DiSiR: fast and robust method to identify ligand-receptor interactions at subunit level from single-cell RNA-sequencing data.

Most cell-cell interactions and crosstalks are mediated by ligand-receptor interactions. The advent of single-cell RNA-sequencing (scRNA-seq) techniques has enabled characterizing tissue heterogeneity at single-cell level. In the past few years, several methods have been developed to study ligand-receptor interactions at cell type level using scRNA-seq data. However, there is still no easy way to query the activity of a specific user-defined signaling pathway in a targeted way or to map the interactions of the same subunit with different ligands as part of different receptor complexes. Here, we present DiSiR, a fast and easy-to-use permutation-based software framework to investigate how individual cells are interacting with each other by analyzing signaling pathways of multi-subunit ligand-activated receptors from scRNA-seq data, not only for available curated databases of ligand-receptor interactions, but also for interactions that are not listed in these databases. We show that, when utilized to infer ligand-receptor interactions from both simulated and real datasets, DiSiR outperforms other well-known permutation-based methods, e.g. CellPhoneDB and ICELLNET. Finally, to demonstrate DiSiR's utility in exploring data and generating biologically relevant hypotheses, we apply it to COVID lung and rheumatoid arthritis (RA) synovium scRNA-seq datasets and highlight potential differences between inflammatory pathways at cell type level for control versus disease samples.

AuNP-based biosensors for the diagnosis of pathogenic human coronaviruses: COVID-19 pandemic developments.

The outbreak rate of human coronaviruses (CoVs) especially highly pathogenic CoVs is increasing alarmingly. Early detection of these viruses allows treatment interventions to be provided more quickly to people at higher risk, as well as helping to identify asymptomatic carriers and isolate them as quickly as possible, thus preventing the disease transmission chain. The current diagnostic methods such as RT-PCR are not ideal due to high cost, low accuracy, low speed, and probability of false results. Therefore, a reliable and accurate method for the detection of CoVs in biofluids can become a front-line tool in order to deal with the spread of these deadly viruses. Currently, the nanomaterial-based sensing devices for detection of human coronaviruses from laboratory diagnosis to point-of-care (PoC) diagnosis are progressing rapidly. Gold nanoparticles (AuNPs) have revolutionized the field of biosensors because of the outstanding optical and electrochemical properties. In this review paper, a detailed overview of AuNP-based biosensing strategies with the varied transducers (electrochemical, optical, etc.) and also different biomarkers (protein antigens and nucleic acids) was presented for the detection of human coronaviruses including SARS-CoV-2, SARS-CoV-1, and MERS-CoV and lowly pathogenic CoVs. The present review highlights the newest trends in the SARS-CoV-2 nanobiosensors from the beginning of the COVID-19 epidemic until 2022. We hope that the presented examples in this review paper convince readers that AuNPs are a suitable platform for the designing of biosensors.

Graphite nanocrystals coated paper-based electrode for detection of SARS-Cov-2 gene using DNA-functionalized Au@carbon dot core-shell nanoparticles.

Currently, the development of biosensors is an urgent need due to the rapid spread of SARS-CoV-2 and the limitations of current standard methods for the diagnosis of COVID-19. Hence, many researchers have focused on the design of high-performance biosensors for measuring coronavirus genes. In this study, a voltammetric genosensor was developed for the determination of SARS-CoV-2 RdRP gene based on the format of cDNA probe/Au@CD core-shell NPs/graphite nanocrystals (GNCs)/paper electrode. For the first time, graphite nanocrystals were used in the electrochemical biosensor design. This genosensor was exposed to different concentrations of virus gene and then the hybridization between cDNA probe and RdRP gene was monitored by redox-active toluidine blue (TB). With increasing the RdRP concentration, the reduction peak current of TB enhanced in a linear range of 0.50 pM-12.00 nM according to the regression equation of I (µA) = 7.60 log CRdRP (pM) + 25.78. The repeatability with a RSD of 2.2% clearly exhibited that the response of modified electrode is stable because of the high adhesion of GNC layer on the paper substrate and the high stability of cDNA-Au@CD bioconjugates. The spike-and-recovery studies showed the acceptable recoveries for the sputum samples (>95%).

Application of an integrated computational antibody engineering platform to design SARS-CoV-2 neutralizers.

As the COVID-19 pandemic continues to spread, hundreds of new initiatives including studies on existing medicines are running to fight the disease. To deliver a potentially immediate and lasting treatment to current and emerging SARS-CoV-2 variants, new collaborations and ways of sharing are required to create as many paths forward as possible. Here, we leverage our expertise in computational antibody engineering to rationally design/engineer three previously reported SARS-CoV neutralizing antibodies and share our proposal towards anti-SARS-CoV-2 biologics therapeutics. SARS-CoV neutralizing antibodies, m396, 80R and CR-3022 were chosen as templates due to their diversified epitopes and confirmed neutralization potency against SARS-CoV (but not SARS-CoV-2 except for CR3022). Structures of variable fragment (Fv) in complex with receptor binding domain (RBD) from SARS-CoV or SARS-CoV-2 were subjected to our established in silico antibody engineering platform to improve their binding affinity to SARS-CoV-2 and developability profiles. The selected top mutations were ensembled into a focused library for each antibody for further screening. In addition, we convert the selected binders with different epitopes into the trispecific format, aiming to increase potency and to prevent mutational escape. Lastly, to avoid antibody-induced virus activation or enhancement, we suggest application of NNAS and DQ mutations to the Fc region to eliminate effector functions and extend half-life.