Bispecific antibodies targeting two glycoproteins on SFTSV exhibit synergistic neutralization and protection in a mouse model.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with a high fatality rate of up to 30% caused by SFTS virus (SFTSV). However, no specific vaccine or antiviral therapy has been approved for clinical use. To develop an effective treatment, we isolated a panel of human monoclonal antibodies (mAbs). SF5 and SF83 are two neutralizing mAbs that recognize two viral glycoproteins (Gn and Gc), respectively. We found that their epitopes are closely located, and we then engineered them as several bispecific antibodies (bsAbs). Neutralization and animal experiments indicated that bsAbs display more potent protective effects than the parental mAbs, and the cryoelectron microscopy structure of a bsAb3 Fab-Gn-Gc complex elucidated the mechanism of protection. In vivo virus passage in the presence of antibodies indicated that two bsAbs resulted in less selective pressure and could efficiently bind to all single parental mAb-escape mutants. Furthermore, epitope analysis of the protective mAbs against SFTSV and RVFV indicated that they are all located on the Gn subdomain I, where may be the hot spots in the phleboviruses. Collectively, these data provide potential therapeutic agents and molecular basis for the rational design of vaccines against SFTSV infection.

A New Bacillus velezensis Strain CML532 Improves Chicken Growth Performance and Reduces Intestinal Clostridium perfringens Colonization.

Bacillus velezensis has gained increasing recognition as a probiotic for improving animal growth performance and gut health. We identified six B. velezensis strains from sixty Bacillus isolates that were isolated from the cecal samples of fifteen different chicken breeds. We characterized the probiotic properties of these six B. velezensis strains. The effect of a selected strain (B. velezensis CML532) on chicken growth performance under normal feeding and Clostridium perfringens challenge conditions was also evaluated. The results revealed that the six B. velezensis strains differed in their probiotic properties, with strain CML532 exhibiting the highest bile salt and acid tolerance and high-yield enzyme and antibacterial activities. Genomic analyses showed that genes related to amino acid and carbohydrate metabolism, as well as genes related to starch and cellulose hydrolysis, were abundant in strain CML532. Dietary supplementation with strain CML532 promoted chicken growth, improved the gut barrier and absorption function, and modulated the gut microbiota. Under the C. perfringens challenge condition, strain CML532 alleviated intestinal damage, reduced ileal colonization of C. perfringens, and also improved chicken growth performance. Collectively, this study demonstrated that the newly isolated B. velezensis strain is a promising probiotic with beneficial effects on chicken growth performance and gut health.

RIscoper 2.0: A deep learning tool to extract RNA biomedical relation sentences from literature.

RNA plays an extensive role in a multi-dimensional regulatory system, and its biomedical relationships are scattered across numerous biological studies. However, text mining works dedicated to the extraction of RNA biomedical relations remain limited. In this study, we established a comprehensive and reliable corpus of RNA biomedical relations, recruiting over 30,000 sentences manually curated from more than 15,000 biomedical literature. We also updated RIscoper 2.0, a BERT-based deep learning tool to extract RNA biomedical relation sentences from literature. Benefiting from approximately 100,000 annotated named entities, we integrated the text classification and named entity recognition tasks in this tool. Additionally, RIscoper 2.0 outperformed the original tool in both tasks and can discover new RNA biomedical relations. Additionally, we provided a user-friendly online search tool that enables rapid scanning of RNA biomedical relationships using local and online resources. Both the online tools and data resources of RIscoper 2.0 are available at http://www.rnainter.org/riscoper.

Dynamic pathological analysis reveals a protective role against skin fibrosis for TREM2-dependent macrophages.

Rationale: Systemic sclerosis (SSc) is a chronic and incurable autoimmune disease with high mortality rates, and skin fibrosis is one of distinguishing hallmarks in the pathogenesis. However, macrophage heterogeneity regulating skin fibrosis remain largely unknown. Methods: We established mouse disease model and performed single-cell RNA-sequencing (scRNA-seq) to resolve the dynamic and heterogenous characteristics of macrophages in skin fibrosis, and the role of TREM2-dependent macrophages in the pathological process was investigated using knockout mice and intraperitoneal transferring TREM2+ macrophages combining with functional assays. Results: We show that TREM2-expressing macrophages (TREM2+ MФs) accumulate in injured skin of mice treated by bleomycin (BLM) and human SSc, and their gene signatures and functional pathways are identified in the course of disease. Genetic ablation of Trem2 in mice globally accelerates and aggravates skin fibrosis, whereas transferring TREM2hi macrophages improves and alleviates skin fibrosis. Amazingly, we found that disease-associated TREM2+ MФs in skin fibrosis exhibit overlapping signatures with fetal skin counterparts in mice and human to maintain skin homeostasis, but each has merits in skin remodeling and development respectively. Conclusion: This study identifies that TREM2 acts as a functional molecule and a major signaling by which macrophage subpopulations play a protective role against fibrosis, and disease-associated TREM2+ MФs in skin fibrosis might undergo a fetal-like reprogramming similar to fetal skin counterparts.

Quantitative microbiome profiling reveals the developmental trajectory of the chicken gut microbiota and its connection to host metabolism.

Revealing the assembly and succession of the chicken gut microbiota is critical for a better understanding of its role in chicken physiology and metabolism. However, few studies have examined dynamic changes of absolute chicken gut microbes using the quantitative microbiome profiling (QMP) method. Here, we revealed the developmental trajectory of the broiler chicken gut bacteriome and mycobiome by combining high-throughput sequencing with a microbial load quantification assay. We showed that chicken gut microbiota abundance and diversity reached a plateau at 7 days posthatch (DPH), forming segment-specific community types after 1 DPH. The bacteriome was more impacted by deterministic processes, and the mycobiome was more affected by stochastic processes. We also observed stage-specific microbes in different gut segments, and three microbial occurrence patterns including "colonization," "disappearance," and "core" were defined. The microbial co-occurrence networks were very different among gut segments, with more positive associations than negative associations. Furthermore, we provided links between the absolute changes in chicken gut microbiota and their serum metabolite variations. Time-course untargeted metabolomics revealed six metabolite clusters with different changing patterns of abundance. The foregut microbiota had more connections with chicken serum metabolites, and the gut microbes were closely related to chicken lipid and amino acid metabolism. The present study provided a full landscape of chicken gut microbiota development in a quantitative manner, and the associations between gut microbes and chicken serum metabolites further highlight the impact of gut microbiota in chicken growth and development.