Cyanobacterial phycobilisome (PBS) pigment-protein complexes harvest light and transfer the energy to reaction centers. Previous ensemble studies have shown that cyanobacteria respond to changes in nutrient availability by modifying the structure of PBS complexes, but this process has not been visualized for individual pigments at the single-cell level due to spectral overlap. We characterized the response of four key photosynthetic pigments to nitrogen depletion and repletion at the subcellular level in individual, live Synechocystis sp. PCC 6803 cells using hyperspectral confocal fluorescence microscopy and multivariate image analysis. Our results revealed that PBS degradation and re-synthesis comprise a rapid response to nitrogen fluctuations, with coordinated populations of cells undergoing pigment modifications. Chlorophyll fluorescence originating from photosystem I and II decreased during nitrogen starvation, but no alteration in subcellular chlorophyll localization was found. We observed differential rod and core pigment responses to nitrogen deprivation, suggesting that PBS complexes undergo a stepwise degradation process.
Herein, we describe a novel multifunctional metal-organic framework (MOF) materials platform that displays both porosity and tunable emission properties as a function of the metal identity (Eu, Nd, and tuned compositions of Nd/Yb). Their emission collectively spans the deep red to near-infrared (NIR) spectral region (∼614-1350 nm), which is highly relevant for in vivo bioimaging. These new materials meet important prerequisites as relevant to biological processes: they are minimally toxic to living cells and retain structural integrity in water and phosphate-buffered saline. To assess their viability as optical bioimaging agents, we successfully synthesized the nanoscale Eu analog as a proof-of-concept system in this series. In vitro studies show that it is cell-permeable in individual RAW 264.7 mouse macrophage and HeLa human cervical cancer tissue culture cells. The efficient discrimination between the Eu emission and cell autofluorescence was achieved with hyperspectral confocal fluorescence microscopy, used here for the first time to characterize MOF materials. Importantly, this is the first report that documents the long-term conservation of the intrinsic emission in live cells of a fluorophore-based MOF to date (up to 48 h). This finding, in conjunction with the materials' very low toxicity, validates the biocompatibility in these systems and qualifies them as promising for use in long-term tracking and biodistribution studies.
Photosystem I (PSI) is the dominant photosystem in cyanobacteria and it plays a pivotal role in cyanobacterial metabolism. Despite its biological importance, the native organization of PSI in cyanobacterial thylakoid membranes is poorly understood. Here, we use atomic force microscopy (AFM) to show that ordered, extensive macromolecular arrays of PSI complexes are present in thylakoids from Thermosynechococcus elongatus, Synechococcus sp PCC 7002, and Synechocystis sp PCC 6803. Hyperspectral confocal fluorescence microscopy and three-dimensional structured illumination microscopy of Synechocystis sp PCC 6803 cells visualize PSI domains within the context of the complete thylakoid system. Crystallographic and AFM data were used to build a structural model of a membrane landscape comprising 96 PSI trimers and 27,648 chlorophyll a molecules. Rather than facilitating intertrimer energy transfer, the close associations between PSI primarily maximize packing efficiency; short-range interactions with Complex I and cytochrome b6f are excluded from these regions of the membrane, so PSI turnover is sustained by long-distance diffusion of the electron donors at the membrane surface. Elsewhere, PSI-photosystem II contact zones provide sites for docking phycobilisomes and the formation of megacomplexes. PSI-enriched domains in cyanobacteria might foreshadow the partitioning of PSI into stromal lamellae in plants, similarly sustained by long-distance diffusion of electron carriers.
Cosmic ray spikes are especially problematic for hyperspectral imaging because of the large number of spikes often present and their negative effects upon subsequent chemometric analysis. Fortunately, while the large number of spectra acquired in a hyperspectral imaging data set increases the probability and number of cosmic spikes observed, the multitude of spectra can also aid in the effective recognition and removal of the cosmic spikes. Zhang and Ben-Amotz were perhaps the first to leverage the additional spatial dimension of hyperspectral data matrices (DM). They integrated principal component analysis (PCA) into the upper bound spectrum method (UBS), resulting in a hybrid method (UBS-DM) for hyperspectral images. Here, we expand upon their use of PCA, recognizing that principal components primarily present in only a few pixels most likely correspond to cosmic spikes. Eliminating the contribution of those principal components in those pixels improves the cosmic spike removal. Both simulated and experimental hyperspectral Raman image data sets are used to test the newly developed UBS-DM-hyperspectral (UBS-DM-HS) method which extends the UBS-DM method by leveraging characteristics of hyperspectral data sets. A comparison is provided between the performance of the UBS-DM-HS method and other methods suitable for despiking hyperspectral images, evaluating both their ability to remove cosmic ray spikes and the extent to which they introduce spectral bias.
Fungi in the Candida genus are the most common fungal pathogens. They not only cause high morbidity and mortality but can also cost billions of dollars in healthcare. To alleviate this burden, early and accurate identification of Candida species is necessary. However, standard identification procedures can take days and have a large false negative error. The method described in this study takes advantage of hyperspectral confocal fluorescence microscopy, which enables the capability to quickly and accurately identify and characterize the unique autofluorescence spectra from different Candida species with up to 84% accuracy when grown in conditions that closely mimic physiological conditions.