HIV-1 and SARS-CoV-2: Patterns in the evolution of two pandemic pathogens.

Cell Host Microbe

T-6: Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, 87545, USA; New Mexico Consortium, Los Alamos, New Mexico, 87545, USA. Electronic address:

Published: July 2021

Humanity is currently facing the challenge of two devastating pandemics caused by two very different RNA viruses: HIV-1, which has been with us for decades, and SARS-CoV-2, which has swept the world in the course of a single year. The same evolutionary strategies that drive HIV-1 evolution are at play in SARS-CoV-2. Single nucleotide mutations, multi-base insertions and deletions, recombination, and variation in surface glycans all generate the variability that, guided by natural selection, enables both HIV-1's extraordinary diversity and SARS-CoV-2's slower pace of mutation accumulation. Even though SARS-CoV-2 diversity is more limited, recently emergent SARS-CoV-2 variants carry Spike mutations that have important phenotypic consequences in terms of both antibody resistance and enhanced infectivity. We review and compare how these mutational patterns manifest in these two distinct viruses to provide the variability that fuels their evolution by natural selection.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173590PMC
http://dx.doi.org/10.1016/j.chom.2021.05.012DOI Listing

Publication Analysis

Top Keywords

natural selection
8
hiv-1 sars-cov-2
4
sars-cov-2 patterns
4
patterns evolution
4
evolution pandemic
4
pandemic pathogens
4
pathogens humanity
4
humanity currently
4
currently facing
4
facing challenge
4

Similar Publications

Comparative analysis of regression algorithms for drug response prediction using GDSC dataset.

BMC Res Notes

January 2025

Department of Computer Engineering, Chungbuk National University, Chungdae-ro 1, Cheongju, 28644, Republic of Korea.

Background: Drug response prediction can infer the relationship between an individual's genetic profile and a drug, which can be used to determine the choice of treatment for an individual patient. Prediction of drug response is recently being performed using machine learning technology. However, high-throughput sequencing data produces thousands of features per patient.

View Article and Find Full Text PDF

The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers.

J Transl Med

January 2025

Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.

Background: It is worthwhile to establish a prognostic prediction model based on microenvironment cells (MCs) infiltration and explore new treatment strategies for triple-negative breast cancer (TNBC).

Methods: The xCell algorithm was used to quantify the cellular components of the TNBC microenvironment based on bulk RNA sequencing (bulk RNA-seq) data. The MCs index (MCI) was constructed using the least absolute shrinkage and selection operator Cox (LASSO-Cox) regression analysis.

View Article and Find Full Text PDF

This review highlights recent progress in exosome-based drug delivery for cancer therapy, covering exosome biogenesis, cargo selection mechanisms, and their application across multiple cancer types. As small extracellular vesicles, exosomes exhibit high biocompatibility and low immunogenicity, making them ideal drug delivery vehicles capable of efficiently targeting cancer cells, minimizing off-target damage and side effects. This review aims to explore the potential of exosomes in cancer therapy, with a focus on applications in chemotherapy, gene therapy, and immunomodulation.

View Article and Find Full Text PDF

Background: Acute respiratory distress syndrome (ARDS) is a prevalent complication among critically ill patients, constituting around 10% of intensive care unit (ICU) admissions and mortality rates ranging from 35 to 46%. Hence, early recognition and prediction of ARDS are crucial for the timely administration of targeted treatment. However, ARDS is frequently underdiagnosed or delayed, and its heterogeneity diminishes the clinical utility of ARDS biomarkers.

View Article and Find Full Text PDF

Cold stress in winter is one of the most severe abiotic stresses on plant growth and flourishing, and the selection of cold tolerant genotypes is an important strategy to ensure the safety of plant growth and development. Cyclocarya paliurus, a diclinous and versatile tree species originally in subtropical regions, has been introduced and cultivated in the warm temperate zone of China to meet the increasing market demand for its leaf yield. However, information regarding its cold tolerance remains limited.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!