Structural and Energetic Characterization of the Ankyrin Repeat Protein Family

Ankyrin repeat containing proteins are one of the most abundant solenoid folds. Usually implicated in specific protein-protein interactions, these proteins are readily amenable for design, with promising biotechnological and biomedical applications. Studying repeat protein families presents technical challenges due to the high sequence divergence among the repeating units. We developed and applied a systematic method to consistently identify and annotate the structural repetitions over the members of the complete Ankyrin Repeat Protein Family, with increased sensitivity over previous studies. We statistically characterized the number of repeats, the folding of the repeat-arrays, their structural variations, insertions and deletions. An energetic analysis of the local frustration patterns reveal the basic features underlying fold stability and its relation to the functional binding regions. We found a strong linear correlation between the conservation of the energetic features in the repeat arrays and their sequence variations, and discuss new insights into the organization and function of these ubiquitous proteins.Fil: Parra, Rodrigo Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Espada, Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Verstraete, Nina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Ferreiro, Diego Ulises. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentin

Amino acid metabolism conflicts with protein diversity

The twenty protein coding amino acids are found in proteomes with different relative abundances. The most abundant amino acid, leucine, is nearly an order of magnitude more prevalent than the least abundant amino acid, cysteine. Amino acid metabolic costs differ similarly, constraining their incorporation into proteins. On the other hand, sequence diversity is necessary for protein folding, function and evolution. Here we present a simple model for a cost-diversity trade-off postulating that natural proteomes minimize amino acid metabolic flux while maximizing sequence entropy. The model explains the relative abundances of amino acids across a diverse set of proteomes. We found that the data is remarkably well explained when the cost function accounts for amino acid chemical decay. More than one hundred proteomes reach comparable solutions to the trade-off by different combinations of cost and diversity. Quantifying the interplay between proteome size and entropy shows that proteomes can get optimally large and diverse

Detection of small tendon lesions by sonoelastographic visualization of strain profile differences: initial experiences

Purpose: To assess the capability of a commercial sonoelastography system to detect small tendon lesions by quantitative analysis of elastogram profiles. Materials and methods: Strips of equine digital flexor tendons were used to model small human tendons. Two tendons were examined. From each tendon, six unmodified tendon strips (controls) and six tendon strips with a central defect of the same tendons were compared. The tendon strips were placed under a physiological tensile strain of 5%. Sonoelastographic visualization of the strain profile was performed. Regions of interest (ROI) were defined left and right of the tendon defects. Average tissue strains in these ROI were compared with tissue strain in controls. Results: In the first series of experiments, there was a significant (p = 0.011) difference in the strain profile in regions proximal and distal to the tendon lesions compared with the respective tendon areas in the control tendon strips. In a second series of experiments, similar trends were observed, but the differences were not significant (p = 0.824). Conclusion: Even under carefully controlled experimental conditions using computational post-processing of sonoelastograms, tendon lesions could only be partially detected within elastograms from a clinical sonoelastography system. The ability to detect differences in some strain profiles indicates that tensile sonoelastography has the potential to identify small tendon lesions (such as those in the hand), but that substantial improvements with respect to quantitative analysis are required to make such measures diagnostically relevan

A single point mutation in cyclin T1 eliminates binding to Hexim1, Cdk9 and RNA but not to AFF4 and enforces repression of HIV transcription

BACKGROUND: Human immunodeficiency virus (HIV) gene expression is primarily regulated at the step of transcription elongation. The viral Tat protein recruits the Positive Transcription Elongation Factor b (P-TEFb) and the Super Elongation Complex (SEC) to the HIV promoter and enhances transcription by host RNA polymerase II. RESULTS: To map residues in the cyclin box of cyclin T1 that mediate the binding of P-TEFb to its interacting host partners and support HIV transcription, a pool of N-terminal cyclin T1 mutants was generated. Binding and functional assays in cells identified specific positions in cyclin T1 that are important for (i) association of P-TEFb with Hexim1, Cdk9 and SEC/AFF4 (ii) supporting Tat-transactivation in murine cells and (iii) inhibition of basal and Tat-dependent HIV transcription in human cells. Significantly, a unique cyclin T1 mutant where a Valine residue at position 107 was mutated to Glutamate (CycT1-V107E) was identified. CycT1-V107E did not bind to Hexim1 or Cdk9, and also could not assemble on HIV TAR or 7SK-snRNA. However, it bound strongly to AFF4 and its association with HIV Tat was slightly impaired. CycT1-V107E efficiently inhibited HIV replication in human T cell lines and in CD4(+) primary cells, and enforced HIV transcription repression in T cell lines that harbor a transcriptionally silenced integrated provirus. CONCLUSIONS: This study outlines the mechanism by which CycT1-V107E mutant inhibits HIV transcription and enforces viral latency. It defines the importance of N-terminal residues of cyclin T1 in mediating contacts of P-TEFb with its transcription partners, and signifies the requirement of a functional P-TEFb and SEC in mediating HIV transcription

Multiscale statistical physics of the pan-viral interactome unravels the systemic nature of SARS-CoV-2 infections

AbstractProtein–protein interaction networks have been used to investigate the influence of SARS-CoV-2 viral proteins on the function of human cells, laying out a deeper understanding of COVID–19 and providing ground for applications, such as drug repurposing. Characterizing molecular (dis)similarities between SARS-CoV-2 and other viral agents allows one to exploit existing information about the alteration of key biological processes due to known viruses for predicting the potential effects of this new virus. Here, we compare the novel coronavirus network against 92 known viruses, from the perspective of statistical physics and computational biology. We show that regulatory spreading patterns, physical features and enriched biological pathways in targeted proteins lead, overall, to meaningful clusters of viruses which, across scales, provide complementary perspectives to better characterize SARS-CoV-2 and its effects on humans. Our results indicate that the virus responsible for COVID–19 exhibits expected similarities, such as to Influenza A and Human Respiratory Syncytial viruses, and unexpected ones with different infection types and from distant viral families, like HIV1 and Human Herpes virus. Taken together, our findings indicate that COVID–19 is a systemic disease with potential effects on the function of multiple organs and human body sub-systems

BioDATA - Biodiversity Data for Internationalisation in Higher Education

BioDATA is an international project on developing skills in biodiversity data management and data publishing. Between 2018 and 2021, undergraduate and postgraduate students from Armenia, Belarus, Tajikistan, and Ukraine, have an opportunity to take part in the intensive courses to become certified professionals in biodiversity data management. They will gain practical skills and obtain appropriate knowledge on: international data standards (Darwin Core); data cleaning software, data publishing software such as the Integrated Publishing Toolkit (IPT), and preparation of data papers. Working with databases, creating datasets, managing data for statistical analyses and publishing research papers are essential for the everyday tasks of a modern biologist. At the same time, these skills are rarely taught in higher education. Most of the contemporary professionals in biodiversity have to gain these skills independently, through colleagues, or through supervision. In addition, all the participants familiarize themselves with one of the important international research data infrastructures such as the Global Biodiversity Information Facility (GBIF). The project is coordinated by the University of Oslo (Norway) and supported by the Global Biodiversity Information Facility (GBIF). The project is funded by the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education (DIKU)

Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets

Objective: To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents. Methods: We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy after TIA or ischemic stroke. Cox regression analyses stratified by trial were performed to study the association between predictors and major bleeding. A risk prediction model was derived and validated in the PERFORM trial. Performance was assessed with the c statistic and calibration plots. Results: Major bleeding occurred in 1,530 of the 43,112 patients during 94,833 person-years of follow-up. The observed 3-year risk of major bleeding was 4.6% (95% confidence interval [CI] 4.4%–4.9%). Predictors were male sex, smoking, type of antiplatelet agents (aspirin-clopidogrel), outcome on modified Rankin Scale ≥3, prior stroke, high blood pressure, lower body mass index, elderly, Asian ethnicity, and diabetes (S2TOP-BLEED). The S2TOP-BLEED score had a c statistic of 0.63 (95% CI 0.60–0.64) and showed good calibration in the development data. Major bleeding risk ranged from 2% in patients aged 45–54 years without additional risk factors to more than 10% in patients aged 75–84 years with multiple risk factors. In external validation, the model had a c statistic of 0.61 (95% CI 0.59–0.63) and slightly underestimated major bleeding risk. Conclusions: The S2TOP-BLEED score can be used to estimate 3-year major bleeding risk in patients with a TIA or ischemic stroke who use antiplatelet agents, based on readily available characteristics. The discriminatory performance may be improved by identifying stronger predictors of major bleeding

Simulation of Nurse-Like Cells in vitro formation in co-cultures

Netlogo simulation of 5000 cells.  Cancer cells are depicted as small arrows (red, yellow or grey for NeedSignal, Apoptotic or Dead state, respectively) and myeloid cells are depicted as pentagons (blue, orange or green for Monocyte, Macrophage or NLC, respectively).</p

Structure-function analysis of the regulation of the positive transcription factor P-TEFB (CDK9/CYCT1) by HEXIM1 and HIV-1 TAT proteins

PARIS-BIUSJ-Biologie recherche (751052107) / SudocSudocFranceF