Leptospira interrogans Bat proteins impair host hemostasis by fibrinogen cleavage and platelet aggregation inhibition.

Leptospirosis is a worldwide spread zoonosis, caused by pathogenic Leptospira. Evidences suggest that compromised hemostasis might be involved in the leptospirosis pathophysiology. In the genome of L. interrogans serovar Copenhageni, we found two genes coding for proteins which comprise von Willebrand factor (VWF) A domains (BatA and BatB). As VWF A domains exhibit multiple binding sites which contributes to human VWF hemostatic functions, we hypothesized that the L. interrogans BatA and BatB proteins could be involved in the hemostatic impairment during leptospirosis. We have cloned, expressed in Escherichia coli, and purified recombinant BatA and BatB. The influence of recombinant BatA and BatB on different in vitro hemostatic assays evaluating the enzymatic activity, platelet aggregation and fibrinogen integrity was investigated. We describe BatB as a new serine protease which is able to cleave thrombin chromogenic substrate, fibrin, fibrinogen, gelatin and casein; while BatA is active only towards fibrinogen. BatA and BatB interfere with the platelet aggregation induced by VWF/ristocetin and thrombin. Our results suggest an important role of the L. interrogans serovar Copenhageni Bat proteins in the hemostasis dysfunction observed during leptospirosis and contribute to the understanding of the leptospirosis pathophysiological mechanisms.

A Novel Leptospira interrogans Protein LIC13086 Inhibits Fibrin Clot Formation and Interacts With Host Components.

Leptospirosis is a neglected zoonosis, caused by pathogenic spirochetes bacteria of the genus Leptospira. The molecular mechanisms of leptospirosis infection are complex, and it is becoming clear that leptospires express several functionally redundant proteins to invade, disseminate, and escape the host's immune response. Here, we describe a novel leptospiral protein encoded by the gene LIC13086 as an outer membrane protein. The recombinant protein LIC13086 can interact with the extracellular matrix component laminin and bind plasminogen, thus possibly participating during the adhesion process and dissemination. Also, by interacting with fibrinogen and plasma fibronectin, the protein LIC13086 probably has an inhibitory effect in the fibrin clot formation during the infection process. The newly characterized protein can also bind molecules of the complement system and the regulator C4BP and, thus, might have a role in the evasion mechanism of Leptospira. Taken together, our results suggest that the protein LIC13086 may have a multifunctional role in leptospiral pathogenesis, participating in host invasion, dissemination, and immune evasion processes.

The Leptospira interrogans LIC10774 is a multifunctional surface protein that binds calcium and interacts with host components.

Leptospirosis is a global re-emerging zoonosis, caused by pathogenic bacteria of the genus Leptospira. Humans are infected mainly through contact with contaminated water or soil. The understanding of the molecular mechanisms of leptospirosis through the characterization of unknown outer membrane proteins may contribute to the development of new treatments, diagnostic methods and vaccines. We have identified using bioinformatics analysis a protein that is encoded by the gene LIC10774, predicted to be localized at the leptospiral outer membrane and exhibit beta-roll folding. Surface exposure was confirmed by flow cytometry, ELISA and immunofluorescence-based confocal microscopy. Through circular dichroism spectroscopy and hydrophobic dye binding we have shown that rLIC10774 binds calcium ions, which imposes changes to secondary and tertiary structures. The recombinant protein was capable of binding to several host extracellular matrix and serum components. Therefore, we describe LIC10774 as a calcium-binding protein exposed in the outer surface of pathogenic leptospires with possible multifunctional roles in adhesion to host tissues, evasion of the immune system and participation in dissemination processes during leptospirosis. In addition, we hypothesize that the calcium binding is important for temperature-dependent functional roles during leptospirosis.

A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

Morphological analysis is the standard method of assessing embryo quality; however, its inherent subjectivity tends to generate discrepancies among evaluators. Using genetic algorithms and artificial neural networks (ANNs), we developed a new method for embryo analysis that is more robust and reliable than standard methods. Bovine blastocysts produced in vitro were classified as grade 1 (excellent or good), 2 (fair), or 3 (poor) by three experienced embryologists according to the International Embryo Technology Society (IETS) standard. The images (n = 482) were subjected to automatic feature extraction, and the results were used as input for a supervised learning process. One part of the dataset (15%) was used for a blind test posterior to the fitting, for which the system had an accuracy of 76.4%. Interestingly, when the same embryologists evaluated a sub-sample (10%) of the dataset, there was only 54.0% agreement with the standard (mode for grades). However, when using the ANN to assess this sub-sample, there was 87.5% agreement with the modal values obtained by the evaluators. The presented methodology is covered by National Institute of Industrial Property (INPI) and World Intellectual Property Organization (WIPO) patents and is currently undergoing a commercial evaluation of its feasibility.

Automatized image processing of bovine blastocysts produced in vitro for quantitative variable determination.

There is currently no objective, real-time and non-invasive method for evaluating the quality of mammalian embryos. In this study, we processed images of in vitro produced bovine blastocysts to obtain a deeper comprehension of the embryonic morphological aspects that are related to the standard evaluation of blastocysts. Information was extracted from 482 digital images of blastocysts. The resulting imaging data were individually evaluated by three experienced embryologists who graded their quality. To avoid evaluation bias, each image was related to the modal value of the evaluations. Automated image processing produced 36 quantitative variables for each image. The images, the modal and individual quality grades, and the variables extracted could potentially be used in the development of artificial intelligence techniques (e.g., evolutionary algorithms and artificial neural networks), multivariate modelling and the study of defined structures of the whole blastocyst.