Multiomics-integrated deep language model enables in silico genome-wide detection of transcription factor binding site in unexplored biosamples.

MOTIVATION: Transcription factor binding sites (TFBS) are regulatory elements that have significant impact on transcription regulation and cell fate determination. Canonical motifs, biological experiments, and computational methods have made it possible to discover TFBS. However, most existing in silico TFBS prediction models are solely DNA-based, and are trained and utilized within the same biosample, which fail to infer TFBS in experimentally unexplored biosamples. RESULTS: Here, we propose TFBS prediction by modified TransFormer (TFTF), a multimodal deep language architecture which integrates multiomics information in epigenetic studies. In comparison to existing computational techniques, TFTF has state-of-the-art accuracy, and is also the first approach to accurately perform genome-wide detection for cell-type and species-specific TFBS in experimentally unexplored biosamples. Compared to peak calling methods, TFTF consistently discovers true TFBS in threshold tuning-free way, with higher recalled rates. The underlying mechanism of TFTF reveals greater attention to the targeted TF's motif region in TFBS, and general attention to the entire peak region in non-TFBS. TFTF can benefit from the integration of broader and more diverse data for improvement and can be applied to multiple epigenetic scenarios. AVAILABILITY AND IMPLEMENTATION: We provide a web server (https://tftf.ibreed.cn/) for users to utilize TFTF model. Users can train TFTF model and discover TFBS with their own data.

Application of a 360-Degree Radiation Thermosonication Technology for the Inactivation of Staphylococcus aureus in Milk.

Milk is easy to be contaminated by microorganisms due to its abundant nutrients. In this study, a 360-degree radiation thermosonication (TS) system was developed and utilized for the inactivation of Staphylococcus aureus in milk. The 360-degree radiation TS system-induced inactivation kinetics of S. aureus was fitted best by the Weibull model compared with biphasic and linear models. The treatment time, the exposure temperature, and the applied ultrasound power was found to affect the bactericidal efficacy of the 360-degree radiation TS system. Additionally, the TS condition of 200 W and 63°C for 7.5 min was successfully applied to achieve complete microbial inactivation (under the limit of detection value) in raw milk. The treatment of 360-degree radiation TS can enhance the zeta potential and decrease the average particle size of milk. It also exhibited better retainment of the proteins in milk compared with the ultrahigh temperature and conventional pasteurization processing. Therefore, the 360-degree radiation TS system developed in this study can be used as an alternative technology to assure the microbiological safety and retain the quality of milk, and the Weibull model could be applied for the prediction of the inactivation levels after exposure to this technology.

A transcription aptasensor: amplified, label-free and culture-independent detection of foodborne pathogens via light-up RNA aptamers.

We report a transcription aptasensor by using a light-up RNA aptamer. It allows for sensitive, label-free and culture-free detection of intact foodborne pathogens, and no separation, purification or enrichment processes are involved.