Oral squamous cell carcinoma (OSCC) is the most common manifestation of oral cancer. It has been proposed that periodontal pathogens contribute to OSCC progression, mainly by their virulence factors. However, the main periodontal pathogen and its mechanism to modulate OSCC cells remains not fully understood. In this study we investigate the main host-pathogen pathways in OSCC by computational proteomics and the mechanism behind cancer progression by the oral microbiome. The main host-pathogen pathways were analyzed in the secretome of biopsies from patients with OSCC and healthy controls by mass spectrometry. Then, functional assays were performed to evaluate the host-pathogen pathways highlighted in oral cancer. Host proteins associated with LPS response, cell migration/adhesion, and metabolism of amino acids were significantly upregulated in the human cancer proteome, whereas the complement cascade was downregulated in malignant samples. Then, the microbiome analysis revealed large number and variety of peptides from Fusobacterium nucleatum (F. nucleatum) in OSCC samples, from which several enzymes from the L-glutamate degradation pathway were found, indicating that L-glutamate from cancer cells is used as an energy source, and catabolized into butyrate by the bacteria. In fact, we observed that F. nucleatum modulates the cystine/glutamate antiporter in an OSCC cell line by increasing SLC7A11 expression, promoting L-glutamate efflux and favoring bacterial infection. Finally, our results showed that F. nucleatum and its metabolic derivates promote tumor spheroids growth, spheroids-derived cell detachment, epithelial-mesenchymal transition and Galectin-9 upregulation. Altogether, F. nucleatum promotes pro-tumoral mechanism in oral cancer.

Tissue regeneration is often impaired in patients with metabolic disorders such as diabetes mellitus and obesity, exhibiting reduced wound repair and limited regeneration capacity. We and others have demonstrated that wound healing under normal metabolic conditions is potentiated by the secretome of human endothelial cell-differentiated mesenchymal stem cells (hMSC-EC). However, it is unknown whether this effect is sustained under hyperglycemic conditions. In this study, the wound healing effect of secretomes from undifferentiated human mesenchymal stem cells (hMSC) and hMSC-EC in a type-2 diabetes mouse model was analyzed. hMSC were isolated from human Wharton’s jelly and differentiated into hMSC-EC. hMSC and hMSC-EC secretomes were analyzed and their wound healing capacity in C57Bl/6J mice fed with control (CD) or high fat diet (HFD) was evaluated. Our results showed that hMSC-EC secretome enhanced endothelial cell proliferation and wound healing in vivo when compared with hMSC secretome. Five soluble proteins (angiopoietin-1, angiopoietin-2, Factor de crecimiento fibroblástico, Matrix metallopeptidase 9, and Vascular Endothelial Growth Factor) were enriched in hMSC-EC secretome in comparison to hMSC secretome. Thus, the five recombinant proteins were mixed, and their pro-healing property was evaluated in vitro and in vivo. Functional analysis demonstrated that a cocktail of these proteins enhanced the wound healing process similar to hMSC-EC secretome in HFD mice. Overall, our results show that hMSC-EC secretome or a combination of specific proteins enriched in the hMSC-EC secretome enhanced wound healing process under hyperglycemic conditions.

CD8+ and CD4+ T-cells play a key role in cellular immune responses against cancer by cytotoxic responses and effector lineages differentiation, respectively. These subsets have been found in different types of cancer; however, it is unclear whether tumor-infiltrating T-cell subsets exhibit similar transcriptome profiling across different types of cancer in comparison with healthy tissue-resident T-cells. Thus, we analyzed the single cell transcriptome of five tumor-infiltrating CD4-T, CD8-T and Treg cells obtained from different types of cancer to identify specific pathways for each subset in malignant environments. An in silico analysis was performed from single-cell RNA-sequencing data available in public repositories (Gene Expression Omnibus) including breast cancer, melanoma, colorectal cancer, lung cancer and head and neck cancer. After dimensionality reduction, clustering and selection of the different subpopulations from malignant and nonmalignant datasets, common genes across different types of cancer were identified and compared to nonmalignant genes for each T-cell subset to identify specific pathways. Exclusive pathways in CD4+ cells, CD8+ cells and Tregs, and common pathways for the tumor-infiltrating T-cell subsets were identified. Finally, the identified pathways were compared with RNAseq and proteomic data obtained from T-cell subsets cultured under malignant environments and we observed that cytokine signaling, especially Th2-type cytokine, was the top overrepresented pathway in Tregs from malignant samples.

Chile is the second-largest producer of Atlantic salmon (Salmo salar), a key industry facing challenges such as infestations by Caligus rogercresseyi, which cause significant economic losses. However, there are no studies exploring how environmental variables in marine culture centers affect salmon’s immune response, considering their poikilothermic characteristics. This study analyzed the effect of the seasonal temperature on the skin transcriptome of Atlantic salmon infested with C. rogercresseyi in fjord-based farms in the Aysén Region during autumn and spring. Two different centers were analyzed (autumn: Farm-A; spring: Farm-S) to ensure the same age of the fish sampled in each season. RNA sequencing (RNA-seq) and functional network analysis revealed notable seasonal transcriptomic differences. In autumn, 253 differentially expressed genes (DEGs) were found, primarily associated with stress response and negative regulation of T-cell proliferation, suggesting an impaired response against the ectoparasite. In spring, 103 DEGs were detected, associated with protein synthesis and the activation of immune mechanisms, including complement activation, granulocyte chemotaxis, and antigen presentation. This is the first study to evaluate the transcriptomic response of healthy skin in C. rogercresseyi-infested salmon under farming conditions, highlighting the importance of considering seasonal variations for the development of more effective management strategies in the aquaculture industry.

Quantitative understanding of microbial growth is an essential prerequisite for successful control of pathogens as well as various biotechnology applications. Even though the growth of cell populations has been extensively studied, microbial growth remains poorly characterised at the spatial level. Indeed, even isogenic populations growing at different locations on solid growth medium typically show significant location-dependent variability in growth. Here we show that this variability can be attributed to the initial physiological states of the populations, the interplay between populations interacting with their local environment and the diffusion of nutrients and energy sources coupling the environments. We further show how the causes of this variability change throughout the growth of a population. We use a dual approach, first applying machine learning regression models to discover that location dominates growth variability at specific times, and, in parallel, developing explicit population growth models to describe this spatial effect. In particular, treating nutrient and energy source concentration as a latent variable allows us to develop a mechanistic resource consumer model that captures growth variability across the shared environment. As a consequence, we are able to determine intrinsic growth parameters for each local population, removing confounders common to location-dependent variability in growth. Importantly, our explicit low-parametric model for the environment paves the way for massively parallel experimentation with configurable spatial niches for testing specific eco-evolutionary hypotheses.