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Biology subjects

Lugo, A.

Publications and source records attributed to Lugo, A..

2 recordsLinked to original sources

Inhibition of SARS-CoV-2 infection by Porphyromonas gingivalis and the oral microbiome

The COVID-19 pandemic persists despite the availability of vaccines, and it is therefore crucial to develop new therapeutic and preventive approaches. In this study, we investigated the potential role of the oral microbiome in SARS-CoV-2 infection. Using an in vitro SARS-CoV-2 pseudovirus infection assay, we found a potent inhibitory effect exerted by Porphyromonas gingivalis on SARS-CoV-2 infection mediated by known P. gingivalis compounds such as phosphoglycerol dihydroceramide (PGDHC) and gingipains as well as by unknown bacterial factors. We found that the gingipain-mediated inhibition of infection is likely due to cytotoxicity, while PGDHC inhibited virus infection by an unknown mechanism. Unidentified factors present in P. gingivalis supernatant inhibited SARS-CoV-2 likely via the fusion step of the virus life cycle. We addressed the role of other oral bacteria and found certain periodontal pathogens capable of inhibiting SARS-CoV-2 pseudovirus infection by inducing cytotoxicity on target cells. In the human oral cavity, we observed the modulatory activity of oral microbial communities varied among individuals in that some saliva-based cultures were capable of inhibiting while others were enhancing infection. These findings contribute to our understanding of the complex relationship between the oral microbiome and viral infections, offering potential avenues for innovative therapeutic strategies in combating COVID-19.

microbiology↗

Beyond synthetic lethality: multiple gene interaction types play a key functional role in cancer

The phenotypic effect of perturbing a genes activity depends on the activity level of other genes, reflecting the notion that phenotypes are emergent properties of a network of functionally interacting genes. In the context of cancer, contemporary investigations have primarily focused on just one type of functional genetic interaction (GI) - synthetic lethality (SL). However, there may be additional types of GIs whose systematic identification would enrich the molecular and functional characterization of cancer. Here, we describe a novel data-driven approach called EnGIne, that applied to TCGA data identifies 71,946 GIs spanning 12 distinct types, only a small minority of which are SLs. The detected GIs explain cancer driver genes tissue-specificity and differences in patients response to drugs, and stratify breast cancer tumors into refined subtypes. These results expand the scope of cancer GIs and lay a conceptual and computational basis for future studies of additional types of GIs and their translational applications. The GI network is accessible online via a web portal [https://amagen.shinyapps.io/cancerapp/].

cancer biology↗