scholarly journals FleN contributes to heterogeneous swimming at high temperatures inPseudomonas syringae

2018 ◽  
Author(s):  
Kevin L. Hockett ◽  
Steven E. Lindow
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Pseudomonas Syringae ◽  
Environmental Conditions ◽  
Promoter Region ◽  
Plant Pathogens ◽  
Incubation Temperature ◽  
Nutrient Depletion ◽  
Synonymous Mutations ◽  
Cell Microscopy

SUMMARYMotility is generally conserved among many animal and plant pathogens. Environmental conditions, however, significantly impact expression of the motile phenotype. In this study, we describe a novel heterogeneous motility phenotype inPseudomonas syringae, where under normally suppressive incubation conditions (30°C) punctate colonies arise that are spatially isolated from the point of inoculation, giving rise to a motility pattern we term constellation swimming (CS). We demonstrate that this phenotype is reproducible, reversible, and dependent on a functioning flagellum. Mirroring the heterogeneous motility phenotype, we demonstrate the existence of a sub-population of cells under non-permissive conditions that express flagellin (fliC) at levels similar to cells incubated under permissive conditions using both quantitative single cell microscopy and flow cytometry. To understand the genetics underlying the CS phenotype, we selected for naturally arising mutants that exhibited a normal swimming phenotype at the warmer incubation temperature. Sequencing these mutants recovered several independent non-synonymous mutations within FleN (also known as FlhG) as well as mutations within the promoter region of FleQ, the master flagellum regulator inPseudomonas. We further show that nutrient depletion is the likely underlying cause of CS, as reduced nutrients will stimulate bothfliCexpression and a normal swimming phenotype at 30 °C.

COLONY OF THE FUNGUS Aspergillus oryzae AND SELF-AFFINE FRACTAL GEOMETRY OF GROWTH FRONTS

Fractals ◽  
1993 ◽  
Vol 01 (01) ◽  
pp. 11-19 ◽  
Author(s):  
SHU MATSUURA ◽  
SASUKE MIYAZIMA
Keyword(s):  
Aspergillus Oryzae ◽  
Environmental Conditions ◽  
Fractal Geometry ◽  
Nutrient Concentration ◽  
Incubation Temperature ◽  
Characteristic Exponent ◽  
Growth Front ◽  
Favorable Condition ◽  
The Self ◽  
The Mean

A variety of colony shapes of the fungus Aspergillus oryzae under varying environmental conditions such as the nutrient concentration, medium stiffness and incubation temperature are obtained, ranging from a homogeneous Eden-like to a ramified DLA-like pattern. The roughness σ(l, h) of the growth front of the band-shaped colony, where h is the mean front height within l of the horizontal range, satisfies the self-affine fractal relation under favorable environmental conditions. In the most favorable condition of our experiments, its characteristic exponent is found to be a little larger than that of the 2-dimensional Eden model.

A droplet-based microfluidic flow cytometry enabling absolute quantification of single-cell proteins leveraging constriction channel

2021 ◽  
Vol 25 (4) ◽  
Author(s):  
Hongyu Yang ◽  
Yuanchen Wei ◽  
Beiyuan Fan ◽  
Lixing Liu ◽  
Ting Zhang ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Absolute Quantification ◽  
Microfluidic Flow

scholarly journals A Synergic Potential of Antimicrobial Peptides against Pseudomonas syringae pv. actinidiae

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1461
Author(s):  
Nuno Mariz-Ponte ◽  
Laura Regalado ◽  
Emil Gimranov ◽  
Natália Tassi ◽  
Luísa Moura ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Antimicrobial Peptides ◽  
Pseudomonas Syringae ◽  
Pathogenic Bacteria ◽  
High Efficiency ◽  
Bacterial Canker ◽  
Membrane Permeation ◽  
Flow Cytometry Analysis ◽  
Pathogenic Agent ◽  
Peptide Mixtures

Pseudomonas syringae pv. actinidiae (Psa) is the pathogenic agent responsible for the bacterial canker of kiwifruit (BCK) leading to major losses in kiwifruit productions. No effective treatments and measures have yet been found to control this disease. Despite antimicrobial peptides (AMPs) having been successfully used for the control of several pathogenic bacteria, few studies have focused on the use of AMPs against Psa. In this study, the potential of six AMPs (BP100, RW-BP100, CA-M, 3.1, D4E1, and Dhvar-5) to control Psa was investigated. The minimal inhibitory and bactericidal concentrations (MIC and MBC) were determined and membrane damaging capacity was evaluated by flow cytometry analysis. Among the tested AMPs, the higher inhibitory and bactericidal capacity was observed for BP100 and CA-M with MIC of 3.4 and 3.4–6.2 µM, respectively and MBC 3.4–10 µM for both. Flow cytometry assays suggested a faster membrane permeation for peptide 3.1, in comparison with the other AMPs studied. Peptide mixtures were also tested, disclosing the high efficiency of BP100:3.1 at low concentration to reduce Psa viability. These results highlight the potential interest of AMP mixtures against Psa, and 3.1 as an antimicrobial molecule that can improve other treatments in synergic action.

scholarly journals IMMU-68. SINGLE-CELL PROTEOMIC ANALYSIS OF IMMUNE CELL RESPONSE TO CHECKPOINT BLOCKADE USING 30-PARAMETER FLOW CYTOMETRY

2018 ◽  
Vol 20 (suppl_6) ◽  
pp. vi137-vi137
Author(s):  
Amber Giles ◽  
Leonard Nettey ◽  
Thomas Liechti ◽  
Margaret Beddall ◽  
Elizabeth Vera ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Cell Response ◽  
Proteomic Analysis ◽  
Immune Cell ◽  
Checkpoint Blockade ◽  
Immune Cell Response

scholarly journals In planta bacterial multi-omics analysis illuminates regulatory principles underlying plant-pathogen interactions

2019 ◽  
Author(s):  
Tatsuya Nobori ◽  
Yiming Wang ◽  
Jingni Wu ◽  
Sara Christina Stolze ◽  
Yayoi Tsuda ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Pseudomonas Syringae ◽  
Protein Level ◽  
Plant Pathogens ◽  
Plant Immunity ◽  
Bacterial Pathogen ◽  
Bacterial Virulence ◽  
In Planta ◽  
Bacterial Gene ◽  
Global Food Security

AbstractUnderstanding how gene expression is regulated in plant pathogens is crucial for pest control and thus global food security. An integrated understanding of bacterial gene regulation in the host is dependent on multi-omic datasets, but these are largely lacking. Here, we simultaneously characterized the transcriptome and proteome of a foliar bacterial pathogen, Pseudomonas syringae, in Arabidopsis thaliana and identified a number of bacterial processes influenced by plant immunity at the mRNA and the protein level. We found instances of both concordant and discordant regulation of bacterial mRNAs and proteins. Notably, the tip component of bacterial type III secretion system was selectively suppressed by the plant salicylic acid pathway at the protein level, suggesting protein-level targeting of the bacterial virulence system by plant immunity. Furthermore, gene co-expression analysis illuminated previously unknown gene regulatory modules underlying bacterial virulence and their regulatory hierarchy. Collectively, the integrated in planta bacterial omics approach provides molecular insights into multiple layers of bacterial gene regulation that contribute to bacterial growth in planta and elucidate the role of plant immunity in controlling pathogens.

scholarly journals New interpretable machine learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy

2019 ◽  
Author(s):  
Evan Greene ◽  
Greg Finak ◽  
Leonard A. D’Amico ◽  
Nina Bhardwaj ◽  
Candice D. Church ◽  
...  
Keyword(s):  
Machine Learning ◽  
Flow Cytometry ◽  
T Cell ◽  
Single Cell ◽  
Cancer Immunotherapy ◽  
Effector Memory ◽  
Machine Learning Method ◽  
Learning Method ◽  
Modeling Framework ◽  
Interpretable Machine Learning

AbstractHigh-dimensional single-cell cytometry is routinely used to characterize patient responses to cancer immunotherapy and other treatments. This has produced a wealth of datasets ripe for exploration but whose biological and technical heterogeneity make them difficult to analyze with current tools. We introduce a new interpretable machine learning method for single-cell mass and flow cytometry studies, FAUST, that robustly performs unbiased cell population discovery and annotation. FAUST processes data on a per-sample basis and returns biologically interpretable cell phenotypes that can be compared across studies, making it well-suited for the analysis and integration of complex datasets. We demonstrate how FAUST can be used for candidate biomarker discovery and validation by applying it to a flow cytometry dataset from a Merkel cell carcinoma anti-PD-1 trial and discover new CD4+ and CD8+ effector-memory T cell correlates of outcome co-expressing PD-1, HLA-DR, and CD28. We then use FAUST to validate these correlates in an independent CyTOF dataset from a published metastatic melanoma trial. Importantly, existing state-of-the-art computational discovery approaches as well as prior manual analysis did not detect these or any other statistically significant T cell sub-populations associated with anti-PD-1 treatment in either data set. We further validate our methodology by using FAUST to replicate the discovery of a previously reported myeloid correlate in a different published melanoma trial, and validate the correlate by identifying it de novo in two additional independent trials. FAUST’s phenotypic annotations can be used to perform cross-study data integration in the presence of heterogeneous data and diverse immunophenotyping staining panels, enabling hypothesis-driven inference about cell sub-population abundance through a multivariate modeling framework we call Phenotypic and Functional Differential Abundance (PFDA). We demonstrate this approach on data from myeloid and T cell panels across multiple trials. Together, these results establish FAUST as a powerful and versatile new approach for unbiased discovery in single-cell cytometry.

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