Epithelial-derived interleukin-23 promotes oral mucosal immunopathology.

At mucosal surfaces, epithelial cells provide a structural barrier and an immune defense system. However, dysregulated epithelial responses can contribute to disease states. Here, we demonstrated that epithelial cell-intrinsic production of interleukin-23 (IL-23) triggers an inflammatory loop in the prevalent oral disease periodontitis. Epithelial IL-23 expression localized to areas proximal to the disease-associated microbiome and was evident in experimental models and patients with common and genetic forms of disease. Mechanistically, flagellated microbial species of the periodontitis microbiome triggered epithelial IL-23 induction in a TLR5 receptor-dependent manner. Therefore, unlike other Th17-driven diseases, non-hematopoietic-cell-derived IL-23 served as an initiator of pathogenic inflammation in periodontitis. Beyond periodontitis, analysis of publicly available datasets revealed the expression of epithelial IL-23 in settings of infection, malignancy, and autoimmunity, suggesting a broader role for epithelial-intrinsic IL-23 in human disease. Collectively, this work highlights an important role for the barrier epithelium in the induction of IL-23-mediated inflammation.

In Vitro Dental Plaque Culture Model for Biofilm Structural Analyses.

Extensive research has focused on the compositional changes in dental plaque microbiome communities during the transition from health to disease, known as dysbiosis. However, alterations in the spatial composition of these communities throughout the progression from health to disease remain under-explored. We describe an in vitro dental plaque model for culturing oral biofilms seeded with dental plaque from human volunteers. Our model recapitulates important features of the in vivo environment including shear force induced by salivary flow over teeth and the nutritional milieu experienced by microbes that inhabit the transitional zone between supragingival and subgingival aspects of the teeth. Importantly, our model is amenable to multiplex fluorescent labeling and multispectral imaging for testing specific hypotheses regarding systems-level community structure and function. The model allows for precise manipulation of various environmental conditions, such as flow rate and nutrient availability to investigate their effects on biofilm development and spatial structure. Furthermore, this model can be used to test the effects of various therapeutic interventions, e.g., antimicrobial agents, on the biofilm composition and structure at the micron to millimeter scale, making it a valuable tool for studying the molecular and cellular basis of dental plaque-mediated diseases and for benchmarking new therapeutic interventions. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Dental plaque-on-a-chip in vitro model culture system Support Protocol: Gingival margin (GM) medium preparation Basic Protocol 2: Microcosm labeling and multispectral image acquisition.

A feedback loop between heterochromatin and the nucleopore complex controls germ-cell-to-oocyte transition during Drosophila oogenesis.

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.

Unmixing biological fluorescence image data with sparse and low-rank Poisson regression.

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.

Gnotobiotic zebrafish microbiota display inter-individual variability affecting host physiology.

Gnotobiotic animal models reconventionalized under controlled laboratory conditions with multi-species bacterial communities are commonly used to study host-microbiota interactions under presumably more reproducible conditions than conventional animals. The usefulness of these models is however limited by inter-animal variability in bacterial colonization and our general lack of understanding of the inter-individual fluctuation and spatio-temporal dynamics of microbiota assemblies at the micron to millimeter scale. Here, we show underreported variability in gnotobiotic models by analyzing differences in gut colonization efficiency, bacterial composition, and host intestinal mucus production between conventional and gnotobiotic zebrafish larvae re-conventionalized with a mix of 9 bacteria isolated from conventional microbiota. Despite similar bacterial community composition, we observed high variability in the spatial distribution of bacteria along the intestinal tract in the reconventionalized model. We also observed that, whereas bacteria abundance and intestinal mucus per fish were not correlated, reconventionalized fish had lower intestinal mucus compared to conventional animals, indicating that the stimulation of mucus production depends on the microbiota composition. Our findings, therefore, suggest that variable colonization phenotypes affect host physiology and impact the reproducibility of experimental outcomes in studies that use gnotobiotic animals. This work provides insights into the heterogeneity of gnotobiotic models and the need to accurately assess re-conventionalization for reproducibility in host-microbiota studies.

Unmixing Biological Fluorescence Image Data with Sparse and Low-Rank Poisson Regression.

Multispectral biological fluorescence microscopy has enabled the identification of multiple targets in complex samples. The accuracy in the unmixing result degrades (1) as the number of fluorophores used in any experiment increases and (2) 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. We propose a regularized sparse and low-rank Poisson unmixing approach (SL-PRU) to deconvolve spectral images labeled with highly overlapping fluorophores which are recorded in low signal-to-noise regimes. Firstly, SL-PRU implements multi-penalty terms when pursuing sparseness and spatial correlation of the resulting abundances in small neighborhoods simultaneously. Secondly, SL-PRU makes use of Poisson regression for unmixing instead of least squares regression to better estimate photon abundance. Thirdly, 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.

Spatial scale in analysis of the dental plaque microbiome.

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.

Recent progress in analyzing the spatial structure of the human microbiome: distinguishing biogeography and architecture in the oral and gut communities.

Fueled by technological advances in methods for sample collection and preservation in sequencing studies, and in advances in computational analyses of high content image data, the spatial structure of the human microbiome is coming to light. In this mini-review, we summarize recent developments in our understanding of the structure of two human microbiomes: the lower gut and the oral cavity. We focus on only the most recent literature and we make an important distinction between two forms of spatial structure, governed by scale: biogeography and architecture. By segmenting the study of microbiome spatial structure into two categories, we demonstrate the potential to greatly advance our understanding of the mechanistic principles that link structure and function in the microbiome.

Interactions between Candida albicans and Enterococcus faecalis in an Organotypic Oral Epithelial Model.

Candida albicans as an opportunistic pathogen exploits the host immune system and causes a variety of life-threatening infections. The polymorphic nature of this fungus gives it tremendous advantage to breach mucosal barriers and cause oral and disseminated infections. Similar to C. albicans, Enterococcus faecalis is a major opportunistic pathogen, which is of critical concern in immunocompromised patients. There is increasing evidence that E. faecalis co-exists with C. albicans in the human body in disease samples. While the interactive profiles between these two organisms have been studied on abiotic substrates and mouse models, studies on their interactions on human oral mucosal surfaces are non-existent. Here, for the first time, we comprehensively characterized the interactive profiles between laboratory and clinical isolates of C. albicans (SC5314 and BF1) and E. faecalis (OG1RF and P52S) on an organotypic oral mucosal model. Our results demonstrated that the dual species biofilms resulted in profound surface erosion and significantly increased microbial invasion into mucosal compartments, compared to either species alone. Notably, several genes of C. albicans involved in tissue adhesion, hyphal formation, fungal invasion, and biofilm formation were significantly upregulated in the presence of E. faecalis. By contrast, E. faecalis genes involved in quorum sensing, biofilm formation, virulence, and mammalian cell invasion were downregulated. This study highlights the synergistic cross-kingdom interactions between E. faecalis and C. albicans in mucosal tissue invasion.

The Structure of Dental Plaque Microbial Communities in the Transition from Health to Dental Caries and Periodontal Disease.

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.

Interacting organelles.

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.

Multispectral Live-Cell Imaging.

Fluorescent proteins and vital dyes are invaluable tools for studying dynamic processes within living cells. However, the ability to distinguish more than a few different fluorescent reporters in a single sample is limited by the spectral overlap of available fluorophores. Here, we present a protocol for imaging live cells labeled with six fluorophores simultaneously. A confocal microscope with a spectral detector is used to acquire images, and linear unmixing algorithms are applied to identify the fluorophores present in each pixel of the image. We describe the application of this method to visualize the dynamics of six different organelles, and to quantify the contacts between organelles. However, this method can be used to image any molecule amenable to tagging with a fluorescent probe. Thus, multispectral live-cell imaging is a powerful tool for systems-level analysis of cellular organization and dynamics. © 2018 by John Wiley & Sons, Inc.

Membrane dynamics and organelle biogenesis-lipid pipelines and vesicular carriers.

Discoveries spanning several decades have pointed to vital membrane lipid trafficking pathways involving both vesicular and non-vesicular carriers. But the relative contributions for distinct membrane delivery pathways in cell growth and organelle biogenesis continue to be a puzzle. This is because lipids flow from many sources and across many paths via transport vesicles, non-vesicular transfer proteins, and dynamic interactions between organelles at membrane contact sites. This forum presents our latest understanding, appreciation, and queries regarding the lipid transport mechanisms necessary to drive membrane expansion during organelle biogenesis and cell growth.

Applying systems-level spectral imaging and analysis to reveal the organelle interactome.

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 ß-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.

Multiplexed Spectral Imaging of 120 Different Fluorescent Labels.

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.

CLASI-FISH: principles of combinatorial labeling and spectral imaging.

Although the number of phylotypes present in a microbial community may number in the hundreds or more, until recently, fluorescence in situ hybridization has been used to label, at most, only a handful of different phylotypes in a single sample. We recently developed a technique, CLASI-FISH for combinatorial labeling and spectral imaging - fluorescence in situ hybridization, to greatly expand the number of distinguishable taxa in a single FISH experiment. The CLASI technique involves labeling microbes of interest with combinations of probes coupled with spectral imaging to allow the use of fluorophores with highly overlapping excitation and emission spectra. Here, we present the basic principles and theory of CLASI-FISH along with some guidelines for performing CLASI-FISH experiments. We further include a protocol for creating fluorescence spectral reference standards, a vital component of successful CLASI-FISH.

Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging.

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.