Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the COVID-19 pandemic. After over 160 million cases and 3.3 million deaths worldwide as of May 2021, it is still unclear when this crisis will end. Thus, there is an urgent need for treatments that improve the prognosis of seriously affected patients. Multiple viruses including HIV, MERS-CoV (coronavirus responsible for Middle East Respiratory Syndrome, MERS), SARS-CoV (coronavirus responsible for SARS) and SARS-CoV-2 use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to successfully replicate. SARS-CoV and SARS-CoV-2 possess a unique RNA pseudoknotted structure that stimulates -1 PRF. Recent experiments identified small molecules as antiviral agents that can bind to the pseudoknot and disrupt its stimulation of -1 PRF. Targeting -1 PRF in SARS-CoV-2 can be an excellent strategy to impair viral replication and improve patients’ prognoses. Crucial to developing these successful therapies is modeling the structure of the SARS-CoV-2 -1 PRF pseudoknot. Following a structural alignment approach, we identify similarities in -1 PRF pseudoknots of SARS-CoV-2, SARS-CoV, and MERS-CoV. In addition, we provide a better understanding of the SARS-CoV-2 -1 PRF pseudoknot by investigating the structural landscape using a hierarchical folding approach. We provide in-depth analysis on alternative structure prediction methods based on SARS-CoV-2 structural reactivity (SHAPE) data to contextualize and motivate future RNA structure-function research. Since understanding the impact of mutations is vital to long-term success of treatments based on predicted RNA functional structures, we provide insight on SARS-CoV-2 -1 PRF pseudoknot sequence mutations and their effect on the resulting structure.
Monitoring the environment for pollution, pesticides, and pathogens is crucial for protecting human, agriculture, and overall ecosystem health. Diverse strategies ranging from physical sensors to sentinel species have been used for environmental monitoring. The European honey bee, Apis mellifera, is a globally managed pollinator that can serve as a continuous biomonitoring species. During foraging, honey bees are exposed to contaminants and pathogens and carry them to their hives where they can be detected and quantified. Although individual bees are vulnerable to environmental stressors, the honey bee colony as a whole is more resilient and can accumulate contaminants or respond to them without collapsing. This allows for long-term monitoring of the colony to map contaminants in a geographical area and study ecotoxicology gradients over space and time. In this paper, we review demonstrated and proposed uses of honey bees for environmental monitoring. We focus our discussion on heavy metals, air pollutants, pesticides, and plant pathogens that can be detected in bees and their hive materials including honey, wax, and stored pollen. We present the use of gene expression, microbiome profiling, and other high-throughput methodologies to study dose-dependent exposure and increase detection sensitivity; for example, stored pollen analysis with next generation sequencing can reveal the presence of plant viruses, fungi, and invasive species earlier than traditional detection methods. Finally, we discuss opportunities for using honey bees to monitor emerging threats such as climate change and antimicrobial resistance. This narrative review highlights the versatility and potential utility of the European honey bee as a biomonitoring species for ecosystem health.