Immunotherapy can elicit robust anticancer responses in the clinic. However, a large proportion of patients with colorectal cancer do not benefit from treatment. Although previous studies have shown that hydrogen sulfide (H2S) is involved in colorectal cancer development and immune escape, further insights into the mechanisms and related molecules are needed to identify approaches to reverse the tumor-supportive functions of H2S. Here, we observed significantly increased H2S levels in colorectal cancer tissues. Decreasing H2S levels by using CBS+/− mice or feeding mice a sulfur amino acid-restricted diet (SARD) led to a marked decrease in differentiated CD4+CD25+Foxp3+ Tregs and an increase in the CD8+ T-cell/Treg ratio. Endogenous or exogenous H2S depletion enhanced the efficacy of anti–PD-L1 and anti–CTLA4 treatment. H2S promoted Treg activation through the persulfidation of ENO1 at cysteine 119. Furthermore, H2S inhibited the migration of CD8+ T cells by increasing the expression of AAK-1 via ELK4 persulfidation at cysteine 25. Overall, reducing H2S levels engenders a favorable immune microenvironment in colorectal cancer by decreasing the persulfidation of ENO1 in Tregs and ELK4 in CD8+ T cells. SARD represents a potential dietary approach to promote responses to immunotherapies in colorectal cancer. Significance: H2S depletion increases the CD8+ T-cell/Treg ratio and enhances the efficacy of anti–PD-L1 and anti–CTLA4 treatment in colon cancer, identifying H2S as an anticancer immunotherapy target.

Migraine is a prevalent, disabling type of primary headache disorder associated with a high socioeconomic burden. The clinical management of migraine is challenging. This study was to identify potential serum lipidomic biomarkers of migraine. The serum lipidomic profile of migraine sufferers was compared with healthy individuals using Liquid Chromatography coupled to Mass Spectrometry (LC-MS). Volcano plot analysis by Student’s t-test was performed to identify the differential metabolites. Receiver operating characteristic (ROC) curves were constructed and the area under ROC curves (AUC) was calculated to evaluate whether the metabolites could be efficiently exploited for constructing a sensitive biomarker of migraine. A total of 29 serum metabolites from 4 classes of lipids including acylcarnitines, non-alpha-hydroxy-sphingosine ceramides (Cer_NSs), lysophosphatidylcholines (lysoPCs) and lysophosphatidylethanolamines (lysoPEs) were significantly different in migraine patients and controls. Of note, Cer_NSs were significantly elevated and lysoPEs were significantly decreased in migraine patients. LysoPE 18:1, lysoPE 18:2 and lysoPE 22:5 were found to be decreased in both positive and negative ion mode. Moreover, except for lysoPC 20:0, other lysoPCs were decreased in migraine patients. ROC curve analysis indicated that lysoPC 16:0 and lysoPC 20:0 are potential sensitive and specific biomarkers for migraine. LysoPC 16:0 and lysoPC 20:0 may be potential biomarkers for migraine. We suggest therapeutic management of these metabolites may be helpful in the prevention and treatment of migraine.

As the ability to collect profiling data in metabolomics increases substantially with the advances in Liquid Chromatography–Mass Spectrometry (LC-MS) instruments, it is urgent to develop new and powerful data analysis approaches to match the big data collected and to extract as much meaningful information as possible from tens of thousands of molecular features. Here, we applied weighted gene co-expression network analysis (WGCNA), an algorithm popularly used in microarray or RNA sequencing, to plasma metabolomic data and demonstrated several advantages of WGCNA over conventional statistical approaches such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). By using WGCNA, a large number of molecular features were clustered into a few modules to reduce the dimension of a dataset, the impact of phenotypic traits such as diet type and genotype on the plasma metabolome was evaluated quantitatively, and hub metabolites were found based on the network graph. Our work revealed that WGCNA is a very powerful tool to decipher, interpret, and visualize metabolomic datasets.

The presence of sub-minimal inhibitory concentration (sub-MIC) antibiotics in our environment is widespread, and their ability to induce antibiotic resistance is inevitable. Acinetobacter baumannii, a pathogen known for its strong ability to acquire antibiotic resistance, has recently shown clinical resistance to the last-line antibiotic tigecycline. To unravel the complex mechanism of A. baumannii drug resistance, we subjected tigecycline-susceptible, -intermediate, and -mildly-resistant strains to successive increases in sub-MIC tigecycline and ultimately obtained tigecycline-resistant strains. The proteome of both key intermediate and final strains during the selection process was analyzed using nanoLC-MS/MS. Among the more than 2600 proteins detected in all strains, we found that RND efflux pump AdeABC was associated with the adaptability of A. baumannii to tigecycline under sub-MIC pressure. qRT-PCR analysis also revealed higher expression of AdeAB in strains that can quickly acquire tigecycline resistance compared with strains that displayed lower adaptability. To validate our findings, we added an efflux pump inhibitor, carbonyl cyanide m-chlorophenyl hydrazine (CCCP), to the medium and observed its ability to inhibit tigecycline resistance in A. baumannii strains with quick adaptability. This study contributes to a better understanding of the mechanisms underlying tigecycline resistance in A. baumannii under sub-MIC pressure.