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Biology subjects

Roumenina, L. T.

Publications and source records attributed to Roumenina, L. T..

2 recordsLinked to original sources

Evolutionary trajectory of the physicochemical mechanism of interaction of SARS-CoV-2 spike protein with ACE2

SARS-CoV-2 infects cells by attachment to its receptor - the angiotensin converting enzyme 2 (ACE2). Regardless of the wealth of structural data, little is known about the physicochemical mechanism of interactions of the viral spike (S) protein with ACE2 and how this mechanism has evolved during the pandemic. Here, we applied experimental and computational approaches to characterize the molecular interaction of S proteins from SARS-CoV-2 variants of concern (VOC). Data on kinetics, activation- and equilibrium thermodynamics of binding of the receptor binding domain (RBD) from VOC with ACE2 as well as data from computational protein electrostatics revealed a profound remodeling of the physicochemical characteristics of the interaction during the evolution. Thus, as compared to RBDs from Wuhan strain and other VOC, Omicron RBD presented as a unique protein in terms of conformational dynamics and types of non-covalent forces driving the complex formation with ACE2. Viral evolution resulted in a restriction of the RBD structural dynamics, and a shift to a major role of polar forces for ACE2 binding. Further, we investigated how the reshaping of the physicochemical characteristics of interaction affect the binding specificity of S proteins. Data from various binding assays revealed that SARS-CoV-2 Wuhan and Omicron RBDs manifest capacity for promiscuous recognition of unrelated human proteins, but they harbor distinct reactivity patterns. These findings might contribute for mechanistic understanding of the viral tropism, and capacity to evade immune responses during evolution.

biochemistry↗

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression

Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases, notably cancer. While numerous methods allow to quantify immune or stromal cells in human tissue samples based on transcriptomic data, very few are available for mouse studies. Here, we introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that allow to accurately quantify 12 immune and 4 stromal murine cell populations. We validated mMCP-counter with flow cytometry data. We also showed that mMCP-counter outperforms existing methods. We showed in mouse models of mesothelioma and kidney cancer that mMCP-counter quantification scores are predictive of response to immune checkpoint blockade Finally, we illustrated mMCP-counters potential to analyze immune impacts of Alzheimers disease. mMCP-counter is available as an R package from GitHub: https://github.com/cit-bioinfo/mMCP-counter.

bioinformatics↗