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Autonomous genome annotation of SARS-CoV-2 genes, proteins and domains

Jacob Scott

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As one of the twenty-first century’s most significant global health issues, the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has indeed altered our lives. Unlike earlier pandemics, however, we now have high-throughput sequencing capabilities to investigate the genome composition of SARS-CoV-2. In addition, we can track and define the viral genome evolution for near real-time surveillance as labs around the world sequence isolates from infected individuals.


VAPiD, Prokka, InterProScan, and other viral genome annotation technologies, for example, attempt to offer autonomous annotation of genes and proteins.


Special releases of some of these tools have been made to aid in the annotation of SARS-CoV-2 genomes. However, many of these methods are designed for more general uses, do not provide sufficient accuracy with “off the shelf” SARS-CoV-2 use, and have not yet been deployed at scale as the amount of SARS-CoV-2 sequence data grows.


Several SARS-CoV-2 genome variants have also been developed, including the D614G variant, which first appeared earlier in the pandemic, and the more recent B.1.1.7 (Alpha) or B.1.617.2 (Delta) variants, which account for the bulk of new cases in the United States and around the world. Unfortunately, the mutations that define these variants can make comprehensive genome annotation difficult, and the SARS-CoV-2 transcriptional slippage site can make things even more difficult.


In a new research paper, a group of scientists from various institutions offers a semi-supervised custom pipeline for annotating all SARS-CoV-2 genes, proteins, and functional domains. These sequences serve as the molecular targets for better diagnostics, antivirals, and vaccinations. This semi-supervised technique was used to analyze 66,905 SARS-CoV-2 genomes from the NCBI GenBank and GISAID databases. The IBM Functional Genomics Platform, a technology made publicly available to the COVID-19 worldwide research community, revealed almost 13 million unique molecular sequences and linkages as a result of this method.


This study is available in the journal Viruses.


Study: Semi-Supervised Pipeline for Autonomous Annotation of SARS-CoV-2 Genomes. Image Credit: NIAID


The study


A COVID-19 genome annotation pipeline must reliably identify all known molecular targets inside a genome to be clinically and biologically useful. The SARS-CoV-2 proteome consists of thirteen protein products, each with a corresponding gene sequence in each genome. SARS-CoV-2 proteins are classified as structural or non-structural, but all are essential for the virus’s life cycle, which involves host cell invasion, replication, and transmission.



Pipeline schematic for semi-supervised identification of molecular targets. The data and analytic steps comprising our SARS-CoV-2 annotation pipeline described in Methods Sections 2.1-2.3 are indicated. Input data are indicated with a dashed line and discarded data, e.g., genomes below quality thresholds, are indicated with a red line. Blue boxes indicate steps where our augmentation of base Prokka and Prodigal yield methodological advancements specific to the requirements of SARS-CoV-2 genomes.

Across all genomes over the aforementioned quality levels, the authors achieved an average per protein identification accuracy of 98.5 +- 2.9% using their gene and protein annotation method. The researchers were able to attain entire or near-complete protein set membership for all genomes based on the number of observations per protein. Because each protein is a translated gene sequence, the same level of gene identification precision is attained.


Furthermore, for accurate genome annotation, not only must the entire set of designated genes and proteins be identified, but the created sequences must also be based on biological reality. Given the relatively recent development of SARS-CoV-2 and documented lower mutation rate than other RNA viruses, in silico projected sequences should not be trimmed compared to the length of known references, and mutational density must be low.


The authors were able to identify full-length protein products that, on a per protein basis, match the expected lengths of known reference sequences with an average observed/expected protein length value of 99.1% using the semi-supervised gene and protein annotation method. Furthermore, by using a two-sample Kolmogorov-Smirnov test, the distributions of the projected and anticipated protein sequence lengths are found to be statistically similar. They are 8.75-fold more similar than those predicted from genomes that do not meet the quality requirements, i.e., poor quality genomes.


The method utilized in this study was able to identify 6.4-fold more protein products compared to base Prokka and was able to generate full-length pp1ab products with high sequence identity to known UniProt references.


The authors compared their pipeline to VAPiD, which generated a specific release for annotating SARS-CoV-2 genomic data, and Prokka, a prokaryotic genome annotation tool for bacteria and viruses, in terms of pipeline accuracy. The obtained protein annotations in terms of set membership, as well as observed protein sequence length versus reference protein sequence length, were examined using the same collection of genomes.


Both VAPiD and the author’s technique obtained good accuracy in truncated proteins, but the pipeline elicited 1.8-fold more proteins in the highest accuracy category and 1.8-fold more protein annotations overall. The open reading frame (ORF) 9b and Protein 3a were consistently absent from VAPiD annotations. Prokka, on the other hand, yielded no full-length pp1ab protein sequences and produced a large number of missing or truncated proteins, particularly for Envelope small membrane protein, ORF9b, and ORF10, among other proteins.


Implications


This approach can be used to monitor and track developing protein variations across hosts swiftly and sampling niches, such as aerosol, wastewater, and surfaces, to inform disease understanding, vaccine specificity, and host protein binding affinity as vaccination rates grow, and the pandemic persists.


Furthermore, future studies will refine the protein sequences and important domains to increase the understanding of interactions with host proteins, antivirals, or diagnostics by utilizing a structural model to corroborate the in silico predicted sequences. Overall, the data obtained as part of this project give a comprehensive database of protein and domain variants observed around the world, which will aid researchers in their efforts to understand and contain the COVID-19 pandemic.

Journal reference:
Semi-Supervised Pipeline for Autonomous Annotation of SARS-CoV-2 Genomes, Kristen L. Beck, Edward Seabolt, Akshay Agarwal, Gowri Nayar, Simone Bianco, Harsha Krishnareddy, Timothy A. Ngo, Mark Kunitomi, Vandana Mukherjee and James H. Kaufman, MDPI, 2021.12.03, https://doi.org/10.3390/v13122426, https://www.mdpi.com/1999-4915/13/12/2426

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Unraveling How Strigoractone Hormone Regulates Massive Gene Networks Controlling Plant Growth

Jacob Scott

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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.

Source:
Journal reference:

Tal, L., et al. (2022) A conformational switch in the SCF-D3/MAX2 ubiquitin ligase facilitates strigolactone signalling. Nature Plants. doi.org/10.1038/s41477-022-01145-7.

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UrFU Sociologists Identify Digital Fears Among Young People

Jacob Scott

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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.

Source:
Journal reference:

Abramova, S.B., et al. (2022) Digital Fears Experienced by Young People in the Age of Technoscience. Changing Societies & Personalities. doi.org/10.15826/csp.2022.6.1.163.

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

Jacob Scott

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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

Background

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. https://www.cell.com/cancer-cell/fulltext/S1535-6108(22)00165-9

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