Evidence of host-virus co-evolution in tetranucleotide usage patterns of bacteriophages and eukaryotic viruses

BACKGROUND: Virus taxonomy is based on morphologic characteristics, as there are no widely used non-phenotypic measures for comparison among virus families. We examined whether there is phylogenetic signal in virus nucleotide usage patterns that can be used to determine ancestral relationships. The well-studied model of tail morphology in bacteriophage classification was used for comparison with nucleotide usage patterns. Tetranucleotide usage deviation (TUD) patterns were chosen since they have previously been shown to contain phylogenetic signal similar to that of 16S rRNA. RESULTS: We found that bacteriophages have unique TUD patterns, representing genomic signatures that are relatively conserved among those with similar host range. Analysis of TUD-based phylogeny indicates that host influences are important in bacteriophage evolution, and phylogenies containing both phages and their hosts support their co-evolution. TUD-based phylogeny of eukaryotic viruses indicates that they cluster largely based on nucleic acid type and genome size. Similarities between eukaryotic virus phylogenies based on TUD and gene content substantiate the TUD methodology. CONCLUSION: Differences between phenotypic and TUD analysis may provide clues to virus ancestry not previously inferred. As such, TUD analysis provides a complementary approach to morphology-based systems in analysis of virus evolution

Sequential Voxel-Based Leaflet Segmentation of Complex Lipid Morphologies

[Image: see text] As molecular dynamics simulations increase in complexity, new analysis tools are necessary to facilitate interpreting the results. Lipids, for instance, are known to form many complicated morphologies, because of their amphipathic nature, becoming more intricate as the particle count increases. A few lipids might form a micelle, where aggregation of tens of thousands could lead to vesicle formation. Millions of lipids comprise a cell and its organelle membranes, and are involved in processes such as neurotransmission and transfection. To study such phenomena, it is useful to have analysis tools that understand what is meant by emerging entities such as micelles and vesicles. Studying such systems at the particle level only becomes extremely tedious, counterintuitive, and computationally expensive. To address this issue, we developed a method to track all the individual lipid leaflets, allowing for easy and quick detection of topological changes at the mesoscale. By using a voxel-based approach and focusing on locality, we forego costly geometrical operations without losing important details and chronologically identify the lipid segments using the Jaccard index. Thus, we achieve a consistent sequential segmentation on a wide variety of (lipid) systems, including monolayers, bilayers, vesicles, inverted hexagonal phases, up to the membranes of a full mitochondrion. It also discriminates between adhesion and fusion of leaflets. We show that our method produces consistent results without the need for prefitting parameters, and segmentation of millions of particles can be achieved on a desktop machine

Patient-reported outcomes during repetitive oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy for isolated unresectable colorectal peritoneal metastases in a multicenter, single-arm, phase 2 trial (CRC-PIPAC)

BACKGROUND: CRC-PIPAC prospectively assessed repetitive oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy (PIPAC-OX) as a palliative monotherapy (i.e., without concomitant systemic therapy in between subsequent procedures) for unresectable colorectal peritoneal metastases (CPM). The present study explored patient-reported outcomes (PROs) during trial treatment. METHODS: In this single-arm phase 2 trial in two tertiary centers, patients with isolated unresectable CPM received 6-weekly PIPAC-OX (92 mg/m(2)). PROs (calculated from EQ-5D-5L, and EORTC QLQ-C30 and QLQ-CR29) were compared between baseline and 1 and 4 weeks after the first three procedures using linear mixed modeling with determination of clinical relevance (Cohen’s D ≥ 0.50) of statistically significant differences. RESULTS: Twenty patients underwent 59 procedures (median 3 [range 1–6]). Several PROs solely worsened 1 week after the first procedure (index value − 0.10, p < 0.001; physical functioning − 20, p < 0.001; role functioning − 27, p < 0.001; social functioning − 18, p < 0.001; C30 summary score − 16, p < 0.001; appetite loss + 15, p = 0.007; diarrhea + 15, p = 0.002; urinary frequency + 13, p = 0.004; flatulence + 13, p = 0.001). These PROs returned to baseline at subsequent time points. Other PROs worsened 1 week after the first procedure (fatigue + 23, p < 0.001; pain + 29, p < 0.001; abdominal pain + 32, p < 0.001), second procedure (fatigue + 20, p < 0.001; pain + 21, p < 0.001; abdominal pain + 20, p = 0.002), and third procedure (pain + 22, p < 0.001; abdominal pain + 22, p = 0.002). Except for appetite loss, all changes were clinically relevant. All analyzed PROs returned to baseline 4 weeks after the third procedure. CONCLUSIONS: Patients receiving repetitive PIPAC-OX monotherapy for unresectable CPM had clinically relevant but reversible worsening of several PROs, mainly 1 week after the first procedure. TRIAL REGISTRATION: Clinicaltrials.gov: NCT03246321; Netherlands trial register: NL6426. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00464-021-08802-6

The eNMR platform for structural biology

The e-NMR project is a European cooperation initiative that aims at providing the bio-NMR user community with a software platform integrating and streamlining the computational approaches necessary for the analysis of bio-NMR data. The e-NMR platform is based on a Grid computational infrastructure. A main focus of the current implementation of the e-NMR platform is on streamlining structure determination protocols. Indeed, to facilitate the use of NMR spectroscopy in the life sciences, the eNMR consortium has set out to provide protocolized services through easy-to-use web interfaces, while still retaining sufficient flexibility to handle specific requests by expert users. Various programs relevant for structural biology applications are already available through the e-NMR portal, including HADDOCK, XPLOR-NIH, CYANA and csRosetta. The implementation of these services, and in particular the distribution of calculations to the GRID infrastructure, has required the development of specific tools. However, the GRID infrastructure is maintained completely transparent to the users. With more than 150 registered users, eNMR is currently the second largest European Virtual Organization in the life sciences

Building Science Gateways for Analysing Molecular Docking Results Using a Generic Framework and Methodology

Molecular docking and virtual screening experiments require large computational and data resources and high-level user interfaces in the form of science gateways. While science gateways supporting such experiments are relatively common, there is a clearly identified need to design and implement more complex environments for further analysis of docking results. This paper describes a generic framework and a related methodology that supports the efficient development of such environments. The framework is modular enabling the reuse of already existing components. The methodology, which proposes three techniques that the development team can use, is agile and encourages active participation of end-users. Based on the framework and methodology, two prototype implementations of science-gateway-based docking environments are presented and evaluated. The first system recommends a receptor-ligand pair for the next docking experiment, and the second filters docking results based on ligand properties

Martini 3 : a general purpose force field for coarse-grained molecular dynamics

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 (http://cgmartini.nl), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.Peer reviewe

Structural Anisotropy in Polar Fluids Subjected to Periodic Boundary Conditions

A heuristic model based on dielectric continuum theory for the long-range solvation free energy of a dipolar system possessing periodic boundary conditions (PBCs) is presented. The predictions of the model are compared to simulation results for Stockmayer fluids simulated using three different cell geometries. The boundary effects induced by the PBCs are shown to lead to anisotropies in the apparent dielectric constant and the long-range solvation free energy of as much as 50%. However, the sum of all of the anisotropic energy contributions yields a value that is very close to the isotropic one derived from dielectric continuum theory, leading to a total system energy close to the dielectric value. It is finally shown that the leading-order contribution to the energetic and structural anisotropy is significantly smaller in the noncubic simulation cell geometries compared to when using a cubic simulation cell

Farseer-NMR: automatic treatment, analysis and plotting of large, multi-variable NMR data

We present Farseer-NMR (https://git.io/vAueU), a software package to treat, evaluate and combine NMR spectroscopic data from sets of protein-derived peaklists covering a range of experimental conditions. The combined advances in NMR and molecular biology enable the study of complex biomolecular systems such as flexible proteins or large multibody complexes, which display a strong and functionally relevant response to their environmental conditions, e.g. the presence of ligands, site-directed mutations, post translational modifications, molecular crowders or the chemical composition of the solution. These advances have created a growing need to analyse those systems’ responses to multiple variables. The combined analysis of NMR peaklists from large and multivariable datasets has become a new bottleneck in the NMR analysis pipeline, whereby information-rich NMR-derived parameters have to be manually generated, which can be tedious, repetitive and prone to human error, or even unfeasible for very large datasets. There is a persistent gap in the development and distribution of software focused on peaklist treatment, analysis and representation, and specifically able to handle large multivariable datasets, which are becoming more commonplace. In this regard, Farseer-NMR aims to close this longstanding gap in the automated NMR user pipeline and, altogether, reduce the time burden of analysis of large sets of peaklists from days/weeks to seconds/minutes. We have implemented some of the most common, as well as new, routines for calculation of NMR parameters and several publication-quality plotting templates to improve NMR data representation. Farseer-NMR has been written entirely in Python and its modular code base enables facile extension