Graph embedding on mass spectrometry- and sequencing-based biomedical data.

Graph embedding techniques are using deep learning algorithms in data analysis to solve problems of such as node classification, link prediction, community detection, and visualization. Although typically used in the context of guessing friendships in social media, several applications for graph embedding techniques in biomedical data analysis have emerged. While these approaches remain computationally demanding, several developments over the last years facilitate their application to study biomedical data and thus may help advance biological discoveries. Therefore, in this review, we discuss the principles of graph embedding techniques and explore the usefulness for understanding biological network data derived from mass spectrometry and sequencing experiments, the current workhorses of systems biology studies. In particular, we focus on recent examples for characterizing protein-protein interaction networks and predicting novel drug functions.

Cytosolic pH regulates cell growth through distinct GTPases, Arf1 and Gtr1, to promote Ras/PKA and TORC1 activity.

Regulation of cell growth by nutrients is governed by highly conserved signaling pathways, yet mechanisms of nutrient sensing are still poorly understood. In yeast, glucose activates both the Ras/PKA pathway and TORC1, which coordinately regulate growth through enhancing translation and ribosome biogenesis and suppressing autophagy. Here, we show that cytosolic pH acts as a cellular signal to activate Ras and TORC1 in response to glucose availability. We demonstrate that cytosolic pH is sensitive to the quality and quantity of the available carbon source (C-source). Interestingly, Ras/PKA and TORC1 are both activated through the vacuolar ATPase (V-ATPase), which was previously identified as a sensor for cytosolic pH in vivo. V-ATPase interacts with two distinct GTPases, Arf1 and Gtr1, which are required for Ras and TORC1 activation, respectively. Together, these data provide a molecular mechanism for how cytosolic pH links C-source availability to the activity of signaling networks promoting cell growth.

A breath of information: the volatilome.

Volatile organic compounds (VOCs) are small molecular mass substances, which exhibit low boiling points and high-vapour pressures. They are ubiquitous in nature and produced by almost any organism of all kingdoms of life. VOCs are involved in many inter- and intraspecies interactions ranging from antimicrobial or fungal effects to plant growth promotion and human taste perception of fermentation products. VOC profiles further reflect the metabolic or phenotypic state of the living organism that produces them. Hence, they can be exploited for non-invasive medicinal diagnoses or industrial fermentation control. Here, we introduce the reader to these diverse applications associated with the monitoring and analysis of VOC emissions. We also present our vision of real-time VOC analysis enabled by newly developed analytical techniques, which will further broaden the use of VOCs in even wider applications. Hence, we foresee a bright future for VOC research and its associated fields of applications.

Single-Cell Mass Spectrometry of Metabolites Extracted from Live Cells by Fluidic Force Microscopy.

Single-cell metabolite analysis provides valuable information on cellular function and response to external stimuli. While recent advances in mass spectrometry reached the sensitivity required to investigate metabolites in single cells, current methods commonly isolate and sacrifice cells, inflicting a perturbed state and preventing complementary analyses. Here, we propose a two-step approach that combines nondestructive and quantitative withdrawal of intracellular fluid with subpicoliter resolution using fluidic force microscopy, followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The developed method enabled the detection and identification of 20 metabolites recovered from the cytoplasm of individual HeLa cells. The approach was further validated in 13C-glucose feeding experiments, which showed incorporation of labeled carbon atoms into different metabolites. Metabolite sampling, followed by mass spectrometry measurements, enabled the preservation of the physiological context and the viability of the analyzed cell, providing opportunities for complementary analyses of the cell before, during, and after metabolite analysis.

Applying mass spectrometry to study non-covalent biomolecule complexes.

Non-covalent interactions are essential for the structural organization of biomacromolecules and play an important role in molecular recognition processes, such as the interactions between proteins, glycans, lipids, DNA, and RNA. Mass spectrometry (MS) is a powerful tool for studying of non-covalent interactions, due to the low sample consumption, high sensitivity, and label-free nature. Nowadays, native-ESI MS is heavily used in studies of non-covalent interactions and to understand the architecture of biomolecular complexes. However, MALDI-MS is also becoming increasingly useful. It is challenging to detect the intact complex without fragmentation when analyzing non-covalent interactions with MALDI-MS. There are two methodological approaches to do so. In the first approach, different experimental and instrumental parameters are fine-tuned in order to find conditions under which the complex is stable, such as applying non-acidic matrices and collecting first-shot spectra. In the second approach, the interacting species are "artificially" stabilized by chemical crosslinking. Both approaches are capable of studying non-covalently bound biomolecules even in quite challenging systems, such as membrane protein complexes. Herein, we review and compare native-ESI and MALDI MS for the study of non-covalent interactions.

Capturing in Vivo Plant Metabolism by Real-Time Analysis of Low to High Molecular Weight Volatiles.

We have deployed an efficient secondary electrospray ionization source coupled to an Orbitrap mass analyzer (SESI-MS) to investigate the emissions of a Begonia semperflorens. We document how hundreds of species can be tracked with an unparalleled time resolution of 2 min during day-night cycles. To further illustrate the capabilities of this system for volatile organic compounds (VOCs) analysis, we subjected the plant to mechanical damage and monitored its response. As a result, ∼1200 VOCs were monitored displaying different kinetics. To validate the soundness of our in vivo measurements, we fully characterized some key compounds via tandem mass spectrometry (MS/MS) and confirmed their expected behavior based on prior gas chromatography/mass spectrometry (GC/MS) studies. For example, ß-caryophyllene, which is directly related to photosynthesis, was found to show a periodic day-night pattern with highest concentrations during the day. We conclude that the capability of SESI-MS to capture highly dynamic VOC emissions and wide analyte coverage makes it an attractive tool to complement GC/MS in plant studies.

Mass spectrometry-based metabolomics of single yeast cells.

Single-cell level measurements are necessary to characterize the intrinsic biological variability in a population of cells. In this study, we demonstrate that, with the microarrays for mass spectrometry platform, we are able to observe this variability. We monitor environmentally (2-deoxy-D-glucose) and genetically (ΔPFK2) perturbed Saccharomyces cerevisiae cells at the single-cell, few-cell, and population levels. Correlation plots between metabolites from the glycolytic pathway, as well as with the observed ATP/ADP ratio as a measure of cellular energy charge, give biological insight that is not accessible from population-level metabolomic data.

Analysis of metabolites in single cells-what is the best micro-platform?

This review covers new innovations and developments in the field of single-cell level analysis of metabolites, involving the role of microfluidic and microarray platforms to manipulate and handle the cells prior their detection. Microfluidic and microarray platforms have shown great promise. The latest developments demonstrate their potential to identify a particular cell or even an ensemble of cells (sharing a common property or phenotype) that co-exist in a much larger cell population. The reason for this is the capability of these platforms to perform several complex analytical processes, such as: cleanup, sorting, derivatization, separation, and detection, with great robustness, speed, and reduced sample/reagent consumption. Here, we present several examples that illustrate the rapid strides that have been made for the routine analysis of metabolites by coupling different microfluidics and microarrays devices to a wide range of analytical detectors (e.g. fluorescent microscopy, electrochemical, and mass spectrometry). Herein, we also present selected examples detailing the use of microfluidics and microarrays in the visualization of the natural occurring cell-to-cell heterogeneity in isogenic populations, in particular during the response to external cues. The possibility to accurate monitor the cell-to-cell heterogeneity based on different levels of key metabolites is of clinical relevance, since cell-to-cell heterogeneity can influence, for example, the outcome of a drug treatment.

Resolution pattern for mass spectrometry imaging.

RATIONALE: Up to now, there is no 'gold standard' for determining the resolution of a mass spectrometry imaging (MSI) setup (comprising the instrument, the sample preparation, the sample and the instrument settings). A standard sample in combination with a standard protocol to define the MSI resolution would be desirable in order to compare the setups of different laboratories, and as a regular quality control/performance check. METHODS: Microstructured resolution patterns were fabricated that can be used to determine the spatial resolution in MSI experiments, down to the range of a few µm. Two different strategies were employed, one where the resolution pattern is laser machined into a thin metal foil, which can be placed over a sample to be imaged, and a second one where hydrophilic grooves are machined into an omniphobic coating covering the surface of an indium tin oxide covered glass slide. When dragging a sample solution over the slide's surface, the sample is automatically retained in the hydrophilic grooves, but repelled by the omniphobic coating. RESULTS: The technology was tested on a commercial matrix-assisted laser desorption/ionization (MALDI) imaging instrument, and a spatial resolution in the vicinity of 50 µm was determined. The finest features of the microstructured resolution patterns are compatible with the best spatial resolution of MALDI imaging systems available to date. CONCLUSIONS: The use of metal resolution grids or glass slides with hydrophilic/hydrophobic structures is suitable for the convenient determination of the resolution limit of the MALDI imaging instrument as determined by its hardware. These structures are straightforward both to produce and to use.

Rapid estimation of the energy charge from cell lysates using matrix-assisted laser desorption/ionization mass spectrometry: role of in-source fragmentation.

Nucleotides are key players in the central energy metabolism of cells. Here we show how to estimate the energy charge from cell lysates by direct negative ion matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) using 9-aminoacridine as matrix. We found a high level of in-source decay of all the phosphorylated nucleotides, with some of them producing considerable amounts of adenosine-5'-diphosphate (ADP) fragment ions. We investigated the behavior of adenosine-5'-monophosphate (AMP), ADP, and adenosine-5'-triphosphate (ATP) as well as the cofactors coenzyme A (CoA) and acetyl-coenzyme A (ACoA) and nicotinamide adenine dinucleotides (NAD⁺ and NADH) in detail. In-source decay of these compounds depends strongly on the applied laser power and on the extraction pulse delay. At standard instrument settings, the 9-aminoacridine (9-AA) matrix resulted in a much higher in-source decay compared with 2,4,6-trihydroxyacetophenone (2,4,6-THAP). By adding ¹³C-labeled ATP to a cell lysate, we were able to determine the degree of in-source decay during an experiment. Analyzing a cell extract of the monocytic cell line THP-1 with [¹³C]ATP as internal standard, we were able to obtain values for the energy charge that were similar to those determined by a reference liquid chromatography electrospray ionization coupled to mass spectrometry (LC-ESI-MS) method.

Molecular phenotypic profiling of a Saccharomyces cerevisiae strain at the single-cell level.

Studying cell-to-cell heterogeneity requires techniques which robustly deliver reproducible results with single-cell sensitivity. Through a new fabrication method for the microarrays for mass spectrometry (MAMS) platform, we now have attained robustness and reproducibility in our single-cell level mass spectrometry measurements that allowed us to combine single-cell MAMS-based measurements from different days and samples. By combining multiple measurements, we were able to identify three co-existing phenotypes in an isogenic population of Saccharomyces cerevisiae characterized by distinctively different levels of glycolytic intermediates.

Mass spectrometry research at the Laboratory for Organic Chemistry, ETH Zurich.

This contribution covers the most important activities of the Zenobi research group at the Organic Chemistry Laboratory, ETH Zurich. We work in a number of interrelated areas that encompass fundamental/mechanistic research, instrument and methods development, and applications. This is illustrated with examples from the mass spectrometric study of noncovalent interactions, using both native ESI and MALDI for ionization, the investigation of the gas-phase conformation of ionized bio-macromolecules, the use of ambient mass spectrometry for rapid, on-line analyses of, for example, exhaled breath, and the use of MALDI and microarray technologies for studying metabolites with extreme sensitivity, sufficient to probe the metabolites from single cells.

Analysis of single algal cells by combining mass spectrometry with Raman and fluorescence mapping.

In order to investigate metabolic properties of single cells of freshwater algae (Haematococcus pluvialis), we implement matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) in combination with microspectroscopic mapping. Straightforward coupling of these two detection platforms was possible thanks to the self-aliquoting properties of micro-arrays for mass spectrometry (MAMS). Following Raman and fluorescence imaging, the isolated cells were covered with a MALDI matrix for targeted metabolic analysis by MALDI-MS. The three consecutive measurements carried out on the same cells yielded complementary information. Using this method, we were able to study the encystment of H. pluvialis - by monitoring the adenosine triphosphate (ATP) to adenosine diphosphate (ADP) ratio during the build-up of astaxanthin in the cells as well as the release of ß-carotene, the precursor of astaxanthin, into the cytosol.

Matrix-assisted laser desorption/ionization matrices for negative mode metabolomics.

Matrix-assisted laser desorption/ionization (MALDI) has been shown to be highly sensitive for analyzing low-mass compounds such as metabolites if the right matrix is used. 9-aminoacridine (9AA) is the most commonly employed matrix for negative mode MALDI-MS in metabolomics. However, matrix interferences and the strongly varying sensitivity for different metabolites make a search for alternative matrices desirable, in order to identify compounds with a different chemical background and/or favoring a different range of analytes. We tested the performance of a series of potential negative mode MALDI matrices with a mix of 29 metabolites containing amino acids, nucleotide phosphates and Krebs cycle intermediates. While ethacridine lactate was found to provide limits of detection (LODs) in the low femtomole range for nucleotide phosphates, amino acids and Krebs cycle intermediates in the low picomole range, 4-amino-2-methylquinoline showed LODs in the picomole range for most metabolites, but is capable of ionizing a broader range of analytes than both 9AA and ethacridine.

Lateralized Movements during the Mating Behavior, Which Are Associated with Sex and Sexual Experience, Increase the Mating Success in Alphitobius diaperinus (Coleoptera: Tenebrionidae).

In the present study, we explored the effects of displacement directionality in mating behavior (i.e., lateralized and non-lateralized movements) on mating success (i.e., copulation occurs) and efficiency (i.e., time length at which copulation is achieved), and its association with sex and sexual experience in A. diaperinus. To do so, we carried out mating experiments and recorded the behavior of the mating pair during the whole mating sequence (i.e., precopulatory and copulatory phases). During the precopulatory phase, independently of sex and sexual experience, all beetles performed non-lateralized (i.e., backside or frontside) approaches; however, only sexually experienced beetles showed lateralized approaches (i.e., right-side and left-side). Notably, experienced males exhibited greater mating success than virgin males. After the approach, both virgin and experienced males displayed lateralized and non-lateralized mounts on the females with distinct mating success. Regardless of their sexual experience, 100% of successful mating attempts were achieved when males mounted from the females' right side. Furthermore, the development of lateralized approaches and mounts reduces the time of mating sequence span compared with non-lateralized behaviors. We highlight the importance of lateralization in mating behavior and sexual experience to achieve higher mating success, addressing a potential learning ability of beetles based on experience.

Chemical Signals Associated With Gender and Sexual Experience Affect Mating and the Attractiveness of the Poultry Pest, Alphitobius diaperinus (Coleoptera: Tenebrionidae).

Alphitobius diaperinus is one of the most significant pests in the poultry industry. Identifying the role of self-produced chemical signals can help control it. Here, we exposed adults to the olfactory signals of other adults of similar and different genders (either males or females) and sexual experiences (i.e., virgin and experienced) to assess their long-range attractiveness and, at short-range, their mating behavior responses (i.e., touching, mounting, and copulation). In olfactometric experiments, our results indicate that adults are attracted to the olfactory signals of other male adults, independently of gender, or sexual condition, indicating the presence of generalized long-range attractive signals, in contrast to female signals, can be both factor-dependent. However, in mating experiments, virgin males developed more robust mating responses (i.e., they mount and copulate longer with females) compared to sexually experienced males, even though they both have similar precopulatory behavioral responses (i.e., time of antennal and leg touching). These results address the importance of short-range chemical signals in eliciting copulation. Furthermore, when virgins of both genders were tested, their mating responses were significantly longer than any other pair combination, indicating that sexual experience also affects mating behavior. Chemical analyses of adult extracts showed that sexual experience, but not gender, is linked to differences in chemical profiles of adults, primarily involved in short-range signaling. These findings provide new insights into the attractiveness and mating responses of A. diaperinus and the role of sexual experience in shaping the behavior and chemical profile of insects that mate multiple times during their lifetime.

Mass Spectrometry-Based Flavor Monitoring of Peruvian Chocolate Fabrication Process.

Flavor is one of the most prominent characteristics of chocolate and is crucial in determining the price the consumer is willing to pay. At present, two types of cocoa beans have been characterized according to their flavor and aroma profile, i.e., (1) the bulk (or ordinary) and (2) the fine flavor cocoa (FFC). The FFC has been distinguished from bulk cocoa for having a great variety of flavors. Aiming to differentiate the FFC bean origin of Peruvian chocolate, an analytical methodology using gas chromatography coupled to mass spectrometry (GC-MS) was developed. This methodology allows us to characterize eleven volatile organic compounds correlated to the aromatic profile of FFC chocolate from this geographical region (based on buttery, fruity, floral, ethereal sweet, and roasted flavors). Monitoring these 11 flavor compounds during the chain of industrial processes in a retrospective way, starting from the final chocolate bar towards pre-roasted cocoa beans, allows us to better understand the cocoa flavor development involved during each stage. Hence, this methodology was useful to distinguish chocolates from different regions, north and south of Peru, and production lines. This research can benefit the chocolate industry as a quality control protocol, from the raw material to the final product.

From the Andes to the desert: 16S rRNA metabarcoding characterization of aquatic bacterial communities in the Rimac river, the main source of water for Lima, Peru.

The Rimac river is the main source of water for Lima, Peru's capital megacity. The river is constantly affected by different types of contamination including mine tailings in the Andes and urban sewage in the metropolitan area. In this work, we aim to produce the first characterization of aquatic bacterial communities in the Rimac river using a 16S rRNA metabarcoding approach which would be useful to identify bacterial diversity and potential understudied pathogens. We report a lower diversity in bacterial communities from the Lower Rimac (Metropolitan zone) in comparison to other sub-basins. Samples were generally grouped according to their geographical location. Bacterial classes Alphaproteobacteria, Bacteroidia, Campylobacteria, Fusobacteriia, and Gammaproteobacteria were the most frequent along the river. Arcobacter cryaerophilus (Campylobacteria) was the most frequent species in the Lower Rimac while Flavobacterium succinicans (Bacteroidia) and Hypnocyclicus (Fusobacteriia) were the most predominant in the Upper Rimac. Predicted metabolic functions in the microbiota include bacterial motility and quorum sensing. Additional metabolomic analyses showed the presence of some insecticides and herbicides in the Parac-Upper Rimac and Santa Eulalia-Parac sub-basins. The dominance in the Metropolitan area of Arcobacter cryaerophilus, an emergent pathogen associated with fecal contamination and antibiotic multiresistance, that is not usually reported in traditional microbiological quality assessments, highlights the necessity to apply next-generation sequencing tools to improve pathogen surveillance. We believe that our study will encourage the integration of omics sciences in Peru and its application on current environmental and public health issues.

Applications of MicroArrays for Mass Spectrometry (MAMS) in Single-Cell Metabolomics.

The metabolic network is the endpoint in the flow of information that begins with the "gene" and ends with "phenotype" (observable function) of the cell. Previously, due to the variety of metabolites analyzed inside cells, the metabolomic measurements were performed with samples including multiple cells. Unfortunately, this sampling process may mask important metabolic phenomena, such as cell-to-cell heterogeneity. For these studies, we must use analytical techniques that can robustly deliver reproducible results with single-cell sensitivity. In this chapter, we summarize laser-based methods for single-cell analysis and a novel approach of MicroArrays for Mass Spectrometry (or MAMS) is described in full detail. This particular type of microarrays was tailored for the study of cells grown in liquid medium using multiple-analytical read-outs, such as optical and laser desorption/ionization (LDI) or MALDI mass spectrometry.

Mass Spectrometry: A Rosetta Stone to Learn How Fungi Interact and Talk.

Fungi are a highly diverse group of heterotrophic organisms that play an important role in diverse ecological interactions, many of which are chemically mediated. Fungi have a very versatile metabolism, which allows them to synthesize a large number of still little-known chemical compounds, such as soluble compounds that are secreted into the medium and volatile compounds that are chemical mediators over short and long distances. Mass spectrometry (MS) is currently playing a dominant role in mycological studies, mainly due to its inherent sensitivity and rapid identification capabilities of different metabolites. Furthermore, MS has also been used as a reliable and accurate tool for fungi identification (i.e., biotyping). Here, we introduce the readers about fungal specialized metabolites, their role in ecological interactions and provide an overview on the MS-based techniques used in fungal studies. We particularly present the importance of sampling techniques, strategies to reduce false-positive identification and new MS-based analytical strategies that can be used in mycological studies, further expanding the use of MS in broader applications. Therefore, we foresee a bright future for mass spectrometry-based research in the field of mycology.