With the ongoing mutation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leading to various variants, there is an urgent need for new diagnostic methods for SARS-CoV-2 infection. The existing nucleic acid test and antigen test suffer from long assay time and low sensitivity, respectively. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based nasal swabs analysis have been demonstrated as a promising technique in SARS-CoV-2 infection screening. However, the applicability of the technique in the different variants of SARS-CoV-2 is uncertain.Given the prevalence of the Omicron variant since 2022, we developed a MALDI-TOFbased diagnosis method with nasal swab samples to detect the infection by this variant. We collected 325 SARS-CoV-2-positive and 221 SARS-CoV-2-negative nasal swab samples, and the molecular mass fingerprints were acquired from the samples by MALDI-TOF MS. Using a random forest machine learning classification model to analyze the molecular mass fingerprints MALDI-TOF mass spectra, the accuracy of 97%, false negative rate of 0%, and false positive rate of 7.6% were achieved for the diagnosis of SARS-CoV-2 infection. Combining the MALDI-TOF analysis with top-down proteomics, we identified four potential protein biomarkers, that is, humanin-like 4, thymosin beta-10, thymosin beta-4 and statherin, in the nasal swab for the diagnosis of coronavirus disease 2019. It was further found that the four protein biomarkers can also differentiate the SARS-CoV-2 original strains infection and Omicron strains infection. These results suggest that the MALDI-TOF MS-based nasal swab analysis holds effective diagnostic capabilities of SARS-CoV-2 infection, and shows promising potential for global application and extension to other infectious diseases.

Colorectal cancer (CRC) is a complex malignancy, influenced not only by cancer cells but also by the tumor microenvironment (TME). Within the TME, emerging evidence highlights the presence and functional roles of diverse microbial entities, referred to as intratumoral microbiota. The distribution of these microbiota exhibits significant heterogeneity and engages in dynamic interactionswith tumor cells, forming a unique ecosystem. Certain bacterial strains distinctly influence the TME of CRC, affecting the characteristics and progression of the tumor. This review summarizes the intricate roles of intratumoral microbiota within CRC’s TME, emphasizing their importance in the disease’s development and progression, and discuss the opportunities and challenges in the field.

Periodontitis development is strongly associated with the succession of the oral microbiome. However, the knowledge about the succession of the oral microbiome in the development of periodontitis remains insufficient. In the present study, an analysis was conducted on the succession of tongue back, the saliva (Sal) microbiome, and gingival crevicular fluid (GCF) from healthy individuals and patients with mild (CPL), moderate (CPM), severe chronic (CPH), and generalized aggressive periodontitis (GAgP). The composition and structure of the oral microbiome gradually changed with the increasing severity of periodontitis, among which GCF showed the highest correlation with periodontitis. With an ecological preference, pathogens in the mouth varied with the development of periodontitis. In healthy and CPL patients, Sal-derived microorganisms accounted for a large proportion of GCF but exhibited a decrease in patients with CPM, CPH, and GAgP. Permutation and time course sequencing analysis revealed that a variety of microorganisms changed with the severity of periodontitis. A majority of these microorganisms are closely related to clinical periodontal indices. Ecological analysis suggested that the composition of oral microbial communities at different stages of periodontitis is controlled by random processes. The comparison ofmicrobial interaction networks demonstrated that a series of key microorganisms drive oral health to severe periodontitis. In this study, the relationship between the succession process of the oral microbiota and the development of periodontitis was revealed.