Detection and visualization of communities in mass spectrometry imaging data.

Wüllems K, Kölling J, Bednarz H, Niehaus K, Hans VH, Nattkemper TW. Detection and visualization of communities in mass spectrometry imaging data. BMC Bioinformatics. 2019;20(1): 303.BACKGROUND: The spatial distribution and colocalization of functionally related metabolites is analysed in order to investigate the spatial (and functional) aspects of molecular networks. We propose to consider community detection for the analysis of m/z-images to group molecules with correlative spatial distribution into communities so they hint at functional networks or pathway activity. To detect communities, we investigate a spectral approach by optimizing the modularity measure. We present an analysis pipeline and an online interactive visualization tool to facilitate explorative analysis of the results. The approach is illustrated with synthetical benchmark data and two real world data sets (barley seed and glioblastoma section).; RESULTS: For the barley sample data set, our approach is able to reproduce the findings of a previous work that identified groups of molecules with distributions that correlate with anatomical structures of the barley seed. The analysis of glioblastoma section data revealed that some molecular compositions are locally focused, indicating the existence of a meaningful separation in at least two areas. This result is in line with the prior histological knowledge. In addition to confirming prior findings, the resulting graph structures revealed new subcommunities of m/z-images (i.e. metabolites) with more detailed distribution patterns. Another result of our work is the development of an interactive webtool called GRINE (Analysis of GRaph mapped Image Data NEtworks).; CONCLUSIONS: The proposed method was successfully applied to identify molecular communities of laterally co-localized molecules. For both application examples, the detected communities showed inherent substructures that could easily be investigated with the proposed visualization tool. This shows the potential of this approach as a complementary addition to pixel clustering methods

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis.

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs

Profiling the metabolic signals involved in chemical communication between microbes using imaging mass spectrometry

The ability of microbes to secrete bioactive chemical signals into their environment has been known for over a century. However, it is only in the last decade that imaging mass spectrometry has provided us with the ability to directly visualize the spatial distributions of these microbial metabolites. This technology involves collecting mass spectra from multiple discrete locations across a biological sample, yielding chemical ‘maps’ that simultaneously reveal the distributions of hundreds of metabolites in two dimensions. Advances in microbial imaging mass spectrometry summarized here have included the identification of novel strain- or coculture-specific compounds, the visualization of biotransformation events (where one metabolite is converted into another by a neighboring microbe), and the implementation of a method to reconstruct the 3D subsurface distributions of metabolites, among others. Here we review the recent literature and discuss how imaging mass spectrometry has spurred novel insights regarding the chemical consequences of microbial interactions

A Winogradsky-based culture system shows an association between microbial fermentation and cystic fibrosis exacerbation.

There is a poor understanding of how the physiology of polymicrobial communities in cystic fibrosis (CF) lungs contributes to pulmonary exacerbations and lung function decline. In this study, a microbial culture system based on the principles of the Winogradsky column (WinCF system) was developed to study the physiology of CF microbes. The system used glass capillary tubes filled with artificial sputum medium to mimic a clogged airway bronchiole. Chemical indicators were added to observe microbial physiology within the tubes. Characterization of sputum samples from seven patients showed variation in pH, respiration, biofilm formation and gas production, indicating that the physiology of CF microbial communities varied among patients. Incubation of homogenized tissues from an explant CF lung mirrored responses of a Pseudomonas aeruginosa pure culture, supporting evidence that end-stage lungs are dominated by this pathogen. Longitudinal sputum samples taken through two exacerbation events in a single patient showed that a two-unit drop in pH and a 30% increase in gas production occurred in the tubes prior to exacerbation, which was reversed with antibiotic treatment. Microbial community profiles obtained through amplification and sequencing of the 16S rRNA gene showed that fermentative anaerobes became more abundant during exacerbation and were then reduced during treatment where P. aeruginosa became the dominant bacterium. Results from the WinCF experiments support the model where two functionally different CF microbial communities exist, the persistent Climax Community and the acute Attack Community. Fermentative anaerobes are hypothesized to be the core members of the Attack Community and production of acidic and gaseous products from fermentation may drive developing exacerbations. Treatment targeting the Attack Community may better resolve exacerbations and resulting lung damage

Visualization of proteomics data using R and bioconductor.

Data visualization plays a key role in high-throughput biology. It is an essential tool for data exploration allowing to shed light on data structure and patterns of interest. Visualization is also of paramount importance as a form of communicating data to a broad audience. Here, we provided a short overview of the application of the R software to the visualization of proteomics data. We present a summary of R's plotting systems and how they are used to visualize and understand raw and processed MS-based proteomics data.LG was supported by the European Union 7th Framework Program (PRIME-XS project, grant agreement number 262067) and a BBSRC Strategic Longer and Larger grant (Award BB/L002817/1). LMB was supported by a BBSRC Tools and Resources Development Fund (Award BB/K00137X/1). TN was supported by a ERASMUS Placement scholarship.This is the final published version of the article. It was originally published in Proteomics (PROTEOMICS Special Issue: Proteomics Data Visualisation Volume 15, Issue 8, pages 1375–1389, April 2015. DOI: 10.1002/pmic.201400392). The final version is available at http://onlinelibrary.wiley.com/doi/10.1002/pmic.201400392/abstract

Dismantling the bacterial glycocalyx: Chemical tools to probe, perturb, and image bacterial glycans

The bacterial glycocalyx is a quintessential drug target comprised of structurally distinct glycans. Bacterial glycans bear unusual monosaccharide building blocks whose proper construction is critical for bacterial fitness, survival, and colonization in the human host. Despite their appeal as therapeutic targets, bacterial glycans are difficult to study due to the presence of rare bacterial monosaccharides that are linked and modified in atypical manners. Their structural complexity ultimately hampers their analytical characterization. This review highlights recent advances in bacterial chemical glycobiology and focuses on the development of chemical tools to probe, perturb, and image bacterial glycans and their biosynthesis. Current technologies have enabled the study of bacterial glycosylation machinery even in the absence of detailed structural information

Visualization is crucial for understanding microbial processes in the ocean

Recent developments in community and single-cell genomic approaches have provided an unprecedented amount of information on the ecology of microbes in the aquatic environment. However, linkages between each specific microbe\u27s identity and their in situ level of activity (be it growth, division or just metabolic activity) are much more scarce. The ultimate goal of marine microbial ecology is to understand how the environment determines the types of different microbes in nature, their function, morphology and cell-to-cell interactions and to do so we should gather three levels of information, the genomic (including identity), the functional (activity or growth), and the morphological, and for as many individual cells as possible. We present a brief overview of methodologies applied to address single-cell activity in marine prokaryotes, together with a discussion of the difficulties in identifying and categorizing activity and growth. We then provide and discuss some examples showing how visualization has been pivotal for challenging established paradigms and for understanding the role of microbes in the environment, unveiling processes and interactions that otherwise would have been overlooked. We conclude by stating that more effort should be directed towards integrating visualization in future approaches if we want to gain a comprehensive insight into how microbes contribute to the functioning of ecosystems