Sporulation Activated via σW Protects Bacillus from a Tse1 Peptidoglycan Hydrolase Type VI Secretion System Effector.

Within bacterial communities, community members engage in interactions employing diverse offensive and defensive tools to reach coexistence. Extracellular-matrix production and sporulation are defensive mechanisms used by Bacillus subtilis cells when they interact with Pseudomonas chlororaphis strains expressing a type VI secretion system (T6SS). Here, we define Tse1 as the main toxin mobilized by the Pseudomonas chlororaphis T6SS that triggers sporulation in Bacillus subtilis. We characterize Tse1 as a peptidoglycan hydrolase that indirectly alters the dynamics and functionality of the Bacillus cell membrane. We also delineate the response of Bacillus cells to Tse1, which through the coordinated actions of the extracellular sigma factor σW and the cytoplasmic histidine kinases KinA and KinB, culminates in activation of the sporulation cascade. We propose that this cellular developmental response permits bacilli to defend against the toxicity of T6SS-mobilized Tse1 effector. IMPORTANCE The study of bacterial interactions is helping to define species-specific strategies used to modulate the competition dynamics underlying the development of community compositions. In this study, we deciphered the role of Pseudomonas T6SS when competing with Bacillus and the mechanism by which a T6SS-toxin modifies Bacillus physiology. We found that Pseudomonas triggers Bacillus sporulation by injecting through T6SS a toxin that we called Tse1. We found that Tse1 is a hydrolase that degrades Bacillus peptidoglycan and indirectly damages Bacillus membrane functionality. In addition, we demonstrated the mechanism by which Bacillus cells increase the sporulation rate upon recognition of the presence of Tse1. Interestingly, asporogenic Bacillus cells are more sensitive to T6SS activity, which led us to propose sporulation as a last resort of bacilli to overcome this family of toxins.

Recommendations for living donor kidney transplantation.

This Guide for Living Donor Kidney Transplantation (LDKT) has been prepared with the sponsorship of the Spanish Society of Nephrology (SEN), the Spanish Transplant Society (SET), and the Spanish National Transplant Organization (ONT). It updates evidence to offer the best chronic renal failure treatment when a potential living donor is available. The core aim of this Guide is to supply clinicians who evaluate living donors and transplant recipients with the best decision-making tools, to optimise their outcomes. Moreover, the role of living donors in the current KT context should recover the level of importance it had until recently. To this end the new forms of incompatible HLA and/or ABO donation, as well as the paired donation which is possible in several hospitals with experience in LDKT, offer additional ways to treat renal patients with an incompatible donor. Good results in terms of patient and graft survival have expanded the range of circumstances under which living renal donors are accepted. Older donors are now accepted, as are others with factors that affect the decision, such as a borderline clinical history or alterations, which when evaluated may lead to an additional number of transplantations. This Guide does not forget that LDKT may lead to risk for the donor. Pre-donation evaluation has to centre on the problems which may arise over the short or long-term, and these have to be described to the potential donor so that they are able take them into account. Experience over recent years has led to progress in risk analysis, to protect donors' health. This aspect always has to be taken into account by LDKT programmes when evaluating potential donors. Finally, this Guide has been designed to aid decision-making, with recommendations and suggestions when uncertainties arise in pre-donation studies. Its overarching aim is to ensure that informed consent is based on high quality studies and information supplied to donors and recipients, offering the strongest possible guarantees.

Live donor kidney transplantation. Situation analysis and roadmap.

Living donor kidney transplantation (LDKT) is the best treatment option for end stage renal disease in terms of both patient and graft survival. However, figures on LDKT in Spain that had been continuously growing from 2005 to 2014, have experienced a continuous decrease in the last five years. One possible explanation for this decrease is that the significant increase in the number of deceased donors in Spain during the last years, both brain death and controlled circulatory death donors, might have generated the false idea that we have coped with the transplant needs. Moreover, a greater number of deceased donor kidney transplants have caused a heavy workload for the transplant teams. Furthermore, the transplant teams could have moved on to a more conservative approach to the information and assessment of patients and families considering the potential long-term risks for donors in recent papers. However, there is a significant variability in the LDKT rate among transplant centers and regions in Spain independent of their deceased donor rates. This fact and the fact that LDKT is usually a preemptive option for patients with advanced chronic renal failure, as time on dialysis is a negative independent factor for transplant outcomes, lead us to conclude that the decrease in LDKT depends on other factors. Thus, in the kidney transplant annual meeting held at ONT site in 2018, a working group was created to identify other causes for the decrease of LDKT in Spain and its relationship with the different steps of the process. The group was formed by transplant teams, a representative of the transplant group of the Spanish Society of Nephrology (SENTRA), a representative of the Spanish Society of Transplants (SET) and representatives of the Spanish National Transplant Organization (ONT). A self-evaluation survey that contains requests about the phases of the LDKT processes (information, donor work out, informed consent, surgeries, follow-up and human resources) were developed and sent to 33 LDKT teams. All the centers answered the questionnaire. The analysis of the answers has resulted in the creation of a national analysis of strengths, weaknesses, opportunities, threats (SWOT) of the LDKT program in Spain and the development of recommendations targeted to improve every step of the donation process. The work performed, the conclusions and recommendations provided, have been reflected in the following report: Spanish living donor kidney transplant program assessment: recommendations for optimization. This document has also been reviewed by a panel of experts, representatives of the scientific societies (Spanish Society of Urology (AEU), Spanish Society of Nephrology Nursery (SEDEN), Spanish Society of Immunology (SEI/GETH)) and the patient association ALCER. Finally, the report has been submitted to public consultation, reaching ample consensus. In addition, the transplant competent authorities of the different regions in Spainhave adopted the report at institutional level. The work done and the recommendations to optimize LDKT are summarized in the present manuscript, organized by the different phases of the donation process.

Native metabolomics identifies the rivulariapeptolide family of protease inhibitors.

The identity and biological activity of most metabolites still remain unknown. A bottleneck in the exploration of metabolite structures and pharmaceutical activities is the compound purification needed for bioactivity assignments and downstream structure elucidation. To enable bioactivity-focused compound identification from complex mixtures, we develop a scalable native metabolomics approach that integrates non-targeted liquid chromatography tandem mass spectrometry and detection of protein binding via native mass spectrometry. A native metabolomics screen for protease inhibitors from an environmental cyanobacteria community reveals 30 chymotrypsin-binding cyclodepsipeptides. Guided by the native metabolomics results, we select and purify five of these compounds for full structure elucidation via tandem mass spectrometry, chemical derivatization, and nuclear magnetic resonance spectroscopy as well as evaluation of their biological activities. These results identify rivulariapeptolides as a family of serine protease inhibitors with nanomolar potency, highlighting native metabolomics as a promising approach for drug discovery, chemical ecology, and chemical biology studies.

Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2-Acylpyrrole Derivatives.

In this work, the SOFT.PTML tool has been used to pre-process a ChEMBL dataset of pre-clinical assays of antileishmanial compound candidates. A comparative study of different ML algorithms, such as logistic regression (LOGR), support vector machine (SVM), and random forests (RF), has shown that the IFPTML-LOGR model presents excellent values of specificity and sensitivity (81-98%) in training and validation series. The use of this software has been illustrated with a practical case study focused on a series of 28 derivatives of 2-acylpyrroles 5a,b, obtained through a Pd(II)-catalyzed C-H radical acylation of pyrroles. Their in vitro leishmanicidal activity against visceral (L. donovani) and cutaneous (L. amazonensis) leishmaniasis was evaluated finding that compounds 5bc (IC50 = 30.87 µM, SI > 10.17) and 5bd (IC50 = 16.87 µM, SI > 10.67) were approximately 6-fold more selective than the drug of reference (miltefosine) in in vitro assays against L. amazonensis promastigotes. In addition, most of the compounds showed low cytotoxicity, CC50 > 100 µg/mL in J774 cells. Interestingly, the IFPMTL-LOGR model predicts correctly the relative biological activity of these series of acylpyrroles. A computational high-throughput screening (cHTS) study of 2-acylpyrroles 5a,b has been performed calculating >20,700 activity scores vs a large space of 647 assays involving multiple Leishmania species, cell lines, and potential target proteins. Overall, the study demonstrates that the SOFT.PTML all-in-one strategy is useful to obtain IFPTML models in a friendly interface making the work easier and faster than before. The present work also points to 2-acylpyrroles as new lead compounds worthy of further optimization as antileishmanial hits.

A Noninvasive Method for Time-Lapse Imaging of Microbial Interactions and Colony Dynamics.

Complex interactions between microbial populations can greatly affect the overall properties of a microbial community, sometimes leading to cooperation and mutually beneficial coexistence, or competition and the death or displacement of organisms or subpopulations. Interactions between different biofilm populations are highly relevant in diverse scientific areas, from antimicrobial resistance to microbial ecology. The utilization of modern microscopic techniques has provided a new and interesting insight into how bacteria interact at the cellular level to form and maintain microbial biofilms. However, our ability to follow complex intraspecies and interspecies interactions in vivo at the microscopic level has remained somewhat limited. Here, we detailed BacLive, a novel noninvasive method for tracking bacterial growth and biofilm dynamics using high-resolution fluorescence microscopy and an associated ImageJ processing macro (https://github.com/BacLive) for easier data handling and image analysis. Finally, we provided examples of how BacLive can be used in the analysis of complex bacterial communities. IMPORTANCE Communication and interactions between single cells are continuously defining the structure and composition of microbial communities temporally and spatially. Methods routinely used to study these communities at the cellular level rely on sample manipulation which makes microscopic time-lapse experiments impossible. BacLive was conceived as a method for the noninvasive study of the formation and development of bacterial communities, such as biofilms, and the formation dynamics of specialized subpopulations in time-lapse experiments at a colony level. In addition, we developed a tool to simplify the processing and analysis of the data generated by this method.

Learning to count biological structures with raters' uncertainty.

Exploiting well-labeled training sets has led deep learning models to astonishing results for counting biological structures in microscopy images. However, dealing with weak multi-rater annotations, i.e., when multiple human raters disagree due to non-trivial patterns, remains a relatively unexplored problem. More reliable labels can be obtained by aggregating and averaging the decisions given by several raters to the same data. Still, the scale of the counting task and the limited budget for labeling prohibit this. As a result, making the most with small quantities of multi-rater data is crucial. To this end, we propose a two-stage counting strategy in a weakly labeled data scenario. First, we detect and count the biological structures; then, in the second step, we refine the predictions, increasing the correlation between the scores assigned to the samples and the raters' agreement on the annotations. We assess our methodology on a novel dataset comprising fluorescence microscopy images of mice brains containing extracellular matrix aggregates named perineuronal nets. We demonstrate that we significantly enhance counting performance, improving confidence calibration by taking advantage of the redundant information characterizing the small sets of available multi-rater data.

BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions.

In this paper, we developed BreastScreening-AI within two scenarios for the classification of multimodal beast images: (1) Clinician-Only; and (2) Clinician-AI. The novelty relies on the introduction of a deep learning method into a real clinical workflow for medical imaging diagnosis. We attempt to address three high-level goals in the two above scenarios. Concretely, how clinicians: i) accept and interact with these systems, revealing whether are explanations and functionalities required; ii) are receptive to the introduction of AI-assisted systems, by providing benefits from mitigating the clinical error; and iii) are affected by the AI assistance. We conduct an extensive evaluation embracing the following experimental stages: (a) patient selection with different severities, (b) qualitative and quantitative analysis for the chosen patients under the two different scenarios. We address the high-level goals through a real-world case study of 45 clinicians from nine institutions. We compare the diagnostic and observe the superiority of the Clinician-AI scenario, as we obtained a decrease of 27% for False-Positives and 4% for False-Negatives. Through an extensive experimental study, we conclude that the proposed design techniques positively impact the expectations and perceptive satisfaction of 91% clinicians, while decreasing the time-to-diagnose by 3 min per patient.

Model-Agnostic Temporal Regularizer for Object Localization Using Motion Fields.

Video analysis often requires locating and tracking target objects. In some applications, the localization system has access to the full video, which allows fine-grain motion information to be estimated. This paper proposes capturing this information through motion fields and using it to improve the localization results. The learned motion fields act as a model-agnostic temporal regularizer that can be used with any localization system based on keypoints. Unlike optical flow-based strategies, our motion fields are estimated from the model domain, based on the trajectories described by the object keypoints. Therefore, they are not affected by poor imaging conditions. The benefits of the proposed strategy are shown on three applications: 1) segmentation of cardiac magnetic resonance; 2) facial model alignment; and 3) vehicle tracking. In each case, combining popular localization methods with the proposed regularizer leads to improvement in overall accuracies and reduces gross errors.

Microwave-assisted palladium catalysed C-H acylation with aldehydes: synthesis and diversification of 3-acylthiophenes.

The use of MW allows the efficient palladium(II)-catalysed C-3 acylation of thiophenes with aldehydes via C(sp2)-H activation for the synthesis of (cyclo)alkyl/aryl thienyl ketones (43 examples). Compared to standard thermal conditions, the use of MW reduces the reaction time (15 to 30 min vs. 1 to 3 hours), leading to improved yields of the ketones (up to 92%). The control of positional selectivity is achieved by 2-pyridinyl and 2-pyrimidyl ortho-directing groups at C-2 of the thiophene scaffold. To show the synthetic applicability, selected ketones were subjected to further transformations, including intramolecular reactions to directly embed the directing group in the core structure of the new molecule.

CyCoSeg: A Cyclic Collaborative Framework for Automated Medical Image Segmentation.

Deep neural networks have been tremendously successful at segmenting objects in images. However, it has been shown they still have limitations on challenging problems such as the segmentation of medical images. The main reason behind this lower success resides in the reduced size of the object in the image. In this paper we overcome this limitation through a cyclic collaborative framework, CyCoSeg. The proposed framework is based on a deep active shape model (D-ASM), which provides prior information about the shape of the object, and a semantic segmentation network (SSN). These two models collaborate to reach the desired segmentation by influencing each other: SSN helps D-ASM identify relevant keypoints in the image through an Expectation Maximization formulation, while D-ASM provides a segmentation proposal that guides the SSN. This cycle is repeated until both models converge. Extensive experimental evaluation shows CyCoSeg boosts the performance of the baseline models, including several popular SSNs, while avoiding major architectural modifications. The effectiveness of our method is demonstrated on the left ventricle segmentation on two benchmark datasets, where our approach achieves one of the most competitive results in segmentation accuracy. Furthermore, its generalization is demonstrated for lungs and kidneys segmentation in CT scans.

Gut microbiota-driven brain Aß amyloidosis in mice requires microglia.

We previously demonstrated that lifelong antibiotic (ABX) perturbations of the gut microbiome in male APPPS1-21 mice lead to reductions in amyloid ß (Aß) plaque pathology and altered phenotypes of plaque-associated microglia. Here, we show that a short, 7-d treatment of preweaned male mice with high-dose ABX is associated with reductions of Aß amyloidosis, plaque-localized microglia morphologies, and Aß-associated degenerative changes at 9 wk of age in male mice only. More importantly, fecal microbiota transplantation (FMT) from transgenic (Tg) or WT male donors into ABX-treated male mice completely restored Aß amyloidosis, plaque-localized microglia morphologies, and Aß-associated degenerative changes. Transcriptomic studies revealed significant differences between vehicle versus ABX-treated male mice and FMT from Tg mice into ABX-treated mice largely restored the transcriptome profiles to that of the Tg donor animals. Finally, colony-stimulating factor 1 receptor (CSF1R) inhibitor-mediated depletion of microglia in ABX-treated male mice failed to reduce cerebral Aß amyloidosis. Thus, microglia play a critical role in driving gut microbiome-mediated alterations of cerebral Aß deposition.

Chemical Proportionality within Molecular Networks.

Molecular networking of non-targeted tandem mass spectrometry data connects structurally related molecules based on similar fragmentation spectra. Here, we report the Chemical Proportionality (ChemProp) contextualization of molecular networks. ChemProp scores the changes of abundance between two connected nodes over sequential data series (e.g., temporal or spatial relationships), which can be displayed as a direction within the network to prioritize potential biological and chemical transformations or proportional changes of (biosynthetically) related compounds. We tested the ChemProp workflow on a ground truth data set of a defined mixture and highlighted the utility of the tool to prioritize specific molecules within biological samples, including bacterial transformations of bile acids, human drug metabolism, and bacterial natural products biosynthesis. The ChemProp workflow is freely available through the Global Natural Products Social Molecular Networking (GNPS) environment.

Management of acquired hemophilia A: results from the Spanish registry.

The Spanish Acquired Hemophilia A (AHA) Registry is intended to update the status of AHA in Spain. One hundred and fifty-four patients were included and retrospectively followed for a median of 12 months. Patients were predominantly male (56.3%), with median age at diagnosis of 74 years. AHA was more frequently idiopathic (44.1%) and autoimmune disorder-associated (31.7%). Thirty-four percent of patients were on antithrombotic therapy at diagnosis. Hemostatic treatment was used in 70% of patients. Recombinant activated factor VII was more frequently infused (60.3% vs 20.6% activated prothrombin complex concentrate). Only 1 patient did not achieve control of hemorrhage. Complete remission (CR) was achieved by 84.2% of cases after immunosuppressive therapy. Steroids alone were less efficient than the other strategies (68.2% vs 87.2%, P = .049), whereas no differences existed among these (steroids/cyclophosphamide, 88.5%, vs steroids/calcineurin inhibitors, 81.2%, vs rituximab-based regimens, 87.5%). Female sex and high inhibitor levels influenced CR negatively. Thirty-six deaths (23.8%) were reported. Main causes of death were infection (15 patients, 9.9%) and hemorrhage (5 patients, 3.3%). All hemorrhage-related and half the infection-related deaths occurred within 2 months of diagnosis. Prior antithrombotic therapy was inversely associated with survival, irrespective of age. Median age of nonsurvivors was significantly higher (79 vs 73 years in survivors). Patients dying of infection were older than the other nonsurvivors (85 vs 78 years). In summary, fatal infection in the first months is common in our series. Antithrombotic therapy is associated with mortality. Particular care should be taken to avoid misdiagnosis.

Live donor kidney transplantation. Situation analysis and roadmap. / Trasplante renal de donante vivo. Análisis de situación y hoja de ruta.

Living donor kidney transplantation (LDKT) is the best treatment option for end stage renal disease in terms of both patient and graft survival. However, figures on LDKT in Spain that had been continuously growing from 2005 to 2014, have experienced a continuous decrease in the last five years. One possible explanation for this decrease is that the significant increase in the number of deceased donors in Spain during the last years, both brain death and controlled circulatory death donors, might have generated the false idea that we have coped with the transplant needs. Moreover, a greater number of deceased donor kidney transplants have caused a heavy workload for the transplant teams. Furthermore, the transplant teams could have moved on to a more conservative approach to the information and assessment of patients and families considering the potential long-term risks for donors in recent papers. However, there is a significant variability in the LDKT rate among transplant centers and regions in Spain independent of their deceased donor rates. This fact and the fact that LDKT is usually a preemptive option for patients with advanced chronic renal failure, as time on dialysis is a negative independent factor for transplant outcomes, lead us to conclude that the decrease in LDKT depends on other factors. Thus, in the kidney transplant annual meeting held at ONT site in 2018, a working group was created to identify other causes for the decrease of LDKT in Spain and its relationship with the different steps of the process. The group was formed by transplant teams, a representative of the transplant group of the Spanish Society of Nephrology (SENTRA), a representative of the Spanish Society of Transplants (SET) and representatives of the Spanish National Transplant Organization (ONT). A self-evaluation survey that contains requests about the phases of the LDKT processes (information, donor work out, informed consent, surgeries, follow-up and human resources) were developed and sent to 33 LDKT teams. All the centers answered the questionnaire. The analysis of the answers has resulted in the creation of a national analysis of strengths, weaknesses, opportunities, threats (SWOT) of the LDKT program in Spain and the development of recommendations targeted to improve every step of the donation process. The work performed, the conclusions and recommendations provided, have been reflected in the following report: Spanish living donor kidney transplant program assessment: recommendations for optimization. This document has also been reviewed by a panel of experts, representatives of the scientific societies (Spanish Society of Urology (AEU), Spanish Society of Nephrology Nursery (SEDEN), Spanish Society of Immunology (SEI/GETH)) and the patient association ALCER. Finally, the report has been submitted to public consultation, reaching ample consensus. In addition, the transplant competent authorities of the different regions in Spain have adopted the report at institutional level. The work done and the recommendations to optimize LDKT are summarized in the present manuscript, organized by the different phases of the donation process.

Chemical interplay and complementary adaptative strategies toggle bacterial antagonism and co-existence.

Bacterial communities are in a continuous adaptive and evolutionary race for survival. In this work we expand our knowledge on the chemical interplay and specific mutations that modulate the transition from antagonism to co-existence between two plant-beneficial bacteria, Pseudomonas chlororaphis PCL1606 and Bacillus amyloliquefaciens FZB42. We reveal that the bacteriostatic activity of bacillaene produced by Bacillus relies on an interaction with the protein elongation factor FusA of P. chlororaphis and how mutations in this protein lead to tolerance to bacillaene and other protein translation inhibitors. Additionally, we describe how the unspecific tolerance of B. amyloliquefaciens to antimicrobials associated with mutations in the glycerol kinase GlpK is provoked by a decrease of Bacillus cell membrane permeability, among other pleiotropic responses. We conclude that nutrient specialization and mutations in basic biological functions are bacterial adaptive dynamics that lead to the coexistence of two primary competitive bacterial species rather than their mutual eradication.