Four-dimensional quantitative analysis of cell plate development in Arabidopsis using lattice light sheet microscopy identifies robust transition points between growth phases.

Cell plate formation during cytokinesis entails multiple stages occurring concurrently and requiring orchestrated vesicle delivery, membrane remodelling, and timely deposition of polysaccharides, such as callose. Understanding such a dynamic process requires dissection in time and space; this has been a major hurdle in studying cytokinesis. Using lattice light sheet microscopy (LLSM), we studied cell plate development in four dimensions, through the behavior of yellow fluorescent protein (YFP)-tagged cytokinesis-specific GTPase RABA2a vesicles. We monitored the entire duration of cell plate development, from its first emergence, with the aid of YFP-RABA2a, in both the presence and absence of cytokinetic callose. By developing a robust cytokinetic vesicle volume analysis pipeline, we identified distinct behavioral patterns, allowing the identification of three easily trackable cell plate developmental phases. Notably, the phase transition between phase I and phase II is striking, indicating a switch from membrane accumulation to the recycling of excess membrane material. We interrogated the role of callose using pharmacological inhibition with LLSM and electron microscopy. Loss of callose inhibited the phase transitions, establishing the critical role and timing of the polysaccharide deposition in cell plate expansion and maturation. This study exemplifies the power of combining LLSM with quantitative analysis to decode and untangle such a complex process.

Semi-blind sparse affine spectral unmixing of autofluorescence-contaminated micrographs.

MOTIVATION: Spectral unmixing methods attempt to determine the concentrations of different fluorophores present at each pixel location in an image by analyzing a set of measured emission spectra. Unmixing algorithms have shown great promise for applications where samples contain many fluorescent labels; however, existing methods perform poorly when confronted with autofluorescence-contaminated images. RESULTS: We propose an unmixing algorithm designed to separate fluorophores with overlapping emission spectra from contamination by autofluorescence and background fluorescence. First, we formally define a generalization of the linear mixing model, called the affine mixture model (AMM), that specifically accounts for background fluorescence. Second, we use the AMM to derive an affine nonnegative matrix factorization method for estimating fluorophore endmember spectra from reference images. Lastly, we propose a semi-blind sparse affine spectral unmixing (SSASU) algorithm that uses knowledge of the estimated endmembers to learn the autofluorescence and background fluorescence spectra on a per-image basis. When unmixing real-world spectral images contaminated by autofluorescence, SSASU greatly improved proportion indeterminacy as compared to existing methods for a given relative reconstruction error. AVAILABILITY AND IMPLEMENTATION: The source code used for this paper was written in Julia and is available with the test data at https://github.com/brossetti/ssasu.

Biogeography of a human oral microbiome at the micron scale.

The spatial organization of complex natural microbiomes is critical to understanding the interactions of the individual taxa that comprise a community. Although the revolution in DNA sequencing has provided an abundance of genomic-level information, the biogeography of microbiomes is almost entirely uncharted at the micron scale. Using spectral imaging fluorescence in situ hybridization as guided by metagenomic sequence analysis, we have discovered a distinctive, multigenus consortium in the microbiome of supragingival dental plaque. The consortium consists of a radially arranged, nine-taxon structure organized around cells of filamentous corynebacteria. The consortium ranges in size from a few tens to a few hundreds of microns in radius and is spatially differentiated. Within the structure, individual taxa are localized at the micron scale in ways suggestive of their functional niche in the consortium. For example, anaerobic taxa tend to be in the interior, whereas facultative or obligate aerobes tend to be at the periphery of the consortium. Consumers and producers of certain metabolites, such as lactate, tend to be near each other. Based on our observations and the literature, we propose a model for plaque microbiome development and maintenance consistent with known metabolic, adherence, and environmental considerations. The consortium illustrates how complex structural organization can emerge from the micron-scale interactions of its constituent organisms. The understanding that plaque community organization is an emergent phenomenon offers a perspective that is general in nature and applicable to other microbiomes.

Microbiota organization is a distinct feature of proximal colorectal cancers.

Environmental factors clearly affect colorectal cancer (CRC) incidence, but the mechanisms through which these factors function are unknown. One prime candidate is an altered colonic microbiota. Here we show that the mucosal microbiota organization is a critical factor associated with a subset of CRC. We identified invasive polymicrobial bacterial biofilms (bacterial aggregates), structures previously associated with nonmalignant intestinal pathology, nearly universally (89%) on right-sided tumors (13 of 15 CRCs, 4 of 4 adenomas) but on only 12% of left-sided tumors (2 of 15 CRCs, 0 of 2 adenomas). Surprisingly, patients with biofilm-positive tumors, whether cancers or adenomas, all had biofilms on their tumor-free mucosa far distant from their tumors. Bacterial biofilms were associated with diminished colonic epithelial cell E-cadherin and enhanced epithelial cell IL-6 and Stat3 activation, as well as increased crypt epithelial cell proliferation in normal colon mucosa. High-throughput sequencing revealed no consistent bacterial genus associated with tumors, regardless of biofilm status. However, principal coordinates analysis revealed that biofilm communities on paired normal mucosa, distant from the tumor itself, cluster with tumor microbiomes as opposed to biofilm-negative normal mucosa bacterial communities also from the tumor host. Colon mucosal biofilm detection may predict increased risk for development of sporadic CRC.

Clumped Nuclei Segmentation with Adjacent Point Match and Local Shape-Based Intensity Analysis in Fluorescence Microscopy Images.

Highly clumped nuclei captured in fluorescence microscopy images are commonly observed in a wide spectrum of tissue-related biomedical investigations. To ensure the quality of downstream biomedical analyses, it is essential to accurately segment clustered nuclei. However, this presents a technical challenge as fluorescence intensity alone is often insufficient for recovering the true nuclei boundaries. In this paper, we propose an segmentation algorithm that identifies point pair connection candidates and evaluates adjacent point connections with a formulated ellipse fitting quality indicator. After connection relationships are determined, we recover the resulting dividing paths by following points with specific eigenvalues from the image Hessian in a constrained searching space. We validate our algorithm with 560 image patches from two classes of tumor regions of seven brain tumor patients. Both qualitative and quantitative experimental results suggest that our algorithm is promising for dividing overlapped nuclei in fluorescence microscopy images widely used in various biomedical research.

Preservation of three-dimensional spatial structure in the gut microbiome.

Preservation of three-dimensional structure in the gut is necessary in order to analyze the spatial organization of the gut microbiota and gut luminal contents. In this study, we evaluated preparation methods for mouse gut with the goal of preserving micron-scale spatial structure while performing fluorescence imaging assays. Our evaluation of embedding methods showed that commonly used media such as Tissue-Tek Optimal Cutting Temperature (OCT) compound, paraffin, and polyester waxes resulted in redistribution of luminal contents. By contrast, a hydrophilic methacrylate resin, Technovit H8100, preserved three-dimensional organization. Our mouse intestinal preparation protocol optimized using the Technovit H8100 embedding method was compatible with microbial fluorescence in situ hybridization (FISH) and other labeling techniques, including immunostaining and staining with both wheat germ agglutinin (WGA) and 4', 6-diamidino-2-phenylindole (DAPI). Mucus could be visualized whether the sample was fixed with paraformaldehyde (PFA) or with Carnoy's fixative. The protocol optimized in this study enabled simultaneous visualization of micron-scale spatial patterns formed by microbial cells in the mouse intestines along with biogeographical landmarks such as host-derived mucus and food particles.

DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES.

High-throughput serial histology imaging provides a new avenue for the routine study of micro-anatomical structures in a 3D space. However, the emergence of serial whole slide imaging poses a new registration challenge, as the gigapixel image size precludes the direct application of conventional registration techniques. In this paper, we develop a three-stage registration with multi-resolution mapping and propagation method to dynamically produce registered subvolumes from serial whole slide images. We validate our algorithm with gigapixel images of serial brain tumor sections and synthetic image volumes. The qualitative and quantitative assessment results demonstrate the efficacy of our approach and suggest its promise for 3D histology reconstruction analysis.

Dynamics of tongue microbial communities with single-nucleotide resolution using oligotyping.

The human mouth is an excellent system to study the dynamics of microbial communities and their interactions with their host. We employed oligotyping to analyze, with single-nucleotide resolution, oral microbial 16S ribosomal RNA (rRNA) gene sequence data from a time course sampled from the tongue of two individuals, and we interpret our results in the context of oligotypes that we previously identified in the oral data from the Human Microbiome Project. Our previous work established that many of these oligotypes had dramatically different distributions between individuals and across oral habitats, suggesting that they represented functionally different organisms. Here we demonstrate the presence of a consistent tongue microbiome but with rapidly fluctuating proportions of the characteristic taxa. In some cases closely related oligotypes representing strains or variants within a single species displayed fluctuating relative abundances over time, while in other cases an initially dominant oligotype was replaced by another oligotype of the same species. We use this high temporal and taxonomic level of resolution to detect correlated changes in oligotype abundance that could indicate which taxa likely interact synergistically or occupy similar habitats, and which likely interact antagonistically or prefer distinct habitats. For example, we found a strong correlation in abundance over time between two oligotypes from different families of Gamma Proteobacteria, suggesting a close functional or ecological relationship between them. In summary, the tongue is colonized by a microbial community of moderate complexity whose proportional abundance fluctuates widely on time scales of days. The drivers and functional consequences of these community dynamics are not known, but we expect they will prove tractable to future, targeted studies employing taxonomically resolved analysis of high-throughput sequencing data sampled at appropriate temporal intervals and spatial scales.