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Bacterial cytokinesis is accomplished by the essential ‘divisome’ machinery. The most widely conserved divisome component, FtsZ, is a tubulin homolog that polymerizes into the ‘FtsZ-ring’ (‘Z-ring’). Previous in vitro studies suggest that Z-ring contraction serves as a major constrictive force generator to limit the progression of cytokinesis. Here, we applied quantitative superresolution imaging to examine whether and how Z-ring contraction limits the rate of septum closure during cytokinesis in Escherichia coli cells. Surprisingly, septum closure rate was robust to substantial changes in all Z-ring properties proposed to be coupled to force generation: FtsZ’s GTPase activity, Z-ring density, and the timing of Z-ring assembly and disassembly. Instead, the rate was limited by the activity of an essential cell wall synthesis enzyme and further modulated by a physical divisome–chromosome coupling. These results challenge a Z-ring–centric view of bacterial cytokinesis and identify cell wall synthesis and chromosome segregation as limiting processes of cytokinesis.

The prokaryotic tubulin homolog, FtsZ, forms a ring-like structure (FtsZ-ring) at midcell. The FtsZ-ring establishes the division plane and enables the assembly of the macromolecular division machinery (divisome). Although many molecular components of the divisome have been identified and their interactions extensively characterized, the spatial organization of these proteins within the divisome is unclear. Consequently, the physical mechanisms that drive divisome assembly, maintenance, and constriction remain elusive. Here we applied single-molecule based superresolution imaging, combined with genetic and biophysical investigations, to reveal the spatial organization of cellular structures formed by four important divisome proteins in E. coli: FtsZ, ZapA, ZapB and MatP. We show that these interacting proteins are arranged into a multi-layered protein network extending from the cell membrane to the chromosome, each with unique structural and dynamic properties. Further, we find that this protein network stabilizes the FtsZ-ring, and unexpectedly, slows down cell constriction, suggesting a new, unrecognized role for this network in bacterial cell division. Our results provide new insight into the structure and function of the divisome, and highlight the importance of coordinated cell constriction and chromosome segregation.

The FtsZ protein, a tubulin-like GTPase, plays a pivotal role in prokaryotic cell division. In vivo it localizes to the midcell and assembles into a ring-like structure-the Z-ring. The Z-ring serves as an essential scaffold to recruit all other division proteins and generates contractile force for cytokinesis, but its supramolecular structure remains unknown. Electron microscopy (EM) has been unsuccessful in detecting the Z-ring due to the dense cytoplasm of bacterial cells, and conventional fluorescence light microscopy (FLM) has only provided images with limited spatial resolution (200-300 nm) due to the diffraction of light. Hence, given the small sizes of bacteria cells, identifying the in vivo structure of the Z-ring presents a substantial challenge. Here, we used photoactivated localization microscopy (PALM), a single molecule-based super-resolution imaging technique, to characterize the in vivo structure of the Z-ring in E. coli. We achieved a spatial resolution of ∼35 nm and discovered that in addition to the expected ring-like conformation, the Z-ring of E. coli adopts a novel compressed helical conformation with variable helical length and pitch. We measured the thickness of the Z-ring to be ∼110 nm and the packing density of FtsZ molecules inside the Z-ring to be greater than what is expected for a single-layered flat ribbon configuration. Our results strongly suggest that the Z-ring is composed of a loose bundle of FtsZ protofilaments that randomly overlap with each other in both longitudinal and radial directions of the cell. Our results provide significant insight into the spatial organization of the Z-ring and open the door for further investigations of structure-function relationships and cell cycle-dependent regulation of the Z-ring.

BackgroundEmerging data suggest predictive biomarkers based on the spatial arrangement of cells or coexpression patterns in tissue sections will play an important role in precision immuno-oncology. Multiplexed immunofluorescence (mIF) is ideally suited to such assessments. Standardization and validation of an end-to-end workflow that supports multisite trials and clinical laboratory processes are vital. Six institutions collaborated to: (1) optimize an automated six-plex assay focused on the PD-1/PD-L1 axis, (2) assess intersite and intrasite reproducibility of staining using a locked down image analysis algorithm to measure tumor cell and immune cell (IC) subset densities, %PD-L1 expression on tumor cells (TCs) and ICs, and PD-1/PD-L1 proximity assessments.MethodsA six-plex mIF panel (PD-L1, PD-1, CD8, CD68, FOXP3, and CK) was rigorously optimized as determined by quantitative equivalence to immunohistochemistry (IHC) chromogenic assays. Serial sections from tonsil and breast carcinoma and non-small cell lung cancer (NSCLC) tissue microarrays (TMAs), TSA-Opal fluorescent detection reagents, and antibodies were distributed to the six sites equipped with a Leica Bond Rx autostainer and a Vectra Polaris multispectral imaging platform. Tissue sections were stained and imaged at each site and delivered to a single site for analysis. Intersite and intrasite reproducibility were assessed by linear fits to plots of cell densities, including %PDL1 expression by TCs and ICs in the breast and NSCLC TMAs.ResultsComparison of the percent positive cells for each marker between mIF and IHC revealed that enhanced amplification in the mIF assay was required to detect low-level expression of PD-1, PD-L1, FoxP3 and CD68. Following optimization, an average equivalence of 90% was achieved between mIF and IHC across all six assay markers. Intersite and intrasite cell density assessments showed an average concordance of R2=0.75 (slope=0.92) and R2=0.88 (slope=0.93) for breast carcinoma, respectively, and an average concordance of R2=0.72 (slope=0.86) and R2=0.81 (slope=0.68) for NSCLC. Intersite concordance for %PD-L1+ICs had an average R2 value of 0.88 and slope of 0.92. Assessments of PD-1/PD-L1 proximity also showed strong concordance (R2=0.82; slope=0.75).ConclusionsAssay optimization yielded highly sensitive, reproducible mIF characterization of the PD-1/PD-L1 axis across multiple sites. High concordance was observed across sites for measures of density of specific IC subsets, measures of coexpression and proximity with single-cell resolution.

Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (t(Thresh) and d(Thresh)) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems.

Summary This review provides a practical introduction to superresolution microscopy from the perspective of microbiological research. Because of the small sizes of bacterial cells, superresolution methods are particularly powerful and suitable for revealing details of cellular structures that are not resolvable under conventional fluorescence light microscopy. Here we describe the methodological concepts behind three major categories of superresolution light microscopy: photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) and stimulated emission‐depletion (STED) microscopy. We then present recent applications of each of these techniques to microbial systems, which have revealed novel conformations of cellular structures and described new properties of in vivo protein function and interactions. Finally, we discuss the unique issues related to implementing each of these superresolution techniques with bacterial specimens and suggest avenues for future development. The goal of this review is to provide the necessary technical background for interested microbiologists to choose the appropriate superresolution method for their biological systems, and to introduce the practical considerations required for designing and analysing superresolution imaging experiments.

The prokaryotic tubulin homolog, FtsZ, forms a ring-like structure (FtsZ-ring) at midcell. The FtsZ-ring establishes the division plane and enables the assembly of the macromolecular division machinery (divisome). Although many molecular components of the divisome have been identified and their interactions extensively characterized, the spatial organization of these proteins within the divisome is unclear. Consequently, the physical mechanisms that drive divisome assembly, maintenance, and constriction remain elusive. Here we applied single-molecule based superresolution imaging, combined with genetic and biophysical investigations, to reveal the spatial organization of cellular structures formed by four important divisome proteins in E. coli: FtsZ, ZapA, ZapB and MatP. We show that these interacting proteins are arranged into a multi-layered protein network extending from the cell membrane to the chromosome, each with unique structural and dynamic properties. Further, we find that this protein network stabilizes the FtsZ-ring, and unexpectedly, slows down cell constriction, suggesting a new, unrecognized role for this network in bacterial cell division. Our results provide new insight into the structure and function of the divisome, and highlight the importance of coordinated cell constriction and chromosome segregation.

BackgroundHematoxylin and eosin (H&E) staining is a traditional and widely used histological stain for elucidating tissue morphology for pathological review. However, H&E staining is not fully removable and prevents or severely limits any further use of the same tissue section. We have developed a method for accurately simulating the H&E staining pattern via removable fluorescent dyes that allows for subsequent re-use of the same tissue section for multiplexed immunofluorescent (mIF) staining methods with no decrease in performance. This workflow allows for the pathological pre-screening, annotation, and triaging of samples to undergo multiplexed IHC.This study demonstrates a novel procedure for creating a realistic and accurate ‘H&E’ view of formalin-fixed, paraffin-embedded (FFPE) sections stained with mIF protocols. The novel stain reveals morphological details and can be removed before applying Akoya Biosciences ‘MOTiF’ 6-plex mIF staining.MethodsSerial FFPE lung cancer sections were used in this study. After deparaffinization and rehydration, these slides were divided into 3 groups. The first group was stained with a traditional H&E protocol. The second group was stained using a MOTiF™ PD-1/PD-L1 Panel kit (Akoya Biosciences, Inc.). The third group was stained with H&E simulation staining reagents, imaged and re-stained using a MOTiF™ PD-1/PD-L1 Panel kit (Akoya Biosciences, Inc.) after removal of the H&E simulation reagents. Multispectral fluorescence imagery was acquired on a Vectra Polaris® automated imaging system and analyzed with inForm® and RStudio software. H&E simulation images are manipulated to represent bright-field H&E using Phenochart and inForm® software (Akoya Biosciences, Inc.).ResultsMimic bright-field H&E images from the simulated H&E staining produced results qualitatively indistinguishable from the traditional H&E-stained lung cancer section. Spectral unmixing and staining intensity analysis showed an improvement in signal for all protein targets in the mIF staining from the simulated H&E-stained group (third group) versus the non-simulated H&E-stained group (second group). Background staining analysis showed no significant corresponding increase in background signal across any of the mIF channels.ConclusionsThis new fluorescent morphology staining method for creating a simulated H&E view facilitates the integration of mIF analysis methods into digital pathology workflows by giving pathologists familiar, conventional views of mIF-stained tissue sections. It enables the assessment of tissue quality prior to antigen retrieval treatment and the H&E-based annotation of mIF imagery and supports eventual translation of mIF methods into clinical standards-of-care.

Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (t.sub.Thresh and d.sub.Thresh) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems.