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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

Pixel: a content management platform for quantitative omics data.

BACKGROUND: In biology, high-throughput experimental technologies, also referred as "omics" technologies, are increasingly used in research laboratories. Several thousands of gene expression measurements can be obtained in a single experiment. Researchers are routinely facing the challenge to annotate, store, explore and mine all the biological information they have at their disposal. We present here the Pixel web application (Pixel Web App), an original content management platform to help people involved in a multi-omics biological project. METHODS: The Pixel Web App is built with open source technologies and hosted on the collaborative development platform GitHub (https://github.com/Candihub/pixel). It is written in Python using the Django framework and stores all the data in a PostgreSQL database. It is developed in the open and licensed under the BSD 3-clause license. The Pixel Web App is also heavily tested with both unit and functional tests, a strong code coverage and continuous integration provided by CircleCI. To ease the development and the deployment of the Pixel Web App, Docker and Docker Compose are used to bundle the application as well as its dependencies. RESULTS: The Pixel Web App offers researchers an intuitive way to annotate, store, explore and mine their multi-omics results. It can be installed on a personal computer or on a server to fit the needs of many users. In addition, anyone can enhance the application to better suit their needs, either by contributing directly on GitHub (encouraged) or by extending Pixel on their own. The Pixel Web App does not provide any computational programs to analyze the data. Still, it helps to rapidly explore and mine existing results and holds a strategic position in the management of research data.

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.

PBxplore: a tool to analyze local protein structure and deformability with Protein Blocks.

This paper describes the development and application of a suite of tools, called PBxplore, to analyze the dynamics and deformability of protein structures using Protein Blocks (PBs). Proteins are highly dynamic macromolecules, and a classical way to analyze their inherent flexibility is to perform molecular dynamics simulations. The advantage of using small structural prototypes such as PBs is to give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, PBs allow analysis of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is able to process large amounts of data such as those produced by molecular dynamics simulations. It produces frequencies, entropy and information logo outputs as text and graphics. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license.

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.

Diagnosis of smear-negative pulmonary tuberculosis based on clinical signs in the Republic of Congo.

BACKGROUND: The diagnosis of pulmonary tuberculosis (PTB) and smear-negative pulmonary tuberculosis (SNPT) in resource-limited countries is often solely based on clinical signs, chest X-ray radiography and sputum smear microscopy. We investigated currently used methods for the routine diagnosis of SNPT in the Republic of Congo (RoC) among TB suspected patients. The specific case of HIV positive patients was also studied. METHODS: A cross-sectional study was conducted at the anti-tuberculosis center (CAT) of Brazzaville, RoC. Tuberculosis suspects were examined for physical signs of TB. Clinical signs, results from sputum smear microscopy, tuberculin skin test (TST) and chest X-ray were recorded. RESULTS: Of the 772 enrolled participants, 372 were diagnosed PTB. Cough was a common symptom for PTB and no PTB patients. Pale skin, positive TST, weight loss and chest X-ray with abnormalities compatible with PTB (PTB-CXR) were significant indicators of PTB. Thirty-six percent of PTB patients were diagnosed SNPT. This category of patients presented less persistent cough and less PTB-CXR. Anorexia and asthenia were significant indicators of SNPT. In the case of HIV+ patients, 57% were SNPT with anorexia, asthenia and shorter cough being strong indicators of SNPT. CONCLUSION: Chest X-ray abnormalities, weight loss, pale skin and positive TST were significant indicators of PTB. Anorexia and asthenia showed good diagnostic performance for SNPT, which deserve to be recommended as index indicators of SNPT diagnosis. Duration of cough is also a relevant indicator, especially for HIV+ patients.

Factors influencing acceptability of voluntary HIV testing among pregnant women in Gamboma, Republic of Congo.

BACKGROUND: This study was carried out to identify factors affecting the acceptability of voluntary HIV testing among pregnant women in a semi-rural city, Gamboma, Republic of Congo. METHODS: A cross-sectional study was conducted between January and September 2012. Pregnant women attending antenatal heath care at an integrated health center were enrolled after informed consent and followed through voluntary HIV testing. RESULTS: Among 136 participants, 98 women (72 %) accepted voluntary HIV testing after pre-test counseling. Women with basic education, those who cited blood transfusion as a mode of transmission and prevention of mother-to-child transmission (MTCT) were more likely to accept testing as well those informed about free HIV testing. Interestingly, pregnant women who had heard about HIV/AIDS from hospital setting were less likely to accept testing. CONCLUSIONS: Our data indicate that increasing general education on HIV transmission/prevention modes is crucial for increasing acceptability of screening. Furthermore, HIV/AIDS knowledge disseminated to patients in hospital settings should be carefully monitored. Lastly, scaling-up MTCT services along with a better and larger community information, may address accessibility barriers observed in the present study.

Protein flexibility in the light of structural alphabets.

Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.

An integrative approach to the study of filamentous oligomeric assemblies, with application to RecA.

Oligomeric macromolecules in the cell self-organize into a wide variety of geometrical motifs such as helices, rings or linear filaments. The recombinase proteins involved in homologous recombination present many such assembly motifs. Here, we examine in particular the polymorphic characteristics of RecA, the most studied member of the recombinase family, using an integrative approach that relates local modes of monomer/monomer association to the global architecture of their screw-type organization. In our approach, local modes of association are sampled via docking or Monte Carlo simulations. This enables shedding new light on fiber morphologies that may be adopted by the RecA protein. Two distinct RecA helical morphologies, the so-called "extended" and "compressed" forms, are known to play a role in homologous recombination. We investigate the variability within each form in terms of helical parameters and steric accessibility. We also address possible helical discontinuities in RecA filaments due to multiple monomer-monomer association modes. By relating local interface organization to global filament morphology, the strategies developed here to study RecA self-assembly are particularly well suited to other DNA-binding proteins and to filamentous protein assemblies in general.