The organization of the eukaryotic cell into discrete membrane-bound organelles allows for the separation of incompatible biochemical processes, yet the activities of these organelles must be coordinated. For example, lipid metabolism is distributed between the endoplasmic reticulum (ER) for lipid synthesis, lipid droplets (LDs) for storage and transport, mitochondria and peroxisomes for β-oxidation, and lysosomes for lipid hydrolysis and recycling1–5. Organelle contacts are increasingly understood to be vital for diverse cellular functions5–8. However, the spatial and temporal organization of organelles within the cell remains poorly characterized due to the inability of fluorescence imaging-based approaches to distinguish more than a few fluorescent labels in a single image9. Here we present a systems-level analysis of the organelle interactome using a multispectral image acquisition method that overcomes the challenge of spectral overlap in the fluorescent protein palette. We employed confocal and lattice light sheet (LLS)10 instrumentation and an imaging informatics pipeline of five steps to achieve mapping of organelle numbers/volumes/speeds/positions and dynamic inter-organelle contacts in live fibroblast cells. We describe the frequency and locality of two-, three-, four-, and five-way interactions among six different membrane-bound organelles (ER, Golgi, lysosome, peroxisome, mitochondria and LD) and show how these relationships change over time. We demonstrate that each organelle has a characteristic distribution and dispersion pattern in three-dimensional space and that there is a reproducible pattern of contacts among the six organelles, impacted by microtubule and cell nutrient status. These live-cell confocal and LLS spectral-imaging approaches are applicable to any cell system expressing multiple fluorescent probes, whether in normal conditions or when cells are exposed to disturbances such as drugs, pathogens or stress. This methodology thus offers a powerful new descriptive tool and source for hypotheses about cellular organization and dynamics.

BackgroundLung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesize that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from 33 controls and 143 cancer cases, we conduct 16S ribosomal RNA (rRNA) bacterial gene sequencing, with RNA-sequencing data from lung cancer cases in The Cancer Genome Atlas serving as the validation cohort.ResultsOverall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma specifically, a separate group of taxa are identified, in which Acidovorax is enriched in smokers. Acidovorax temporans is identified within tumor sections by fluorescent in situ hybridization and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax, exhibit higher abundance among the subset of squamous cell carcinoma cases with TP53 mutations, an association not seen in adenocarcinomas.ConclusionsThe results of this comprehensive study show both microbiome-gene and microbiome-exposure interactions in squamous cell carcinoma lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can impair epithelial function, have a unique bacterial consortium that is higher in relative abundance in smoking-associated tumors of this type. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1501-6) contains supplementary material, which is available to authorized users.

Microbes in nature frequently function as members of complex multitaxon communities, but the structural organization of these communities at the micrometer level is poorly understood because of limitations in labeling and imaging technology. We report here a combinatorial labeling strategy coupled with spectral image acquisition and analysis that greatly expands the number of fluorescent signatures distinguishable in a single image. As an imaging proof of principle, we first demonstrated visualization of Escherichia coli labeled by fluorescence in situ hybridization (FISH) with 28 different binary combinations of eight fluorophores. As a biological proof of principle, we then applied this Combinatorial Labeling and Spectral Imaging FISH (CLASI-FISH) strategy using genus-and family-specific probes to visualize simultaneously and differentiate 15 different phylotypes in an artificial mixture of laboratory-grown microbes. We then illustrated the utility of our method for the structural analysis of a natural microbial community, namely, human dental plaque, a microbial biofilm. We demonstrate that 15 taxa in the plaque community can be imaged simultaneously and analyzed and that this community was dominated by early colonizers, including species of Streptococcus, Prevotella, Actinomyces, and Veillonella. Proximity analysis was used to determine the frequency of inter-and intrataxon cell-to-cell associations which revealed statistically significant intertaxon pairings. Cells of the genera Prevotella and Actinomyces showed the most interspecies associations, suggesting a central role for these genera in establishing and maintaining biofilm complexity. The results provide an initial systems-level structural analysis of biofilm organization.cell biology | fluorescence | microbial diversity | oral biofilm

The human oral cavity harbors diverse communities of microbes that live as biofilms: highly ordered, surface-associated assemblages of microbes embedded in an extracellular matrix. Oral microbial communities contribute to human health by fine-tuning immune responses and reducing dietary nitrate. Dental caries and periodontal disease are together the most prevalent microbiallymediated human diseases, worldwide. Both of these oral diseases are known to be caused not by the introduction of exogenous pathogens to the oral environment, but rather by a homeostasis breakdown that leads to changes in the structure of the microbial communities present in states of health. Both dental caries and periodontal disease are mediated by synergistic interactions within communities and both diseases are further driven by specific host inputs: diet and behavior in the case of dental caries and immune system interactions in the case of periodontal disease. Changes in community structure (taxonomic identity and abundance) are well documented during the transition from health to disease. In this review, changes in biofilm physical structure during the transition from oral health to disease and the concomitant relationship between structure and community function will be emphasized.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.