The gut microbiota is closely associated with inflammatory bowel disease (IBD) and colorectal cancer (CRC). Probiotics such as Clostridium butyricum (CB) or Akkermansia muciniphila (AKK) have the potential to treat inflammatory bowel disease (IBD) or colorectal cancer (CRC). However, research on the combined therapeutic effects and immunomodulatory mechanisms of CB and AKK in treating IBD or CRC has never been studied. This study evaluates the potential of co-administration of CB and AKK in treating DSS/AOM-induced IBD and colitis-associated CRC. Our results indicate that compared to mono-administration, the co-administration of CB and AKK not only significantly alleviates symptoms such as weight loss, colon shortening, and increased Disease Activity Index in IBD mice but also regulates the gut microbiota composition and effectively suppresses colonic inflammatory responses. In the colitis-associated CRC mice model, a combination of CB and AKK significantly alleviates weight loss and markedly reduces inflammatory infiltration of macrophages and cytotoxic T lymphocytes (CTLs) in the colon, thereby regulating anti-tumor immunity and inhibiting the occurrence of inflammation-induced CRC. In addition, we found that the combined probiotic therapy of CB and AKK can enhance the sensitivity of colitis-associated CRC mice to the immune checkpoint inhibitor anti-mouse PD-L1 (aPD-L1), significantly improving the anti-tumor efficacy of immunotherapy and the survival rate of colitis-associated CRC mice. Furthermore, fecal microbiota transplantation therapy showed that transplanting feces from CRC mice treated with the co-administration of CB and AKK into other CRC mice alleviated the tumor loads in the colon and significantly extended their survival rate. Our study suggests that the combined use of two probiotics, CB and AKK, can not only alleviate chronic intestinal inflammation but also inhibit the progression to CRC. This may be a natural and relatively safe method to support the gut microbiota and enhance the host’s immunity against cancer. IMPORTANCE: Our study suggests that the combined administration of CB and AKK probiotics, as opposed to a single probiotic strain, holds considerable promise in preventing the advancement of IBD to CRC. This synergistic effect is attributed to the ability of this probiotic combination to more effectively modulate the gut microbiota, curb inflammatory reactions, bolster the efficacy of immunotherapeutic approaches, and optimize treatment results via fecal microbiota transplantation.

Cardiovascular disease (CVD) is the leading cause of mortality, disability, and healthcare costs, with a significant impact on the elderly and contributing to premature deaths across various age groups, including those below age 70. Despite decades of transformative discoveries and clinical efforts, the challenges of diagnosis, prevention, and treatment of CVD persist on a massive scale. This study aimed to unravel potential CVD-associated biomarkers and establish a machine learning model for the risk assessment of CVD. Untargeted metabolic assay with ultra-high performance liquid chromatography-tandem mass spectrometry and routine clinical biochemistry test were undertaken on the fasting venous blood specimens from 57 subjects. Four relevant clinical traits and 164 CVD-associated metabolites were identified, especially those related to glycerophospholipid metabolism and biosynthesis of unsaturated fatty acids. The machine learning model achieved from an integrated biomarker panel of palmitic amide, oleic acid, 138-pos (the 138th detected metabolomic feature in positive ion mode), phosphatidylcholine, linoleic acid, age, direct bilirubin, and inorganic phosphate, was able to improve the accuracy of CVD risk assessment up to a high satisfactory value of 0.91. The findings indicate that disorders in the metabolic processes of biological membranes and energy are significantly associated with increased risk of vascular damage in CVD patients. With machine learning methods, the pivotal metabolites and clinical biomarkers offer a promising potential for the efficient risk assessment and diagnosis of CVD.