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Determination of the effectiveness of COVID-19 vaccination using T cell receptor repertoire

Jacob Scott



Scientists have worked at an unprecedented speed to develop coronavirus disease 2019 (COVID-19) vaccines to contain the ongoing pandemic caused by the rapid spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). To date, several COVID-19 vaccines have received emergency use authorization (EUA) from global regulatory bodies, and vaccination programs have commenced in the majority of the countries of the world.

Study: The T cell receptor repertoire reflects the dynamics of the immune response to vaccination. Image Credit: NIAID

How do Vaccines Protect Individuals from Diseases?

Vaccines offer prophylactic immunization against specific diseases by triggering a persistent, adaptive immune response that generates immunological memory, protecting against future infections. Typically, T cells offer adaptive immune protection, and the humoral antibody response is mediated by B cells. After vaccination, the B cells get activated and produce neutralizing antibodies that can bind to target proteins of a virus and, subsequently, protect the individual from the disease. The cell-mediated immune response is associated with the activation of the effector CD4 T cells, which stimulate B cells to produce antibodies. These cells may also employ other cells, such as macrophages, which possess microbicidal functions. Activated CD8 T cells eliminate virus-infected cells. Both CD4 and CD8 memory T cells persist long after vaccination and are primed to become effector T cells. Previous studies have shown that natural killer cells also possess memory-like behavior.

Through vaccines, pathogenic protein subunits are introduced in an individual that stimulates the B and T cells responses. Some of the common forms of vaccines are inactivated viruses, vectors that infect cells to generate viral proteins, messenger RNA (mRNA), and viral proteins. mRNA COVID-19 vaccines are likely to induce both CD4 and CD8 T cells responses.

Determination of Vaccine Effectiveness

In the current scenario, it is extremely important to measure the effectiveness of the vaccines as well as vaccination strategies. Typically, the response to vaccines is evaluated by detecting and measuring antibodies against viral proteins present in the serum. Vaccine response can also be evaluated by detecting activated B and/or T cells.

One of the shortcomings of antibody-based assays (e.g., ELISA) is that they cannot detect low levels of antibodies, which might be sufficient in protecting from a particular disease. In many instances, the levels of antibodies decrease significantly long after vaccination or natural infection, but they offer strong protection against the disease. Detectable levels of antibodies may develop, for antibody-based assays, at least a few weeks post-vaccination.

ELISpot is a technique that is used to detect T and B cells that are responsive to the vaccine. This assay can measure interferon-gamma or granzyme B from the activated cells. Although this method can indirectly assess the activity of immune cells, it is not always accurate.

Evaluation of Vaccine effectiveness Via T cell Receptors (TCR) Repertoire

A new study published on the bioRxiv* preprint server has hypothesized that T cell receptors (TCR) repertoire can measure the response to vaccines, as it would identify the TCR of clones that respond to the vaccination.

Previous studies have revealed that TCR is a heterodimer of two trans-membrane polypeptide chains (TCR? and TCR?) linked by covalent disulfide bonds and a complete TCR repertoire can reflect the T cells present in an individual.

Researchers have developed a novel and accurate method known as Tseek, which is unbiased and provides sensitive profiling of TCR? and TCR? chains or TCR repertoire by sequencing the TCR a and b chains. To evaluate the effectiveness of Tseek in the assessment of vaccine responses, researchers compared the responses to mRNA COVID-19 vaccines and the annual influenza vaccines. Based on epidemiological and antibody data, the vaccines have very different rates of efficacy, i.e., the effectiveness of the COVID-19 vaccine is 90%, whereas the influenza vaccine is 30%.

Clustering of T cell repertoire (CDR3 a) from the Covid/Flu vaccine samples. Distances between samples were defined for the CDR3 data using the Jensen-Shannon metric (an information-theoretic measure, Supplementary material). The heatmaps show the distance between pairs of samples, while the dendrograms show the samples cluster by an individual. A) Covid CDR3 b. The first dose is s1, the second dose is s2, d0 is the pre-vaccine sample, d7 is 7 days post-vaccination, w3 is 3 weeks post-vaccination. For each individual, the two samples after the second vaccine dose (s2_d7 and s2_w3), cluster separately from the two samples after the first vaccine dose (s1_d7 and s1_w3) suggesting distinct sets of T cells react to the two doses. The second dose broadens viral epitopes targeted, likely improving the immunity provided by the vaccination. (Fig. 3A shows the corresponding tree) B) Flu b CDR3 19_20 refers to the 2019-2020 flu season, d0 is the pre-vaccine sample, d7 is 7 days post-vaccination, m1 is 1-month post-vaccination. The clustering by vaccine dose does not occur in some individuals (B, D), and the m4 and m6 samples seem to have lost “memory” of the dose, the T cell response does not persist beyond 2-3 months. Even though there are responsive clones for each flu season (Table 2A, B), the relative lack of clustering of the tree by vaccine dose, in contrast to the covid vaccine data, suggests that the response is “weaker” and has more individual and seasonal variability. Fig. S3 shows data for the b.

Scientists have evaluated the different outcomes of the vaccines using the Tseek method. In this context, they utilized PBMC samples from individuals who consistently received yearly influenza vaccines over several flu seasons for several years. Additionally, researchers collected PBMC samples from individuals who received two doses of COVID-19 mRNA vaccines were obtained. Neutralizing antibody titers were also measured in COVID-19 vaccine samples.

This study revealed that an individual’s TCR signature evolves gradually over the years in response to infections. Scientists found that SARS-CoV-2 vaccination induced a broad-spectrum T cell response that involved many expanded clones; however, this was not the case for the influenza vaccine, which elicited a narrower response involving fewer clones. In addition, many T cell clones provided temporal details that are typically not obtained from antibody measurements, especially, before the antibodies are detectable.


The current study revealed that TCR repertoire is a valuable biomarker for studying immune reactions to the vaccine. The authors highlighted some of the advantages of using Tseek to determine the response to vaccines, including it being a non-invasive approach, rapid assessment of vaccine efficacy, i.e., within a few days of vaccination, and a highly sensitive and specific method. The current study truly demonstrates that TCR repertoire sequencing can be effectively used for early and sensitive measurement of the adaptive immune response to vaccination, which can help improve the selection of the immunogen and optimize vaccine strategy.

*Important Notice

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
Mohammed, K. et al. (2021) The T cell receptor repertoire reflects the dynamics of the immune response to vaccination. bioRxiv 2021.12.09.471735; doi:,

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Unraveling How Strigoractone Hormone Regulates Massive Gene Networks Controlling Plant Growth

Jacob Scott



As sessile organisms, plants have to continually adapt their growth and architecture to the ever-changing environment. To do so, plants have evolved distinct molecular mechanisms to sense and respond to the environment and integrate the signals from outside with endogenous developmental programs.

New research from Nitzan Shabek’s laboratory at the UC Davis College of Biological Sciences, published in Nature Plants, unravels the underlying mechanism of protein targeting and destruction in a specific plant hormone signaling pathway.

Our lab aims at deciphering sensing mechanisms in plants and understanding how specific enzymes function can be regulated at the molecular levels. We have been studying a new plant hormone signal, strigolactone, that governs numerous processes of growth and development including branching and root architecture.”

Nitzan Shabek, assistant professor of biochemistry and structural biology, Department of Plant Biology

The work stems from a study by Shabek, published in Nature in 2018, unravelling molecular and structural changes in an enzyme, MAX2 (or D3) ubiquitin ligase. MAX2 was found in locked or unlocked forms that can recruit a strigolactone sensor, D14, and target for destruction a DNA transcriptional repressor complex, D53. Ubiquitins are small proteins, found in all eukaryotes, that “tag” other proteins for destruction within a cell.

To find the key to unlock MAX2 and to better understand its molecular dynamics in plants, postdoctoral fellows Lior Tal and Malathy Palayam, with junior specialist Aleczander Young, used an approach that integrated advanced structural biology, biochemistry, and plant genetics.

“We leveraged structure-guided approaches to systemically mutate MAX2 enzyme in Arabidopsis and created a MAX2 stuck in an unlocked form”, said Shabek, “some of these mutations were made by guiding CRISPR/Cas9 genome editing thus providing us a discovery platform to study and analyze the different signaling outputs and illuminate the role of MAX2 dynamics.”

They found that in the unlocked conformation, MAX2 can target the repressor proteins and biochemically decorate them with small ubiquitin proteins, tagging them for destruction. Removing these repressors allows other genes to be expressed – activating a massive gene network that governs shoot branching, root architecture, leaf senescence, and symbiosis with fungi, Shabek said.

Sending these repressors to the proteasome disposal complexes requires the enzyme to relock again. The team also showed that MAX2 not only target the repressors proteins, but once it is locked the strigolactone sensor itself gets destroyed, returning the system to its original state.

Finally, the study uncovered the key to the lock, an organic acid metabolite that can directly trigger the conformational switch.

“Beyond the implication in plants signaling, this is the first work that placed a primary metabolite as a direct new regulator of this type of ubiquitin ligase enzymes and will open new avenues of study in this direction,” Shabek said.

Additional coauthors on the paper are specialist Mily Ron and Professor Anne Britt, Department of Plant Biology. The study was supported by NSF CAREER and EAGER grants to Shabek. X-ray crystallography data was obtained at the Advanced Light Source, Lawrence Berkeley National Laboratory, a U.S. Department of Energy user facility.

Journal reference:

Tal, L., et al. (2022) A conformational switch in the SCF-D3/MAX2 ubiquitin ligase facilitates strigolactone signalling. Nature Plants.

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UrFU Sociologists Identify Digital Fears Among Young People

Jacob Scott



Sociologists at the Ural Federal University (UrFU) have identified digital fears among young people. According to experts, these are additional fears that do not replace, but complement and reinforce traditional ones. They emerged against the background of uncertainty, the growth of forces beyond human control. Developed emotional intelligence, creativity, and the ability to collaborate help to overcome them.

In the study, sociologists interviewed 1,050 people aged 18-30. Respondents were asked to assess which digital risks concern them most. The study was launched in 2020 and the results were published in April 2022 in the Changing Societies & Personalities journal.

The first group of fears is influence and control. It touches on the problem of interference with privacy by technical means. This category is the most significant for young people: 55.8% are afraid of total control by means of video-surveillance and monitoring software on their mobile devices. 48.5% of respondents believe they are at risk of wiretapping, tracking content in social networks, and inability to keep correspondence secret.”

Natalia Antonova, Professor, Department of Applied Sociology, UrFU

45.8% of young people fear the manipulative influence of the media and an increase in fake news. At the same time, only 27.8% and 18.1% of respondents are concerned about microchipping and genetic manipulation, respectively. It is likely that these threats seem more controllable, both from the individual (through control of food choices, medical procedures, etc.) and from government programs, the researchers believe.

The second group of concerns is crime and security. Here young people are wary of illegal actions using digital technology.

“One of the main fears of 56% of young people is the security of personal data. This is related both to the growth of personal information in social networks and messengers, and to the growth of hacker attacks and viruses. 42.9% of young citizens are afraid of Internet fraudsters, and 25.8% are afraid of losing important information, including smashing their phones, not saving data, forgetting their passwords, or being without an Internet connection,” explains Sofia Abramova, Associate Professor at the Department of Applied Sociology at UrFU.

The third group of fears is based on changes in the way and pace of life, ways of interaction. Thus, 28.4% of respondents indicate a constant lack of time, the acceleration of communications, and worries about not being able to complete all tasks in time. Respondents are also concerned about the growth of online communications and communications with electronic systems (bots, autoresponders, product systems, etc.).

“As a result, 15.3% of young people raise problems related to increasing social distrust against the background of increasing dependence of human life and health on other people and electronic systems: in public transport, planes, elevators, medical intervention,” explains Sofia Abramova.

Respondents also fear the negative consequences of technological development. For example, 22.2% of young citizens fear the robotization of labor processes and the displacement of humans by robots. 14.6% speak directly about negative emotions in relation to the expansion of artificial intelligence.

The fifth type of fear is social inequality. Young people negatively assess the growth of inequality in access to information resources and technology, the exclusion of citizens from the economy depending on the level of digital competence and education, and age. As a result, they fear that benefits will be distributed more and more unequally, both among the inhabitants of the country and between countries.

“It is noteworthy that young people are simultaneously afraid of total surveillance via phone and afraid of being left without mobile devices. Fears shape the irrational behavior of the digital generation, entailing serious transformations in everyday life,” says Natalia Antonova.

Journal reference:

Abramova, S.B., et al. (2022) Digital Fears Experienced by Young People in the Age of Technoscience. Changing Societies & Personalities.

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Study demonstrates increased incidence of SARS-CoV-2 Omicron breakthrough infection in cancer patients

Jacob Scott



In a recently published article in the journal Cancer Cell, scientists have demonstrated the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in cancer patients residing in Austria and Italy. The study reveals an induction in Omicron breakthrough infections in patients with hematologic and solid cancers.

Study: Enhanced SARS-CoV-2 breakthrough infections in patients with hematologic and solid cancers due to Omicron. Image Credit: Lightspring/Shutterstock


Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019 (COVID-19) pandemic, has been found to cause severe infections in immunocompromised patients, including cancer patients. Moreover, a relatively lower level of neutralizing antibodies in response to COVID-19 vaccines has also been observed in cancer patients, especially those receiving B cell-targeting therapies.

The emergence of SARS-CoV-2 variants with improved immune fitness, such as delta and Omicron variants, has caused a sharp increase in breakthrough infections even in fully vaccinated individuals. However, the vaccines still show high protective efficacy against severe and fatal infections. COVID-19 vaccines have shown acceptable efficacy against severe disease, even in Omicron-infected cancer patients. However, the isolation and quarantine measures associated with SARS-CoV-2 infection may impair the routine administration of anticancer therapy, which can reduce the survival prognosis in cancer patients.

In the current study, the scientists have assessed the incidence of SARS-CoV-2 infection in cancer patients throughout the pandemic.

Study design

The study included 3,959 cancer patients, of whom 77% had solid cancer, and 23% had hematologic cancer. About 69% of the patients did not receive any anticancer treatment at the time of COVID-19 vaccination. Regarding vaccine coverage, about 85% of the patients had received at least one vaccine dose, and 15% remained unvaccinated. The incidence of SARS-CoV-2 infection in these patients was assessed between February 2020 and 2022.

Important observations

SARS-CoV-2 infection was detected in about 24% of the patients during the study period. During the delta-dominated wave, vaccine breakthrough infection was observed in 43% of the patients. In contrast, a significantly higher percentage of breakthrough infection (70%) was observed among the patients during the Omicron-dominated wave. During both delta and Omicron waves, cancer patients receiving systemic anticancer treatment showed a significantly higher percentage of breakthrough infection than those not receiving treatment (83% vs. 56%).

Regarding disease severity irrespective of vaccination status, a higher frequency of COVID-19-related hospitalization was observed during the delta wave compared to that during the Omicron wave. However, a relatively shorter duration of hospital stay was observed in vaccinated patients compared to that in unvaccinated patients. In addition, only 9% of patients with breakthrough infections were admitted to the intensive care unit (ICU). This highlights the protective efficacy of COVID-19 vaccines against severe disease.

Humoral immune response to vaccination

To determine vaccine-induced antibody response against delta and Omicron variants, the scientists measured blood levels of anti-delta and anti-Omicron spike receptor-binding domain (RBD) antibodies in a total of 78 cancer patients. In the analysis, they also included 25 healthcare workers as controls.

In response to vaccination, healthcare workers showed higher levels of total anti-spike antibodies compared to cancer patients. The lowest level of wildtype RBD-specific antibodies was observed in hematologic cancer patients receiving B cell-targeted treatment, followed by hematologic cancer patients not receiving B cell-targeted treatment and patients with solid tumors. A similar trend was observed for delta- and Omicron-specific spike RBD antibodies.

The serum samples collected from hematologic cancer patients without B cell-targeted treatment and solid tumor patients significantly inhibited the interaction between wildtype/delta RBD and angiotensin-converting enzyme 2 (ACE2; host cell receptor for viral entry). However, a significantly lower level of inhibition was observed for patients receiving B cell-targeted treatment. Importantly, a marked reduction in inhibition of Omicron RBD – ACE2 interaction was observed for all patients with solid tumors and hematologic cancer.

Study significance

The study demonstrates an increased incidence of vaccine breakthrough infections but a reduced disease severity among patients with solid tumors and hematologic cancer during the Omicron wave compared to the delta wave.

The study also highlights that COVID-19 vaccine-induced antibody response is lower in cancer patients than in healthy individuals. The reduction in antibody response is highest among hematologic patients receiving B cell-targeted treatment. Overall, a significant impairment in vaccine-induced Omicron neutralization has been observed in cancer patients.

Journal reference:
Mair, M. et al. (2022) “Enhanced SARS-CoV-2 breakthrough infections in patients with hematologic and solid cancers due to Omicron”, Cancer Cell. doi: 10.1016/j.ccell.2022.04.003.

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