Biology subjects

Xiao, O.

Publications and source records attributed to Xiao, O..

2 recordsLinked to original sources

bioRxiv2023

pan-MHC and cross-Species Prediction of T Cell Receptor-Antigen Binding

Profiling the binding of T cell receptors (TCRs) of T cells to antigenic peptides presented by MHC proteins is one of the most important unsolved problems in modern immunology. Experimental methods to probe TCR-antigen interactions are slow, labor-intensive, costly, and yield moderate throughput. To address this problem, we developed pMTnet-omni, an Artificial Intelligence (AI) system based on hybrid protein sequence and structure information, to predict the pairing of TCRs of {beta} T cells with peptide-MHC complexes (pMHCs). pMTnet-omni is capable of handling peptides presented by both class I and II pMHCs, and capable of handling both human and mouse TCR-pMHC pairs, through information sharing enabled this hybrid design. pMTnet-omni achieves a high overall Area Under the Curve of Receiver Operator Characteristics (AUROC) of 0.888, which surpasses competing tools by a large margin. We showed that pMTnet-omni can distinguish binding affinity of TCRs with similar sequences. Across a range of datasets from various biological contexts, pMTnet-omni characterized the longitudinal evolution and spatial heterogeneity of TCR-pMHC interactions and their functional impact. We successfully developed a biomarker based on pMTnet-omni for predicting immune-related adverse events of immune checkpoint inhibitor (ICI) treatment in a cohort of 57 ICI-treated patients. pMTnet-omni represents a major advance towards developing a clinically usable AI system for TCR-pMHC pairing prediction that can aid the design and implementation of TCR-based immunotherapeutics.

immunology↗

bioRxiv2021

Soil chemistry determines whether defensive plant secondary metabolites promote or suppress herbivore growth

Specialized metabolites mediate important interactions in both the rhizosphere and the phyllosphere. How this compartmentalized multifunctionality influences plant-environment interactions is unknown. Here, we investigated how the dual role of maize benzoxazinoids as leaf defenses and root siderophores shapes the interaction between maize and a major global insect pest, the fall armyworm. We find that benzoxazinoids suppress fall armyworm growth in soils with low bioavailable iron but enhance growth in soils with higher bioavailable iron. Manipulation experiments confirm that benzoxazinoids suppress herbivore growth under iron-deficient conditions but enhance herbivore growth when iron is present in its free form. This reversal of the protective effect of benzoxazinoids is not associated with major changes in plant primary metabolism. Plant defense activation is modulated by the interplay between soil iron and benzoxazinoids but does not explain fall armyworm performance. Instead, increased iron supply to the fall armyworm by benzoxazinoids in the presence of free iron enhances larval performance. This work identifies soil chemistry as a decisive factor for the impact of plant secondary metabolites on herbivore growth. It also demonstrates how the multifunctionality of plant secondary metabolites drives interactions between abiotic and biotic factors, with major consequences for plant health in variable environments.

plant biology↗