A Deep Mining Strategy for Peptide Rapid Identification in Lactobacillus reuteri Based on LC-MS/MS Integrated with FBMN and De Novo Sequencing.

Lactobacillus reuteri (L. reuteri) is widely recognized as a probiotic that produces prebiotics. However, studies on bioactive peptides or amino acid (AA) derivatives produced by L. reuteri are still lacking, whereas many bioactive peptides and AA derivatives have been found in other Lactobacillus species. In addition, rapid identification of peptides is challenged by the large amount of data and is limited by the coverage of protein databases. In this study, we performed a rapid and thorough profile of peptides in L. reuteri incorporating Global Natural Products Social Molecular Networking (GNPS) platform database searching, de novo sequencing, and deep mining, based on feature-based molecular networking (FBMN). According to FBMN, it was found that peptides containing identical or similar AA compositions were grouped into the same clusters, especially cyclic dipeptides (CDPs). Therefore, the grouping characteristics of clusters, differences in precursor ions, and characteristic fragment ions were utilized for the mining of deeply unknown compounds. Through this strategy, a total of 192 compounds, including 184 peptides, were rapidly identified. Among them, 53 CDPs, including four novel ones, were found for the first time in L. reuteri. Then, one of the novel CDPs, cyclo(5-OMe-Glu-4-OH-Pro), was isolated and characterized, which was consistent with the identification results. Moreover, some of the identified peptides exhibited considerable interactions with seven anti-inflammatory-related target proteins through molecular docking. According to the binding energies of peptides with different AA consistencies, it was considered that the existence of unnatural AAs in CDPs might contribute to their anti-inflammatory activity. These results provide a valuable strategy for the rapid identification of peptides, including CDPs. This study also reveals the substance basis for the potential anti-inflammatory effects exerted by L. reuteri.

Successful Treatment of Primary CNS Extranodal NK/T-Cell Lymphoma with Surgery and Chemotherapy Combined with Sintilimab: A Case Report and Literature Review.

Primary central nervous system extranodal natural killer/T-cell lymphoma (PCNS ENK/TCL) is an extremely rare lymphoma. Only 23 cases of PCNS ENK/TCL have been reported in the English literature. Due to the rarity of this lymphoma, an effective therapeutic strategy has not been defined. Generally, this type of lymphoma is treated with surgery, intrathecal chemotherapy, and postoperative chemoradiation therapy. The prognosis is poor. Herein, we present a case of primary brain NK/T cell lymphoma in a 50-year-old immunocompetent Chinese female and review the literature. The patient underwent intracranial tumor resection and was subsequently treated with a PD1 monoclonal antibody (Sintilimab) combined with chemotherapy. The patient survived 15 months after diagnosis. This is the first report of PCNS ENK/TCL treated with surgery and chemotherapy combined with immunotherapy and suggests an effective treatment regimen for PCNS ENK/TCL.

Investigation and dynamic profiling of oligopeptides, free amino acids and derivatives during Pu-erh tea fermentation by ultra-high performance liquid chromatography tandem mass spectrometry.

Microbial fermentation is the critical step of Pu-erh tea manufacture, which will induce dramatic changes in the chemical composition and content of tea. In this research, we applied multi-methods based on UHPLC-Q-TOF/MS to profile the dynamic changes of oligopeptides, free amino acids, and derivatives (OPADs) during Pu-erh fermentation and predicted the potential bioactivities in silico. A total of 60 oligopeptides, 18 free amino acids, and 42 amino acid derivatives were identified, and the contents of most of them decreased after fermentation. But several N-acetyl amino acids increased 7-36 times after fermentation, and they might be the potential inhibitors of neurokinin-1 receptor. Moreover, the results of metamicrobiology showed Aspergillus niger and Aspergillus luchuensis were more prominent to metabolize protein, oligopeptides, and amino acids. Overall, these findings provide valuable insights about dynamic variations of OPADs during Pu-erh tea fermentation and are beneficial for guiding practical fermentation and quality control of Pu-erh tea.

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes.

Diffuse large B-cell lymphoma (DLBCL) is an extremely heterogeneous tumor entity, which makes prognostic prediction challenging. The tumor microenvironment (TME) has a crucial role in fostering and restraining tumor development. Consequently, we performed a systematic investigation of the TME and genetic factors associated with DLBCL to identify prognostic biomarkers for DLBCL. Data for a total of 1,084 DLBCL patients from the Gene Expression Omnibus database were included in this study, and patients were divided into a training group, an internal validation group, and two external validation groups. We calculated the abundance of immune-stromal components of DLBCL and found that they were related to tumor prognosis and progression. Then, differentially expressed genes were obtained based on immune and stromal scores, and prognostic TME-related genes were further identified using a protein-protein interaction network and univariate Cox regression analysis. These genes were analyzed by the least absolute shrinkage and selection operator Cox regression model to establish a seven-gene signature, comprising TIMP2, QKI, LCP2, LAMP2, ITGAM, CSF3R, and AAK1. The signature was shown to have critical prognostic value in the training and validation sets and was also confirmed to be an independent prognostic factor. Subgroup analysis also indicated the robust prognostic ability of the signature. A nomogram integrating the seven-gene signature and components of the International Prognostic Index was shown to have value for prognostic prediction. Gene set enrichment analysis between risk groups demonstrated that immune-related pathways were enriched in the low-risk group. In conclusion, a novel and reliable TME relevant gene signature was proposed and shown to be capable of predicting the survival of DLBCL patients at high risk of poor survival.