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Archive for the ‘mRNA Therapeutics’ Category


2021 Virtual World Medical Innovation Forum, Mass General Brigham, Gene and Cell Therapy, VIRTUAL May 19–21, 2021

 

The 2021 Virtual World Medical Innovation Forum will focus on the growing impact of gene and cell therapy.
Senior healthcare leaders from all over look to shape and debate the area of gene and cell therapy. Our shared belief: no matter the magnitude of change, responsible healthcare is centered on a shared commitment to collaborative innovation–industry, academia, and practitioners working together to improve patients’ lives.

https://worldmedicalinnovation.org/agenda/

Virtual | May 19–21, 2021

 

 

Leaders in Pharmaceutical Business Intelligence (LPBI) Group

will cover the event in Real Time

 

Aviva Lev-Ari, PhD, RN

Founder LPBI 1.0 & LPBI 2.0

will be in attendance producing the e-Proceedings

and the Tweet Collection of this Global event expecting +15,000 attendees

 

 

LPBI’s Eighteen Books in Medicine

https://lnkd.in/ekWGNqA

Among them, books on Gene and Cell Therapy include the following:

 

 

Topics

The 2021 Forum will be held virtually and focus on gene and cell therapy.

AAV | Ophthalmology, Otology and Neurology

Gene Therapy | Oncolytic Viruses

CAR- T | Cellular Therapies

Stem Cells | Neurodegenerative Diseases, Regenerative Medicine

GCT | Infectious Disease, Hematology and Diabetes

Gene Editing | RNA Technologies

GCT Manufacturing | Supply Chain

Equity and Access | Emerging GCT Environment

GCT Investor Priorities

Putting GCT to Work | Payers, Providers | Regulatory

*Our agenda is currently under formation and is subject to change. Please continue checking for a more up to date agenda.

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Inhibitory CD161 receptor recognized as a potential immunotherapy target in glioma-infiltrating T cells by single-cell analysis

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

 

Brain tumors, especially the diffused Gliomas are of the most devastating forms of cancer and have so-far been resistant to immunotherapy. It is comprehended that T cells can penetrate the glioma cells, but it still remains unknown why infiltrating cells miscarry to mount a resistant reaction or stop the tumor development.

Gliomas are brain tumors that begin from neuroglial begetter cells. The conventional therapeutic methods including, surgery, chemotherapy, and radiotherapy, have accomplished restricted changes inside glioma patients. Immunotherapy, a compliance in cancer treatment, has introduced a promising strategy with the capacity to penetrate the blood-brain barrier. This has been recognized since the spearheading revelation of lymphatics within the central nervous system. Glioma is not generally carcinogenic. As observed in a number of cases, the tumor cells viably reproduce and assault the adjoining tissues, by and large, gliomas are malignant in nature and tend to metastasize. There are four grades in glioma, and each grade has distinctive cell features and different treatment strategies. Glioblastoma is a grade IV glioma, which is the crucial aggravated form. This infers that all glioblastomas are gliomas, however, not all gliomas are glioblastomas.

Decades of investigations on infiltrating gliomas still take off vital questions with respect to the etiology, cellular lineage, and function of various cell types inside glial malignancies. In spite of the available treatment options such as surgical resection, radiotherapy, and chemotherapy, the average survival rate for high-grade glioma patients remains 1–3 years (1).

A recent in vitro study performed by the researchers of Dana-Farber Cancer Institute, Massachusetts General Hospital, and the Broad Institute of MIT and Harvard, USA, has recognized that CD161 is identified as a potential new target for immunotherapy of malignant brain tumors. The scientific team depicted their work in the Cell Journal, in a paper entitled, “Inhibitory CD161 receptor recognized in glioma-infiltrating T cells by single-cell analysis.” on 15th February 2021.

To further expand their research and findings, Dr. Kai Wucherpfennig, MD, PhD, Chief of the Center for Cancer Immunotherapy, at Dana-Farber stated that their research is additionally important in a number of other major human cancer types such as 

  • melanoma,
  • lung,
  • colon, and
  • liver cancer.

Dr. Wucherpfennig has praised the other authors of the report Mario Suva, MD, PhD, of Massachusetts Common Clinic; Aviv Regev, PhD, of the Klarman Cell Observatory at Broad Institute of MIT and Harvard, and David Reardon, MD, clinical executive of the Center for Neuro-Oncology at Dana-Farber.

Hence, this new study elaborates the effectiveness of the potential effectors of anti-tumor immunity in subsets of T cells that co-express cytotoxic programs and several natural killer (NK) cell genes.

The Study-

IMAGE SOURCE: Experimental Strategy (Mathewson et al., 2021)

 

The group utilized single-cell RNA sequencing (RNA-seq) to mull over gene expression and the clonal picture of tumor-infiltrating T cells. It involved the participation of 31 patients suffering from diffused gliomas and glioblastoma. Their work illustrated that the ligand molecule CLEC2D activates CD161, which is an immune cell surface receptor that restrains the development of cancer combating activity of immune T cells and tumor cells in the brain. The study reveals that the activation of CD161 weakens the T cell response against tumor cells.

Based on the study, the facts suggest that the analysis of clonally expanded tumor-infiltrating T cells further identifies the NK gene KLRB1 that codes for CD161 as a candidate inhibitory receptor. This was followed by the use of 

  • CRISPR/Cas9 gene-editing technology to inactivate the KLRB1 gene in T cells and showed that CD161 inhibits the tumor cell-killing function of T cells. Accordingly,
  • genetic inactivation of KLRB1 or
  • antibody-mediated CD161 blockade

enhances T cell-mediated killing of glioma cells in vitro and their anti-tumor function in vivo. KLRB1 and its associated transcriptional program are also expressed by substantial T cell populations in other forms of human cancers. The work provides an atlas of T cells in gliomas and highlights CD161 and other NK cell receptors as immune checkpoint targets.

Further, it has been identified that many cancer patients are being treated with immunotherapy drugs that disable their “immune checkpoints” and their molecular brakes are exploited by the cancer cells to suppress the body’s defensive response induced by T cells against tumors. Disabling these checkpoints lead the immune system to attack the cancer cells. One of the most frequently targeted checkpoints is PD-1. However, recent trials of drugs that target PD-1 in glioblastomas have failed to benefit the patients.

In the current study, the researchers found that fewer T cells from gliomas contained PD-1 than CD161. As a result, they said, “CD161 may represent an attractive target, as it is a cell surface molecule expressed by both CD8 and CD4 T cell subsets [the two types of T cells engaged in response against tumor cells] and a larger fraction of T cells express CD161 than the PD-1 protein.”

However, potential side effects of antibody-mediated blockade of the CLEC2D-CD161 pathway remain unknown and will need to be examined in a non-human primate model. The group hopes to use this finding in their future work by

utilizing their outline by expression of KLRB1 gene in tumor-infiltrating T cells in diffuse gliomas to make a remarkable contribution in therapeutics related to immunosuppression in brain tumors along with four other common human cancers ( Viz. melanoma, non-small cell lung cancer (NSCLC), hepatocellular carcinoma, and colorectal cancer) and how this may be manipulated for prevalent survival of the patients.

References

(1) Anders I. Persson, QiWen Fan, Joanna J. Phillips, William A. Weiss, 39 – Glioma, Editor(s): Sid Gilman, Neurobiology of Disease, Academic Press, 2007, Pages 433-444, ISBN 9780120885923, https://doi.org/10.1016/B978-012088592-3/50041-4.

Main Source

Mathewson ND, Ashenberg O, Tirosh I, Gritsch S, Perez EM, Marx S, et al. 2021. Inhibitory CD161 receptor identified in glioma-infiltrating T cells by single-cell analysis. Cell.https://www.cell.com/cell/fulltext/S0092-8674(21)00065-9?elqTrackId=c3dd8ff1d51f4aea87edd0153b4f2dc7

Related Articles

VIDEOS on Cancer Biology, Cancer Genetics, Cancer Immunotherapy

19th Annual Koch Institute Summer Symposium on Cancer Immunotherapy, June 12, 2020 at MIT’s Kresge Auditorium

 

Other related articles published in this Open Access Online Scientific Journal include the following:

 

Single Cell Sequencing:

Part 4.1 in Genomics Volume 2

Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology 

On Amazon.com since 12/28/2019

https://www.amazon.com/dp/B08385KF87

 

4.1.3   Single-cell Genomics: Directions in Computational and Systems Biology – Contributions of Prof. Aviv Regev @Broad Institute of MIT and Harvard, Cochair, the Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/09/03/single-cell-genomics-directions-in-computational-and-systems-biology-contributions-of-ms-aviv-regev-phd-broad-institute-of-mit-and-harvard-cochair-the-human-cell-atlas-organizing-committee-wit/

 

4.1.4   Cellular Genetics

https://www.sanger.ac.uk/science/programmes/cellular-genetics

 

4.1.5   Cellular Genomics

https://www.garvan.org.au/research/cellular-genomics

 

4.1.6   SINGLE CELL GENOMICS 2019 – sometimes the sum of the parts is greater than the whole, September 24-26, 2019, Djurönäset, Stockholm, Sweden http://www.weizmann.ac.il/conferences/SCG2019/single-cell-genomics-2019

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2019/05/29/single-cell-genomics-2019-september-24-26-2019-djuronaset-stockholm-sweden/

 

4.1.7   Norwich Single-Cell Symposium 2019, Earlham Institute, single-cell genomics technologies and their application in microbial, plant, animal and human health and disease, October 16-17, 2019, 10AM-5PM

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2019/06/04/norwich-single-cell-symposium-2019-earlham-institute-single-cell-genomics-technologies-and-their-application-in-microbial-plant-animal-and-human-health-and-disease-october-16-17-2019-10am-5pm/

 

4.1.8   Newly Found Functions of B Cell

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2019/05/23/newly-found-functions-of-b-cell/

 

4.1.9 RESEARCH HIGHLIGHTS: HUMAN CELL ATLAS

https://www.broadinstitute.org/research-highlights-human-cell-atlas

 

CRISPR – 200 articles in the Journal

 

Chapter 21 in Genomics Volume 1

Genomics Orientations for Personalized Medicine. On Amazon.com since 11/23/2015

http://www.amazon.com/dp/B018DHBUO6

 

Glioblastoma – 150 articles in the Journal

Most recent

 

Immunotherapy may help in glioblastoma survival

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2019/03/16/immunotherapy-may-help-in-glioblastoma-survival/

 

New Treatment in Development for Glioblastoma: Hopes for Sen. John McCain

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/25/new-treatment-in-development-for-glioblastoma-hopes-for-sen-john-mccain/

 

Funding Oncorus’s Immunotherapy Platform: Next-generation Oncolytic Herpes Simplex Virus (oHSV) for Brain Cancer, Glioblastoma Multiforme (GBM)

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/12/28/funding-oncoruss-immunotherapy-platform-next-generation-oncolytic-herpes-simplex-virus-ohsv-for-brain-cancer-glioblastoma-multiforme-gbm/

 

Glioma, Glioblastoma and Neurooncology

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2015/10/19/glioma-glioblastoma-and-neurooncology/

 

Positron Emission Tomography (PET) and Near-Infrared Fluorescence Imaging:  Noninvasive Imaging of Cancer Stem Cells (CSCs)  monitoring of AC133+ glioblastoma in subcutaneous and intracerebral xenograft tumors

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/01/29/positron-emission-tomography-pet-and-near-infrared-fluorescence-imaging-noninvasive-imaging-of-cancer-stem-cells-cscs-monitoring-of-ac133-glioblastoma-in-subcutaneous-and-intracerebral-xenogra/

 

Gamma Linolenic Acid (GLA) as a Therapeutic tool in the Management of Glioblastoma

Eric Fine* (1), Mike Briggs* (1,2), Raphael Nir# (1,2,3)

https://pharmaceuticalintelligence.com/2013/07/15/gamma-linolenic-acid-gla-as-a-therapeutic-tool-in-the-management-of-glioblastoma/

 

 

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Dysregulation of ncRNAs in association with Neurodegenerative Disorders

Curator: Amandeep Kaur

Research over the years has added evidences to the hypothesis of “RNA world” which explains the evolution of DNA and protein from a simple RNA molecule. Our understanding of RNA biology has dramatically changed over the last 50 years and rendered the scientists with the conclusion that apart from coding for protein synthesis, RNA also plays an important role in regulation of gene expression.

Figure: Overall Taxonomy of ncRNAs
Figure: Overall Taxonomy of ncRNAs
https://www.nature.com/articles/s42256-019-0051-2

The universe of non-coding RNAs (ncRNAs) is transcending the margins of preconception and altered the traditional thought that the coding RNAs or messenger RNAs (mRNAs) are more prevalent in our cells. Research on the potential use of ncRNAs in therapeutic relevance increased greatly after the discovery of RNA interference (RNAi) and provided important insights into our further understanding of etiology of complex disorders.

Figure: Atomic Structure of Non-coding RNA
https://en.wikipedia.org/wiki/Non-coding_RNA

Latest research on neurodegenerative disorders has shown the perturbed expression of ncRNAs which provides the functional association between neurodegeneration and ncRNAs dysfunction. Due to the diversity of functions and abundance of ncRNAs, they are classified into Housekeeping RNAs and Regulatory ncRNAs.

The best known classes of ncRNAs are the microRNAs (miRNAs) which are extensively studied and are of research focus. miRNAs are present in both intronic and exonic regions of matured RNA (mRNA) and are crucial for development of CNS. The reduction of Dicer-1, a miRNA biogenesis-related protein affects neural development and the elimination of Dicer in specifically dopaminergic neurons causes progressive degeneration of these neuronal cells in striatum of mice.

A new class of regulatory ncRNAs, tRNAs-derived fragments (tRFs) is superabundantly present in brain cells. tRFs are considered as risk factors in conditions of neural degeneration because of accumulation with aging. tRFs have heterogenous functions with regulation of gene expression at multiple layers including regulation of mRNA processing and translation, inducing the activity of silencing of target genes, controlling cell growth and differentiation processes.

The existence of long non-coding RNAs (lncRNAs) was comfirmed by the ENCODE project. Numerous studies reported that approximately 40% of lncRNAs are involved in gene expression, imprinting and pluripotency regulation in the CNS. lncRNA H19 is of paramount significance in neural viability and contribute in epilepsy condition by activating glial cells. Other lncRNAs are highly bountiful in neurons including Evf2 and MALAT1 which play important function in regulating neural differentiation and synapse formation and development of dendritic cells respectively.

Recently, a review article in Nature mentioned about the complex mechanisms of ncRNAs contributing to neurodegenerative conditions. The ncRNA-mediated mechanisms of regulation are as follows:

  • Epigenetic regulation: Various lncRNAs such as BDNF-AS, TUG1, MEG3, NEAT1 and TUNA are differentially expressed in brain tissue and act as epigenetic regulators.
  • RNAi: RNA interference includes post-transcriptional repression by small-interfering RNAs (siRNAs) and binding of miRNAs to target genes. In a wide spectrum of neurodegenerative diseases such as Alzheimer’s disease, Parkinson disease, Huntington’s disease, Amyotrophic lateral sclerosis, Fragile X syndrome, Frontotemporal dementia, and Spinocerebellar ataxia, have shown perturbed expression of miRNA.
  • Alternative splicing: Variation in splicing of transcripts of ncRNAs has shown adverse affects in neuropathology of degenerative diseases.
  • mRNA stability: The stability of mRNA may be affected by RNA-RNA duplex formation which leads to the degradation of sense mRNA or blocking the access to proteins involved in RNA turnover and modify the progression of neurodegenerative disorders.
  • Translational regulation: Numerous ncRNAs including BC200 directly control the translational process of transcripts of mRNAs and effect human brain of Alzheimer’s disease.
  • Molecular decoys: Non-coding RNAs (ncRNAs) dilute the expression of other RNAs by molecular trapping, also known as competing endogenous RNAs (ceRNAs) which hinder the normal functioning of RNAs. The ceRNAs proportion must be equivalent to the number of target miRNAs that can be sequestered by each ncRNAs in order to induce consequential de-repression of the target molecules.
Table: ncRNAs and related processes involved in neurodegenerative disorders
https://www.nature.com/articles/nrn.2017.90

The unknown functions of numerous annotated ncRNAs may explain the underlying complexity in neurodegenerative disorders. The profiling of ncRNAs of patients suffering from neurodevelopmental and neurodegenerative conditions are required to outline the changes in ncRNAs and their role in specific regions of brain and cells. Analysis of Large-scale gene expression and functional studies of ncRNAs may contribute to our understanding of these diseases and their remarkable connections. Therefore, targeting ncRNAs may provide effective therapeutic perspective for the treatment of neurodegenerative diseases.

References https://www.nature.com/scitable/topicpage/rna-functions-352/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6035743/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695195/ https://link.springer.com/article/10.1007/s13670-012-0023-4 https://www.nature.com/articles/nrn.2017.90

 

Other related articles were published in this Open Access Online Scientific Journal, including the following:

RNA in synthetic biology

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/03/26/rna-in-synthetic-biology/

mRNA Data Survival Analysis

Curators: Larry H. Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/06/18/mrna-data-survival-analysis/

Recent progress in neurodegenerative diseases and gliomas

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/05/28/recent-progress-in-neurodegenerative-diseases-and-gliomas/

Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious Depression

Reporter and writer: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/02/19/genomic-promise-for-neurodegenerative-diseases-dementias-autism-spectrum-schizophrenia-and-serious-depression/

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Nanoparticles can turn off genes in bone marrow cells

Reporter : Irina Robu, PhD

MIT engineers developed an alternative to turn off specific genes which play a vital role in producing blood cells of the bone marrow using specialized nanoparticles. These nanoparticles can be made-to-order to treat heart disease or increase the yield of stem cells in patience who need stem cell transplants. The particles are coated with lipids that help stabilize them, and they can target organs such as the lungs, heart, and spleen, depending on the particles’ composition and molecular weight. This genetic therapy, also known as RNA interference is difficult to target organs other than the liver, where most of the nanoparticles tend to collect.

RNA interference is an approach that could theoretically be used to treat a variety of diseases by delivering short strands of RNA that block specific genes from being turned on in a cell. Yet, the main obstacle to this kind of therapy has been  delivering it to the right part of the body. When injected into the bloodstream, nanoparticles carrying RNA tend to accrue in the liver, which various biotech companies have taken advantage of to develop new experimental treatments for liver disease.

In their recent study, scientists set out to adapt the nanoparticles so that they could reach the bone marrow which contains stem cells that produce different types of blood cells. Stimulating the process , they could enhance the yield of hematopoietic stem cells for stem cell transplantation and they created variants that have different arrangements of surface coating, polyethylene glycol. They were able to test 15 particles and determined one that was able to avoid being caught in the liver or the lungs, and that could effectively accumulate in endothelial cells of the bone marrow. They also showed that RNA carried by this particle could reduce the expression of a target gene by up to 80 percent.

The scientists then tested this approach with two genes. The first gene, SDF1 is a molecule that normally prevents hematopoietic stem cells from leaving the bone marrow. They realized that turning off the SDF1 gene could have the same effect as the drugs that are being used to induce hematopoietic stem cell release in patients who need undergo radiation treatments for blood cancers. These stem cells are later transplanted to repopulate the patient’s blood cells. By knocking down SDF1, they could boost the release of hematopoietic cells fivefold which is comparable to the levels achieved by the drugs that are now used to enhance stem cell release.

The second gene researchers use is MCP1, a molecule that plays a key role in heart disease.  They realized that when MCP1 is released by bone marrow cells after a heart attack, it stimulates a flood of immune cells to leave the bone marrow and travel to the heart. Researchers realize that by delivering RNA that targets MCP1 reduced the number of immune cells that went to the heart after a heart attack.

Using these new particles, researchers hypothesized that they could further develop treatments for heart disease and other conditions.

SOURCE

https://news.mit.edu/2020/nanoparticles-bone-marrow-rnai-1005

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RNA from the SARS-CoV-2 virus taking over the cells it infects: Virulence – Pathogen’s ability to infect a Resistant Host: The Imbalance between Controlling Virus Replication versus Activation of the Adaptive Immune Response

Curator: Aviva Lev-Ari, PhD, RN – I added colors and bold face

 

UPDATED on 9/8/2020

What bats can teach us about developing immunity to Covid-19 | Free to read

Clive Cookson, Anna Gross and Ian Bott, London

https://www.ft.com/content/743ce7a0-60eb-482d-b1f4-d4de11182fa9?utm_source=Nature+Briefing&utm_campaign=af64422080-briefing-dy-20200908&utm_medium=email&utm_term=0_c9dfd39373-af64422080-43323101

 

UPDATED on 6/29/2020

Another duality and paradox in the Treatment of COVID-19 Patients in ICUs was expressed by Mike Yoffe, MD, PhD, David H. Koch Professor of Biology and Biological Engineering, Massachusetts Institute of Technology. Dr. Yaffe has a joint appointment in Acute Care Surgery, Trauma, and Surgical Critical Care, and in Surgical Oncology @BIDMC

on 6/29 at SOLUTIONS with/in/sight at Koch Institute @MIT

How Are Cancer Researchers Fighting COVID-19? (Part II)” Jun 29, 2020 11:30 AM EST

Mike Yoffe, MD, PhD 

In COVID-19 patients: two life threatening conditions are seen in ICUs:

  • Blood Clotting – Hypercoagulability or Thrombophilia
  • Cytokine Storm – immuno-inflammatory response
  • The coexistence of 1 and 2 – HINDERS the ability to use effectively tPA as an anti-clotting agent while the cytokine storm is present.

Mike Yoffe’s related domain of expertise:

Signaling pathways and networks that control cytokine responses and inflammation

Misregulation of cytokine feedback loops, along with inappropriate activation of the blood clotting cascade causes dysregulation of cell signaling pathways in innate immune cells (neutrophils and macrophages), resulting in tissue damage and multiple organ failure following trauma or sepsis. Our research is focused on understanding the role of the p38-MK2 pathway in cytokine control and innate immune function, and on cross-talk between cytokines, clotting factors, and neutrophil NADPH oxidase-derived ROS in tissue damage, coagulopathy, and inflammation, using biochemistry, cell biology, and mouse knock-out/knock-in models.  We recently discovered a particularly important link between abnormal blood clotting and the complement pathway cytokine C5a which causes excessive production of extracellular ROS and organ damage by neutrophils after traumatic injury.

SOURCE

https://www.bidmc.org/research/research-by-department/surgery/acute-care-surgery-trauma-and-surgical-critical-care/michael-b-yaffe

 

See

The Genome Structure of CORONAVIRUS, SARS-CoV-2

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/05/04/the-genome-structure-of-coronavirus-sars-cov-2-i-awaited-for-this-article-for-60-days/

 

Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19

Open Access Published:May 15, 2020DOI:https://doi.org/10.1016/j.cell.2020.04.026

Highlights

  • SARS-CoV-2 infection induces low IFN-I and -III levels with a moderate ISG response
  • Strong chemokine expression is consistent across in vitroex vivo, and in vivo models
  • Low innate antiviral defenses and high pro-inflammatory cues contribute to COVID-19

Summary

Viral pandemics, such as the one caused by SARS-CoV-2, pose an imminent threat to humanity. Because of its recent emergence, there is a paucity of information regarding viral behavior and host response following SARS-CoV-2 infection. Here we offer an in-depth analysis of the transcriptional response to SARS-CoV-2 compared with other respiratory viruses. Cell and animal models of SARS-CoV-2 infection, in addition to transcriptional and serum profiling of COVID-19 patients, consistently revealed a unique and inappropriate inflammatory response. This response is defined by low levels of type I and III interferons juxtaposed to elevated chemokines and high expression of IL-6. We propose that reduced innate antiviral defenses coupled with exuberant inflammatory cytokine production are the defining and driving features of COVID-19.

Graphical Abstract

Keywords

Results

Defining the Transcriptional Response to SARS-CoV-2 Relative to Other Respiratory Viruses

To compare the transcriptional response of SARS-CoV-2 with other respiratory viruses, including MERS-CoV, SARS-CoV-1, human parainfluenza virus 3 (HPIV3), respiratory syncytial virus (RSV), and IAV, we first chose to focus on infection in a variety of respiratory cell lines (Figure 1). To this end, we collected poly(A) RNA from infected cells and performed RNA sequencing (RNA-seq) to estimate viral load. These data show that virus infection levels ranged from 0.1% to more than 50% of total RNA reads (Figure 1A).

Discussion

In the present study, we focus on defining the host response to SARS-CoV-2 and other human respiratory viruses in cell lines, primary cell cultures, ferrets, and COVID-19 patients. In general, our data show that the overall transcriptional footprint of SARS-CoV-2 infection was distinct in comparison with other highly pathogenic coronaviruses and common respiratory viruses such as IAV, HPIV3, and RSV. It is noteworthy that, despite a reduced IFN-I and -III response to SARS-CoV-2, we observed a consistent chemokine signature. One exception to this observation is the response to high-MOI infection in A549-ACE2 and Calu-3 cells, where replication was robust and an IFN-I and -III signature could be observed. In both of these examples, cells were infected at a rate to theoretically deliver two functional virions per cell in addition to any defective interfering particles within the virus stock that were not accounted for by plaque assays. Under these conditions, the threshold for PAMP may be achieved prior to the ability of the virus to evade detection through production of a viral antagonist. Alternatively, addition of multiple genomes to a single cell may disrupt the stoichiometry of viral components, which, in turn, may itself generate PAMPs that would not form otherwise. These ideas are supported by the fact that, at a low-MOI infection in A549-ACE2 cells, high levels of replication could also be achieved, but in the absence of IFN-I and -III induction. Taken together, these data suggest that, at low MOIs, the virus is not a strong inducer of the IFN-I and -III system, as opposed to conditions where the MOI is high.
Taken together, the data presented here suggest that the response to SARS-CoV-2 is imbalanced with regard to controlling virus replication versus activation of the adaptive immune response. Given this dynamic, treatments for COVID-19 have less to do with the IFN response and more to do with controlling inflammation. Because our data suggest that numerous chemokines and ILs are elevated in COVID-19 patients, future efforts should focus on U.S. Food and Drug Administration (FDA)-approved drugs that can be rapidly deployed and have immunomodulating properties.

SOURCE

https://www.cell.com/cell/fulltext/S0092-8674(20)30489-X

SARS-CoV-2 ORF3b is a potent interferon antagonist whose activity is further increased by a naturally occurring elongation variant

Yoriyuki KonnoIzumi KimuraKeiya UriuMasaya FukushiTakashi IrieYoshio KoyanagiSo NakagawaKei Sato

Abstract

One of the features distinguishing SARS-CoV-2 from its more pathogenic counterpart SARS-CoV is the presence of premature stop codons in its ORF3b gene. Here, we show that SARS-CoV-2 ORF3b is a potent interferon antagonist, suppressing the induction of type I interferon more efficiently than its SARS-CoV ortholog. Phylogenetic analyses and functional assays revealed that SARS-CoV-2-related viruses from bats and pangolins also encode truncated ORF3b gene products with strong anti-interferon activity. Furthermore, analyses of more than 15,000 SARS-CoV-2 sequences identified a natural variant, in which a longer ORF3b reading frame was reconstituted. This variant was isolated from two patients with severe disease and further increased the ability of ORF3b to suppress interferon induction. Thus, our findings not only help to explain the poor interferon response in COVID-19 patients, but also describe a possibility of the emergence of natural SARS-CoV-2 quasi-species with extended ORF3b that may exacerbate COVID-19 symptoms.

Highlights

  • ORF3b of SARS-CoV-2 and related bat and pangolin viruses is a potent IFN antagonist

  • SARS-CoV-2 ORF3b suppresses IFN induction more efficiently than SARS-CoV ortholog

  • The anti-IFN activity of ORF3b depends on the length of its C-terminus

  • An ORF3b with increased IFN antagonism was isolated from two severe COVID-19 cases

Competing Interest Statement

The authors have declared no competing interest.

Paper in collection COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv

 

SOURCE

https://www.biorxiv.org/content/10.1101/2020.05.11.088179v1

 

 

A deep dive into how the new coronavirus infects cells has found that it orchestrates a hostile takeover of their genes unlike any other known viruses do, producing what one leading scientist calls “unique” and “aberrant” changes.Recent studies show that in seizing control of genes in the human cells it invades, the virus changes how segments of DNA are read, doing so in a way that might explain why the elderly are more likely to die of Covid-19 and why antiviral drugs might not only save sick patients’ lives but also prevent severe disease if taken before infection.“It’s something I have never seen in my 20 years of” studying viruses, said virologist Benjamin tenOever of the Icahn School of Medicine at Mount Sinai, referring to how SARS-CoV-2, the virus that causes Covid-19, hijacks cells’ genomes.The “something” he and his colleagues saw is how SARS-CoV-2 blocks one virus-fighting set of genes but allows another set to launch, a pattern never seen with other viruses. Influenza and the original SARS virus (in the early 2000s), for instance, interfere with both arms of the body’s immune response — what tenOever dubs “call to arms” genes and “call for reinforcement” genes.The first group of genes produces interferons. These proteins, which infected cells release, are biological semaphores, signaling to neighboring cells to activate some 500 of their own genes that will slow down the virus’ ability to make millions of copies of itself if it invades them. This lasts seven to 10 days, tenOever said, controlling virus replication and thereby buying time for the second group of genes to act.This second set of genes produce their own secreted proteins, called chemokines, that emit a biochemical “come here!” alarm. When far-flung antibody-making B cells and virus-killing T cells sense the alarm, they race to its source. If all goes well, the first set of genes holds the virus at bay long enough for the lethal professional killers to arrive and start eradicating viruses.

“Most other viruses interfere with some aspect of both the call to arms and the call for reinforcements,” tenOever said. “If they didn’t, no one would ever get a viral illness”: The one-two punch would pummel any incipient infection into submission.

SARS-CoV-2, however, uniquely blocks one cellular defense but activates the other, he and his colleagues reported in a study published last week in Cell. They studied healthy human lung cells growing in lab dishes, ferrets (which the virus infects easily), and lung cells from Covid-19 patients. In all three, they found that within three days of infection, the virus induces cells’ call-for-reinforcement genes to produce cytokines. But it blocks their call-to-arms genes — the interferons that dampen the virus’ replication.

The result is essentially no brakes on the virus’s replication, but a storm of inflammatory molecules in the lungs, which is what tenOever calls an “unique” and “aberrant” consequence of how SARS-CoV-2 manipulates the genome of its target.

In another new study, scientists in Japan last week identified how SARS-CoV-2 accomplishes that genetic manipulation. Its ORF3b gene produces a protein called a transcription factor that has “strong anti-interferon activity,” Kei Sato of the University of Tokyo and colleagues found — stronger than the original SARS virus or influenza viruses. The protein basically blocks the cell from recognizing that a virus is present, in a way that prevents interferon genes from being expressed.

In fact, the Icahn School team found no interferons in the lung cells of Covid-19 patients. Without interferons, tenOever said, “there is nothing to stop the virus from replicating and festering in the lungs forever.”

That causes lung cells to emit even more “call-for-reinforcement” genes, summoning more and more immune cells. Now the lungs have macrophages and neutrophils and other immune cells “everywhere,” tenOever said, causing such runaway inflammation “that you start having inflammation that induces more inflammation.”

At the same time, unchecked viral replication kills lung cells involved in oxygen exchange. “And suddenly you’re in the hospital in severe respiratory distress,” he said.

In elderly people, as well as those with diabetes, heart disease, and other underlying conditions, the call-to-arms part of the immune system is weaker than in younger, healthier people, even before the coronavirus arrives. That reduces even further the cells’ ability to knock down virus replication with interferons, and imbalances the immune system toward the dangerous inflammatory response.

The discovery that SARS-CoV-2 strongly suppresses infected cells’ production of interferons has raised an intriguing possibility: that taking interferons might prevent severe Covid-19 or even prevent it in the first place, said Vineet Menachery of the University of Texas Medical Branch.

In a study of human cells growing in lab dishes, described in a preprint (not peer-reviewed or published in a journal yet), he and his colleagues also found that SARS-CoV-2 “prevents the vast amount” of interferon genes from turning on. But when cells growing in lab dishes received the interferon IFN-1 before exposure to the coronavirus, “the virus has a difficult time replicating.”

After a few days, the amount of virus in infected but interferon-treated cells was 1,000- to 10,000-fold lower than in infected cells not pre-treated with interferon. (The original SARS virus, in contrast, is insensitive to interferon.)

Ending the pandemic and preventing its return is assumed to require an effective vaccine to prevent infectionand antiviral drugs such as remdesivir to treat the very sick, but the genetic studies suggest a third strategy: preventive drugs.

It’s possible that treatment with so-called type-1 interferon “could stop the virus before it could get established,” Menachery said.

Giving drugs to healthy people is always a dicey proposition, since all drugs have side effects — something considered less acceptable than when a drug is used to treat an illness. “Interferon treatment is rife with complications,” Menachery warned. The various interferons, which are prescribed for hepatitis, cancers, and many other diseases, can cause flu-like symptoms.

But the risk-benefit equation might shift, both for individuals and for society, if interferons or antivirals or other medications are shown to reduce the risk of developing serious Covid-19 or even make any infection nearly asymptomatic.

Interferon “would be warning the cells the virus is coming,” Menachery said, so such pretreatment might “allow treated cells to fend off the virus better and limit its spread.” Determining that will of course require clinical trials, which are underway.

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The Genome Structure of CORONAVIRUS, SARS-CoV-2

“I awaited for this article for 60 days”

Aviva Lev-Ari, PhD, RN

Reporter: Aviva Lev-Ari, PhD, RN

 

UPDATED on 8/9/2020

 

The Genome Structure of CORONAVIRUS, SARS-CoV-2

Note:

  • The four letters of DNA are A, C, G and T.
  • In RNA molecules like the coronavirus genome, the T (thymine) is replaced with U (uracil).

Sources:

  • Fan Wu et al., Nature;
  • National Center for Biotechnology Information;
  • Dr. David Gordon, University of California, San Francisco;
  • Dr. Matthew B.   and Dr. Stuart Weston, University of Maryland School of Medicine;
  • Dr. Pleuni Pennings, San Francisco State University;
  • David Haussler and Jason Fernandes, U.C. Santa Cruz Genomics Institute; Journal of Virology;
  • Annual Review of Virology.

Model sources:

  • Coronavirus by Maria Voigt, RCSB Protein Data Bank headquartered at Rutgers University–New Brunswick;
  • Ribosome from Heena Khatter et al., Nature;
  • Proteins from Yang Zhang’s Research Group, University of Michigan.

Bad News Wrapped in Protein: Inside the Coronavirus Genome

A virus is “simply a piece of bad news wrapped up in protein,” the biologists Jean and Peter Medawar wrote in 1977.

In January, scientists deciphered a piece of very bad news: the genome of SARS-CoV-2, the virus that causes Covid-19. The sample came from a 41-year-old man who worked at the seafood market in Wuhan where the first cluster of cases appeared.

Researchers are now racing to make sense of this viral recipe, which could inspire drugs, vaccines and other tools to fight the ongoing pandemic.

A String of RNA

Viruses must hijack living cells to replicate and spread. When the coronavirus finds a suitable cell, it injects a strand of RNA that contains the entire coronavirus genome.

The genome of the new coronavirus is less than 30,000 “letters” long. (The human genome is over 3 billion.) Scientists have identified genes for as many as 29 proteins, which carry out a range of jobs from making copies of the coronavirus to suppressing the body’s immune responses.

The first sequence of RNA letters reads:

auuaaagguuuauaccuucccagguaacaaaccaaccaacuuucgaucucuuguagaucuguucucuaaacgaacuuuaaaaucuguguggcugucacucggcugcaugcuuagugcacucacgcaguauaauuaauaacuaauuacugucguugacaggacacgaguaacucgucuaucuucugcaggcugcuuacgguuucguccguguugcagccgaucaucagcacaucuagguuucguccgggugugaccgaaagguaag

This sequence recruits machinery inside the infected cell to read the RNA letters — acg and u — and translate them into coronavirus proteins.

The full coronavirus genome and the proteins it encodes are shown below.

A Chain of Proteins · ORF1ab

The first viral protein created inside the infected cell is actually a chain of 16 proteins joined together. Two of these proteins act like scissors, snipping the links between the different proteins and freeing them to do their jobs.

See graph at https://www.nytimes.com/interactive/2020/04/03/science/coronavirus-genome-bad-news-wrapped-in-protein.html

Research on other coronaviruses has given scientists a good understanding of what some of the SARS-CoV-2 proteins do. But other proteins are far more mysterious, and some might do nothing at all.

Cellular Saboteur · NSP1

This protein slows down the infected cell’s production of its own proteins. This sabotage forces the cell to make more virus proteins and prevents it from assembling antiviral proteins that could stop the virus.

auggagagccuugucccugguuucaacgagaaaacacacguccaacucaguuugccuguuuuacagguucgcgacgugcucguacguggcuuuggagacuccguggaggaggucuuaucagaggcacgucaacaucuuaaagauggcacuuguggcuuaguagaaguugaaaaaggcguuuugccucaacuugaacagcccuauguguucaucaaacguucggaugcucgaacugcaccucauggucauguuaugguugagcugguagcagaacucgaaggcauucaguacggucguaguggugagacacuugguguccuugucccucaugugggcgaaauaccaguggcuuaccgcaagguucuucuucguaagaacgguaauaaaggagcugguggccauaguuacggcgccgaucuaaagucauuugacuuaggcgacgagcuuggcacugauccuuaugaagauuuucaagaaaacuggaacacuaaacauagcagugguguuacccgugaacucaugcgugagcuuaacggaggg

Mystery Protein · NSP2

Scientists aren’t sure what NSP2 does. The other proteins it attaches to may offer some clues. Two of them help move molecule-filled bubbles called endosomes around the cell.

gcauacacucgcuaugucgauaacaacuucuguggcccugauggcuacccucuugagugcauuaaagaccuucuagcacgugcugguaaagcuucaugcacuuuguccgaacaacuggacuuuauugacacuaagagggguguauacugcugccgugaacaugagcaugaaauugcuugguacacggaacguucugaaaagagcuaugaauugcagacaccuuuugaaauuaaauuggcaaagaaauuugacaccuucaauggggaauguccaaauuuuguauuucccuuaaauuccauaaucaagacuauucaaccaaggguugaaaagaaaaagcuugauggcuuuauggguagaauucgaucugucuauccaguugcgucaccaaaugaaugcaaccaaaugugccuuucaacucucaugaagugugaucauuguggugaaacuucauggcagacgggcgauuuuguuaaagccacuugcgaauuuuguggcacugagaauuugacuaaagaaggugccacuacuugugguuacuuaccccaaaaugcuguuguuaaaauuuauuguccagcaugucacaauucagaaguaggaccugagcauagucuugccgaauaccauaaugaaucuggcuugaaaaccauucuucguaaggguggucgcacuauugccuuuggaggcuguguguucucuuauguugguugccauaacaagugugccuauuggguuccacgugcuagcgcuaacauagguuguaaccauacagguguuguuggagaagguuccgaaggucuuaaugacaaccuucuugaaauacuccaaaaagagaaagucaacaucaauauuguuggugacuuuaaacuuaaugaagagaucgccauuauuuuggcaucuuuuucugcuuccacaagugcuuuuguggaaacugugaaagguuuggauuauaaagcauucaaacaaauuguugaauccugugguaauuuuaaaguuacaaaaggaaaagcuaaaaaaggugccuggaauauuggugaacagaaaucaauacugaguccucuuuaugcauuugcaucagaggcugcucguguuguacgaucaauuuucucccgcacucuugaaacugcucaaaauucugugcguguuuuacagaaggccgcuauaacaauacuagauggaauuucacaguauucacugagacucauugaugcuaugauguucacaucugauuuggcuacuaacaaucuaguuguaauggccuacauuacaggugguguuguucaguugacuucgcaguggcuaacuaacaucuuuggcacuguuuaugaaaaacucaaacccguccuugauuggcuugaagagaaguuuaaggaagguguagaguuucuuagagacgguugggaaauuguuaaauuuaucucaaccugugcuugugaaauugucgguggacaaauugucaccugugcaaaggaaauuaaggagaguguucagacauucuuuaagcuuguaaauaaauuuuuggcuuugugugcugacucuaucauuauugguggagcuaaacuuaaagccuugaauuuaggugaaacauuugucacgcacucaaagggauuguacagaaaguguguuaaauccagagaagaaacuggccuacucaugccucuaaaagccccaaaagaaauuaucuucuuagagggagaaacacuucccacagaaguguuaacagaggaaguugucuugaaaacuggugauuuacaaccauuagaacaaccuacuagugaagcuguugaagcuccauugguugguacaccaguuuguauuaacgggcuuauguugcucgaaaucaaagacacagaaaaguacugugcccuugcaccuaauaugaugguaacaaacaauaccuucacacucaaaggcggu

Untagging and Cutting · NSP3

NSP3 is a large protein that has two important jobs. One is cutting loose other viral proteins so they can do their own tasks. It also alters many of the infected cell’s proteins.

Normally, a healthy cell tags old proteins for destruction. But the coronavirus can remove those tags, changing the balance of proteins and possibly reducing the cell’s ability to fight the virus.

gcaccaacaaagguuacuuuuggugaugacacugugauagaagugcaagguuacaagagugugaauaucacuuuugaacuugaugaaaggauugauaaaguacuuaaugagaagugcucugccuauacaguugaacucgguacagaaguaaaugaguucgccuguguuguggcagaugcugucauaaaaacuuugcaaccaguaucugaauuacuuacaccacugggcauugauuuagaugaguggaguauggcuacauacuacuuauuugaugagucuggugaguuuaaauuggcuucacauauguauuguucuuucuacccuccagaugaggaugaagaagaaggugauugugaagaagaagaguuugagccaucaacucaauaugaguaugguacugaagaugauuaccaagguaaaccuuuggaauuuggugccacuucugcugcucuucaaccugaagaagagcaagaagaagauugguuagaugaugauagucaacaaacuguuggucaacaagacggcagugaggacaaucagacaacuacuauucaaacaauuguugagguucaaccucaauuagagauggaacuuacaccaguuguucagacuauugaagugaauaguuuuagugguuauuuaaaacuuacugacaauguauacauuaaaaaugcagacauuguggaagaagcuaaaaagguaaaaccaacagugguuguuaaugcagccaauguuuaccuuaaacauggaggagguguugcaggagccuuaaauaaggcuacuaacaaugccaugcaaguugaaucugaugauuacauagcuacuaauggaccacuuaaagugggugguaguuguguuuuaagcggacacaaucuugcuaaacacugucuucauguugucggcccaaauguuaacaaaggugaagacauucaacuucuuaagagugcuuaugaaaauuuuaaucagcacgaaguucuacuugcaccauuauuaucagcugguauuuuuggugcugacccuauacauucuuuaagaguuuguguagauacuguucgcacaaaugucuacuuagcugucuuugauaaaaaucucuaugacaaacuuguuucaagcuuuuuggaaaugaagagugaaaagcaaguugaacaaaagaucgcugagauuccuaaagaggaaguuaagccauuuauaacugaaaguaaaccuucaguugaacagagaaaacaagaugauaagaaaaucaaagcuuguguugaagaaguuacaacaacucuggaagaaacuaaguuccucacagaaaacuuguuacuuuauauugacauuaauggcaaucuucauccagauucugccacucuuguuagugacauugacaucacuuucuuaaagaaagaugcuccauauauagugggugauguuguucaagaggguguuuuaacugcugugguuauaccuacuaaaaaggcugguggcacuacugaaaugcuagcgaaagcuuugagaaaagugccaacagacaauuauauaaccacuuacccgggucaggguuuaaaugguuacacuguagaggaggcaaagacagugcuuaaaaaguguaaaagugccuuuuacauucuaccaucuauuaucucuaaugagaagcaagaaauucuuggaacuguuucuuggaauuugcgagaaaugcuugcacaugcagaagaaacacgcaaauuaaugccugucuguguggaaacuaaagccauaguuucaacuauacagcguaaauauaaggguauuaaaauacaagagggugugguugauuauggugcuagauuuuacuuuuacaccaguaaaacaacuguagcgucacuuaucaacacacuuaacgaucuaaaugaaacucuuguuacaaugccacuuggcuauguaacacauggcuuaaauuuggaagaagcugcucgguauaugagaucucucaaagugccagcuacaguuucuguuucuucaccugaugcuguuacagcguauaaugguuaucuuacuucuucuucuaaaacaccugaagaacauuuuauugaaaccaucucacuugcugguuccuauaaagauugguccuauucuggacaaucuacacaacuagguauagaauuucuuaagagaggugauaaaaguguauauuacacuaguaauccuaccacauuccaccuagauggugaaguuaucaccuuugacaaucuuaagacacuucuuucuuugagagaagugaggacuauuaagguguuuacaacaguagacaacauuaaccuccacacgcaaguuguggacaugucaaugacauauggacaacaguuugguccaacuuauuuggauggagcugauguuacuaaaauaaaaccucauaauucacaugaagguaaaacauuuuauguuuuaccuaaugaugacacucuacguguugaggcuuuugaguacuaccacacaacugauccuaguuuucuggguagguacaugucagcauuaaaucacacuaaaaaguggaaauacccacaaguuaaugguuuaacuucuauuaaaugggcagauaacaacuguuaucuugccacugcauuguuaacacuccaacaaauagaguugaaguuuaauccaccugcucuacaagaugcuuauuacagagcaagggcuggugaagcugcuaacuuuugugcacuuaucuuagccuacuguaauaagacaguaggugaguuaggugauguuagagaaacaaugaguuacuuguuucaacaugccaauuuagauucuugcaaaagagucuugaacgugguguguaaaacuuguggacaacagcagacaacccuuaaggguguagaagcuguuauguacaugggcacacuuucuuaugaacaauuuaagaaagguguucagauaccuuguacgugugguaaacaagcuacaaaauaucuaguacaacaggagucaccuuuuguuaugaugucagcaccaccugcucaguaugaacuuaagcaugguacauuuacuugugcuagugaguacacugguaauuaccaguguggucacuauaaacauauaacuucuaaagaaacuuuguauugcauagacggugcuuuacuuacaaaguccucagaauacaaagguccuauuacggauguuuucuacaaagaaaacaguuacacaacaaccauaaaaccaguuacuuauaaauuggaugguguuguuuguacagaaauugacccuaaguuggacaauuauuauaagaaagacaauucuuauuucacagagcaaccaauugaucuuguaccaaaccaaccauauccaaacgcaagcuucgauaauuuuaaguuuguaugugauaauaucaaauuugcugaugauuuaaaccaguuaacugguuauaagaaaccugcuucaagagagcuuaaaguuacauuuuucccugacuuaaauggugaugugguggcuauugauuauaaacacuacacacccucuuuuaagaaaggagcuaaauuguuacauaaaccuauuguuuggcauguuaacaaugcaacuaauaaagccacguauaaaccaaauaccugguguauacguugucuuuggagcacaaaaccaguugaaacaucaaauucguuugauguacugaagucagaggacgcgcagggaauggauaaucuugccugcgaagaucuaaaaccagucucugaagaaguaguggaaaauccuaccauacagaaagacguucuugaguguaaugugaaaacuaccgaaguuguaggagacauuauacuuaaaccagcaaauaauaguuuaaaaauuacagaagagguuggccacacagaucuaauggcugcuuauguagacaauucuagucuuacuauuaagaaaccuaaugaauuaucuagaguauuagguuugaaaacccuugcuacucaugguuuagcugcuguuaauagugucccuugggauacuauagcuaauuaugcuaagccuuuucuuaacaaaguuguuaguacaacuacuaacauaguuacacgguguuuaaaccguguuuguacuaauuauaugccuuauuucuuuacuuuauugcuacaauuguguacuuuuacuagaaguacaaauucuagaauuaaagcaucuaugccgacuacuauagcaaagaauacuguuaagagugucgguaaauuuugucuagaggcuucauuuaauuauuugaagucaccuaauuuuucuaaacugauaaauauuauaauuugguuuuuacuauuaaguguuugccuagguucuuuaaucuacucaaccgcugcuuuagguguuuuaaugucuaauuuaggcaugccuucuuacuguacugguuacagagaaggcuauuugaacucuacuaaugucacuauugcaaccuacuguacugguucuauaccuuguaguguuugucuuagugguuuagauucuuuagacaccuauccuucuuuagaaacuauacaaauuaccauuucaucuuuuaaaugggauuuaacugcuuuuggcuuaguugcagagugguuuuuggcauauauucuuuucacuagguuuuucuauguacuuggauuggcugcaaucaugcaauuguuuuucagcuauuuugcaguacauuuuauuaguaauucuuggcuuaugugguuaauaauuaaucuuguacaaauggccccgauuucagcuaugguuagaauguacaucuucuuugcaucauuuuauuauguauggaaaaguuaugugcauguuguagacgguuguaauucaucaacuuguaugauguguuacaaacguaauagagcaacaagagucgaauguacaacuauuguuaaugguguuagaagguccuuuuaugucuaugcuaauggagguaaaggcuuuugcaaacuacacaauuggaauuguguuaauugugauacauucugugcugguaguacauuuauuagugaugaaguugcgagagacuugucacuacaguuuaaaagaccaauaaauccuacugaccagucuucuuacaucguugauaguguuacagugaagaaugguuccauccaucuuuacuuugauaaagcuggucaaaagacuuaugaaagacauucucucucucauuuuguuaacuuagacaaccugagagcuaauaacacuaaagguucauugccuauuaauguuauaguuuuugaugguaaaucaaaaugugaagaaucaucugcaaaaucagcgucuguuuacuacagucagcuuaugugucaaccuauacuguuacuagaucaggcauuagugucugauguuggugauagugcggaaguugcaguuaaaauguuugaugcuuacguuaauacguuuucaucaacuuuuaacguaccaauggaaaaacucaaaacacuaguugcaacugcagaagcugaacuugcaaagaauguguccuuagacaaugucuuaucuacuuuuauuucagcagcucggcaaggguuuguugauucagauguagaaacuaaagauguuguugaaugucuuaaauugucacaucaaucugacauagaaguuacuggcgauaguuguaauaacuauaugcucaccuauaacaaaguugaaaacaugacaccccgugaccuuggugcuuguauugacuguagugcgcgucauauuaaugcgcagguagcaaaaagucacaacauugcuuugauauggaacguuaaagauuucaugucauugucugaacaacuacgaaaacaaauacguagugcugcuaaaaagaauaacuuaccuuuuaaguugacaugugcaacuacuagacaaguuguuaauguuguaacaacaaagauagcacuuaaggguggu

Bubble Maker · NSP4

Combining with other proteins, NSP4 helps build fluid-filled bubbles within infected cells. Inside these bubbles, parts for new copies of the virus are constructed.

aaaauuguuaauaauugguugaagcaguuaauuaaaguuacacuuguguuccuuuuuguugcugcuauuuucuauuuaauaacaccuguucaugucaugucuaaacauacugacuuuucaagugaaaucauaggauacaaggcuauugaugguggugucacucgugacauagcaucuacagauacuuguuuugcuaacaaacaugcugauuuugacacaugguuuagccagcguggugguaguuauacuaaugacaaagcuugcccauugauugcugcagucauaacaagagaaguggguuuugucgugccugguuugccuggcacgauauuacgcacaacuaauggugacuuuuugcauuucuuaccuagaguuuuuagugcaguugguaacaucuguuacacaccaucaaaacuuauagaguacacugacuuugcaacaucagcuuguguuuuggcugcugaauguacaauuuuuaaagaugcuucugguaagccaguaccauauuguuaugauaccaauguacuagaagguucuguugcuuaugaaaguuuacgcccugacacacguuaugugcucauggauggcucuauuauucaauuuccuaacaccuaccuugaagguucuguuagagugguaacaacuuuugauucugaguacuguaggcacggcacuugugaaagaucagaagcugguguuuguguaucuacuagugguagauggguacuuaacaaugauuauuacagaucuuuaccaggaguuuucugugguguagaugcuguaaauuuacuuacuaauauguuuacaccacuaauucaaccuauuggugcuuuggacauaucagcaucuauaguagcuggugguauuguagcuaucguaguaacaugccuugccuacuauuuuaugagguuuagaagagcuuuuggugaauacagucauguaguugccuuuaauacuuuacuauuccuuaugucauucacuguacucuguuuaacaccaguuuacucauucuuaccugguguuuauucuguuauuuacuuguacuugacauuuuaucuuacuaaugauguuucuuuuuuagcacauauucaguggaugguuauguucacaccuuuaguaccuuucuggauaacaauugcuuauaucauuuguauuuccacaaagcauuucuauugguucuuuaguaauuaccuaaagagacguguagucuuuaaugguguuuccuuuaguacuuuugaagaagcugcgcugugcaccuuuuuguuaaauaaagaaauguaucuaaaguugcguagugaugugcuauuaccucuuacgcaauauaauagauacuuagcucuuuauaauaaguacaaguauuuuaguggagcaauggauacaacuagcuacagagaagcugcuuguugucaucucgcaaaggcucucaaugacuucaguaacucagguucugauguucuuuaccaaccaccacaaaccucuaucaccucagcuguuuugcag

Protein Scissors · NSP5

This protein makes most of the cuts that free other NSP proteins to carry out their own jobs.

agugguuuuagaaaaauggcauucccaucugguaaaguugaggguuguaugguacaaguaacuugugguacaacuacacuuaacggucuuuggcuugaugacguaguuuacuguccaagacaugugaucugcaccucugaagacaugcuuaacccuaauuaugaagauuuacucauucguaagucuaaucauaauuucuugguacaggcugguaauguucaacucaggguuauuggacauucuaugcaaaauuguguacuuaagcuuaagguugauacagccaauccuaagacaccuaaguauaaguuuguucgcauucaaccaggacagacuuuuucaguguuagcuuguuacaaugguucaccaucugguguuuaccaaugugcuaugaggcccaauuucacuauuaaggguucauuccuuaaugguucaugugguaguguugguuuuaacauagauuaugacugugucucuuuuuguuacaugcaccauauggaauuaccaacuggaguucaugcuggcacagacuuagaagguaacuuuuauggaccuuuuguugacaggcaaacagcacaagcagcugguacggacacaacuauuacaguuaauguuuuagcuugguuguacgcugcuguuauaaauggagacaggugguuucucaaucgauuuaccacaacucuuaaugacuuuaaccuuguggcuaugaaguacaauuaugaaccucuaacacaagaccauguugacauacuaggaccucuuucugcucaaacuggaauugccguuuuagauaugugugcuucauuaaaagaauuacugcaaaaugguaugaauggacguaccauauuggguagugcuuuauuagaagaugaauuuacaccuuuugauguuguuagacaaugcucagguguuacuuuccaa

Bubble Factory · NSP6

Works with NSP3 and NSP4 to make virus factory bubbles.

agugcagugaaaagaacaaucaaggguacacaccacugguuguuacucacaauuuugacuucacuuuuaguuuuaguccagaguacucaauggucuuuguucuuuuuuuuguaugaaaaugccuuuuuaccuuuugcuauggguauuauugcuaugucugcuuuugcaaugauguuugucaaacauaagcaugcauuucucuguuuguuuuuguuaccuucucuugccacuguagcuuauuuuaauauggucuauaugccugcuaguugggugaugcguauuaugacaugguuggauaugguugauacuaguuugucugguuuuaagcuaaaagacuguguuauguaugcaucagcuguaguguuacuaauccuuaugacagcaagaacuguguaugaugauggugcuaggagaguguggacacuuaugaaugucuugacacucguuuauaaaguuuauuaugguaaugcuuuagaucaagccauuuccaugugggcucuuauaaucucuguuacuucuaacuacucagguguaguuacaacugucauguuuuuggccagagguauuguuuuuauguguguugaguauugcccuauuuucuucauaacugguaauacacuucaguguauaaugcuaguuuauuguuucuuaggcuauuuuuguacuuguuacuuuggccucuuuuguuuacucaaccgcuacuuuagacugacucuugguguuuaugauuacuuaguuucuacacaggaguuuagauauaugaauucacagggacuacucccacccaagaauagcauagaugccuucaaacucaacauuaaauuguuggguguugguggcaaaccuuguaucaaaguagccacuguacag

Copy Assistants · NSP7 and NSP8

These two proteins help NSP12 make new copies of the RNA genome, which can ultimately end up inside new viruses.

ucuaaaaugucagauguaaagugcacaucaguagucuuacucucaguuuugcaacaacucagaguagaaucaucaucuaaauugugggcucaauguguccaguuacacaaugacauucucuuagcuaaagauacuacugaagccuuugaaaaaaugguuucacuacuuucuguuuugcuuuccaugcagggugcuguagacauaaacaagcuuugugaagaaaugcuggacaacagggcaaccuuacaa

gcuauagccucagaguuuaguucccuuccaucauaugcagcuuuugcuacugcucaagaagcuuaugagcaggcuguugcuaauggugauucugaaguuguucuuaaaaaguugaagaagucuuugaauguggcuaaaucugaauuugaccgugaugcagccaugcaacguaaguuggaaaagauggcugaucaagcuaugacccaaauguauaaacaggcuagaucugaggacaagagggcaaaaguuacuagugcuaugcagacaaugcuuuucacuaugcuuagaaaguuggauaaugaugcacucaacaacauuaucaacaaugcaagagaugguuguguucccuugaacauaauaccucuuacaacagcagccaaacuaaugguugucauaccagacuauaacacauauaaaaauacgugugaugguacaacauuuacuuaugcaucagcauugugggaaauccaacagguuguagaugcagauaguaaaauuguucaacuuagugaaauuaguauggacaauucaccuaauuuagcauggccucuuauuguaacagcuuuaagggccaauucugcugucaaauuacag

At the Heart of the Cell · NSP9

This protein infiltrates tiny channels in the infected cell’s nucleus, which holds our own genome. It may be able to influence the movement of molecules in and out of the nucleus — but for what purpose, no one knows.

aauaaugagcuuaguccuguugcacuacgacagaugucuugugcugccgguacuacacaaacugcuugcacugaugacaaugcguuagcuuacuacaacacaacaaagggagguagguuuguacuugcacuguuauccgauuuacaggauuugaaaugggcuagauucccuaagagugauggaacugguacuaucuauacagaacuggaaccaccuuguagguuuguuacagacacaccuaaagguccuaaagugaaguauuuauacuuuauuaaaggauuaaacaaccuaaauagagguaugguacuugguaguuuagcugccacaguacgucuacaa

Genetic Camouflage · NSP10

Human cells have antiviral proteins that find viral RNA and shred it. This protein works with NSP16 to camouflage the virus’s genes so that they don’t get attacked.

gcugguaaugcaacagaagugccugccaauucaacuguauuaucuuucugugcuuuugcuguagaugcugcuaaagcuuacaaagauuaucuagcuagugggggacaaccaaucacuaauuguguuaagauguuguguacacacacugguacuggucaggcaauaacaguuacaccggaagccaauauggaucaagaauccuuugguggugcaucguguugucuguacugccguugccacauagaucauccaaauccuaaaggauuuugugacuuaaaagguaaguauguacaaauaccuacaacuugugcuaaugacccuguggguuuuacacuuaaaaacacagucuguaccgucugcgguauguggaaagguuauggcuguaguugugaucaacuccgcgaacccaugcuucag

Copy Machine · NSP12

This protein assembles genetic letters into new virus genomes. Researchers have found that the antiviral remdesivir interferes with NSP12 in other coronaviruses, and trials are now underway to see if the drug can treat Covid-19.

The infected cell begins reading the RNA sequence for NSP12:

ucagcugaugcacaaucguuuuuaaac

Then it backtracks and reads c again, continuing as:

cggguuugcgguguaagugcagcccgucuuacaccgugcggcacaggcacuaguacugaugucguauacagggcuuuugacaucuacaaugauaaaguagcugguuuugcuaaauuccuaaaaacuaauuguugucgcuuccaagaaaaggacgaagaugacaauuuaauugauucuuacuuuguaguuaagagacacacuuucucuaacuaccaacaugaagaaacaauuuauaauuuacuuaaggauuguccagcuguugcuaaacaugacuucuuuaaguuuagaauagacggugacaugguaccacauauaucacgucaacgucuuacuaaauacacaauggcagaccucgucuaugcuuuaaggcauuuugaugaagguaauugugacacauuaaaagaaauacuugucacauacaauuguugugaugaugauuauuucaauaaaaaggacugguaugauuuuguagaaaacccagauauauuacgcguauacgccaacuuaggugaacguguacgccaagcuuuguuaaaaacaguacaauucugugaugccaugcgaaaugcugguauuguugguguacugacauuagauaaucaagaucucaaugguaacugguaugauuucggugauuucauacaaaccacgccagguaguggaguuccuguuguagauucuuauuauucauuguuaaugccuauauuaaccuugaccagggcuuuaacugcagagucacauguugacacugacuuaacaaagccuuacauuaagugggauuuguuaaaauaugacuucacggaagagagguuaaaacucuuugaccguuauuuuaaauauugggaucagacauaccacccaaauuguguuaacuguuuggaugacagaugcauucugcauugugcaaacuuuaauguuuuauucucuacaguguucccaccuacaaguuuuggaccacuagugagaaaaauauuuguugaugguguuccauuuguaguuucaacuggauaccacuucagagagcuagguguuguacauaaucaggauguaaacuuacauagcucuagacuuaguuuuaaggaauuacuuguguaugcugcugacccugcuaugcacgcugcuucugguaaucuauuacuagauaaacgcacuacgugcuuuucaguagcugcacuuacuaacaauguugcuuuucaaacugucaaacccgguaauuuuaacaaagacuucuaugacuuugcugugucuaaggguuucuuuaaggaaggaaguucuguugaauuaaaacacuucuucuuugcucaggaugguaaugcugcuaucagcgauuaugacuacuaucguuauaaucuaccaacaaugugugauaucagacaacuacuauuuguaguugaaguuguugauaaguacuuugauuguuacgaugguggcuguauuaaugcuaaccaagucaucgucaacaaccuagacaaaucagcugguuuuccauuuaauaaaugggguaaggcuagacuuuauuaugauucaaugaguuaugaggaucaagaugcacuuuucgcauauacaaaacguaaugucaucccuacuauaacucaaaugaaucuuaaguaugccauuagugcaaagaauagagcucgcaccguagcuggugucucuaucuguaguacuaugaccaauagacaguuucaucaaaaauuauugaaaucaauagccgccacuagaggagcuacuguaguaauuggaacaagcaaauucuauggugguuggcacaacauguuaaaaacuguuuauagugauguagaaaacccucaccuuauggguugggauuauccuaaaugugauagagccaugccuaacaugcuuagaauuauggccucacuuguucuugcucgcaaacauacaacguguuguagcuugucacaccguuucuauagauuagcuaaugagugugcucaaguauugagugaaauggucauguguggcgguucacuauauguuaaaccagguggaaccucaucaggagaugccacaacugcuuaugcuaauaguguuuuuaacauuugucaagcugucacggccaauguuaaugcacuuuuaucuacugaugguaacaaaauugccgauaaguauguccgcaauuuacaacacagacuuuaugagugucucuauagaaauagagauguugacacagacuuugugaaugaguuuuacgcauauuugcguaaacauuucucaaugaugauacucucugacgaugcuguuguguguuucaauagcacuuaugcaucucaaggucuaguggcuagcauaaagaacuuuaagucaguucuuuauuaucaaaacaauguuuuuaugucugaagcaaaauguuggacugagacugaccuuacuaaaggaccucaugaauuuugcucucaacauacaaugcuaguuaaacagggugaugauuauguguaccuuccuuacccagauccaucaagaauccuaggggccggcuguuuuguagaugauaucguaaaaacagaugguacacuuaugauugaacgguucgugucuuuagcuauagaugcuuacccacuuacuaaacauccuaaucaggaguaugcugaugucuuucauuuguacuuacaauacauaagaaagcuacaugaugaguuaacaggacacauguuagacauguauucuguuaugcuuacuaaugauaacacuucaagguauugggaaccugaguuuuaugaggcuauguacacaccgcauacagucuuacag

Another sequence, NSP11, overlaps part of the same stretch of RNA. But it’s not clear if the tiny protein encoded by this gene has any function at all.

Unwinding RNA · NSP13

Normally, virus RNA is wound into intricate twists and turns. Scientists suspect that NSP13 unwinds it so that other proteins can read its sequence and make new copies.

gcuguuggggcuuguguucuuugcaauucacagacuucauuaagauguggugcuugcauacguagaccauucuuauguuguaaaugcuguuacgaccaugucauaucaacaucacauaaauuagucuugucuguuaauccguauguuugcaaugcuccagguugugaugucacagaugugacucaacuuuacuuaggagguaugagcuauuauuguaaaucacauaaaccacccauuaguuuuccauugugugcuaauggacaaguuuuugguuuauauaaaaauacauguguugguagcgauaauguuacugacuuuaaugcaauugcaacaugugacuggacaaaugcuggugauuacauuuuagcuaacaccuguacugaaagacucaagcuuuuugcagcagaaacgcucaaagcuacugaggagacauuuaaacugucuuaugguauugcuacuguacgugaagugcugucugacagagaauuacaucuuucaugggaaguugguaaaccuagaccaccacuuaaccgaaauuaugucuuuacugguuaucguguaacuaaaaacaguaaaguacaaauaggagaguacaccuuugaaaaaggugacuauggugaugcuguuguuuaccgagguacaacaacuuacaaauuaaauguuggugauuauuuugugcugacaucacauacaguaaugccauuaagugcaccuacacuagugccacaagagcacuauguuagaauuacuggcuuauacccaacacucaauaucucagaugaguuuucuagcaauguugcaaauuaucaaaagguugguaugcaaaaguauucuacacuccagggaccaccugguacugguaagagucauuuugcuauuggccuagcucucuacuacccuucugcucgcauaguguauacagcuugcucucaugccgcuguugaugcacuaugugagaaggcauuaaaauauuugccuauagauaaauguaguagaauuauaccugcacgugcucguguagaguguuuugauaaauucaaagugaauucaacauuagaacaguaugucuuuuguacuguaaaugcauugccugagacgacagcagauauaguugucuuugaugaaauuucaauggccacaaauuaugauuugaguguugucaaugccagauuacgugcuaagcacuauguguacauuggcgacccugcucaauuaccugcaccacgcacauugcuaacuaagggcacacuagaaccagaauauuucaauucaguguguagacuuaugaaaacuauagguccagacauguuccucggaacuugucggcguuguccugcugaaauuguugacacugugagugcuuugguuuaugauaauaagcuuaaagcacauaaagacaaaucagcucaaugcuuuaaaauguuuuauaaggguguuaucacgcaugauguuucaucugcaauuaacaggccacaaauaggcgugguaagagaauuccuuacacguaacccugcuuggagaaaagcugucuuuauuucaccuuauaauucacagaaugcuguagccucaaagauuuugggacuaccaacucaaacuguugauucaucacagggcucagaauaugacuaugucauauucacucaaaccacugaaacagcucacucuuguaauguaaacagauuuaauguugcuauuaccagagcaaaaguaggcauacuuugcauaaugucugauagagaccuuuaugacaaguugcaauuuacaagucuugaaauuccacguaggaauguggcaacuuuacaa

Viral Proofreader · NSP14

As NSP12 duplicates the coronavirus genome, it sometimes adds a wrong letter to the new copy. NSP14 cuts out these errors, so that the correct letter can be added instead.

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Cleaning Up · NSP15

Researchers suspect that this protein chops up leftover virus RNA as a way to hide from the infected cell’s antiviral defenses.

agaguuuagaaaauguggcuuuuaauguuguaaauaagggacacuuugauggacaacagggugaaguaccaguuucuaucauuaauaacacuguuuacacaaaaguugaugguguugauguagaauuguuugaaaauaaaacaacauuaccuguuaauguagcauuugagcuuugggcuaagcgcaacauuaaaccaguaccagaggugaaaauacucaauaauuuggguguggacauugcugcuaauacugugaucugggacuacaaaagagaugcuccagcacauauaucuacuauugguguuuguucuaugacugacauagccaagaaaccaacugaaacgauuugugcaccacucacugucuuuuuugaugguagaguugauggucaaguagacuuauuuagaaaugcccguaaugguguucuuauuacagaagguaguguuaaagguuuacaaccaucuguaggucccaaacaagcuagucuuaauggagucacauuaauuggagaagccguaaaaacacaguucaauuauuauaagaaaguugaugguguuguccaacaauuaccugaaacuuacuuuacucagaguagaaauuuacaagaauuuaaacccaggagucaaauggaaauugauuucuuagaauuagcuauggaugaauucauugaacgguauaaauuagaaggcuaugccuucgaacauaucguuuauggagauuuuagucauagucaguuaggugguuuacaucuacugauuggacuagcuaaacguuuuaaggaaucaccuuuugaauuagaagauuuuauuccuauggacaguacaguuaaaaacuauuucauaacagaugcgcaaacagguucaucuaaguguguguguucuguuauugauuuauuacuugaugauuuuguugaaauaauaaaaucccaagauuuaucuguaguuucuaagguugucaaagugacuauugacuauacagaaauuucauuuaugcuuugguguaaagauggccauguagaaacauuuuacccaaaauuacaa

More Camouflage · NSP16

NSP16 works with NSP10 to help the virus’s genes hide from proteins that chop up viral RNA.

ucuagucaagcguggcaaccggguguugcuaugccuaaucuuuacaaaaugcaaagaaugcuauuagaaaagugugaccuucaaaauuauggugauagugcaacauuaccuaaaggcauaaugaugaaugucgcaaaauauacucaacugugucaauauuuaaacacauuaacauuagcuguacccuauaauaugagaguuauacauuuuggugcugguucugauaaaggaguugcaccagguacagcuguuuuaagacagugguugccuacggguacgcugcuugucgauucagaucuuaaugacuuugucucugaugcagauucaacuuugauuggugauugugcaacuguacauacagcuaauaaaugggaucucauuauuagugauauguacgacccuaagacuaaaaauguuacaaaagaaaaugacucuaaagaggguuuuuucacuuacauuuguggguuuauacaacaaaagcuagcucuuggagguuccguggcuauaaagauaacagaacauucuuggaaugcugaucuuuauaagcucaugggacacuucgcaugguggacagccuuuguuacuaaugugaaugcgucaucaucugaagcauuuuuaauuggauguaauuaucuuggcaaaccacgcgaacaaauagaugguuaugucaugcaugcaaauuacauauuuuggaggaauacaaauccaauucaguugucuuccuauucuuuauuugacaugaguaaauuuccccuuaaauuaagggguacugcuguuaugucuuuaaaagaaggucaaaucaaugauaugauuuuaucucuucuuaguaaagguagacuuauaauuagagaaaacaacagaguuguuauuucuagugauguucuuguuaacaacuaaacgaaca

Spike Protein · S

The spike protein is one of four structural proteins — SEM and N — that form the outer layer of the coronavirus and protect the RNA inside. Structural proteins also help assemble and release new copies of the virus.

The S proteins form prominent spikes on the surface of the virus by arranging themselves in groups of three. These crownlike spikes give coronaviruses their name.

Part of the spike can extend and attach to a protein called ACE2 (in yellow below), which appears on particular cells in the human airway. The virus can then invade the cell.

The gene for the spike protein in SARS-CoV-2 has an insertion of 12 genetic letters: ccucggcgggca. This mutation may help the spikes bind tightly to human cells — a crucial step in its evolution from a virus that infected bats and other species.

A number of scientific teams are now designing vaccines that could prevent the spikes from attaching to human cells.

auguuuguuuuucuuguuuuauugccacuagucucuagucaguguguuaaucuuacaaccagaacucaauuacccccugcauacacuaauucuuucacacgugguguuuauuacccugacaaaguuuucagauccucaguuuuacauucaacucaggacuuguucuuaccuuucuuuuccaauguuacuugguuccaugcuauacaugucucugggaccaaugguacuaagagguuugauaacccuguccuaccauuuaaugaugguguuuauuuugcuuccacugagaagucuaacauaauaagaggcuggauuuuugguacuacuuuagauucgaagacccagucccuacuuauuguuaauaacgcuacuaauguuguuauuaaagucugugaauuucaauuuuguaaugauccauuuuuggguguuuauuaccacaaaaacaacaaaaguuggauggaaagugaguucagaguuuauucuagugcgaauaauugcacuuuugaauaugucucucagccuuuucuuauggaccuugaaggaaaacaggguaauuucaaaaaucuuagggaauuuguguuuaagaauauugaugguuauuuuaaaauauauucuaagcacacgccuauuaauuuagugcgugaucucccucaggguuuuucggcuuuagaaccauugguagauuugccaauagguauuaacaucacuagguuucaaacuuuacuugcuuuacauagaaguuauuugacuccuggugauucuucuucagguuggacagcuggugcugcagcuuauuauguggguuaucuucaaccuaggacuuuucuauuaaaauauaaugaaaauggaaccauuacagaugcuguagacugugcacuugacccucucucagaaacaaaguguacguugaaauccuucacuguagaaaaaggaaucuaucaaacuucuaacuuuagaguccaaccaacagaaucuauuguuagauuuccuaauauuacaaacuugugcccuuuuggugaaguuuuuaacgccaccagauuugcaucuguuuaugcuuggaacaggaagagaaucagcaacuguguugcugauuauucuguccuauauaauuccgcaucauuuuccacuuuuaaguguuauggagugucuccuacuaaauuaaaugaucucugcuuuacuaaugucuaugcagauucauuuguaauuagaggugaugaagucagacaaaucgcuccagggcaaacuggaaagauugcugauuauaauuauaaauuaccagaugauuuuacaggcugcguuauagcuuggaauucuaacaaucuugauucuaagguuggugguaauuauaauuaccuguauagauuguuuaggaagucuaaucucaaaccuuuugagagagauauuucaacugaaaucuaucaggccgguagcacaccuuguaaugguguugaagguuuuaauuguuacuuuccuuuacaaucauaugguuuccaacccacuaaugguguugguuaccaaccauacagaguaguaguacuuucuuuugaacuucuacaugcaccagcaacuguuuguggaccuaaaaagucuacuaauuugguuaaaaacaaaugugucaauuucaacuucaaugguuuaacaggcacagguguucuuacugagucuaacaaaaaguuucugccuuuccaacaauuuggcagagacauugcugacacuacugaugcuguccgugauccacagacacuugagauucuugacauuacaccauguucuuuugguggugucaguguuauaacaccaggaacaaauacuucuaaccagguugcuguucuuuaucaggauguuaacugcacagaagucccuguugcuauucaugcagaucaacuuacuccuacuuggcguguuuauucuacagguucuaauguuuuucaaacacgugcaggcuguuuaauaggggcugaacaugucaacaacucauaugagugugacauacccauuggugcagguauaugcgcuaguuaucagacucagacuaauucuccucggcgggcacguaguguagcuagucaauccaucauugccuacacuaugucacuuggugcagaaaauucaguugcuuacucuaauaacucuauugccauacccacaaauuuuacuauuaguguuaccacagaaauucuaccagugucuaugaccaagacaucaguagauuguacaauguacauuuguggugauucaacugaaugcagcaaucuuuuguugcaauauggcaguuuuuguacacaauuaaaccgugcuuuaacuggaauagcuguugaacaagacaaaaacacccaagaaguuuuugcacaagucaaacaaauuuacaaaacaccaccaauuaaagauuuuggugguuuuaauuuuucacaaauauuaccagauccaucaaaaccaagcaagaggucauuuauugaagaucuacuuuucaacaaagugacacuugcagaugcuggcuucaucaaacaauauggugauugccuuggugauauugcugcuagagaccucauuugugcacaaaaguuuaacggccuuacuguuuugccaccuuugcucacagaugaaaugauugcucaauacacuucugcacuguuagcggguacaaucacuucugguuggaccuuuggugcaggugcugcauuacaaauaccauuugcuaugcaaauggcuuauagguuuaaugguauuggaguuacacagaauguucucuaugagaaccaaaaauugauugccaaccaauuuaauagugcuauuggcaaaauucaagacucacuuucuuccacagcaagugcacuuggaaaacuucaagauguggucaaccaaaaugcacaagcuuuaaacacgcuuguuaaacaacuuagcuccaauuuuggugcaauuucaaguguuuuaaaugauauccuuucacgucuugacaaaguugaggcugaagugcaaauugauagguugaucacaggcagacuucaaaguuugcagacauaugugacucaacaauuaauuagagcugcagaaaucagagcuucugcuaaucuugcugcuacuaaaaugucagaguguguacuuggacaaucaaaaagaguugauuuuuguggaaagggcuaucaucuuauguccuucccucagucagcaccucaugguguagucuucuugcaugugacuuaugucccugcacaagaaaagaacuucacaacugcuccugccauuugucaugauggaaaagcacacuuuccucgugaaggugucuuuguuucaaauggcacacacugguuuguaacacaaaggaauuuuuaugaaccacaaaucauuacuacagacaacacauuugugucugguaacugugauguuguaauaggaauugucaacaacacaguuuaugauccuuugcaaccugaauuagacucauucaaggaggaguuagauaaauauuuuaagaaucauacaucaccagauguugauuuaggugacaucucuggcauuaaugcuucaguuguaaacauucaaaaagaaauugaccgccucaaugagguugccaagaauuuaaaugaaucucucaucgaucuccaagaacuuggaaaguaugagcaguauauaaaauggccaugguacauuuggcuagguuuuauagcuggcuugauugccauaguaauggugacaauuaugcuuugcuguaugaccaguugcuguaguugucucaagggcuguuguucuuguggauccugcugcaaauuugaugaagacgacucugagccagugcucaaaggagucaaauuacauuacacauaaacgaacuu

Escape Artist · ORF3a

The SARS-CoV-2 genome also encodes a group of so-called “accessory proteins.” They help change the environment inside the infected cell to make it easier for the virus to replicate.

The ORF3a protein pokes a hole in the membrane of an infected cell, making it easier for new viruses to escape. It also triggers inflammation, one of the most dangerous symptoms of Covid-19.

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ORF3b overlaps the same RNA, but scientists aren’t sure if SARS-CoV-2 uses this gene to make proteins.

Envelope Protein · E

The envelope protein is a structural protein that helps form the oily bubble of the virus. It may also have jobs to do once the virus is inside the cell. Researchers have found that it latches onto proteins that help turn our own genes on and off. It’s possible that pattern changes when the E protein interferes.

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Membrane Protein · M

Another structural protein that forms part of the outer coat of the virus.

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Signal Blocker · ORF6

This accessory protein blocks signals that the infected cell would send out to the immune system. It also blocks some of the cell’s own virus-fighting proteins, the same ones targeted by other viruses such as polio and influenza.

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Virus Liberator · ORF7a

When new viruses try to escape a cell, the cell can snare them with proteins called tetherin. Some research suggests that ORF7a cuts down an infected cell’s supply of tetherin, allowing more of the viruses to escape. Researchers have also found that the protein can trigger infected cells to commit suicide — which contributes to the damage Covid-19 causes to the lungs.

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ORF7b overlaps this same stretch of RNA, but it’s not clear what, if anything, the gene does.

Mystery Protein · ORF8

The gene for this accessory protein is dramatically different in SARS-CoV-2 than in other coronaviruses. Researchers are debating what it does.

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Nucleocapsid Protein · N

The N protein protects the virus RNA, keeping it stable inside the virus. Many N proteins link together in a long spiral, wrapping and coiling the RNA:

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The accessory proteins ORF9b and ORF9c overlap this same stretch of RNA. ORF9b blocks interferon, a key molecule in the defense against viruses, but it’s not clear if ORF9c is used at all.

Mystery Protein · ORF10

Close relatives of the SARS-CoV-2 virus don’t have the gene for this tiny accessory protein, so it’s hard to know what it’s for yet — or even if the virus makes proteins from it.

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End of the Line

The coronavirus genome ends with a snippet of RNA that stops the cell’s protein-making machinery. It then trails away as a repeating sequence of aaaaaaaaaaaaa

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Other related articles in this Open Access Online Scientific Journal include the following:

 

  • Structure-guided Drug Discovery: (1) The Coronavirus 3CL hydrolase (Mpro) enzyme (main protease) essential for proteolytic maturation of the virus and (2) viral protease, the RNA polymerase, the viral spike protein, a viral RNA as promising two targets for discovery of cleavage inhibitors of the viral spike polyprotein preventing the Coronavirus Virion the spread of infection

Curators and Reporters: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/03/12/structure-guided-drug-discovery-1-the-coronavirus-3cl-hydrolase-mpro-enzyme-main-protease-essential-for-proteolytic-maturation-of-the-virus-and-2-viral-protease-the-rna-polymerase-the-viral/

  • Predicting the Protein Structure of Coronavirus: Inhibition of Nsp15 can slow viral replication and Cryo-EM – Spike protein structure (experimentally verified) vs AI-predicted protein structures (not experimentally verified) of DeepMind (Parent: Google) aka AlphaFold

Curators: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/03/08/predicting-the-protein-structure-of-coronavirus-inhibition-of-nsp15-can-slow-viral-replication-and-cryo-em-spike-protein-structure-experimentally-verified-vs-ai-predicted-protein-structures-not/

  • Promise of Synthetic Biology for Covid-19 Vaccine

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2020/03/23/promise-of-synthetic-biology-for-covid-19-vaccine/

  • Glycobiology vs Proteomics: Glycobiologists Prespective in the effort to explain the origin, etiology and potential therapeutics for the Coronavirus Pandemic (COVID-19).

 Curator: Ofer Markman, PhD

https://pharmaceuticalintelligence.com/2020/03/26/glycobiology-vs-proteomics-glycobiologists-prespective-in-the-effort-to-explain-the-origin-etiology-and-potential-therapeutics-for-the-coronavirus-pandemic-covid-19/

  • Worldwide trial uses AI to quickly identify ideal Covid-19 treatments

Reporter : Irina Robu, PhD

https://pharmaceuticalintelligence.com/2020/04/09/worldwide-trial-uses-ai-to-quickly-identify-ideal-covid-19-treatments/

  • Updated listing of COVID-19 vaccine and therapeutic trials from NIH Clinical Trials.gov

Curator: Stephen J. Williams, PhD

https://pharmaceuticalintelligence.com/2020/04/16/updated-listing-of-covid-19-vaccine-and-therapeutic-trials-from-nih-clinical-trials-gov/

  • Actemra, immunosuppressive which was designed to treat rheumatoid arthritis but also approved in 2017 to treat cytokine storms in cancer patients SAVED the sickest of all COVID-19 patients

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/04/14/actemra-immunosuppressive-which-was-designed-to-treat-rheumatoid-arthritis-but-also-approved-in-2017-to-treat-cytokine-storms-in-cancer-patients-saved-the-sickest-of-all-covid-19-patients/

  • Innate Immune Genes and Two Nasal Epithelial Cell Types: Expression of SARS-CoV-2 Entry Factors – COVID19 Cell Atlas

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/04/23/innate-immune-genes-and-two-nasal-epithelial-cell-types-expression-of-sars-cov-2-entry-factors-covid19-cell-atlas/

 

Read Full Post »


Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

RNA plays various roles in determining how the information in our genes drives cell behavior. One of its roles is to carry information encoded by our genes from the cell nucleus to the rest of the cell where it can be acted on by other cell components. Rresearchers have now defined how RNA also participates in transmitting information outside cells, known as extracellular RNA or exRNA. This new role of RNA in cell-to-cell communication has led to new discoveries of potential disease biomarkers and therapeutic targets. Cells using RNA to talk to each other is a significant shift in the general thought process about RNA biology.

 

Researchers explored basic exRNA biology, including how exRNA molecules and their transport packages (or carriers) were made, how they were expelled by producer cells and taken up by target cells, and what the exRNA molecules did when they got to their destination. They encountered surprising complexity both in the types of carriers that transport exRNA molecules between cells and in the different types of exRNA molecules associated with the carriers. The researchers had to be exceptionally creative in developing molecular and data-centric tools to begin making sense of the complexity, and found that the type of carrier affected how exRNA messages were sent and received.

 

As couriers of information between cells, exRNA molecules and their carriers give researchers an opportunity to intercept exRNA messages to see if they are associated with disease. If scientists could change or engineer designer exRNA messages, it may be a new way to treat disease. The researchers identified potential exRNA biomarkers for nearly 30 diseases including cardiovascular disease, diseases of the brain and central nervous system, pregnancy complications, glaucoma, diabetes, autoimmune diseases and multiple types of cancer.

 

As for example some researchers found that exRNA in urine showed promise as a biomarker of muscular dystrophy where current studies rely on markers obtained through painful muscle biopsies. Some other researchers laid the groundwork for exRNA as therapeutics with preliminary studies demonstrating how researchers might load exRNA molecules into suitable carriers and target carriers to intended recipient cells, and determining whether engineered carriers could have adverse side effects. Scientists engineered carriers with designer RNA messages to target lab-grown breast cancer cells displaying a certain protein on their surface. In an animal model of breast cancer with the cell surface protein, the researchers showed a reduction in tumor growth after engineered carriers deposited their RNA cargo.

 

Other than the above research work the scientists also created a catalog of exRNA molecules found in human biofluids like plasma, saliva and urine. They analyzed over 50,000 samples from over 2000 donors, generating exRNA profiles for 13 biofluids. This included over 1000 exRNA profiles from healthy volunteers. The researchers found that exRNA profiles varied greatly among healthy individuals depending on characteristics like age and environmental factors like exercise. This means that exRNA profiles can give important and detailed information about health and disease, but careful comparisons need to be made with exRNA data generated from people with similar characteristics.

 

Next the researchers will develop tools to efficiently and reproducibly isolate, identify and analyze different carrier types and their exRNA cargos and allow analysis of one carrier and its cargo at a time. These tools will be shared with the research community to fill gaps in knowledge generated till now and to continue to move this field forward.

 

References:

 

https://www.nih.gov/news-events/news-releases/scientists-explore-new-roles-rna

 

https://www.cell.com/consortium/exRNA

 

https://www.sciencedaily.com/releases/2016/06/160606120230.htm

 

https://www.pasteur.fr/en/multiple-roles-rnas

 

https://www.nature.com/scitable/topicpage/rna-functions-352

 

https://www.umassmed.edu/rti/biology/role-of-rna-in-biology/

 

Read Full Post »


Single-cell Genomics: Directions in Computational and Systems Biology – Contributions of Prof. Aviv Regev @Broad Institute of MIT and Harvard, Cochair, the Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute

 

Curator: Aviva Lev-Ari, PhD, RN

 

Dana Pe’er, PhD, now chair of computational and systems biology at the Sloan Kettering Institute at the Memorial Sloan Kettering Cancer Center and a member of the Human Cell Atlas Organizing Committee,

what really sets Regev apart is the elegance of her work. Regev, says Pe’er, “has a rare, innate ability of seeing complex biology and simplifying it and formalizing it into beautiful, abstract, describable principles.”

Dr. Aviv Regev, an MIT biology professor who is also chair of the faculty of the Broad and director of its Klarman Cell Observatory and Cell Circuits Program, was reviewing a newly published white paper detailing how the Human Cell Atlas is expected to change the way we diagnose, monitor, and treat disease at a gathering of international scientists at Israel’s Weizmann Institute of Science, 10/2017.

For Regev, the importance of the Human Cell Atlas goes beyond its promise to revolutionize biology and medicine. As she once put it, without an atlas of our cells, “we don’t really know what we’re made of.”

Regev, turned to a technique known as RNA interference (she now uses CRISPR), which allowed her to systematically shut genes down. Then she looked at which genes were expressed to determine how the cells’ response changed in each case. Her team singled out 100 different genes that were involved in regulating the response to the pathogens—some of which weren’t previously known to be involved in immune function. The study, published in Science, generated headlines.

The project, the Human Cell Atlas, aims to create a reference map that categorizes all the approximately 37 trillion cells that make up a human. The Human Cell Atlas is often compared to the Human Genome Project, the monumental scientific collaboration that gave us a complete readout of human DNA, or what might be considered the unabridged cookbook for human life. In a sense, the atlas is a continuation of that project’s work. But while the same DNA cookbook is found in every cell, each cell type reads only some of the recipes—that is, it expresses only certain genes, following their DNA instructions to produce the proteins that carry out a cell’s activities. The promise of the Human Cell Atlas is to reveal which specific genes are expressed in every cell type, and where the cells expressing those genes can be found.

Regev says,

The final product, will amount to nothing less than a “periodic table of our cells,” a tool that is designed not to answer one specific question but to make countless new discoveries possible.

Sequencing the RNA of the cells she’s studying can tell her only so much. To understand how the circuits change under different circumstances, Regev subjects cells to different stimuli, such as hormones or pathogens, to see how the resulting protein signals change.

“the modeling step”—creating algorithms that try to decipher the most likely sequence of molecular events following a stimulus. And just as someone might study a computer by cutting out circuits and seeing how that changes the machine’s operation, Regev tests her model by seeing if it can predict what will happen when she silences specific genes and then exposes the cells to the same stimulus.

By sequencing the RNA of individual cancer cells in recent years—“Every cell is an experiment now,” she says—she has found remarkable differences between the cells of a single tumor, even when they have the same mutations. (Last year that work led to Memorial Sloan Kettering’s Paul Marks Prize for Cancer Research.) She found that while some cancers are thought to develop resistance to therapy, a subset of melanoma cells were resistant from the start. And she discovered that two types of brain cancer, oligodendroglioma and astrocytoma, harbor the same cancer stem cells, which could have important implications for how they’re treated.

As a 2017 overview of the Human Cell Atlas by the project’s organizing committee noted, an atlas “is a map that aims to show the relationships among its elements.” Just as corresponding coastlines seen in an atlas of Earth offer visual evidence of continental drift, compiling all the data about our cells in one place could reveal relationships among cells, tissues, and organs, including some that are entirely unexpected. And just as the periodic table made it possible to predict the existence of elements yet to be observed, the Human Cell Atlas, Regev says, could help us predict the existence of cells that haven’t been found.

This year alone it will fund 85 Human Cell Atlas grants. Early results are already pouring in.

  • In March, Swedish researchers working on cells related to human development announced they had sequenced 250,000 individual cells.
  • In May, a team at the Broad made a data set of more than 500,000 immune cells available on a preview site.

The goal, Regev says, is for researchers everywhere to be able to use the open-source platform of the Human Cell Atlas to perform joint analyses.

Eric Lander, PhDthe founding director and president of the Broad Institute and a member of the Human Cell Atlas Organizing Committee, likens it to genomics.

“People thought at the beginning they might use genomics for this application or that application,” he says. “Nothing has failed to be transformed by genomics, and nothing will fail to be transformed by having a cell atlas.”

“How did we ever imagine we were going to solve a problem without single-cell resolution?”

SOURCE

https://www.technologyreview.com/s/611786/the-cartographer-of-cells/?utm_source=MIT+Technology+Review&utm_campaign=Alumni-Newsletter_Sep-Oct-2018&utm_medium=email

Other related articles published in this Open Access Online Scientific Journal include the following:

 

University of California Santa Cruz’s Genomics Institute will create a Map of Human Genetic Variations

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/01/13/university-of-california-santa-cruzs-genomics-institute-will-create-a-map-of-human-genetic-variations/

 

Recognitions for Contributions in Genomics by Dan David Prize Awards

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/31/recognitions-for-contributions-in-genomics-by-dan-david-prize-awards/

 

ENCODE (Encyclopedia of DNA Elements) program: ‘Tragic’ Sequestration Impact on NHGRI Programs

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/09/18/encode-encyclopedia-of-dna-elements-program-tragic-sequestration-impact-on-nhgri-programs/

 

Single-cell Sequencing

Genomic Diagnostics: Three Techniques to Perform Single Cell Gene Expression and Genome Sequencing Single Molecule DNA Sequencing

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/04/genomic-diagnostics-three-techniques-to-perform-single-cell-gene-expression-and-genome-sequencing-single-molecule-dna-sequencing/

 

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT – See, Aviv Regev

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/03/13/16th-annual-cancer-research-symposium-koch-institute-friday-june-16-9am-5pm-kresge-auditorium-mit/

 

LIVE 11/3/2015 1:30PM @The 15th Annual EmTech MIT – MIT Media Lab: Top 10 Breakthrough Technologies & 2015 Innovators Under 35 – See, Gilead Evrony

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN
https://pharmaceuticalintelligence.com/2015/11/03/live-1132015-130pm-the-15th-annual-emtech-mit-mit-media-lab-top-10-breakthrough-technologies-2015-innovators-under-35/

 

Cellular Guillotine Created for Studying Single-Cell Wound Repair

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2017/06/29/cellular-guillotine-created-for-studying-single-cell-wound-repair/

 

New subgroups of ILC immune cells discovered through single-cell RNA sequencing

Reporter: Stephen J Williams, PhD

https://pharmaceuticalintelligence.com/2016/02/17/new-subgroups-of-ilc-immune-cells-discovered-through-single-cell-rna-sequencing-from-karolinska-institute/

 

#JPM16: Illumina’s CEO on new genotyping array called Infinium XT and Bio-Rad Partnership for single-cell sequencing workflow

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/jpm16-illuminas-ceo-on-new-genotyping-array-called-infinium-xt-and-bio-rad-partnership-for-single-cell-sequencing-workflow/

 

Juno Acquires AbVitro for $125M: high-throughput and single-cell sequencing capabilities for Immune-Oncology Drug Discovery

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/juno-acquires-abvitro-for-125m-high-throughput-and-single-cell-sequencing-capabilities-for-immune-oncology-drug-discovery/

 

NIH to Award Up to $12M to Fund DNA, RNA Sequencing Research: single-cell genomics,  sample preparation,  transcriptomics and epigenomics, and  genome-wide functional analysis.

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/10/27/nih-to-award-up-to-12m-to-fund-dna-rna-sequencing-research-single-cell-genomics-sample-preparation-transcriptomics-and-epigenomics-and-genome-wide-functional-analysis/

 

Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2012/08/07/genome-wide-single-cell-analysis-of-recombination-activity-and-de-novo-mutation-rates-in-human-sperm/

REFERENCES to Original studies

In Science, 2018

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors

 See all authors and affiliations

Science  21 Apr 2017:
Vol. 356, Issue 6335, eaah4573
DOI: 10.1126/science.aah4573
Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis

See all authors and affiliations

Science  26 Apr 2018:
eaar3131
DOI: 10.1126/science.aar3131

In Nature, 2018 and 2017

How to build a human cell atlas

Aviv Regev is a maven of hard-core biological analyses. Now she is part of an effort to map every cell in the human body.

  1. Research | 

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  6. Amendments and Corrections | 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Researchers have embraced CRISPR gene-editing as a method for altering genomes, but some have reported that unwanted DNA changes may slip by undetected. The tool can cause large DNA deletions and rearrangements near its target site on the genome. Such alterations can confuse the interpretation of experimental results and could complicate efforts to design therapies based on CRISPR. The finding is in line with previous results from not only CRISPR but also other gene-editing systems.

 

CRISPR -Cas9 gene editing relies on the Cas9 enzyme to cut DNA at a particular target site. The cell then attempts to reseal this break using its DNA repair mechanisms. These mechanisms do not always work perfectly, and sometimes segments of DNA will be deleted or rearranged, or unrelated bits of DNA will become incorporated into the chromosome.

 

Researchers often use CRISPR to generate small deletions in the hope of knocking out a gene’s function. But when examining CRISPR edits, researchers found large deletions (often several thousand nucleotides) and complicated rearrangements of DNA sequences in which previously distant DNA sequences were stitched together. Many researchers use a method for amplifying short snippets of DNA to test whether their edits have been made properly. But this approach might miss larger deletions and rearrangements.

 

These deletions and rearrangements occur only with gene-editing techniques that rely on DNA cutting and not with some other types of CRISPR modifications that avoid cutting DNA. Such as a modified CRISPR system to switch one nucleotide for another without cutting DNA and other systems use inactivated Cas9 fused to other enzymes to turn genes on or off, or to target RNA. Overall, these unwanted edits are a problem that deserves more attention, but this should not stop anyone from using CRISPR. Only when people use it, they need to do a more thorough analysis about the outcome.

 

References:

 

https://www.nature.com/articles/d41586-018-05736-3?utm_source=briefing-dy

 

https://www.ncbi.nlm.nih.gov/pubmed/28561021

 

https://www.ncbi.nlm.nih.gov/pubmed/30010673

 

https://www.ncbi.nlm.nih.gov/pubmed/24651067

 

https://www.ncbi.nlm.nih.gov/pubmed/25398350

 

https://www.ncbi.nlm.nih.gov/pubmed/24838573

 

https://www.ncbi.nlm.nih.gov/pubmed/25200087

 

https://www.ncbi.nlm.nih.gov/pubmed/25757625

 

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Knowing the genetic vulnerability of bladder cancer for therapeutic intervention

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

A mutated gene called RAS gives rise to a signalling protein Ral which is involved in tumour growth in the bladder. Many researchers tried and failed to target and stop this wayward gene. Signalling proteins such as Ral usually shift between active and inactive states.

 

So, researchers next tried to stop Ral to get into active state. In inacvtive state Ral exposes a pocket which gets closed when active. After five years, the researchers found a small molecule dubbed BQU57 that can wedge itself into the pocket to prevent Ral from closing and becoming active. Now, BQU57 has been licensed for further development.

 

Researchers have a growing genetic data on bladder cancer, some of which threaten to overturn the supposed causes of bladder cancer. Genetics has also allowed bladder cancer to be reclassified from two categories into five distinct subtypes, each with different characteristics and weak spots. All these advances bode well for drug development and for improved diagnosis and prognosis.

 

Among the groups studying the genetics of bladder cancer are two large international teams: Uromol (named for urology and molecular biology), which is based at Aarhus University Hospital in Denmark, and The Cancer Genome Atlas (TCGA), based at institutions in Texas and Boston. Each team tackled a different type of cancer, based on the traditional classification of whether or not a tumour has grown into the muscle wall of the bladder. Uromol worked on the more common, earlier form, non-muscle-invasive bladder cancer, whereas TCGA is looking at muscle-invasive bladder cancer, which has a lower survival rate.

 

The Uromol team sought to identify people whose non-invasive tumours might return after treatment, becoming invasive or even metastatic. Bladder cancer has a high risk of recurrence, so people whose non-invasive cancer has been treated need to be monitored for many years, undergoing cystoscopy every few months. They looked for predictive genetic footprints in the transcriptome of the cancer, which contains all of a cell’s RNA and can tell researchers which genes are turned on or off.

 

They found three subgroups with distinct basal and luminal features, as proposed by other groups, each with different clinical outcomes in early-stage bladder cancer. These features sort bladder cancer into genetic categories that can help predict whether the cancer will return. The researchers also identified mutations that are linked to tumour progression. Mutations in the so-called APOBEC genes, which code for enzymes that modify RNA or DNA molecules. This effect could lead to cancer and cause it to be aggressive.

 

The second major research group, TCGA, led by the National Cancer Institute and the National Human Genome Research Institute, that involves thousands of researchers across USA. The project has already mapped genomic changes in 33 cancer types, including breast, skin and lung cancers. The TCGA researchers, who study muscle-invasive bladder cancer, have looked at tumours that were already identified as fast-growing and invasive.

 

The work by Uromol, TCGA and other labs has provided a clearer view of the genetic landscape of early- and late-stage bladder cancer. There are five subtypes for the muscle-invasive form: luminal, luminal–papillary, luminal–infiltrated, basal–squamous, and neuronal, each of which is genetically distinct and might require different therapeutic approaches.

 

Bladder cancer has the third-highest mutation rate of any cancer, behind only lung cancer and melanoma. The TCGA team has confirmed Uromol research showing that most bladder-cancer mutations occur in the APOBEC genes. It is not yet clear why APOBEC mutations are so common in bladder cancer, but studies of the mutations have yielded one startling implication. The APOBEC enzyme causes mutations early during the development of bladder cancer, and independent of cigarette smoke or other known exposures.

 

The TCGA researchers found a subset of bladder-cancer patients, those with the greatest number of APOBEC mutations, had an extremely high five-year survival rate of about 75%. Other patients with fewer APOBEC mutations fared less well which is pretty surprising.

 

This detailed knowledge of bladder-cancer genetics may help to pinpoint the specific vulnerabilities of cancer cells in different people. Over the past decade, Broad Institute researchers have identified more than 760 genes that cancer needs to grow and survive. Their genetic map might take another ten years to finish, but it will list every genetic vulnerability that can be exploited. The goal of cancer precision medicine is to take the patient’s tumour and decode the genetics, so the clinician can make a decision based on that information.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/29117162

 

https://www.ncbi.nlm.nih.gov/pubmed/27321955

 

https://www.ncbi.nlm.nih.gov/pubmed/28583312

 

https://www.ncbi.nlm.nih.gov/pubmed/24476821

 

https://www.ncbi.nlm.nih.gov/pubmed/28988769

 

https://www.ncbi.nlm.nih.gov/pubmed/28753430

 

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