Addressing the challenge of petroleomics data

Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) is currently the state-of-the-art instrument in terms of resolving power and accuracy for mass spectrometry and is able to resolve an unprecedented number of components in complex chemical mixtures, such as petroleum. The data analysis tools necessary struggle to keep pace with advancing instrument capabilities and the ever-increasing quantities of data generated. The existing workflows rely on combining different tools, not necessarily compatible between them and often generate a significant amount of manual repetitive tasks. A first issue is that the current standard practice does not utilise replicates to improve the reliability of an analysis. A second issue is that spectral stitching methods to combine data from multiple experiments performed for a single sample are not automated, and hence generate substantial manual work that precludes the routine applications of these experiments. Hyphenated ultra-high resolution, can provide structural information but the data analysis tools are lacking leading to loss retention time precision and labour-intensive workflows. A final issue explored in this thesis is that molecular assignments are performed using commercial software or in-house algorithms but currently no evaluation of the false positive assignments has been performed. During this PhD, algorithms were developed to address those needs and implemented using the R language. The tools needed to be accessible to a wide audience, not necessarily comfortable using scripted languages so interactive interfaces were created using the Shiny framework. Overall, the work presented in the thesis brings improved reliability when analysing complex mixture using Fourier transform mass spectrometry thanks to combining replicates or stitching multiple experiments, and assessing reproducibility. Further, it helps accelerate analyse hyphenated ultra-high-resolution mass spectrometry decreasing the time necessary from days to hours while bringing a deeper and more accurate insight into the data also capable to analyse and compare molecular assignments for petroleum related samples

Rhapso : automatic stitching of mass segments from fourier transform ion cyclotron resonance mass spectra

Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) provides the resolution and mass accuracy needed to analyze complex mixtures such as crude oil. When mixtures contain many different components, a competitive effect within the ICR cell takes place that hampers the detection of a potentially large fraction of the components. Recently, a new data collection technique, which consists of acquiring several spectra of small mass ranges and assembling a complete spectrum afterward, enabled the observation of a record number of peaks with greater accuracy compared to broadband methods. There is a need for statistical methods to combine and preprocess segmented acquisition data. A particular challenge of quadrupole isolation is that near the window edges there is a drop in intensity, hampering the stitching of consecutive windows. We developed an algorithm called Rhapso to stitch peak lists corresponding to multiple different m/z regions from crude oil samples. Rhapso corrects potential edge effects to enable the use of smaller windows and reduce the required overlap between windows, corrects mass shifts between windows, and generates a single peak list for the full spectrum. Relative to a stitching performed manually, Rhapso increased the data processing speed and avoided potential human errors, simplifying the subsequent chemical analysis of the sample. Relative to a broadband spectrum, the stitched output showed an over 2-fold increase in assigned peaks and reduced mass error by a factor of 2. Rhapso is expected to enable routine use of this spectral stitching method for ultracomplex samples, giving a more detailed characterization of existing samples and enabling the characterization of samples that were previously too complex to analyze

Revealing the reactivity of individual chemical entities in complex mixtures : the chemistry behind bio-oil upgrading

Bio-oils are precursors for biofuels but are highly corrosive necessitating further upgrading. Furthermore, bio-oil samples are highly complex and represent a broad range of chemistries. They are complex mixtures not simply because of the large number of poly-oxygenated compounds but because each composition can comprise many isomers with multiple functional groups. The use of hyphenated ultrahigh-resolution mass spectrometry affords the ability to separate isomeric species of complex mixtures. Here, we present for the first time, the use of this powerful analytical technique combined with chemical reactivity to gain greater insights into the reactivity of the individual isomeric species of bio-oils. A pyrolysis bio-oils and its esterified bio-oil were analyzed using gas chromatography coupled to Fourier transform ion cyclotron resonance mass spectrometry, and in-house software (KairosMS) was used for fast comparison of the hyphenated data sets. The data revealed a total of 10,368 isomers in the pyrolysis bio-oil and an increase to 18,827 isomers after esterification conditions. Furthermore, the comparison of the isomeric distribution before and after esterification provide new light on the reactivities within these complex mixtures; these reactivities would be expected to correspond with carboxylic acid, aldehyde, and ketone functional groups. Using this approach, it was possible to reveal the increased chemical complexity of bio-oils after upgrading and target detection of valuable compounds within the bio-oils. The combination of chemical reactions alongside with in-depth molecular characterization opens a new window for the understanding of the chemistry and reactivity of complex mixtures

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Themis : batch preprocessing for ultrahigh-resolution mass spectra of complex mixtures

Fourier transform ion cyclotron resonance mass spectrometry affords the resolving power to determine an unprecedented number of components in complex mixtures, such as petroleum. The software tools required to also analyze these data struggle to keep pace with advancing instrument capabilities and increasing quantities of data, particularly in terms of combining information efficiently across multiple replicates. Improved confidence in data and the use of replicates is particularly important where strategic decisions will be based upon the analysis. We present a new algorithm named Themis, developed using R, to jointly preprocess replicate measurements of a sample with the aim of improving consistency as a preliminary step to assigning peaks to chemical compositions. The main features of the algorithm are quality control criteria to detect failed runs, ensuring comparable magnitudes across replicates, peak alignment, and the use of an adaptive mixture model-based strategy to help distinguish true peaks from noise. The algorithm outputs a list of peaks reliably observed across replicates and facilitates data handling by preprocessing all replicates in a single step. The processed data produced by our algorithm can subsequently be analyzed by use of relevant specialized software. While Themis has been demonstrated with petroleum as an example of a complex mixture, its basic framework will be useful for complex samples arising from a variety of other applications

Characterization of bio-crude components derived from pyrolysis of soft wood and its esterified product by ultrahigh resolution mass spectrometry and spectroscopic techniques

In this work, a detailed analysis of a bio-oil obtained by pyrolysis of softwoods and its esterified product is described. Information of the type of chemical function groups were obtained by 13C and 1H nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy (FT-IR) and compositional analysis was obtained by Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS). The results obtained indicate that aliphatic hydrogen and carbon atoms are found in higher abundance, compared with aromatic hydrogen-carbon frameworks. Furthermore, a decrease in oxygen functional groups was observed after esterification. According to the FTICR MS results, the samples contain highly oxygenated species corresponding to compound classes Ox, NOx and BOx, with a high predominance of Ox species. After esterification, the compositions shifted towards lower oxygen-content, lower number of rings and double bonds, and longer alkyl chains as a consequence of the water removal via the condensation reaction

Comprehensive analysis of multiple asphaltene fractions combining statistical analyses and novel visualization tools

Marine heavy fuel oils (HFOs), derived from and often blended with hydrotreated residual cuts, typically possess high boiling point, viscosity, and molecular complexity, and so are inherently challenging to analyze at the molecular level. Their high asphaltene content is associated with undesirable phenomena including flocculation, deposition, and black paint formation in marine engines. Asphaltene fractions of eight HFOs were selected for analysis by Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) due to their differing behaviour, including responsiveness to additive chemistries designed to stabilise against asphaltene handling issues. A selected mass region was isolated and fragmented using infra-red multiphoton dissociation (IRMPD), and the relative heteroatom content in asphaltene cores and smaller aromatic moieties, and degree of alkylation and aromaticity, of the fragments generated for each sample compared. A more extensive elucidation of the molecular-level differences between the n-alkane insoluble asphaltene fractions is afforded, with key components underlying variation in bulk behaviour identified through statistical approaches. The approach presented allows additive packages to be adjusted to address asphaltene handling issues presented by more challenging samples, and simpler and more ubiquitous formulations may eventually be developed

KairosMS: a new solution for the processing of hyphenated ultrahigh resolution mass spectrometry data

The use of hyphenated Fourier transform mass spectrometry (FTMS) methods affords additional information about complex chemical mixtures. Coeluted components can be resolved thanks to the ultrahigh resolving power, which also allows extracted ion chromatograms (EICs) to be used for the observation of isomers. As such data sets can be large and data analyses laborious, improved tools are needed for data analyses and extraction of key information. The typical workflow for this type of data is based upon manually dividing the total ion chromatogram (TIC) into several windows of usually equal retention time, averaging the signal of each window to create a single mass spectrum, extracting a peak list, performing the compositional assignments, visualizing the results, and repeating the process for each window. Through removal of the need to manually divide a data set into many time windows and analyze each one, a time-consuming workflow has been significantly simplified. An environmental sample from the oil sands region of Alberta, Canada, and dissolved organic matter samples from the Suwannee River Fulvic Acid (SRFA) and marine waters (Marine DOM) were used as a test bed for the new method. A complete solution named KairosMS was developed in the R language utilizing the Tidyverse packages and Shiny for the user interface. KairosMS imports raw data from common file types, processes it, and exports a mass list for compositional assignments. KairosMS then incorporates those assignments for analysis and visualization. The present method increases the computational speed while reducing the manual work of the analysis when compared to other current methods. The algorithm subsequently incorporates the assignments into the processed data set, generating a series of interactive plots, EICs for individual components or entire compound classes, and can export raw data or graphics for off-line use. Using the example of petroleum related data, it is then visualized according to heteroatom class, carbon number, double bond equivalents, and retention time. The algorithm also gives the ability to screen for isomeric contributions and to follow homologous series or compound classes, instead of individual components, as a function of time

An international laboratory comparison of dissolved organic matter composition by high resolution mass spectrometry : Are we getting the same answer?

High-resolution mass spectrometry (HRMS) has become a vital tool for dissolved organic matter (DOM) characterization. The upward trend in HRMS analysis of DOM presents challenges in data comparison and interpretation among laboratories operating instruments with differing performance and user operating conditions. It is therefore essential that the community establishes metric ranges and compositional trends for data comparison with reference samples so that data can be robustly compared among research groups. To this end, four identically prepared DOM samples were each measured by 16 laboratories, using 17 commercially purchased instruments, using positive-ion and negative-ion mode electrospray ionization (ESI) HRMS analyses. The instruments identified similar to 1000 common ions in both negative- and positive-ion modes over a wide range of m/z values and chemical space, as determined by van Krevelen diagrams. Calculated metrics of abundance-weighted average indices (H/C, O/C, aromaticity and m/z) of the commonly detected ions showed that hydrogen saturation and aromaticity were consistent for each reference sample across the instruments, while average mass and oxygenation were more affected by differences in instrument type and settings. In this paper we present 32 metric values for future benchmarking. The metric values were obtained for the four different parameters from four samples in two ionization modes and can be used in future work to evaluate the performance of HRMS instruments