Background: Despite the known importance of somatic cells for oocyte developmental competence acquisition, the overall mechanisms underlying the acquisition of full developmental competence are far from being understood, especially in non-mammalian species. The present work aimed at identifying key molecular signals from somatic origin that would be shared by vertebrates. Results: Using a parallel transcriptomic analysis in 4 vertebrate species - a teleost fish, an amphibian, and two mammals - at similar key steps of developmental competence acquisition, we identified a large number of species-specific differentially expressed genes and a surprisingly high number of orthologous genes exhibiting similar expression profiles in the 3 tetrapods and in the 4 vertebrates. Among the evolutionary conserved players participating in developmental competence acquisition are genes involved in key processes such as cellular energy metabolism, cell-to-cell communications, and meiosis control. In addition, we report many novel molecular actors from somatic origin that have never been studied in the vertebrate ovary. Interestingly, a significant number of these new players actively participate in Drosophila oogenesis. Conclusions: Our study provides a comprehensive overview of evolutionary-conserved mechanisms from somatic origin participating in oocyte developmental competence acquisition in 4 vertebrates. Together our results indicate that despite major differences in ovarian follicular structure, some of the key players from somatic origin involved in oocyte developmental competence acquisition would be shared, not only by vertebrates, but also by metazoans. The conservation of these mechanisms during vertebrate evolution further emphasizes the important contribution of the somatic compartment to oocyte quality and paves the way for future investigations aiming at better understanding what makes a good egg.

Subsets of mature B cell neoplasms are linked to infection with intracellular pathogens such as Epstein-Barr virus (EBV), hepatitis C virus (HCV), or Helicobacter pylori . However, the association between infection and the immunoglobulin-secreting (Ig-secreting) B proliferative disorders remains largely unresolved. We investigated whether the monoclonal IgG (mc IgG) produced by patients diagnosed with monoclonal gammopathy of undetermined significance (MGUS) or multiple myeloma (MM) targets infectious pathogens. Antigen specificity of purified mc IgG from a large patient cohort ( n = 244) was determined using a multiplex infectious-antigen array (MIAA), which screens for reactivity to purified antigens or lysates from 9 pathogens. Purified mc IgG from 23.4% of patients (57 of 244) specifically recognized 1 pathogen in the MIAA. EBV was the most frequent target (15.6%), with 36 of 38 mc IgGs recognizing EBV nuclear antigen-1 (EBNA-1). MM patients with EBNA-1–specific mc IgG (14.0%) showed substantially greater bone marrow plasma cell infiltration and higher β ₂ -microglobulin and inflammation/infection–linked cytokine levels compared with other smoldering myeloma/MM patients. Five other pathogens were the targets of mc IgG: herpes virus simplex-1 (2.9%), varicella zoster virus (1.6%), cytomegalovirus (0.8%), hepatitis C virus (1.2%), and H . pylori (1.2%). We conclude that a dysregulated immune response to infection may underlie disease onset and/or progression of MGUS and MM for subsets of patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent responsible for the recent coronavirus disease 2019 (COVID-19) pandemic. Productive SARS-CoV-2 infection relies on viral entry into cells expressing angiotensin-converting enzyme 2 (ACE2). Indeed, viral entry into cells is mostly mediated by the early interaction between the viral spike protein S and its ACE2 receptor. The S/ACE2 complex is, thus, the first contact point between the incoming virus and its cellular target; consequently, it has been considered an attractive therapeutic target. To further characterize this interaction and the cellular processes engaged in the entry step of the virus, we set up various in silico, in vitro and in cellulo approaches that allowed us to specifically monitor the S/ACE2 association. We report here a computational model of the SARS-CoV-2 S/ACE2 complex, as well as its biochemical and biophysical monitoring using pulldown, AlphaLISA and biolayer interferometry (BLI) binding assays. This led us to determine the kinetic parameters of the S/ACE2 association and dissociation steps. In parallel to these in vitro approaches, we developed in cellulo transduction assays using SARS-CoV-2 pseudotyped lentiviral vectors and HEK293T-ACE2 cell lines generated in-house. This allowed us to recapitulate the early replication stage of the infection mediated by the S/ACE2 interaction and to detect cell fusion induced by the interaction. Finally, a cell imaging system was set up to directly monitor the S/ACE2 interaction in a cellular context and a flow cytometry assay was developed to quantify this association at the cell surface. Together, these different approaches are available for both basic and clinical research, aiming to characterize the entry step of the original SARS-CoV-2 strain and its variants as well as to investigate the possible chemical modulation of this interaction. All these models will help in identifying new antiviral agents and new chemical tools for dissecting the virus entry step.

High-throughput protein assays are crucial for modern diagnostics, drug discovery, proteomics, and other fields of biology and medicine. It allows simultaneous detection of hundreds of analytes and miniaturization of both fabrication and analytical procedures. Photonic crystal surface mode (PC SM) imaging is an effective alternative to surface plasmon resonance (SPR) imaging used in conventional gold-coated, label-free biosensors. PC SM imaging is advantageous as a quick, label-free, and reproducible technique for multiplexed analysis of biomolecular interactions. PC SM sensors are characterized by a longer signal propagation at the cost of a lower spatial resolution, which makes them more sensitive than classical SPR imaging sensors. We describe an approach for designing label-free protein biosensing assays employing PC SM imaging in the microfluidic mode. Label-free, real-time detection of PC SM imaging biosensors using two-dimensional imaging of binding events has been designed to study arrays of model proteins (antibodies, immunoglobulin G-binding proteins, serum proteins, and DNA repair proteins) at 96 points prepared by automated spotting. The data prove feasibility of simultaneous PC SM imaging of multiple protein interactions. The results pave the way to further develop PC SM imaging as an advanced label-free microfluidic assay for the multiplexed detection of protein interactions.

Photonic crystals (PCs) are promising tools for label-free sensing in drug discovery screening, diagnostics, and analysis of ligand–receptor interactions. Imaging of PC surface modes has emerged as a novel approach to the detection of multiple binding events at the sensor surface. PC surface modification and decoration with recognition units yield an interface providing the highly sensitive detection of cancer biomarkers, antibodies, and oligonucleotides. The RAD51 protein plays a central role in DNA repair via the homologous recombination pathway. This recombinase is essential for the genome stability and its overexpression is often correlated with aggressive cancer. RAD51 is therefore a potential target in the therapeutic strategy for cancer. Here, we report the designing of a PC-based array sensor for real-time monitoring of oligonucleotide–RAD51 recruitment by means of surface mode imaging and validation of the concept of this approach. Our data demonstrate that the designed biosensor ensures the highly sensitive multiplexed analysis of association–dissociation events and detection of the biomarker of DNA damage using a microfluidic PC array. The obtained results highlight the potential of the developed technique for testing the functionality of candidate drugs, discovering new molecular targets and drug entities. This paves the way to further adaption and bioanalytical use of the biosensor for high-content screening to identify new DNA repair inhibitor drugs targeting the RAD51 nucleoprotein filament or to discover new molecular targets.