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 microbially mediated 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.
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•Dental caries and periodontal disease are the most prevalent microbially mediated diseases that afflict humans.•Dental plaque has a highly ordered structure mediated by intercellular interactions, and environmental and host inputs.•Periodontal disease is associated with shifts in microbial community structure, that is, taxonomic membership and abundance.•Periodontal disease is thought to be mediated by synergist interactions between subgingival microbial communities and host.•Spatial structure of intact supragingival and subgingival biofilms is equally important as taxonomic composition for understanding microbiome changes in health and disease.
Interacting organelles Cohen, Sarah; Valm, Alex M; Lippincott-Schwartz, Jennifer
Current opinion in cell biology,
08/2018, Letnik:
53
Journal Article
Recenzirano
Odprti dostop
Eukaryotic cells are organized into membrane-bound organelles. These organelles communicate with one another through vesicular trafficking pathways and membrane contact sites (MCSs). MCSs are sites ...of close apposition between two or more organelles that play diverse roles in the exchange of metabolites, lipids and proteins. Organelle interactions at MCSs also are important for organelle division and biogenesis. For example, the division of several organelles, including mitochondria and endosomes, seem to be regulated by contacts with the endoplasmic reticulum (ER). Moreover, the biogenesis of autophagosomes and peroxisomes involves contributions from the ER and multiple other cellular compartments. Thus, organelle-organelle interactions allow cells to alter the shape and activities of their membrane-bound compartments, allowing them to cope with different developmental and environmental conditions.
The number of fluorescent labels that can unambiguously be distinguished in a single image when acquired through band pass filters is severely limited by the spectral overlap of available ...fluorophores. The recent development of spectral microscopy and the application of linear unmixing algorithms to spectrally recorded image data have allowed simultaneous imaging of fluorophores with highly overlapping spectra. However, the number of distinguishable fluorophores is still limited by the unavoidable decrease in signal to noise ratio when fluorescence signals are fractionated over multiple wavelength bins. Here we present a spectral image analysis algorithm to greatly expand the number of distinguishable objects labeled with binary combinations of fluorophores. Our algorithm utilizes a priori knowledge about labeled specimens and imposes a binary label constraint on the unmixing solution. We have applied our labeling and analysis strategy to identify microbes labeled by fluorescence in situ hybridization and here demonstrate the ability to distinguish 120 differently labeled microbes in a single image.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The organization of the eukaryotic cell into discrete membrane-bound organelles allows for the separation of incompatible biochemical processes, but the activities of these organelles must be ...coordinated. For example, lipid metabolism is distributed between the endoplasmic reticulum for lipid synthesis, lipid droplets for storage and transport, mitochondria and peroxisomes for β-oxidation, and lysosomes for lipid hydrolysis and recycling. It is increasingly recognized that organelle contacts have a vital role in diverse cellular functions. However, the spatial and temporal organization of organelles within the cell remains poorly characterized, as fluorescence imaging approaches are limited in the number of different labels that can be distinguished in a single image. 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 used confocal and lattice light sheet 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 cells from a monkey fibroblast cell line. We describe the frequency and locality of two-, three-, four- and five-way interactions among six different membrane-bound organelles (endoplasmic reticulum, Golgi, lysosome, peroxisome, mitochondria and lipid droplet) 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, that is affected by microtubule and cell nutrient status. These live-cell confocal and lattice light sheet 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 descriptive tool and can be used to develop hypotheses about cellular organization and dynamics.
Ecologists have long recognized the importance of spatial scale in understanding structure‐function relationships among communities of organisms within their environment. Here, we review historical ...and contemporary studies of dental plaque community structure in the context of three distinct scales: the micro (1‐10 µm), meso (10‐100 µm) and macroscale (100 µm to ≥1 cm). Within this framework, we analyze the compositional nature of dental plaque at the macroscale, the molecular interactions of microbes at the microscale, and the emergent properties of dental plaque biofilms at the mesoscale. Throughout our analysis of dental plaque across spatial scales, we draw attention to disease and health‐associated structure‐function relationships and include a discussion of host immune involvement in the mesoscale structure of periodontal disease–associated biofilms. We end with a discussion of two filamentous organisms, Fusobacterium nucleatum and Corynebacterium matruchotii, and their relevant contributions in structuring dental plaque biofilms.
Abstract
Motivation
Multispectral biological fluorescence microscopy has enabled the identification of multiple targets in complex samples. The accuracy in the unmixing result degrades (i) as the ...number of fluorophores used in any experiment increases and (ii) as the signal-to-noise ratio in the recorded images decreases. Further, the availability of prior knowledge regarding the expected spatial distributions of fluorophores in images of labeled cells provides an opportunity to improve the accuracy of fluorophore identification and abundance.
Results
We propose a regularized sparse and low-rank Poisson regression unmixing approach (SL-PRU) to deconvolve spectral images labeled with highly overlapping fluorophores which are recorded in low signal-to-noise regimes. First, SL-PRU implements multipenalty terms when pursuing sparseness and spatial correlation of the resulting abundances in small neighborhoods simultaneously. Second, SL-PRU makes use of Poisson regression for unmixing instead of least squares regression to better estimate photon abundance. Third, we propose a method to tune the SL-PRU parameters involved in the unmixing procedure in the absence of knowledge of the ground truth abundance information in a recorded image. By validating on simulated and real-world images, we show that our proposed method leads to improved accuracy in unmixing fluorophores with highly overlapping spectra.
Availability and implementation
The source code used for this article was written in MATLAB and is available with the test data at https://github.com/WANGRUOGU/SL-PRU.
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.
Lung 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.
Overall, 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.
The 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.
Germ cells differentiate into oocytes that launch the next generation upon fertilization. How the highly specialized oocyte acquires this distinct cell fate is poorly understood. During Drosophila ...oogenesis, H3K9me3 histone methyltransferase SETDB1 translocates from the cytoplasm to the nucleus of germ cells concurrently with oocyte specification. Here, we discovered that nuclear SETDB1 is required for silencing a cohort of differentiation-promoting genes by mediating their heterochromatinization. Intriguingly, SETDB1 is also required for upregulating 18 of the ∼30 nucleoporins (Nups) that compose the nucleopore complex (NPC), promoting NPC formation. NPCs anchor SETDB1-dependent heterochromatin at the nuclear periphery to maintain H3K9me3 and gene silencing in the egg chambers. Aberrant gene expression due to the loss of SETDB1 or Nups results in the loss of oocyte identity, cell death, and sterility. Thus, a feedback loop between heterochromatin and NPCs promotes transcriptional reprogramming at the onset of oocyte specification, which is critical for establishing oocyte identity.
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•H3K9me3 heterochromatin silences early-oogenesis genes during oocyte specification•H3K9me3 heterochromatin is required for nucleopore complex formation•Function of NPCs is required for silencing early-oogenesis genes•Silencing of early-oogenesis genes is essential for the maintenance of oocyte fate
Sarkar et al. describe how a cohort of early-oogenesis genes are silenced by heterochromatin formation during oocyte specification. The heterochromatin promotes nucleopore complex (NPC) formation, which in turn helps maintain silenced genes to developmentally regulate gene silencing and fertility.
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