Merbecoviruses, closely related to the Middle East respiratory syndrome coronavirus, circulate in hedgehogs throughout Europe and Asia, raising concerns about zoonotic transmission to humans and domestic animals. However, it is not clear how these viruses enter host cells. Here we tested three coronavirus receptors from European hedgehogs (Erinaceus europaeus) in cell-based assays and identified aminopeptidase N (APN) as a receptor for hedgehog merbecoviruses. We verified it by pseudotype experiments using an in vitro reporter system based on replication competent vesicular stomatitis virus and protein binding assays. Hedgehog coronavirus spike proteins showed enhanced infectivity when produced at 33 °C, approximating the physiological hedgehog body temperature, as compared with 37 °C. A screen of 30 mammalian APN orthologues showed restricted cross-species receptor use, including the inability to use human APN. Electron cryomicroscopy revealed a distinct glycoprotein-receptor interface unlike known coronavirus spike-APN interactions, clarifying species barriers. These findings broaden our understanding of receptor use across merbecoviruses and betacoronaviruses and inform risk assessments for viral emergence.
M. Jin, Victoria A. Jefferson, Zhe Zhao et al.· Nature Microbiology· 0 citations
For rapidly mutating viruses such as influenza viruses and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), immune memory recalled by antigenically drifted variants primarily comprises antibodies that cross-react to the priming strain rather than de novo elicited responses, a phenomenon termed original antigenic sin or immune imprinting. The composition and functionality of de novo responses elicited by variant exposures remain unclear. Here we isolated and characterized hundreds of recall and de novo neutralizing monoclonal antibodies after sequential exposures to SARS-CoV-2 variants in ancestral-imprinted humans. De novo variant type-specific antibodies used different V(D)J genes that were closer to germline sequence, potently neutralized future variants and targeted distinct receptor binding domain epitopes compared to ancestral cross-reactive (recall) antibodies. Nevertheless, neutralizing responses to the updated 2024–2025 booster were predominantly ancestral cross-reactive. These results reveal the distinct contributions of recall and de novo antibodies to a balanced immune response and underscore the benefit of updated booster vaccines, which augment both subsets. Updated SARS-CoV-2 boosters broaden humoral immunity by recalling cross-reactive antibodies and eliciting new less cross-reactive Omicron type-specific antibodies that target distinct RBD epitopes and more potently neutralize recent variants.
T. Johnston, S. Li, M. Painter et al.· Nature Immunology· 2 citations
Abstract Human RNA sequencing (RNA-seq) data originally generated for human transcriptome profiling are overwhelmingly dominated by host sequences, yet they often contain a small fraction of non-human reads that can be exploited for microbial detection. When such datasets are repurposed for secondary microbiome-oriented analyses, extracting and accurately classifying this weak microbial signal becomes technically challenging, and no ready-to-use pipeline currently exists. In this study, we evaluate computational strategies for filtering host reads and classifying microbial transcripts in host-dominated RNA sequencing data. We compare assembly-based approaches similar to those used in a previous study focusing on microbial translocation with state-of-the-art assembly-free methods, and assess their respective strengths and limitations using simulated datasets reflecting low microbial abundance. Our results show that assembly-based methods yield accurate taxonomic predictions but struggle at low read depth, whereas assembly-free methods are more robust in sparse settings at the cost of reduced precision. To leverage the complementarity of both approaches, we propose a hybrid pipeline that integrates assembly-based and assembly-free classification. On simulated data, this hybrid strategy improves microbial classification performance compared with either approach alone. Application to a real human metatranscriptomic dataset analyzed in a microbial translocation context illustrates the broader microbial signal captured by the hybrid approach, despite intrinsic challenges related to the absence of reliable ground truth and the risk of host read misclassification. Our work provides a framework for extracting microbial signals from host-dominated human metatranscriptomes, enabling the reuse of existing transcriptomic datasets for microbiome-related analyses, including but not limited to microbial translocation studies.
Antonino Colajanni, R. Uricaru, S. Darko et al.· Briefings in Bioinformatics· 0 citations
Virus exposure history, particularly first exposure, is believed to shape vaccine efficacy and infection susceptibility; however, evidence for mechanistic links between immune responses in individuals and epidemiological outcome in populations is scarce. Recent co-circulation of SARS-CoV-2 variants XFG and BA.3.2 has revealed a striking enrichment in BA.3.2 cases among children. By combining epidemiological modeling, serology and monoclonal antibody analysis in children and adults, we show the dependence of effective variant-specific antibodies on vaccination history which may explain birth-year influence on differential susceptibility to these co-circulating variants. Ancestral cross-reactive site I antibodies frequently neutralize BA.3.2, but not XFG. By contrast, Omicron type-specific site I/III and III antibodies frequently neutralize XFG but not BA.3.2, revealing a tradeoff in the ability to neutralize these two co-circulating strains. These findings mechanistically link immune history, variant neutralization, antibody repertoire and variant infection risk, and suggest that vaccination regimens in children should prioritize neutralization breadth.
T. Johnston, Rahul Subramanian, Wakinyan Benhamou et al.· bioRxiv· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
