Wearing blue surgical gowns and white respirator hoods, research scientist Pradeep Uchil and post-doctoral fellow Irfan Ullah carry an anesthetized mouse to the lab’s imaging unit. Two days ago, the mouse was infected with a SARS-CoV-2 virus engineered to produce a bioluminescent protein. After an injection of a bioluminescence substrate, a blue glow starts to emanate from within the mouse’s nasal cavity and chest, visible to the imaging unit’s camera and Uchil’s eyes.
“We were never able to see this kind of signal with retrovirus infections.” Uchil is a research scientist at the Yale School of Medicine whose work focuses on the in vivo imaging of retroviral infections. Normally, the mouse would have to be sacrificed and “opened up” for viral bioluminescent signals from internal tissues to be imaged directly.
Most of us, after we flush the toilet, don’t think twice about our body waste. To us, it’s garbage. To epidemiologists, however, wastewater can provide valuable information about public health and help save lives.
History of Wastewater-Based Epidemiology
Wastewater-based epidemiology (WBE) is the analysis of wastewater to monitor public health. The term first emerged in 2001, when a study proposed the idea of analyzing wastewater in sewage-treatment facilities to determine the collective usage of illegal drugs within a community. At the time, this idea to bridge environmental and social sciences seemed radical, but there were clear advantages. Monitoring wastewater is a nonintrusive and relatively inexpensive way to obtain real-time data that accurately reflects community-wide drug usage while ensuring the anonymity of individuals.
The Delta Variant poses a unique challenge to global health. We’ve compiled answers to some of the most common questions about Delta and other SARS-CoV-2 variants.
What is a variant?
A variant is a form of a virus that is genetically distinct from the original form.
“All organisms have mutation rates,” says Luis A Haddock, a graduate student at University of Wisconsin – Madison. “Unfortunately for us, viruses have one of the highest mutation rates of everything that currently exists. And even more unfortunately, RNA viruses have the highest mutation rates even among viruses.”
Luis works in the Friedrich Lab at UW-Madison, which has been sequencing SARS-CoV-2 genomes from positive test samples since the beginning of the pandemic. SARS-CoV-2 is constantly evolving, and sequencing can help us follow it through time and space. Most of the variants don’t behave any differently. A single nucleotide substitution might not even change the amino acid sequence of an encoded protein. However, occasionally a mutation will alter the structure or function of a protein.
The Brazilian state of Amazonas experienced two distinct waves of COVID-19 infections in 2020. After the first wave, a team from the University of Sao Paolo projected that the city of Manaus would reach the theoretical threshold for herd immunity by the end of the summer. However, a second COVID-19 wave erupted in December 2020, coinciding with the rise of Variant of Concern (VOC) P.1.
New research published in Nature Medicineexamined the different lineages of COVID-19 present in Brazil over time and determined that the two waves were driven by different variants. The first wave was driven by the variant B.1.195, which was imported from Europe in the spring. The second wave was largely driven by VOC P.1. The Nature Medicine study is the first to use viral sequences from samples collected throughout 2020 to explore the epidemiological and virological factors behind the two distinct COVID-19 waves.
Detecting VOC P.1 in Amazonas Samples
The researchers started by generating whole-genome sequences of 250 SARS-CoV-2 samples collected between March 2020 and January 2021. The survey showed that 20% of the sequences belonged to the B.1.195 lineage, and these mostly corresponded with the first exponential growth phase. 24% of the samples belonged to the P.1 lineage, and all of these samples corresponded with the rise of the second exponential growth phase. The largest share belonged to B.1.1.28 (37%), which replaced B.1.195 as the dominant variant in Brazil shortly after the first wave until the rise of VOC P.1.
The team also used real-time RT-PCR to analyze 1,232 positive samples collected in Amazonas between November 1, 2020 and January 21, 2021. The assay was designed to detect a deletion in NSP6, which is a signature mutation of VOC P.1. None of the samples collected before December 16 showed the NSP6 deletion, but it was common in samples starting in mid-December. Combining the two analysis methods, the team found the P.1 lineage in 0% of samples collected in November 2020, but by January 1-15 it was present in 73.8% of samples.
This data supports the theory that VOC P.1 first emerged in December 2020 and was the dominant lineage driving the second wave in Amazonas.
Two COVID-19 Waves: Virological and Epidemiological Factors
In addition to tracking the prevalence of lineages throughout the pandemic, the researchers also offered suggestions for how Amazonas experienced two distinct waves of COVID-19 infections.
Using computer modeling, the team found a significant reduction in reproductive efficiency (Re) of lineages B.1.195 and B.1.1.28 in April-May 2020, around the same time that Amazonas increased social distancing measures. Transmission rates remained low until the interventions were relaxed in September 2020. This suggests that the reduction in cases was not a result of herd immunity. Instead, nonpharmaceutical interventions (NPI) limited the first wave and contained the spread through the summer.
Using real-time RT-PCR, the researchers found that the viral load of P.1 infections was nearly ten times the viral load of non-P.1 infection. They also referenced other research that found that VOC P.1 has a stronger affinity for the human receptor ACE2 than B.1.195 and B.1.1.28. P.1 is clearly a highly transmissible VOC, and it evolved in an ideal environment for rapid spread. Amazonas had relaxed social distancing measures by late 2020, P.1 was able to quickly reach extremely high infection rates.
The study did not directly address theories that P.1 evades immunity developed from prior infections, but they concluded that a combination of epidemiological and virological factors allowed P.1 to drive a second wave of COVID-19 in Amazonas starting in December.
The paper includes a supplementary note suggesting that NPIs instituted in Manaus in January 2021 significantly reduced transmission rates of VOC P.1. The team ends the paper by reiterating the importance of adequate social distancing measures to limit the spread of COVID-19 and prevent the emergence of new Variants of Concern.
B cells are the immune cells that produce antibodies (immunoglobulins or Ig) to detect intruding pathogens. B cells produce a variety of classes of antibodies. Generally during an immune response to a pathogen, whether viral or bacterial, B cells produce immunoglobulins (Ig) IgM and IgD, and later in the response, IgG and IgA, that are specific to the intruding organism. These Igs capture and aid in neutralizing the pathogen.
Ig classes can be studied by sequencing the B cell receptor (BCR), which binds antigen specifically. BCRs are formed via irreversible gene segment rearrangements of variable, diversity and joining (VDJ) genes. Ig classes can be diversified through somatic hypermutation and class-switch recombination of these gene segments (1).
B cell receptors with high sequence similarity can be found in individuals exposed to the same antigen, demonstrating that antigen exposure can result in similar B cell clones and memory B cells between individuals, both adults and children (1).
However, B cell immune responses can differ between adults and children. For example, children use more B cell clones that form neutralizing antibodies to HIV-1. And children infected with SARS-CoV-2 generally have milder illness than infected adults. SARS-CoV-2-infected children have lower antibody titers to the virus and more IgG-specific response to SARS-CoV-2 spike protein than to the nucleocapsid protein (1). These differences can contribute to faster SARS-CoV-2 clearance and lower viral loads in children versus adults.
Science is the practice of figuring out how things work and then using that knowledge to further our understanding or to create tools that can solve problems facing the world. Bioluminescent tools and assays are examples of science doing all these things. Bioluminescence is the light-yielding (luminescence) chemical reaction that is used by many lifeforms. When fireflies flicker in the twilight, they are using bioluminescence to flash on and off. Chemically, bioluminescence happens when an enzyme called luciferase acts on a light-emitting compound, luciferin, in the presence of adenosine triphosphate (ATP), magnesium and oxygen.
For scientists, bioluminescence can serve as a tool to help them understand many cellular functions. Since few animal or plant cells produce their own light, there is little to no background signal (light) to be concerned about. This lack of background means that all light coming from the sample can be measured. In fact, bioluminescence is often a preferred tool for scientists because it does not require an external light source or special filters, which are required for fluorescence-based technologies.
Promega scientists have developed bioluminescent tools and assays to support leading edge scientific research for decades, beginning in 1990 with the Luciferase biosensor technology based on firefly luciferase. Luciferase is a wonderful tool for studying how enzymes work because its output (light) is so easy to measure: samples are placed into a special instrument called a luminometer, and the amount of light being produced (Relative Light Units) is recorded. Bioluminescence technology can be configured to measure a variety of cellular biology, ranging from cell health to enzyme activity down to the specific event of turning a gene on or off. The advent of new techniques for genetic manipulation, along with an enhanced understanding of bioluminescence and the discovery and engineering of better luciferases, enables science to use bioluminescence in even more unique ways.
Inflammation, a process that was meant to defend our body from infection, has been found to contribute to a wide range of diseases, such as chronic inflammation, neurodegenerative disorders—and more recently, COVID-19. The development of new tools and methods to measure inflammation is crucial to help researchers understand these diseases.
Cytokines—small signaling molecules that regulate inflammation and immunity—have recently become the focus of inflammation research due to their role in causing severe COVID-19 symptoms. In these severe cases, the patient’s immune system responds to the infection with uncontrolled cytokine release and immune cell activation, called the “cytokine storm”. Although the cytokine storm can be treated using established drugs, more research is needed to understand what causes this severe immune response and why only some patients develop it.
This blog was written by guest author, Amy Landreman, PhD.
Drug repurposing, identifying new uses for approved or investigational drugs, is an attractive strategy when looking for new disease treatments. Because the compounds have already gone through some level of pre-clinical optimization and safety testing, this approach can reduce risk, reduce cost, and speed up the timeline for further drug development. An additional benefit of this approach is that it can result in new biological insights or a better understanding of disease mechanisms since these compounds usually already have some level of mechanistic characterization. Indeed, there are now a number of compound collections openly available specifically for the purpose of facilitating drug repurposing efforts. For example, the ReFRAME (Repurposing, Focused Rescue, and Accelerated Medchem) library is a collection of 12,000 compounds developed by Scripps Research Center and has been screened to identify novel candidate therapeutics for Cryptosporidium infection (1). The Broad Institute also offers a drug repurposing hub that contains an annotated collection of over 7,000 compounds.
Drug repurposing libraries, although often smaller than novel compound small molecule libraries, are designed for implementation into high-throughput screening workflows in order to efficiently triage compounds for the desired result. Effective compound screens require assays that can be scaled to 384 or 1536-well microplate formats and implemented in batch or continuous processing workflows. The firefly luciferase reaction has been leveraged to create many assays that are well-suited to these types of high-throughput screening approaches. In particular, the generation of “Glow” assays that have stable luminescent signals and homogenous assay design is a good fit. The signal stability allows for multi-plate processing and because the reagent is added directly to cells in culture, pre-processing steps are eliminated allowing for automated workflows. Assay reagents such as the CellTiter-Glo® Cell Viability Assay and the ADP-Glo™ Kinase Assay are commonly used in screening efforts including those done with repurposing libraries. In addition, there are several firefly luciferase reporter assay reagents such as Steady-Glo® and Bright-Glo™ Luciferase Assays that have been optimized for high-throughput detection of firefly luciferase activity making them well-suited to repurposing screens.
Every time a genome is replicated, there’s a chance that an error will be introduced. This is true for all life forms. On a small scale, these mutations can lead to genetic diseases or cancers. On a much larger scale, random mutations are an important tool of evolution.
During the COVID-19 pandemic, the SARS-CoV-2 virus has picked up many mutations as it spread around the world. Most of these mutations have been inconsequential – the virus didn’t change in any significant way. Others have given rise to variants such as B.1.1.7 and B.1.351, which present complications for public health efforts. By studying the evolution of the virus, we can monitor how it’s spreading and predict the characteristics of variants as they are detected.
Before the COVID-19 global pandemic began, Dr. Xuping Xie, Assistant Professor of the University of Texas Medical Branch at Galveston, TX has been studying viruses, such as Dengue and Zika, for more than 10 years. Once the pandemic hit in early 2020, he was prepared to join the fight against the virus. “There was an urgent need to know: Is there a quicker way to develop therapeutics or antibodies to target SARS-CoV-2?” says Dr. Xie. “That’s why we immediately launched our SARS-CoV-2 project.”
His goal was to create an assay that could 1) screen for antiviral drugs and 2) quickly measure neutralizing antibody levels. The assay could be used to determine the immune status of previously infected individuals and to evaluate various vaccines under development. To achieve this, he wanted to create a reporter virus that is genetically stable and replicates similarly to the wild-type virus in cell culture.
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