Refine
Language
- English (5)
Has Fulltext
- yes (5) (remove)
Is part of the Bibliography
- no (5)
Keywords
- COVID-19 (1)
- SARS-CoV-2 (1)
- neutralizing antibodies (1)
- spike protein (1)
- variants of concern (1)
Institute
TRIANNI mice carry an entire set of human immunoglobulin V region gene segments and are a powerful tool to rapidly isolate human monoclonal antibodies. After immunizing these mice with DNA encoding the spike protein of SARS-CoV-2 and boosting with spike protein, we identified 29 hybridoma antibodies that reacted with the SARS-CoV-2 spike protein. Nine antibodies neutralize SARS-CoV-2 infection at IC50 values in the subnanomolar range. ELISA-binding studies and DNA sequence analyses revealed one cluster of three clonally related neutralizing antibodies that target the receptor-binding domain and compete with the cellular receptor hACE2. A second cluster of six clonally related neutralizing antibodies bind to the N-terminal domain of the spike protein without competing with the binding of hACE2 or cluster 1 antibodies. SARS-CoV-2 mutants selected for resistance to an antibody from one cluster are still neutralized by an antibody from the other cluster. Antibodies from both clusters markedly reduced viral spread in mice transgenic for human ACE2 and protected the animals from SARS-CoV-2-induced weight loss. The two clusters of potent noncompeting SARS-CoV-2 neutralizing antibodies provide potential candidates for therapy and prophylaxis of COVID-19. The study further supports transgenic animals with a human immunoglobulin gene repertoire as a powerful platform in pandemic preparedness initiatives.
Vaccines are central to controlling the coronavirus disease 2019 (COVID-19) pandemic but the durability of protection is limited for currently approved COVID-19 vaccines. Further, the emergence of variants of concern (VoCs) that evade immune recognition has reduced vaccine effectiveness, compounding the problem. Here, we show that a single dose of a murine cytomegalovirus (MCMV)-based vaccine, which expresses the spike (S) protein of the virus circulating early in the pandemic (MCMVS), protects highly susceptible K18-hACE2 mice from clinical symptoms and death upon challenge with a lethal dose of D614G SARS-CoV-2. Moreover, MCMVS vaccination controlled two immune-evading VoCs, the Beta (B.1.135) and the Omicron (BA.1) variants in BALB/c mice, and S-specific immunity was maintained for at least 5 months after immunization, where neutralizing titers against all tested VoCs were higher at 5-months than at 1-month post-vaccination. Thus, cytomegalovirus (CMV)-based vector vaccines might allow for long-term protection against COVID-19.
Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.
Results: We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.
Conclusion: TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Background Eukaryotic gene expression is controlled by cis-regulatory elements (CREs) including promoters and enhancers which are bound by transcription factors (TFs). Differential expression of TFs and their putative binding sites on CREs cause tissue and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and thus gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined ChIP-seq and RNA-seq data exist, they do not offer good usability, have limited support for large-scale data processing, and provide only minimal functionality for visual result interpretation.
Results We developed TF-Prioritizer, an automated java pipeline to prioritize condition-specific TFs derived from multi-modal data. TF-Prioritizer creates an interactive, feature-rich, and user-friendly web report of its results. To showcase the potential of TF-Prioritizer, we identified known active TFs (e.g., Stat5, Elf5, Nfib, Esr1), their target genes (e.g., milk proteins and cell-cycle genes), and newly classified lactating mammary gland TFs (e.g., Creb1, Arnt).
Conclusion TF-Prioritizer accepts ChIP-seq and RNA-seq data, as input and suggests TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Resveratrol shows beneficial effects in inflammation-based diseases like cancer, cardiovascular and chronic inflammatory diseases. Therefore, the molecular mechanisms of the anti-inflammatory resveratrol effects deserve more attention. In human epithelial DLD-1 and monocytic Mono Mac 6 cells resveratrol decreased the expression of iNOS, IL-8 and TNF-α by reducing mRNA stability without inhibition of the promoter activity. Shown by pharmacological and siRNA-mediated inhibition, the observed effects are SIRT1-independent. Target-fishing and drug responsive target stability experiments showed selective binding of resveratrol to the RNA-binding protein KSRP, a central post-transcriptional regulator of pro-inflammatory gene expression. Knockdown of KSRP expression prevented resveratrol-induced mRNA destabilization in human and murine cells. Resveratrol did not change KSRP expression, but immunoprecipitation experiments indicated that resveratrol reduces the p38 MAPK-related inhibitory KSRP threonine phosphorylation, without blocking p38 MAPK activation or activity. Mutation of the p38 MAPK target site in KSRP blocked the resveratrol effect on pro-inflammatory gene expression. In addition, resveratrol incubation enhanced KSRP-exosome interaction, which is important for mRNA degradation. Finally, resveratrol incubation enhanced its intra-cellular binding to the IL-8, iNOS and TNF-α mRNA. Therefore, modulation of KSRP mRNA binding activity and, thereby, enhancement of mRNA degradation seems to be the common denominator of many anti-inflammatory effects of resveratrol.