The five pillars of computational reproducibility: bioinformatics and beyond.

Computational reproducibility is a simple premise in theory, but is difficult to achieve in practice. Building upon past efforts and proposals to maximize reproducibility and rigor in bioinformatics, we present a framework called the five pillars of reproducible computational research. These include (1) literate programming, (2) code version control and sharing, (3) compute environment control, (4) persistent data sharing and (5) documentation. These practices will ensure that computational research work can be reproduced quickly and easily, long into the future. This guide is designed for bioinformatics data analysts and bioinformaticians in training, but should be relevant to other domains of study.

Out-of-plane arrivals recorded by drifting hydrophones during the Northern Ocean Rapid Surface Evolution Experiment.

This paper reports on an observation of three-dimensional (3D) arrivals for which the change in the direction of horizontally refracted sound is nearly 180°. The experimental site is Jan Mayen Channel (JMCh), which connects the Greenland and Norwegian Seas. During the experiment, signals from a moored source transmitting a 500-1500 Hz sweep every 4 h were recorded by three surface drifters equipped with hydrophone arrays. Over a 3-day period, the drifters moved north across JMCh toward the moored source. In each recording, an in-plane arrival is identified. In a subset of these recordings, a second arrival is observed, having travel time consistent with propagation from the moored source, turning at the ridge on the south side of the channel, and arriving at the drifters. In a smaller subset of recordings, a third arrival is also observed having travel time consistent with a turning point on the face of the bathymetric rise on the west end of the channel that forms the Jan Mayen volcano. A 3D ray trace is employed to show the change in direction results from repeated reflections from the seafloor such that it is classified as horizontal refraction and not a single-bounce reflection.

Comparing the Currents Measured by CARTHE, CODE and SVP Drifters as a Function of Wind and Wave Conditions in the Southwestern Mediterranean Sea.

Instruments drifting at the ocean surface are quasi-Lagrangian, that is, they do not follow exactly the near-surface ocean currents. The currents measured by three commonly-used drifters (CARTHE, CODE and SVP) are compared in a wide range of sea state conditions (winds up to 17 m/s and significant wave height up to 3 m). Nearly collocated and simultaneous drifter measurements in the southwestern Mediterranean reveal that the CARTHE and CODE drifters measure the currents in the first meter below the surface in approximately the same way. When compared to SVP drogued at 15 m nominal depth, the CODE and CARTHE currents are essentially downwind (and down-wave), with a typical speed of 0.5-1% of the wind speed. However, there is a large scatter in velocity differences between CODE/CARTHE and SVP for all wind and sea state conditions encountered, principally due to vertical and horizontal shears not related to the wind. For the CODE drifter with wind speed larger than 10 m/s and significant wave height larger than 1 m, about 30-40% of this difference can be explained by Stokes drift.

Novel Insights into Quantitative Proteomics from an Innovative Bottom-Up Simple Light Isotope Metabolic (bSLIM) Labeling Data Processing Strategy.

Simple light isotope metabolic labeling (SLIM labeling) is an innovative method to quantify variations in the proteome based on an original in vivo labeling strategy. Heterotrophic cells grown in U-[12C] as the sole source of carbon synthesize U-[12C]-amino acids, which are incorporated into proteins, giving rise to U-[12C]-proteins. This results in a large increase in the intensity of the monoisotope ion of peptides and proteins, thus allowing higher identification scores and protein sequence coverage in mass spectrometry experiments. This method, initially developed for signal processing and quantification of the incorporation rate of 12C into peptides, was based on a multistep process that was difficult to implement for many laboratories. To overcome these limitations, we developed a new theoretical background to analyze bottom-up proteomics data using SLIM-labeling (bSLIM) and established simple procedures based on open-source software, using dedicated OpenMS modules, and embedded R scripts to process the bSLIM experimental data. These new tools allow computation of both the 12C abundance in peptides to follow the kinetics of protein labeling and the molar fraction of unlabeled and 12C-labeled peptides in multiplexing experiments to determine the relative abundance of proteins extracted under different biological conditions. They also make it possible to consider incomplete 12C labeling, such as that observed in cells with nutritional requirements for nonlabeled amino acids. These tools were validated on an experimental dataset produced using various yeast strains of Saccharomyces cerevisiae and growth conditions. The workflows are built on the implementation of appropriate calculation modules in a KNIME working environment. These new integrated tools provide a convenient framework for the wider use of the SLIM-labeling strategy.

Meet-U: Educating through research immersion.

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master's students in bioinformatics and modeling, with protein-protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org.

New High-Tech Flexible Networks for the Monitoring of Deep-Sea Ecosystems.

Increasing interest in the acquisition of biotic and abiotic resources from within the deep sea (e.g., fisheries, oil-gas extraction, and mining) urgently imposes the development of novel monitoring technologies, beyond the traditional vessel-assisted, time-consuming, high-cost sampling surveys. The implementation of permanent networks of seabed and water-column-cabled (fixed) and docked mobile platforms is presently enforced, to cooperatively measure biological features and environmental (physicochemical) parameters. Video and acoustic (i.e., optoacoustic) imaging are becoming central approaches for studying benthic fauna (e.g., quantifying species presence, behavior, and trophic interactions) in a remote, continuous, and prolonged fashion. Imaging is also being complemented by in situ environmental-DNA sequencing technologies, allowing the traceability of a wide range of organisms (including prokaryotes) beyond the reach of optoacoustic tools. Here, we describe the different fixed and mobile platforms of those benthic and pelagic monitoring networks, proposing at the same time an innovative roadmap for the automated computing of hierarchical ecological information on deep-sea ecosystems (i.e., from single species' abundance and life traits to community composition, and overall biodiversity).

Plasmodium falciparum infection in febrile Congolese children: prevalence of clinical malaria 10 years after introduction of artemisinin-combination therapies.

OBJECTIVES: To investigate the proportion of malaria infection in febrile children consulting a paediatric hospital in Brazzaville, to determine the prevalence of submicroscopic malaria infection, to characterise Plasmodium falciparum infection and compare the prevalence of uncomplicated P. falciparum malaria according to haemoglobin profiles. METHODS: Blood samples were collected from children aged <10 years with an axillary temperature ≥37.5 °C consulting the paediatric ward of Marien Ngouabi Hospital in Brazzaville. Parasite density was determined and all samples were screened for P. falciparum by nested polymerase chain reaction (PCR) using the P. falciparum msp-2 marker to detect submicroscopic infections and characterise P. falciparum infection. Sickle cell trait was screened by PCR. RESULTS: A total of 229 children with fever were recruited, of whom 10% were diagnosed with uncomplicated malaria and 21% with submicroscopic infection. The mean parasite density in children with uncomplicated malaria was 42 824 parasites/µl of blood. The multiplicity of infection (MOI) was 1.59 in children with uncomplicated malaria and 1.69 in children with submicroscopic infection. The mean haemoglobin level was 10.1 ± 1.7 for children with uncomplicated malaria and 12.0 ± 8.6 for children with submicroscopic infection. About 13% of the children harboured the sickle cell trait (HbAS); the rest had normal haemoglobin (HbAA). No difference in prevalence of uncomplicated malaria and submicroscopic infection, parasite density, haemoglobin level, MOI and P. falciparum genetic diversity was observed according to haemoglobin type. CONCLUSION: The low prevalence of uncomplicated malaria in febrile Congolese children indicates the necessity to investigate carefully other causes of fever.

Prostaglandin E2 release from astrocytes triggers gonadotropin-releasing hormone (GnRH) neuron firing via EP2 receptor activation.

Astrocytes in the hypothalamus release prostaglandin E(2) (PGE(2)) in response to cell-cell signaling initiated by neurons and glial cells. Upon release, PGE(2) stimulates the secretion of gonadotropin-releasing hormone (GnRH), the neuropeptide that controls reproduction, from hypothalamic neuroendocrine neurons. Whether this effect on GnRH secretion is accompanied by changes in the firing behavior of these neurons is unknown. Using patch-clamp recording we demonstrate that PGE(2) exerts a dose-dependent postsynaptic excitatory effect on GnRH neurons. These effects are mimicked by an EP2 receptor agonist and attenuated by protein kinase A (PKA) inhibitors. The acute blockade of prostaglandin synthesis by indomethacin (INDO) or the selective inhibition of astrocyte metabolism by fluoroacetate (FA) suppresses the spontaneous firing activity of GnRH neurons in brain slices. Similarly, GnRH neuronal activity is reduced in mice with impaired astrocytic PGE(2) release due to defective erbB signaling in astrocytes. These results indicate that astrocyte-to-neuron communication in the hypothalamus is essential for the activity of GnRH neurons and suggest that PGE(2) acts as a gliotransmitter within the GnRH neurosecretory system.

The αIIb p.Leu841Met (Cab3(a+) ) polymorphism results in a new human platelet alloantigen involved in neonatal alloimmune thrombocytopenia.

BACKGROUND: Fetal-neonatal alloimmune thrombocytopenia (FNAIT) diagnosis relies on maternofetal incompatibility and alloantibody identification. Genotyping for rare platelet (PLT) polymorphisms allowed the identification of three families with suspected or confirmed maternofetal incompatibility for the αIIb-c.2614C>A mutation (Halle et al., Transfusion 2008;48:14-15). STUDY DESIGN AND METHODS: A polymerase chain reaction-sequence-specific primers amplification assay was designed to genotype the αIIb-c.2614C>A mutation. HEK293 cells expressing αIIb-Leu841 or αIIb-Met841 αIIbß3 forms were used to probe the reactivity of maternal sera from these families and to study the effects of the substitution on αIIbß3 expression and functions. RESULTS: Tested by flow cytometry (FCM), one serum sample specifically reacted with αIIb-Met841 but not with αIIb-Leu841 αIIbß3. This specificity revealed the αIIb-Leu841 polymorphism as a new alloantigen named Cab3(a+) . Cross-match testing using FCM also showed the Cab3(a+) antigen to be expressed at the PLT surface. As for anti-human PLT alloantigen (HPA)-3a (or -3b) and anti-HPA-9bw, detection of anti-Cab3(a+) alloantibodies appeared difficult and required whole PLT assays when classical monoclonal antibody-specific immobilization of PLT antigen test failed. In our FNAIT set, the immune response to Cab3(a+) maternofetal incompatibility could induce severe thrombocytopenias and life-threatening hemorrhages. The p.Leu841Met substitution has limited effects, if any, on local αIIb structure, preserving both αIIbß3 expression and functions. CONCLUSION: The Cab3(a+) polymorphism is a new rare alloantigen (allelic frequency <1%) carried by αIIb that might result in severe life-threatening thrombocytopenias. In Sub-Saharan African populations, higher Cab3(a+) gene frequencies (up to 8.2%; Halle et al., Transfusion 2008;48:14-15) and homozygous people are observed.

Cis-trans isomerization of omega dihedrals in proteins.

Peptide bonds in protein structures are mainly found in trans conformation with a torsion angle ω close to 180°. Only a very low proportion is observed in cis conformation with ω angle around 0°. Cis-trans isomerization leads to local conformation changes which play an important role in many biological processes. In this paper, we reviewed the recent discoveries and research achievements in this field. First, we presented some interesting cases of biological processes in which cis-trans isomerization is directly implicated. It is involved in protein folding and various aspect of protein function like dimerization interfaces, autoinhibition control, channel gating, membrane binding. Then we reviewed conservation studies of cis peptide bonds which emphasized evolution constraints in term of sequence and local conformation. Finally we made an overview of the numerous molecular dynamics studies and prediction methodologies already developed to take into account this structural feature in the research area of protein modeling. Many cis peptide bonds have not been recognized as such due to the limited resolution of the data and to the refinement protocol used. Cis-trans proline isomerization reactions represents a vast and promising research area that still needs to be further explored for a better understanding of isomerization mechanism and improvement of cis peptide bond predictions.

A field guide for implementing a flipped classroom.

The way flipped classrooms are perceived and even practiced by teachers is sometimes approximate. For instance, while the Covid-19 pandemic has pushed many universities to adopt distance learning, flipped classrooms have often been mentioned as a solution in that context. This inducement maintains a confusion between flipped classrooms and distance learning that might be detrimental for students and teachers. Moreover, embarking on a new pedagogical practice such as flipped classroom could be intimidating and time-consuming for the newcomer teacher. For these reasons, this article aims to share some tips for implementing a flipped classroom, with examples from biology and biochemistry. Based on our experiences but also on the current scientific literature, we structured these advise around three phases: preparation, implementation, and follow-up. In the preparation phase, we advise planning early to invert time in class and outside the classroom, but also to say it explicitly, as well as to identify (or optionally create) resources for students to learn in autonomy. In the implementation phase, we suggest to (i) be explicit in the acquisition of knowledge and foster students' autonomy; (ii) explore active learning in class; (iii) develop cooperation and sharing skills; and (iv) differentiate teaching practices to adapt to student needs. Lastly, in the follow-up phase, we propose to (i) evaluate both student learning and the pedagogical setting; (ii) take care of the logistics and the teacher's posture; (iii) document the flipped classroom, and (iv) share the teaching experience.

3D models of fungal chromosomes to enhance visual integration of omics data.

The functions of eukaryotic chromosomes and their spatial architecture in the nucleus are reciprocally dependent. Hi-C experiments are routinely used to study chromosome 3D organization by probing chromatin interactions. Standard representation of the data has relied on contact maps that show the frequency of interactions between parts of the genome. In parallel, it has become easier to build 3D models of the entire genome based on the same Hi-C data, and thus benefit from the methodology and visualization tools developed for structural biology. 3D modeling of entire genomes leverages the understanding of their spatial organization. However, this opportunity for original and insightful modeling is underexploited. In this paper, we show how seeing the spatial organization of chromosomes can bring new perspectives to omics data integration. We assembled state-of-the-art tools into a workflow that goes from Hi-C raw data to fully annotated 3D models and we re-analysed public omics datasets available for three fungal species. Besides the well-described properties of the spatial organization of their chromosomes (Rabl conformation, hypercoiling and chromosome territories), our results highlighted (i) in Saccharomyces cerevisiae, the backbones of the cohesin anchor regions, which were aligned all along the chromosomes, (ii) in Schizosaccharomyces pombe, the oscillations of the coiling of chromosome arms throughout the cell cycle and (iii) in Neurospora crassa, the massive relocalization of histone marks in mutants of heterochromatin regulators. 3D modeling of the chromosomes brings new opportunities for visual integration of omics data. This holistic perspective supports intuition and lays the foundation for building new concepts.

A case study of impacts of an extreme weather system on the Mediterranean Sea circulation features: Medicane Apollo (2021).

The attention of the scientific community, policymakers, and public opinion on the Medicanes has recently grown because of their increase in intensity and harmful potential. Although Medicanes may be influenced by pre-existing upper-ocean conditions, uncertainties remain about how such weather extremes influence ocean circulation. This work examines a condition that has been never described before in the Mediterranean, which involves the interplay between an atmospheric cyclone (Medicane Apollo-October 2021) and a cyclonic gyre located in the western Ionian Sea. During the event, the temperature in the core of the cold gyre dropped dramatically, due to a local maximum in the wind-stress curl, Ekman pumping, and relative vorticity. Cooling and vertical mixing of the surface layer combined with upwelling in the subsurface layer caused a shoaling of the Mixed Layer Depth, halocline, and nutricline. The resulting biogeochemical impacts included an increase in oxygen solubility, chlorophyll concentration, productivity at the surface, and decreases in the subsurface layer. The presence of a cold gyre along Apollo's trajectory leads to a different ocean response from that observed with previous Medicanes, endorsing the efficiency of a multi-platform observation system integrated into an operational model for future mitigation of weather-related damages.

MDverse: Shedding Light on the Dark Matter of Molecular Dynamics Simulations.

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2,000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation, such as temperature and simulation length, and identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore collected MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and increase populating and standardizing metadata to reuse this valuable matter.

Modeling the early stage of DNA sequence recognition within RecA nucleoprotein filaments.

Homologous recombination is a fundamental process enabling the repair of double-strand breaks with a high degree of fidelity. In prokaryotes, it is carried out by RecA nucleofilaments formed on single-stranded DNA (ssDNA). These filaments incorporate genomic sequences that are homologous to the ssDNA and exchange the homologous strands. Due to the highly dynamic character of this process and its rapid propagation along the filament, the sequence recognition and strand exchange mechanism remains unknown at the structural level. The recently published structure of the RecA/DNA filament active for recombination (Chen et al., Mechanism of homologous recombination from the RecA-ssDNA/dsDNA structure, Nature 2008, 453, 489) provides a starting point for new exploration of the system. Here, we investigate the possible geometries of association of the early encounter complex between RecA/ssDNA filament and double-stranded DNA (dsDNA). Due to the huge size of the system and its dense packing, we use a reduced representation for protein and DNA together with state-of-the-art molecular modeling methods, including systematic docking and virtual reality simulations. The results indicate that it is possible for the double-stranded DNA to access the RecA-bound ssDNA while initially retaining its Watson-Crick pairing. They emphasize the importance of RecA L2 loop mobility for both recognition and strand exchange.

AutoClassWeb: a simple web interface for Bayesian clustering of omics data.

OBJECTIVE: Data clustering is a common exploration step in the omics era, notably in genomics and proteomics where many genes or proteins can be quantified from one or more experiments. Bayesian clustering is a powerful unsupervised algorithm that can classify several thousands of genes or proteins. AutoClass C, its original implementation, handles missing data, automatically determines the best number of clusters but is not user-friendly. RESULTS: We developed an online tool called AutoClassWeb, which provides an easy-to-use and simple web interface for Bayesian clustering with AutoClass. Input data are entered as TSV files and quality controlled. Results are provided in formats that ease further analyses with spreadsheet programs or with programming languages, such as Python or R. AutoClassWeb is implemented in Python and is published under the 3-Clauses BSD license. The source code is available at https://github.com/pierrepo/autoclassweb along with a detailed documentation.

Additional insights into the organization of transcriptional regulatory modules based on a 3D model of the Saccharomyces cerevisiae genome.

OBJECTIVES: Transcriptional regulatory modules are usually modelled via a network, in which nodes correspond to genes and edges correspond to regulatory associations between them. In the model yeast Saccharomyces cerevisiae, the topological properties of such a network are well-described (distribution of degrees, hierarchical levels, organization in network motifs, etc.). To go further on this, our aim was to search for additional information resulting from the new combination of classical representations of transcriptional regulatory networks with more realistic models of the spatial organization of S. cerevisiae genome in the nucleus. RESULTS: Taking advantage of independent studies with high-quality datasets, i.e. lists of target genes for specific transcription factors and chromosome positions in a three dimensional space representing the nucleus, particular spatial co-localizations of genes that shared common regulatory mechanisms were searched. All transcriptional modules of S. cerevisiae, as described in the latest release of the YEASTRACT database were analyzed and significant biases toward co-localization for a few sets of target genes were observed. To help other researchers to reproduce such analysis with any list of genes of their interest, an interactive web tool called 3D-Scere ( https://3d-scere.ijm.fr/ ) is provided.

Quantitative Proteomics in Yeast : From bSLIM and Proteome Discoverer Outputs to Graphical Assessment of the Significance of Protein Quantification Scores.

Simple light isotope metabolic labeling (bSLIM) is an innovative method to accurately quantify differences in protein abundance at the proteome level in standard bottom-up experiments. The quantification process requires computation of the ratio of intensity of several isotopologs in the isotopic cluster of every identified peptide. Thus, appropriate bioinformatic workflows are required to extract the signals from the instrument files and calculate the required ratio to infer peptide/protein abundance. In a previous study (Sénécaut et al., J Proteome Res 20:1476-1487, 2021), we developed original open-source workflows based on OpenMS nodes implemented in a KNIME working environment. Here, we extend the use of the bSLIM labeling strategy in quantitative proteomics by presenting an alternative procedure to extract isotopolog intensities and process them by taking advantage of new functionalities integrated into the Minora node of Proteome Discoverer 2.4 software. We also present a graphical strategy to evaluate the statistical robustness of protein quantification scores and calculate the associated false discovery rates (FDR). We validated these approaches in a case study in which we compared the differences between the proteomes of two closely related yeast strains.

On the assessment of Argo float trajectory assimilation in the Mediterranean Forecasting System.

The Mediterranean Forecasting System (MFS) has been operational for a decade, and is continuously providing forecasts and analyses for the region. These forecasts comprise local- and basin-scale information of the environmental state of the sea and can be useful for tracking oil spills and supporting search-and-rescue missions. Data assimilation is a widely used method to improve the forecast skill of operational models and, in this study, the three-dimensional variational (OceanVar) scheme has been extended to include Argo float trajectories, with the objective of constraining and ameliorating the numerical output primarily in terms of the intermediate velocity fields at 350 m depth. When adding new datasets, it is furthermore crucial to ensure that the extended OceanVar scheme does not decrease the performance of the assimilation of other observations, e.g., sea-level anomalies, temperature, and salinity. Numerical experiments were undertaken for a 3-year period (2005-2007), and it was concluded that the Argo float trajectory assimilation improves the quality of the forecasted trajectories with ~15%, thus, increasing the realism of the model. Furthermore, the MFS proved to maintain the forecast quality of the sea-surface height and mass fields after the extended assimilation scheme had been introduced. A comparison between the modeled velocity fields and independent surface drifter observations suggested that assimilating trajectories at intermediate depth could yield improved forecasts of the upper ocean currents.

PTools: an opensource molecular docking library.

BACKGROUND: Macromolecular docking is a challenging field of bioinformatics. Developing new algorithms is a slow process generally involving routine tasks that should be found in a robust library and not programmed from scratch for every new software application. RESULTS: We present an object-oriented Python/C++ library to help the development of new docking methods. This library contains low-level routines like PDB-format manipulation functions as well as high-level tools for docking and analyzing results. We also illustrate the ease of use of this library with the detailed implementation of a 3-body docking procedure. CONCLUSION: The PTools library can handle molecules at coarse-grained or atomic resolution and allows users to rapidly develop new software. The library is already in use for protein-protein and protein-DNA docking with the ATTRACT program and for simulation analysis. This library is freely available under the GNU GPL license, together with detailed documentation.