Hatching with the enemy: Daphnia diapausing eggs hatch in the presence of fish kairomones

Summary.: Infochemicals are known to play a key role in mediating predator-prey interactions, both in aquatic and terrestrial communities. However, state-dependent variation may exist in how effectively individuals can use this information, depending on genotype, life stage and experience. For our study, we used the predator-prey model system fish-waterflea Daphnia magna Straus (Cladocera, Daphniidae). Adult Daphnia use fish-derived infochemicals, so-called kairomones, as indicators of predation risk, and exhibit a spectrum of morphological, behavioural and life-history responses to the presence of fish kairomones. Here, we investigate whether diapausing eggs, an embryonic resting stage in the life cycle of D. magna, also use fish kairomones and tune their hatching to the risk of fish predation, as reported for diapausing stages of dinoflagellates. In two laboratory experiments, we studied hatching proportion and time until hatching of D. magna diapausing eggs in the absence and presence of fish kairomones. D. magna families differed significantly in their response to the presence of fish kairomones; some families reduced hatching proportion, whereas others increased it. Our results imply genotype-dependent differences in the hatching reactions to fish kairomones as observed for other traits in adult Daphni

Genomic, genetic and structural analysis of pyoverdine-mediated iron acquisition in the plant growth-promoting bacterium Pseudomonas fluorescens SBW25

<p>Abstract</p> <p>Background</p> <p>Pyoverdines (PVDs) are high affinity siderophores, for which the molecular mechanisms of biosynthesis, uptake and regulation have been extensively studied in <it>Pseudomonas aeruginosa </it>PAO1. However, the extent to which this regulatory model applies to other pseudomonads is unknown. Here, we describe the results of a genomic, genetic and structural analysis of pyoverdine-mediated iron uptake by the plant growth-promoting bacterium <it>P. fluorescens </it>SBW25.</p> <p>Results</p> <p><it>In silico </it>analysis of the complete, but un-annotated, SBW25 genome sequence identified 31 genes putatively involved in PVD biosynthesis, transport or regulation, which are distributed across seven different regions of the genome. PVD gene iron-responsiveness was tested using '<it>lacZ </it>fusions to five PVD loci, representative of structural and regulatory genes. Transcription of all fusions increased in response to iron starvation. <it>In silico </it>analyses suggested that regulation of <it>fpvR </it>(which is predicted to encode a cytoplasmic membrane-spanning anti-sigma factor) may be unique. Transcriptional assays using gene expression constructs showed that <it>fpvR </it>is positively regulated by FpvI (an extracytoplasmic family (ECF) sigma factor), and not directly by the ferric uptake regulator (Fur) as for PAO1. Deletion of <it>pvdL</it>, encoding a predicted non-ribosomal peptide synthetase (NRPS) involved in PVD chromophore biosynthesis confirmed the necessity of PvdL for PVD production and for normal growth in iron-limited media. Structural analysis of the SBW25 PVD shows a partly cyclic seven residue peptide backbone, identical to that of <it>P. fluorescens </it>ATCC13525. At least 24 putative siderophore receptor genes are present in the SBW25 genome enabling the bacterium to utilize 19 structurally distinct PVDs from 25 different <it>Pseudomonas </it>isolates.</p> <p>Conclusion</p> <p>The genome of <it>P. fluorescens </it>SBW25 contains an extensively dispersed set of PVD genes in comparison to other sequenced <it>Pseudomonas </it>strains. The PAO1 PVD regulatory model, which involves a branched Fpv signaling pathway, is generally conserved in SBW25, however there is a significant difference in <it>fpvR </it>regulation. SBW25 produces PVD with a partly cyclic seven amino acid residue backbone, and is able to utilize a wide variety of exogenous PVDs.</p

Selective metal extraction by biologically produced siderophores during bioleaching from low-grade primary and secondary mineral resources

Siderophores are a class of biogenic macromolecules that have high affinities for metals in the environment, thus could be exploited for alternate sustainable metal recovery technologies. Here, we assess the role of siderophores in the extraction and complexation of metals from an iron oxide-rich metallurgical processing residue and a low-grade primary Ni ore. Evaluation of the biological siderophore production by three pseudomonads, P. fluorescens, P. azotoformans and P. putida identified that P. putida could generate the highest siderophore yield, which was characterized as a hydroxamate and catecholate mixed-type pyoverdine PyoPpC-3B. Key physicochemical parameters involved in raw siderophore mediated metal extraction were identified using a fractional factorial design of experiments (DOE) and subsequently employed in purified PyoPpC-3B leaching experiments. Further targeted experiments with hydroxamate and catecholate functional analogues of PyoPpC-3B confirmed their marked ability to competitively or selectively leach and chelate hard metal ions, including Al(OH)(4)(-), Mn2+ and Zn2+. Interestingly, complexation of Mn and Zn ions exceeded the natural affinity of pyoverdine for Fe3+, thus despite the low metal recoveries from the materials tested in this study, this work provides important new insights in siderophore-metal interactions

HapX-Mediated Iron Homeostasis Is Essential for Rhizosphere Competence and Virulence of the Soilborne Pathogen Fusarium oxysporum

Soilborne fungal pathogens cause devastating yield losses and are highly persistent and difficult to control. During the infection process, these organisms must cope with limited availability of iron. Here we show that the bZIP protein HapX functions as a key regulator of iron homeostasis and virulence in the vascular wilt fungus Fusarium oxysporum. Deletion of hapX does not affect iron uptake but causes derepression of genes involved in iron-consuming pathways, leading to impaired growth under iron-depleted conditions. F. oxysporum strains lacking HapX are reduced in their capacity to invade and kill tomato (Solanum lycopersicum) plants and immunodepressed mice. The virulence defect of ΔhapX on tomato plants is exacerbated by coinoculation of roots with a biocontrol strain of Pseudomonas putida, but not with a siderophore-deficient mutant, indicating that HapX contributes to iron competition of F. oxysporum in the tomato rhizosphere. These results establish a conserved role for HapX-mediated iron homeostasis in fungal infection of plants and mammals

Automated image registration of cerebral digital subtraction angiography

Purpose: Our aim is to automatically align digital subtraction angiography (DSA) series, recorded before and after endovascular thrombectomy. Such alignment may enable quantification of procedural success. Methods: Firstly, we examine the inherent limitations for image registration, caused by the projective characteristics of DSA imaging, in a representative set of image pairs from thrombectomy procedures. Secondly, we develop and assess various image registration methods (SIFT, ORB). We assess these methods using manually annotated point correspondences for thrombectomy image pairs. Results: Linear transformations that account for scale differences are effective in aligning DSA sequences. Two anatomical landmarks can be reliably identified for registration using a U-net. Point-based registration using SIFT and ORB proves to be most effective for DSA registration and are applicable to recordings for all patient sub-types. Image-based techniques are less effective and did not refine the results of the best point-based registration method. Conclusion: We developed and assessed an automated image registration approach for cerebral DSA sequences, recorded before and after endovascular thrombectomy. Accurate results were obtained for approximately 85% of our image pairs.</p

Antimicrobial properties of Pseudomonas strains producing the antibiotic mupirocin

peer reviewe

CAVE:Cerebral artery–vein segmentation in digital subtraction angiography

Cerebral X-ray digital subtraction angiography (DSA) is a widely used imaging technique in patients with neurovascular disease, allowing for vessel and flow visualization with high spatio-temporal resolution. Automatic artery–vein segmentation in DSA plays a fundamental role in vascular analysis with quantitative biomarker extraction, facilitating a wide range of clinical applications. The widely adopted U-Net applied on static DSA frames often struggles with disentangling vessels from subtraction artifacts. Further, it falls short in effectively separating arteries and veins as it disregards the temporal perspectives inherent in DSA. To address these limitations, we propose to simultaneously leverage spatial vasculature and temporal cerebral flow characteristics to segment arteries and veins in DSA. The proposed network, coined CAVE, encodes a 2D+time DSA series using spatial modules, aggregates all the features using temporal modules, and decodes it into 2D segmentation maps. On a large multi-center clinical dataset, CAVE achieves a vessel segmentation Dice of 0.84 (±0.04) and an artery–vein segmentation Dice of 0.79 (±0.06). CAVE surpasses traditional Frangi-based k-means clustering (P &lt; 0.001) and U-Net (P &lt; 0.001) by a significant margin, demonstrating the advantages of harvesting spatio-temporal features. This study represents the first investigation into automatic artery–vein segmentation in DSA using deep learning. The code is publicly available at https://github.com/RuishengSu/CAVE_DSA.</p

Spatio-Temporal U-Net for Cerebral Artery and Vein Segmentation in Digital Subtraction Angiography

X-ray digital subtraction angiography (DSA) is widely used for vessel and/or flow visualization and interventional guidance during endovascular treatment of patients with a stroke or aneurysm. To assist in peri-operative decision making as well as post-operative prognosis, automatic DSA analysis algorithms are being developed to obtain relevant image-based information. Such analyses include detection of vascular disease, evaluation of perfusion based on time intensity curves (TIC), and quantitative biomarker extraction for automated treatment evaluation in endovascular thrombectomy. Methodologically, such vessel-based analysis tasks may be facilitated by automatic and accurate artery-vein segmentation algorithms. The present work describes to the best of our knowledge the first study that addresses automatic artery-vein segmentation in DSA using deep learning. We propose a novel spatio-temporal U-Net (ST U-Net) architecture which integrates convolutional gated recurrent units (ConvGRU) in the contracting branch of U-Net. The network encodes a 2D+t DSA series of variable length and decodes it into a 2D segmentation image. On a multi-center routinely acquired dataset, the proposed method significantly outperformed U-Net (P<0.001) and traditional Frangi-based K-means clustering (P$<$0.001). Particularly in artery-vein segmentation, ST U-Net achieved a Dice coefficient of 0.794, surpassing the existing state-of-the-art methods by a margin of 12\%-20\%. Code will be made publicly available upon acceptance

autoTICI: Automatic Brain Tissue Reperfusion Scoring on 2D DSA Images of Acute Ischemic Stroke Patients

The Thrombolysis in Cerebral Infarction (TICI) score is an important metric for reperfusion therapy assessment in acute ischemic stroke. It is commonly used as a technical outcome measure after endovascular treatment (EVT). Existing TICI scores are defined in coarse ordinal grades based on visual inspection, leading to inter- and intra-observer variation. In this work, we present autoTICI, an automatic and quantitative TICI scoring method. First, each digital subtraction angiography (DSA) sequence is separated into four phases (non-contrast, arterial, parenchymal and venous phase) using a multi-path convolutional neural network (CNN), which exploits spatio-temporal features. The network also incorporates sequence level label dependencies in the form of a state-transition matrix. Next, a minimum intensity map (MINIP) is computed using the motion corrected arterial and parenchymal frames. On the MINIP image, vessel, perfusion and background pixels are segmented. Finally, we quantify the autoTICI score as the ratio of reperfused pixels after EVT. On a routinely acquired multi-center dataset, the proposed autoTICI shows good correlation with the extended TICI (eTICI) reference with an average area under the curve (AUC) score of 0.81. The AUC score is 0.90 with respect to the dichotomized eTICI. In terms of clinical outcome prediction, we demonstrate that autoTICI is overall comparable to eTICI.Comment: 10 pages; submitted to IEEE TM

Optimizing Nervous System-Specific Gene Targeting with Cre Driver Lines: Prevalence of Germline Recombination and Influencing Factors.

The Cre-loxP system is invaluable for spatial and temporal control of gene knockout, knockin, and reporter expression in the mouse nervous system. However, we report varying probabilities of unexpected germline recombination in distinct Cre driver lines designed for nervous system-specific recombination. Selective maternal or paternal germline recombination is showcased with sample Cre lines. Collated data reveal germline recombination in over half of 64 commonly used Cre driver lines, in most cases with a parental sex bias related to Cre expression in sperm or oocytes. Slight differences among Cre driver lines utilizing common transcriptional control elements affect germline recombination rates. Specific target loci demonstrated differential recombination; thus, reporters are not reliable proxies for another locus of interest. Similar principles apply to other recombinase systems and other genetically targeted organisms. We hereby draw attention to the prevalence of germline recombination and provide guidelines to inform future research for the neuroscience and broader molecular genetics communities