Lovato, A. | Search bioRxiv

bioRxiv2025

pH-Controlled Regioselective Rapid Ene-type Reaction (RRER) Enables Bioconjugation of Histone Serotonylation

Triazolinedione (TAD) derivatives have been commonly utilized as protection and labeling reagents for indole and phenol moieties via a reversible ene-type reaction. Previous studies showed that the TAD probes could selectively modify tyrosine and tryptophan side-chains within proteins and peptides under distinct pH conditions. Here, we report a pH-controlled regioselective rapid ene-type reaction (RRER) between TAD and 5-hydroxyindole, where the modification occurs on the C4 position rather than the C3 of inactivated indole rings. Employing this unique reaction, we have performed the selective bioconjugation of serotonylation occurring on the fifth amino acid residue, glutamine, of histone H3 (H3Q5), which does not contain any tryptophan in its protein sequence. Finally, RRER was applied to determine the H3Q5 serotonylation levels in cultured cells and tissue samples, which served as a newly developed powerful tool for in vitro and in vivo histone monoaminylation analysis. Overall, our findings in this research expanded the chemical biology toolbox for investigating histone monoaminylation and facilitated the understandings of TAD-mediated ene-type reactions.

biochemistry↗

bioRxiv2018

Sparse additive interaction learning

A conceptual paradigm for onset of a new disease is often considered to be the result of changes in entire biological networks whose states are affected by a complex interaction of genetic and environmental factors. However, when modelling a relevant phenotype as a function of high dimensional measurements, power to estimate interactions is low, the number of possible interactions could be enormous and their effects may be non-linear. In this work, we introduce a method called sail for detecting non-linear interactions with a key environmental or exposure variable in high-dimensional settings which respects the strong or weak heredity constraints. We prove that asymptotically, our method possesses the oracle property, i.e., it performs as well as if the true model were known in advance. We develop a computationally efficient fitting algorithm with automatic tuning parameter selection, which scales to high-dimensional datasets. Through an extensive simulation study, we show that sail outperforms existing penalized regression methods in terms of prediction accuracy and support recovery when there are non-linear interactions with an exposure variable. We apply sail to detect non-linear interactions between genes and a prenatal psychosocial intervention program on cognitive performance in children at 4 years of age. Results show that individuals who are genetically predisposed to lower educational attainment are those who stand to benefit the most from the intervention. Our algorithms are implemented in an R package available on CRAN (https://cran.r-project.org/package=sail).

bioinformatics↗