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.

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.

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.

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.

Cytosolic pH regulates proliferation and tumour growth by promoting expression of cyclin D1.

Enhanced growth and proliferation of cancer cells are accompanied by profound changes in cellular metabolism. These metabolic changes are also common under physiological conditions, and include increased glucose fermentation accompanied by elevated cytosolic pH (pHc)1,2. However, how these changes contribute to enhanced cell growth and proliferation is unclear. Here, we show that elevated pHc specifically orchestrates an E2F-dependent transcriptional programme to drive cell proliferation by promoting cyclin D1 expression. pHc-dependent transcription of cyclin D1 requires the transcription factors CREB1, ATF1 and ETS1, and the histone acetyltransferases p300 and CBP. Biochemical characterization revealed that the CREB1-p300/CBP interaction acts as a pH sensor and coincidence detector, integrating different mitotic signals to regulate cyclin D1 transcription. We also show that elevated pHc contributes to increased cyclin D1 expression in malignant pleural mesotheliomas (MPMs), and renders these cells hypersensitive to pharmacological reduction of pHc. Taken together, these data demonstrate that elevated pHc is a critical cellular signal regulating G1 progression, and provide a mechanism linking elevated pHc to oncogenic activation of cyclin D1 in MPMs, and possibly other cyclin D1~dependent tumours. Thus, an increase of pHc may represent a functionally important, early event in the aetiology of cancer that is amenable to therapeutic intervention.

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.

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.

Translating secondary electrospray ionization-high-resolution mass spectrometry to the clinical environment.

While there has been progress in making use of breath tests to guide clinical decision making, the full potential of exhaled breath analysis still remains to be exploited. Here we summarize some of the reasons why this is the case, what we have done so far to overcome some of the existing obstacles, and our vision of how we think breath analysis will play a more prominent role in the coming years. In particular, we envision that real-time high-resolution mass spectrometry will provide valuable information in biomarker discovery studies. However, this can only be achieved by a coordinated effort, using standardized equipment and methods in multi-center studies to eventually deliver tangible advances in the field of breath analysis in a clinical setting. Concrete aspects such as sample integrity, compound identification, quantification and standardization are discussed. Novel secondary electrospray ionization developments with the aim of facilitating inter-groups comparisons and biomarker validation studies are also presented.

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.

Comprehensive Real-Time Analysis of the Yeast Volatilome.

While yeast is one of the most studied organisms, its intricate biology remains to be fully mapped and understood. This is especially the case when it comes to capture rapid, in vivo fluctuations of metabolite levels. Secondary electrospray ionization-high resolution mass spectrometry SESI-HRMS is introduced here as a sensitive and noninvasive analytical technique for online monitoring of microbial metabolic activity. The power of this technique is exemplarily shown for baker's yeast fermentation, for which the time-resolved abundance of about 300 metabolites is demonstrated. The results suggest that a large number of metabolites produced by yeast from glucose neither are reported in the literature nor are their biochemical origins deciphered. With the technique demonstrated here, researchers interested in distant disciplines such as yeast physiology and food quality will gain new insights into the biochemical capability of this simple eukaryote.

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.

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.

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.

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.

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.

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.

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.

Single-cell imaging for the study of oncometabolism.

Metabolic profiling is commonly employed to investigate the global metabolic alterations of malignant cells or tissues. In the latter setting, neoplastic lesions are separated from adjacent, healthy tissues and their metabolites are quantified upon a chromatographic run coupled to mass spectrometry. Changes in the abundance of specific metabolites are then mapped on metabolic networks and the underlying metabolic circuitries are investigated as potential targets for the development of novel anticancer drugs. This approach, however, does not take into account the intrinsic heterogeneity of neoplastic lesions, which contain a large amount of non-transformed cells. To circumvent this issue, techniques have been developed that allow for the imaging of metabolites at the single-cell level. Here, we summarize established protocols that are suitable for imaging metabolites in animal cells (be them malignant or not) as well as in plant and prokaryotic cells. These methods are relevant for the study of the metabolic alterations that accompany oncogenesis and tumor progression.