microscopy.

We describe a compact, non-contact design for a total emission detection (c-TED) system for intra-vital multiphoton imaging. To conform to a standard upright two-photon microscope design, this system uses a parabolic mirror surrounding a standard microscope objective in concert with an optical path that does not interfere with normal microscope operation. The non-contact design of this device allows for maximal light collection without disrupting the physiology of the specimen being examined. Tests were conducted on exposed tissues in live animals to examine the emission collection enhancement of the c-TED device compared to heavily optimized objective-based emission collection. The best light collection enhancement was seen from murine fat (5×-2× gains as a function of depth), whereas murine skeletal muscle and rat kidney showed gains of over two and just under twofold near the surface, respectively. Gains decreased with imaging depth (particularly in the kidney). Zebrafish imaging on a reflective substrate showed close to a twofold gain throughout the entire volume of an intact embryo (approximately 150 µm deep). Direct measurement of bleaching rates confirmed that the lower laser powers, enabled by greater light collection efficiency, yielded reduced photobleaching in vivo. The potential benefits of increased light collection in terms of speed of imaging and reduced photo-damage, as well as the applicability of this device to other multiphoton imaging methods is discussed.

Nanostructures formed by displacement of porous silicon with copper: from nanoparticles to porous membranes.

The application of porous silicon as a template for the fabrication of nanosized copper objects is reported. Three different types of nanostructures were formed by displacement deposition of copper on porous silicon from hydrofluoric acid-based solutions of copper sulphate: (1) copper nanoparticles, (2) quasi-continuous copper films, and (3) free porous copper membranes. Managing the parameters of porous silicon (pore sizes, porosity), deposition time, and wettability of the copper sulphate solution has allowed to achieve such variety of the copper structures. Elemental and structural analyses of the obtained structures are presented. Young modulus measurements of the porous copper membrane have been carried out and its modest activity in surface enhanced Raman spectroscopy is declared.

In vivo fluorescence lifetime imaging monitors binding of specific probes to cancer biomarkers.

One of the most important factors in choosing a treatment strategy for cancer is characterization of biomarkers in cancer cells. Particularly, recent advances in Monoclonal Antibodies (MAB) as primary-specific drugs targeting tumor receptors show that their efficacy depends strongly on characterization of tumor biomarkers. Assessment of their status in individual patients would facilitate selection of an optimal treatment strategy, and the continuous monitoring of those biomarkers and their binding process to the therapy would provide a means for early evaluation of the efficacy of therapeutic intervention. In this study we have demonstrated for the first time in live animals that the fluorescence lifetime can be used to detect the binding of targeted optical probes to the extracellular receptors on tumor cells in vivo. The rationale was that fluorescence lifetime of a specific probe is sensitive to local environment and/or affinity to other molecules. We attached Near-InfraRed (NIR) fluorescent probes to Human Epidermal Growth Factor 2 (HER2/neu)-specific Affibody molecules and used our time-resolved optical system to compare the fluorescence lifetime of the optical probes that were bound and unbound to tumor cells in live mice. Our results show that the fluorescence lifetime changes in our model system delineate HER2 receptor bound from the unbound probe in vivo. Thus, this method is useful as a specific marker of the receptor binding process, which can open a new paradigm in the "image and treat" concept, especially for early evaluation of the efficacy of the therapy.

Conformational heterogeneity and quasi-static self-quenching in DNA containing a fluorescent guanine analogue, 3MI or 6MI.

Two different microenvironments in the DNA sequence 5'-act aGa gat ccc tca gac cct ttt agt cag tGt gga-3' (in both single- and double-stranded forms) are explored using two similar fluorescent nucleoside analogues, 3MI and 6MI. Each probe was evaluated in two environments, one strand with the probe flanked by thymines (PTRT) and the other by adenines (PTRA) with positions indicated by G's in the sequence. Both time-resolved anisotropies and lifetimes of the probes depend upon local interactions, and these are altered by duplex formation. Integrals of lifetime curves compared with quantum yields reveal that each probe displays a "dark" component (below detection limits, with a lifetime of <70 ps). For 6MI in PTRA, this QSSQ "quasi-static self-quenching" or "dark" component represents approximately half the molecules, whether in single- or double-stranded form. In PTRT, 6MI displays an unusual increase in the quantum yield upon formation of the double strand (from 0.107 to 0.189) apparently the result of escape from QSSQ which simultaneously declines from 66 to 33%. This is also accompanied by doubling of steady-state anisotropy. Only 6MI in the PTRT duplex displays a rotational correlation time of >7 ns. In other words, the DS 6MI PTRA environment fails to constrain local motion and QSSQ remains the same as in the single strand; in contrast, the flanking T duplex environment restricts local motion and halves QSSQ. We collected both steady-state and time-resolved fluorescence quenching titrations of 3MI and 6MI in solution with the mononucleotides AMP, CMP, GMP, and TMP. The dynamic quenching rank of the free probes (quenching constant, kq: T > A > G > C) is totally different from that of incorporated probes. We hypothesize the production of weak 3MI.C or 6MI.C complexes that are somehow rendered less subject to dynamic quenching by collision with subsequent C molecules.

Optimization of multiphoton excitation microscopy by total emission detection using a parabolic light reflector.

We have constructed a device that maximizes the probability of collecting all of the scattered and ballistic light isotropically generated at the focal spot of multiphoton excited emissions (MPE) to optimize the signal-to-noise ratio (SNR) for micro-imaging. This was accomplished by optically coupling a parabolic reflector (that surrounds the sample and top of the objective) to a pair of collimating lenses (above the sample) that redirects emitted light to a separate detector. These additional optics, combined with the objective, allow the total emission detection (TED) condition to be approached. Numerical simulations suggest an approximately 10-fold improvement in SNR with TED. Comparisons between the objective detection and TED reveal an enhancement of 8.9 in SNR (77% of predicted) for GFP-labelled brain slices and similar results for fluorescent beads. This increase in SNR can be used to improve time resolution, reduce laser power requirements/photodynamic damage, and, in certain cases, detection depth, for MPE imaging techniques.

Quantitative detection of the ligand-dependent interaction between the androgen receptor and the co-activator, Tif2, in live cells using two color, two photon fluorescence cross-correlation spectroscopy.

Two-photon, two-color fluorescence cross-correlation spectroscopy (TPTCFCCS) was used to directly detect ligand-dependent interaction between an eCFP-fusion of the androgen receptor (eCFP-AR) and an eYFP fusion of the nuclear receptor co-activator, Tif2 (eYFP-Tif2) in live cells. As expected, these two proteins were co-localized in the nucleus in the presence of ligand. Analysis of the cross-correlation amplitude revealed that AR was on average 81% bound to Tif2 in the presence of agonist, whereas the fractional complex formation decreased to 56% in the presence of antagonist. Residual AR-Tif2 interaction in presence of antagonist is likely mediated by its ligand-independent activation function. These studies demonstrate that using TPTCFCCS it is possible to quantify ligand-dependent interaction of nuclear receptors with co-regulator partners in live cells, making possible a vast array of structure-function studies for these important transcriptional regulators.

Combined spectral karyotyping, comparative genomic hybridization, and in vitro apoptyping of a panel of Burkitt's lymphoma-derived B cell lines reveals an unexpected complexity of chromosomal aberrations and a recurrence of specific abnormalities in chemoresistant cell lines.

The comprehensive cytogenetic profiles of a panel of 10 Burkitt's lymphoma (BL)-derived B cell lines, designated Akata, BL-28, BL-41, Daudi, DG-75, Mutu I, Mutu III, Namalwa, Rael, and Ramos, respectively, are reported herein. The unique origin of each cell line was established using multiplex quantitative fluorescence polymerase chain reaction (QF-PCR). Spectral karyotyping (SKY) revealed a large number of structural and numerical chromosomal aberrations, many of which had not been previously identified or resolved by conventional G-banding techniques. Notably, whereas all 10 cell lines harbored the hallmark translocation t(8;14)(q24;q32), no other common structural aberrations were identified, although translocations involving chromosomes 3, 13, and 17 were frequently seen. Moreover, analysis of chromosomal breakpoints by comparative genomic hybridization (CGH) revealed a number of recurring aberrations, such as gain of chromosomes 7 and 20, gains of regions at 2p, 3q, 13q and 16q, and losses at 3p, 4q and 17p. In addition, apoptyping (i.e. determination of in vitro responses to apoptosis stimulation) of the cell lines suggested specific association patterns between karyotypic changes (e.g. translocations involving 17p, and gains of portions of chromosomes 7 and 20) and resistance to the chemotherapeutic agent, etoposide. The current molecular cytogenetic characterization of 10 BL cell lines has thus identified several novel sites of rearrangements; moreover, the combined karyotyping and functional assessment (apoptyping) of these cell lines serves to enhance their utility in future studies aimed at gene discovery and gene function.