SuperSegger: robust image segmentation,analysis and lineage tracking of bacterial cells

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame‐to‐frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB‐based image processing package well‐suited to quantitative analysis of high‐throughput live‐cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine‐learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame‐to‐frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell‐cycle dynamics in bacteria as well as cell‐contact mediated phenomena. This package has a range of built‐in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution.     

A comparison of direct infusion MS and GC-MS for metabolic footprinting of yeast mutants

Recent technical advances in mass spectrometry (MS) have propelled this technology to the forefront of methods employed in metabolome analysis. Here, we compare two distinct analytical approaches based on MS for their potential in revealing specific metabolic footprints of yeast single-deletion mutants. Filtered fermentation broth samples were analyzed by GC-MS and direct infusion ESI-MS. The potential of both methods in producing specific and, therefore, discriminant metabolite profiles was evaluated using samples from several yeast deletion mutants grown in batch-culture conditions with glucose as the carbon source. The mutants evaluated were cat8, gln3, ino2, opi1, and nil1, all with deletion of genes involved in nutrient sensing and regulation. From the analysis, we found that both methods can be used to classify mutants, but the classification depends on which metabolites are measured. Thus, the GC-MS method is good for classification of mutants with altered nitrogen regulation as it primarily measures amino acids, whereas this method cannot classify mutants involved in regulation of phospholipids metabolism as well as the direct infusion MS (DI-MS) method. From the analysis, we find that it is possible to discriminate the mutants in both the exponential and stationary growth phase, but the data from the exponential growth phase provide more physiological relevant information. Based on the data, we identified metabolites that are primarily involved in discrimination of the different mutants, and hereby providing a link between high-throughput metabolome analysis, strain classification, and physiology.     

Reduced skin bacterial diversity correlates with increased pathogen infection intensity in an endangered amphibian host

The fungal pathogen Batrachochytrium dendrobatidis (Bd) infects the skin of amphibians and has caused severe declines and extinctions of amphibians globally. In this study, we investigate the interaction between Bd and the bacterial skin microbiome of the endangered Sierra Nevada yellow‐legged frog, Rana sierrae, using both culture‐dependent and culture‐independent methods. Samples were collected from two populations of R. sierrae that likely underwent Bd epizootics in the past, but that continue to persist with Bd in an enzootic disease state, and we address the hypothesis that such “persistent” populations are aided by mutualistic skin microbes. Our 16S rRNA metabarcoding data reveal that the skin microbiome of highly infected juvenile frogs is characterized by significantly reduced species richness and evenness, and by strikingly lower variation between individuals, compared to juveniles and adults with lower infection levels. Over 90% of DNA sequences from the skin microbiome of highly infected frogs were derived from bacteria in a single order, Burkholderiales, compared to just 54% in frogs with lower infection levels. In a culture‐dependent Bd inhibition assay, the bacterial metabolites we evaluated all inhibited the growth of Bd. Together, these results illustrate the disruptive effects of Bd infection on host skin microbial community structure and dynamics, and suggest possible avenues for the development of anti‐Bd probiotic treatments.     

The Role of Cysteine Residues in Redox Regulation and Protein Stability of Arabidopsis thaliana Starch Synthase 1

Starch biosynthesis in Arabidopsis thaliana is strictly regulated. In leaf extracts, starch synthase 1 (AtSS1) responds to the redox potential within a physiologically relevant range. This study presents data testing two main hypotheses: 1) that specific thiol-disulfide exchange in AtSS1 influences its catalytic function 2) that each conserved Cys residue has an impact on AtSS1 catalysis. Recombinant AtSS1 versions carrying combinations of cysteine-to-serine substitutions were generated and characterized in vitro. The results demonstrate that AtSS1 is activated and deactivated by the physiological redox transmitters thioredoxin f1 (Trxf1), thioredoxin m4 (Trxm4) and the bifunctional NADPH-dependent thioredoxin reductase C (NTRC). AtSS1 displayed an activity change within the physiologically relevant redox range, with a midpoint potential equal to -306 mV, suggesting that AtSS1 is in the reduced and active form during the day with active photosynthesis. Cys164 and Cys545 were the key cysteine residues involved in regulatory disulfide formation upon oxidation. A C164S_C545S double mutant had considerably decreased redox sensitivity as compared to wild type AtSS1 (30% vs 77%). Michaelis-Menten kinetics and molecular modeling suggest that both cysteines play important roles in enzyme catalysis, namely, Cys545 is involved in ADP-glucose binding and Cys164 is involved in acceptor binding. All the other single mutants had essentially complete redox sensitivity (98–99%). In addition of being part of a redox directed activity “light switch”, reactivation tests and low heterologous expression levels indicate that specific cysteine residues might play additional roles. Specifically, Cys265 in combination with Cys164 can be involved in proper protein folding or/and stabilization of translated protein prior to its transport into the plastid. Cys442 can play an important role in enzyme stability upon oxidation. The physiological and phylogenetic relevance of these findings is discussed.     

Discovery of a seventh <Emphasis Type="Italic">Rpp</Emphasis> soybean rust resistance locus in soybean accession PI 605823

Key message

A novel Rpp gene from PI 605823 for resistance to Phakopsora pachyrhizi was mapped on chromosome 19.

Abstract

Soybean rust, caused by the obligate biotrophic fungal pathogen Phakopsora pachyrhizi Syd. & P. Syd, is a disease threat to soybean production in regions of the world with mild winters. Host plant resistance conditioned by resistance to P. pachyrhizi (Rpp) genes has been found in numerous soybean accessions, and at least 10 Rpp genes or alleles have been mapped to six genetic loci. Identifying additional disease-resistance genes will facilitate development of soybean cultivars with durable resistance. PI 605823, a plant introduction from Vietnam, was previously identified as resistant to US populations of P. pachyrhizi in greenhouse and field trials. In this study, bulked segregant analysis using an F₂ population derived from ‘Williams 82’ × PI 605823 identified a genomic region associated with resistance to P. pachyrhizi isolate GA12, which had been collected in the US State of Georgia in 2012. To further map the resistance locus, linkage mapping was carried out using single-nucleotide polymorphism markers and phenotypic data from greenhouse assays with an F_2:3 population derived from Williams 82 × PI 605823 and an F_4:5 population derived from ‘5601T’ × PI 605823. A novel resistance gene, Rpp7, was mapped to a 154-kb interval (Gm19: 39,462,291–39,616,643 Glyma.Wm82.a2) on chromosome 19 that is different from the genomic locations of any previously reported Rpp genes. This new gene could be incorporated into elite breeding lines to help provide more durable resistance to soybean rust.

     

A reverse-phase liquid chromatography/mass spectrometry method for the analysis of high-molecular-weight fructooligosaccharides

Many important crop and forage plants accumulate polymeric water-soluble carbohydrates as fructooligosaccharides (or fructans). We have developed an improved method for the analysis of the full fructan complement in plant extracts based on porous graphitized carbon chromatography coupled to negative electrospray ionization mass spectrometry. By the use of profile data collection and multiple charge state ions, the effective mass range of the ion trap was extended to allow for the analysis of very high-molecular-weight oligosaccharides. This method allows the separation and quantification of isomeric fructan oligomers ranging from degree of polymerization (DP) 3 to DP 49.     

Identification of Required Host Factors for SARS-CoV-2 Infection in Human Cells

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Biologically meaningful coverage indicators for eliminating malaria transmission

Mosquitoes, which evade contact with long-lasting insecticidal nets and indoor residual sprays, by feeding outdoors or upon animals, are primary malaria vectors in many tropical countries. They can also dominate residual transmission where high coverage of these front-line vector control measures is achieved. Complementary strategies, which extend insecticide coverage beyond houses and humans, are required to eliminate malaria transmission in most settings. The overwhelming diversity of the world's malaria transmission systems and optimal strategies for controlling them can be simply conceptualized and mapped across two-dimensional scenario space defined by the proportion of blood meals that vectors obtain from humans and the proportion of human exposure to them which occurs indoors.     

An exometabolomics approach to monitoring microbial contamination in microalgal fermentation processes by using metabolic footprint analysis

The early detection of microbial contamination is crucial to avoid process failure and costly delays in fermentation industries. However, traditional detection methods such as plate counting and microscopy are labor-intensive, insensitive, and time-consuming. Modern techniques that can detect microbial contamination rapidly and cost-effectively are therefore sought. In the present study, we propose gas chromatography-mass spectrometry (GC-MS)-based metabolic footprint analysis as a rapid and reliable method for the detection of microbial contamination in fermentation processes. Our metabolic footprint analysis detected statistically significant differences in metabolite profiles of axenic and contaminated batch cultures of microalgae as early as 3 h after contamination was introduced, while classical detection methods could detect contamination only after 24 h. The data were analyzed by discriminant function analysis and were validated by leave-one-out cross-validation. We obtained a 97% success rate in correctly classifying samples coming from contaminated or axenic cultures. Therefore, metabolic footprint analysis combined with discriminant function analysis presents a rapid and cost-effective approach to monitor microbial contamination in industrial fermentation processes.     

Label‐free spectroscopic tissue characterization using fluorescence excitation‐scanning spectral imaging

Spectral imaging approaches provide new possibilities for measuring and discriminating fluorescent molecules in living cells and tissues. These approaches often employ tunable filters and robust image processing algorithms to identify many fluorescent labels in a single image set. Here, we present results from a novel spectral imaging technology that scans the fluorescence excitation spectrum, demonstrating that excitation‐scanning hyperspectral image data can discriminate among tissue types and estimate the molecular composition of tissues. This approach allows fast, accurate quantification of many fluorescent species from multivariate image data without the need of exogenous labels or dyes. We evaluated the ability of the excitation‐scanning approach to identify endogenous fluorescence signatures in multiple unlabeled tissue types. Signatures were screened using multi‐pass principal component analysis. Endmember extraction techniques revealed conserved autofluorescent signatures across multiple tissue types. We further examined the ability to detect known molecular signatures by constructing spectral libraries of common endogenous fluorophores and applying multiple spectral analysis techniques on test images from lung, liver and kidney. Spectral deconvolution revealed structure‐specific morphologic contrast generated from pure molecule signatures. These results demonstrate that excitation‐scanning spectral imaging, coupled with spectral imaging processing techniques, provides an approach for discriminating among tissue types and assessing the molecular composition of tissues. Additionally, excitation scanning offers the ability to rapidly screen molecular markers across a range of tissues without using fluorescent labels. This approach lays the groundwork for translation of excitation‐scanning technologies to clinical imaging platforms.