Cell-type-specific transcriptomics uncovers spatial regulatory networks in bioenergy sorghum stems.

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum's 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about cell-type gene expression and regulation in stems was available to enable engineering. To obtain this information, laser capture microdissection was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type-specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type-specific gene regulatory networks (GRNs) revealed that unique transcription factor families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with known secondary cell wall (SCW) networks to identify the GRNs that differentially activate SCW formation in vascular sclerenchyma and epidermal cells. The spatial transcriptomic dataset provides a valuable source of information about the function of different sorghum cell types and GRNs that will enable the engineering of bioenergy sorghum stems, and an interactive web application developed during this project will allow easy access and exploration of the data (https://mc-lab.shinyapps.io/lcm-dataset/).

Shaping Nanobodies and Intrabodies against Proteoforms.

Proteoforms expand genomic diversity and direct developmental processes. While high-resolution mass spectrometry has accelerated characterization of proteoforms, molecular techniques working to bind and disrupt the function of specific proteoforms have lagged behind. In this study, we worked to develop intrabodies capable of binding specific proteoforms. We employed a synthetic camelid nanobody library expressed in yeast to identify nanobody binders of different SARS-CoV-2 receptor binding domain (RBD) proteoforms. Importantly, employment of the positive and negative selection mechanisms inherent to the synthetic system allowed for amplification of nanobody-expressing yeast that bind to the original (Wuhan strain RBD) but not the E484 K (Beta variant) mutation. Nanobodies raised against specific RBD proteoforms were validated by yeast-2-hybrid analysis and sequence comparisons. These results provide a framework for development of nanobodies and intrabodies that target proteoforms.

Capturing an Early Gene Induction Event during Wood Decay by the Brown Rot Fungus Rhodonia placenta.

Brown rot fungi dominate wood decomposition in coniferous forests, and their carbohydrate-selective mechanisms are of commercial interest. Brown rot was recently described as a two-step, sequential mechanism orchestrated by fungi using differentially expressed genes (DEGs) and consisting of oxidation via reactive oxygen species (ROS) followed by enzymatic saccharification. There have been indications, however, that the initial oxidation step itself might require induction. To capture this early gene regulation event, here, we integrated fine-scale cryosectioning with whole-transcriptome sequencing to dissect gene expression at the single-hyphal-cell scale (tens of micrometers). This improved the spatial resolution 50-fold, relative to previous work, and we were able to capture the activity of the first 100 µm of hyphal front growth by Rhodonia placenta in aspen wood. This early decay period was dominated by delayed gene expression patterns as the fungus ramped up its mechanism. These delayed DEGs included many genes implicated in ROS pathways (lignocellulose oxidation [LOX]) that were previously and incorrectly assumed to be constitutively expressed. These delayed DEGs, which include those with and without predicted functions, also create a focused subset of target genes for functional genomics. However, this delayed pattern was not universal, with a few genes being upregulated immediately at the hyphal front. Most notably, this included a gene commonly implicated in hydroquinone and iron redox cycling: benzoquinone reductase. IMPORTANCE Earth's aboveground terrestrial biomass is primarily wood, and fungi dominate wood decomposition. Here, we studied these fungal pathways in a common "brown rot"-type fungus, Rhodonia placenta, that selectively extracts sugars from carbohydrates embedded within wood lignin. Using a space-for-time design to map fungal gene expression at the extreme hyphal front in wood, we made two discoveries. First, we found that many genes long assumed to be "on" (constitutively expressed) from the very beginning of decay were instead "off" before being upregulated, when mapped (via transcriptome sequencing [RNA-seq]) at a high resolution. Second, we found that the gene encoding benzoquinone reductase was "on" in incipient decay and quickly downregulated, implying a key role in "kick-starting" brown rot.

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics.

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

Facile One-Pot Nanoproteomics for Label-Free Proteome Profiling of 50-1000 Mammalian Cells.

Recent advances in sample preparation enable label-free mass spectrometry (MS)-based proteome profiling of small numbers of mammalian cells. However, specific devices are often required to downscale sample processing volume from the standard 50-200 µL to sub-µL for effective nanoproteomics, which greatly impedes the implementation of current nanoproteomics methods by the proteomics research community. Herein, we report a facile one-pot nanoproteomics method termed SOPs-MS (surfactant-assisted one-pot sample processing at the standard volume coupled with MS) for convenient robust proteome profiling of 50-1000 mammalian cells. Building upon our recent development of SOPs-MS for label-free single-cell proteomics at a low µL volume, we have systematically evaluated its processing volume at 10-200 µL using 100 human cells. The processing volume of 50 µL that is in the range of volume for standard proteomics sample preparation has been selected for easy sample handling with a benchtop micropipette. SOPs-MS allows for reliable label-free quantification of ∼1200-2700 protein groups from 50 to 1000 MCF10A cells. When applied to small subpopulations of mouse colon crypt cells, SOPs-MS has revealed protein signatures between distinct subpopulation cells with identification of ∼1500-2500 protein groups for each subpopulation. SOPs-MS may pave the way for routine deep proteome profiling of small numbers of cells and low-input samples.

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography-Mass Spectrometry for High-Throughput Single-Cell Proteomics.

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. We have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ∼77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets.

Current mass spectrometry (MS)-based proteomics approaches are ineffective for mapping protein expression in tissue sections with high spatial resolution because of the limited overall sensitivity of conventional workflows. Here we report an integrated and automated method to advance spatially resolved proteomics by seamlessly coupling laser capture microdissection (LCM) with a recently developed nanoliter-scale sample preparation system termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples). The workflow is enabled by prepopulating nanowells with DMSO, which serves as a sacrificial capture liquid for microdissected tissues. The DMSO droplets efficiently collect laser-pressure catapulted LCM tissues as small as 20 µm in diameter with success rates >87%. We also demonstrate that tissue treatment with DMSO can significantly improve proteome coverage, likely due to its ability to dissolve lipids from tissue and enhance protein extraction efficiency. The LCM-nanoPOTS platform was able to identify 180, 695, and 1827 protein groups on average from 12-µm-thick rat brain cortex tissue sections having diameters of 50, 100, and 200 µm, respectively. We also analyzed 100-µm-diameter sections corresponding to 10-18 cells from three different regions of rat brain and comparatively quantified ∼1000 proteins, demonstrating the potential utility for high-resolution spatially resolved mapping of protein expression in tissues.

Fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) for accurate detection and counting of RNA copies in single cells.

Quantitative gene expression analysis in intact single cells can be achieved using single molecule-based fluorescence in situ hybridization (smFISH). This approach relies on fluorescence intensity to distinguish between true signals, emitted from an RNA copy hybridized with multiple oligonucleotide probes, and background noise. Thus, the precision in smFISH is often compromised by partial or nonspecific probe binding and tissue autofluorescence, especially when only a small number of probes can be fitted to the target transcript. Here we provide an accurate approach for setting quantitative thresholds between true and false signals, which relies on on-off duty cycles of photoswitchable dyes. This fluctuation localization imaging-based FISH (fliFISH) uses on-time fractions (measured over a series of exposures) collected from transcripts bound to as low as 8 probes, which are distinct from on-time fractions collected from nonspecifically bound probes or autofluorescence. Using multicolor fliFISH, we identified radial gene expression patterns in mouse pancreatic islets for insulin, the transcription factor, NKX2-2 and their ratio (Nkx2-2/Ins2). These radial patterns, showing higher values in ß cells at the islet core and lower values in peripheral cells, were lost in diabetic mouse islets. In summary, fliFISH provides an accurate, quantitative approach for detecting and counting true RNA copies and rejecting false signals by their distinct on-time fractions, laying the foundation for reliable single-cell transcriptomics.

High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform.

Effective extension of mass spectrometry-based proteomics to single cells remains challenging. Herein we combined microfluidic nanodroplet technology with tandem mass tag (TMT) isobaric labeling to significantly improve analysis throughput and proteome coverage for single mammalian cells. Isobaric labeling facilitated multiplex analysis of single cell-sized protein quantities to a depth of ∼1 600 proteins with a median CV of 10.9% and correlation coefficient of 0.98. To demonstrate in-depth high throughput single cell analysis, the platform was applied to measure protein expression in 72 single cells from three murine cell populations (epithelial, immune, and endothelial cells) in <2 days instrument time with over 2 300 proteins identified. Principal component analysis grouped the single cells into three distinct populations based on protein expression with each population characterized by well-known cell-type specific markers. Our platform enables high throughput and unbiased characterization of single cell heterogeneity at the proteome level.

Carrier-Assisted Single-Tube Processing Approach for Targeted Proteomics Analysis of Low Numbers of Mammalian Cells.

Heterogeneity in composition is inherent in all cell populations, even those containing a single cell type. Single-cell proteomics characterization of cell heterogeneity is currently achieved by antibody-based technologies, which are limited by the availability of high-quality antibodies. Herein we report a simple, easily implemented, mass spectrometry (MS)-based targeted proteomics approach, termed cLC-SRM (carrier-assisted liquid chromatography coupled to selected reaction monitoring), for reliable multiplexed quantification of proteins in low numbers of mammalian cells. We combine a new single-tube digestion protocol to process low numbers of cells with minimal loss together with sensitive LC-SRM for protein quantification. This single-tube protocol builds upon trifluoroethanol digestion and further minimizes sample losses by tube pretreatment and the addition of carrier proteins. We also optimized the denaturing temperature and trypsin concentration to significantly improve digestion efficiency. cLC-SRM was demonstrated to have sufficient sensitivity for reproducible detection of most epidermal growth factor receptor (EGFR) pathway proteins expressed at levels ≥30 000 and ≥3000 copies per cell for 10 and 100 mammalian cells, respectively. Thus, cLC-SRM enables reliable quantification of low to moderately abundant proteins in less than 100 cells and could be broadly useful for multiplexed quantification of important proteins in small subpopulations of cells or in size-limited clinical samples. Further improvements of this method could eventually enable targeted single-cell proteomics when combined with either SRM or other emerging ultrasensitive MS detection.

Spatially Resolved Proteome Profiling of <200 Cells from Tomato Fruit Pericarp by Integrating Laser-Capture Microdissection with Nanodroplet Sample Preparation.

Due to sensitivity limitations, global proteome measurements generally require large amounts of biological starting material, which masks heterogeneity within the samples and differential protein expression among constituent cell types. Methods for spatially resolved proteomics are being developed to resolve protein expression for distinct cell types among highly heterogeneous tissues, but have primarily been applied to mammalian systems. Here we evaluate the performance of cell-type-specific proteome analysis of tomato fruit pericarp tissues by a platform integrating laser-capture microdissection (LCM) and a recently developed automated sample preparation system (nanoPOTS, nanodroplet processing in one pot for trace samples). Tomato fruits were cryosectioned prior to LCM and tissues were dissected and captured directly into nanoPOTS chips for processing. Following processing, samples were analyzed by nanoLC-MS/MS. Approximately 1900 unique peptides and 422 proteins were identified on average from ∼0.04 mm2 tissues comprising ∼8-15 parenchyma cells. Spatially resolved proteome analyses were performed using cells of outer epidermis, collenchyma, and parenchyma. Using ≤200 cells, a total of 1,870 protein groups were identified and the various tissues were easily resolved. The results provide spatial and tissue-specific insights into key enzymes and pathways involved in carbohydrate transport and source-sink relationships in tomato fruit. Of note, at the time of fruit ripening studied here, we identified differentially abundant proteins throughout the pericarp related to chlorophyll biogenesis, photosynthesis, and especially transport.

Proteomic Analysis of Single Mammalian Cells Enabled by Microfluidic Nanodroplet Sample Preparation and Ultrasensitive NanoLC-MS.

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analyzed by ultrasensitive nanoLC-MS. An average of circa 670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single-cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells.

High resolution visualization and exo-proteomics reveal the physiological role of XlnR and AraR in plant biomass colonization and degradation by Aspergillus niger.

In A. niger, two transcription factors, AraR and XlnR, regulate the production of enzymes involved in degradation of arabinoxylan and catabolism of the released l-arabinose and d-xylose. Deletion of both araR and xlnR in leads to reduced production of (hemi)cellulolytic enzymes and reduced growth on arabinan, arabinogalactan and xylan. In this study, we investigated the colonization and degradation of wheat bran by the A. niger reference strain CBS 137562 and araR/xlnR regulatory mutants using high-resolution microscopy and exo-proteomics. We discovered that wheat bran flakes have a 'rough' and 'smooth' surface with substantially different affinity towards fungal hyphae. While colonization of the rough side was possible for all strains, the xlnR mutants struggled to survive on the smooth side of the wheat bran particles after 20 and 40 h post inoculation. Impaired colonization ability of the smooth surface of wheat bran was linked to reduced potential of ΔxlnR to secrete arabinoxylan and cellulose-degrading enzymes and indicates that XlnR is the major regulator that drives colonization of wheat bran in A. niger.

Sensitive targeted quantification of ERK phosphorylation dynamics and stoichiometry in human cells without affinity enrichment.

Targeted mass spectrometry is a promising technology for site-specific quantification of posttranslational modifications. However, a major constraint is the limited sensitivity for quantifying low-abundance PTMs, requiring the use of affinity reagents for enrichment. Herein, we demonstrate the direct site-specific quantification of ERK phosphorylation isoforms (pT, pY, pTpY) and their relative stoichiometry using a sensitive targeted MS approach termed high-pressure, high-resolution separations with intelligent selection, and multiplexing (PRISM). PRISM provides effective enrichment of target peptides into a given fraction from complex mixture, followed by selected reaction monitoring quantification. Direct quantification of ERK phosphorylation in human mammary epithelial cells (HMEC) was demonstrated from as little as 25 µg tryptic peptides from whole cell lysates. Compared to immobilized metal-ion affinity chromatography, PRISM provided ∼10-fold higher signal intensities, presumably due to the better peptide recovery of PRISM. This approach was applied to quantify ERK phosphorylation dynamics in HMEC treated by different doses of epidermal growth factor at both the peak activation (10 min) and steady state (2 h). The maximal ERK activation was observed with 0.3 and 3 ng/mL doses for 10 min and 2 h time points, respectively. The dose-response profiles of individual phosphorylated isoforms showed that singly phosphorylated pT-ERK never increases significantly, while the increase of pY-ERK paralleled that of pTpY-ERK. This data supports for a processive, rather than distributed model of ERK phosphorylation. The PRISM-SRM quantification of protein phosphorylation illustrates the potential for simultaneous quantification of multiple PTMs.

Lipopolysaccharide Density and Structure Govern the Extent and Distance of Nanoparticle Interaction with Actual and Model Bacterial Outer Membranes.

Design of nanomedicines and nanoparticle-based antimicrobial and antifouling formulations and assessment of the potential implications of nanoparticle release into the environment requires understanding nanoparticle interaction with bacterial surfaces. Here we demonstrate the electrostatically driven association of functionalized nanoparticles with lipopolysaccharides of Gram-negative bacterial outer membranes and find that lipopolysaccharide structure influences the extent and location of binding relative to the outer leaflet-solution interface. By manipulating the lipopolysaccharide content in Shewanella oneidensis outer membranes, we observed the electrostatically driven interaction of cationic gold nanoparticles with the lipopolysaccharide-containing leaflet. We probed this interaction by quartz crystal microbalance with dissipation monitoring (QCM-D) and second harmonic generation (SHG) using solid-supported lipopolysaccharide-containing bilayers. The association of cationic nanoparticles increased with lipopolysaccharide content, while no association of anionic nanoparticles was observed. The harmonic-dependence of QCM-D measurements suggested that a population of the cationic nanoparticles was held at a distance from the outer leaflet-solution interface of bilayers containing smooth lipopolysaccharides (those bearing a long O-polysaccharide). Additionally, smooth lipopolysaccharides held the bulk of the associated cationic particles outside of the interfacial zone probed by SHG. Our results demonstrate that positively charged nanoparticles are more likely to interact with Gram-negative bacteria than are negatively charged particles, and this interaction occurs primarily through lipopolysaccharides.

In situ molecular imaging of a hydrated biofilm in a microfluidic reactor by ToF-SIMS.

A novel microfluidic reactor for biofilm growth and in situ characterization using time-of-flight secondary ion mass spectrometry (ToF-SIMS) was constructed to enable two-dimensional chemical imaging of hydrated biofilms. We demonstrate the detection of characteristic fatty acid fragments from microfluidic reactor-grown biofilms and illustrate advantages of hydrated-state ToF-SIMS imaging.

Organelle-specific activity-based protein profiling in living cells.

A multimodal activity-based probe for targeting acidic organelles was developed to measure subcellular native enzymatic activity in cells by fluorescence microscopy and mass spectrometry. A cathepsin-reactive warhead conjugated to a weakly basic amine and a clickable alkyne, for subsequent appendage of a fluorophore or biotin reporter tag, accumulated in lysosomes as observed by structured illumination microscopy (SIM) in J774 mouse macrophage cells. Analysis of in vivo labeled J774 cells by mass spectrometry showed that the probe was very selective for cathepsins B and Z, two lysosomal cysteine proteases. Analysis of starvation-induced autophagy, a catabolic pathway involving lysosomes, showed a large increase in the number of tagged proteins and an increase in cathepsin activity. The organelle-targeting of activity-based probes holds great promise for the characterization of enzyme activities in the myriad diseases linked to specific subcellular locations, particularly the lysosome.

Dynamic nitrogen fixation in an aerobic endophyte of Populus.

Biological nitrogen fixation by microbial diazotrophs can contribute significantly to nitrogen availability in non-nodulating plant species. In this study of molecular mechanisms and gene expression relating to biological nitrogen fixation, the aerobic nitrogen-fixing endophyte Burkholderia vietnamiensis, strain WPB, isolated from Populus trichocarpa served as a model for endophyte-poplar interactions. Nitrogen-fixing activity was observed to be dynamic on nitrogen-free medium with a subset of colonies growing to form robust, raised globular like structures. Secondary ion mass spectrometry (NanoSIMS) confirmed that N-fixation was uneven within the population. A fluorescent transcriptional reporter (GFP) revealed that the nitrogenase subunit nifH is not uniformly expressed across genetically identical colonies of WPB and that only ~11% of the population was actively expressing the nifH gene. Higher nifH gene expression was observed in clustered cells through monitoring individual bacterial cells using single-molecule fluorescence in situ hybridization. Through 15N2 enrichment, we identified key nitrogenous metabolites and proteins synthesized by WPB and employed targeted metabolomics in active and inactive populations. We cocultivated WPB Pnif-GFP with poplar within a RhizoChip, a synthetic soil habitat, which enabled direct imaging of microbial nifH expression within root epidermal cells. We observed that nifH expression is localized to the root elongation zone where the strain forms a unique physical interaction with the root cells. This work employed comprehensive experimentation to identify novel mechanisms regulating both biological nitrogen fixation and beneficial plant-endophyte interactions.

Analysis of carbohydrate storage granules in the diazotrophic cyanobacterium Cyanothece sp. PCC 7822.

The unicellular diazotrophic cyanobacteria of the genus Cyanothece demonstrate oscillations in nitrogenase activity and H2 production when grown under 12 h light-12 h dark cycles. We established that Cyanothece sp. PCC 7822 allows for the construction of knock-out mutants and our objective was to improve the growth characteristics of this strain and to identify the nature of the intracellular storage granules. We report the physiological and morphological effects of reduction in nitrate and phosphate concentrations in BG-11 media on this strain. We developed a series of BG-11-derived growth media and monitored batch culture growth, nitrogenase activity and nitrogenase-mediated hydrogen production, culture synchronicity, and intracellular storage content. Reduction in NaNO3 and K2HPO4 concentrations from 17.6 and 0.23 to 4.41 and 0.06 mM, respectively, improved growth characteristics such as cell size and uniformity, and enhanced the rate of cell division. Cells grown in this low NP BG-11 were less complex, a parameter that related to the composition of the intracellular storage granules. Cells grown in low NP BG-11 had less polyphosphate, fewer polyhydroxybutyrate granules and many smaller granules became evident. Biochemical analysis and transmission electron microscopy using the histocytochemical PATO technique demonstrated that these small granules contained glycogen. The glycogen levels and the number of granules per cell correlated nicely with a 2.3 to 3.3-fold change from the minimum at L0 to the maximum at D0. The differences in granule morphology and enzymes between Cyanothece ATCC 51142 and Cyanothece PCC 7822 provide insights into the formation of large starch-like granules in some cyanobacteria.

Optimization of Molecular Methods for Detecting Duckweed-Associated Bacteria.

The bacterial colonization dynamics of plants can differ between phylogenetically similar bacterial strains and in the context of complex bacterial communities. Quantitative methods that can resolve closely related bacteria within complex communities can lead to a better understanding of plant-microbe interactions. However, current methods often lack the specificity to differentiate phylogenetically similar bacterial strains. In this study, we describe molecular strategies to study duckweed-associated bacteria. We first systematically optimized a bead-beating protocol to co-isolate nucleic acids simultaneously from duckweed and bacteria. We then developed a generic fingerprinting assay to detect bacteria present in duckweed samples. To detect specific duckweed-bacterium associations, we developed a genomics-based computational pipeline to generate bacterial strain-specific primers. These strain-specific primers differentiated bacterial strains from the same genus and enabled the detection of specific duckweed-bacterium associations present in a community context. Moreover, we used these strain-specific primers to quantify the bacterial colonization of duckweed by normalization to a plant reference gene and revealed differences in colonization levels between strains from the same genus. Lastly, confocal microscopy of inoculated duckweed further supported our PCR results and showed bacterial colonization of the duckweed root-frond interface and root interior. The molecular methods introduced in this work should enable the tracking and quantification of specific plant-microbe associations within plant-microbial communities.