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Archive for the ‘mRNA Therapeutics’ Category

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.

gcugaaaauguaacaggacucuuuaaagauuguaguaagguaaucacuggguuacauccuacacaggcaccuacacaccucaguguugacacuaaauucaaaacugaagguuuauguguugacauaccuggcauaccuaaggacaugaccuauagaagacucaucucuaugauggguuuuaaaaugaauuaucaaguuaaugguuacccuaacauguuuaucacccgcgaagaagcuauaagacauguacgugcauggauuggcuucgaugucgaggggugucaugcuacuagagaagcuguugguaccaauuuaccuuuacagcuagguuuuucuacagguguuaaccuaguugcuguaccuacagguuauguugauacaccuaauaauacagauuuuuccagaguuagugcuaaaccaccgccuggagaucaauuuaaacaccucauaccacuuauguacaaaggacuuccuuggaauguagugcguauaaagauuguacaaauguuaagugacacacuuaaaaaucucucugacagagucguauuugucuuaugggcacauggcuuugaguugacaucuaugaaguauuuugugaaaauaggaccugagcgcaccuguugucuaugugauagacgugccacaugcuuuuccacugcuucagacacuuaugccuguuggcaucauucuauuggauuugauuacgucuauaauccguuuaugauugauguucaacaaugggguuuuacagguaaccuacaaagcaaccaugaucuguauugucaaguccaugguaaugcacauguagcuaguugugaugcaaucaugacuaggugucuagcuguccacgagugcuuuguuaagcguguugacuggacuauugaauauccuauaauuggugaugaacugaagauuaaugcggcuuguagaaagguucaacacaugguuguuaaagcugcauuauuagcagacaaauucccaguucuucacgacauugguaacccuaaagcuauuaaguguguaccucaagcugauguagaauggaaguucuaugaugcacagccuuguagugacaaagcuuauaaaauagaagaauuauucuauucuuaugccacacauucugacaaauucacagaugguguaugccuauuuuggaauugcaaugucgauagauauccugcuaauuccauuguuuguagauuugacacuagagugcuaucuaaccuuaacuugccugguugugaugguggcaguuuguauguaaauaaacaugcauuccacacaccagcuuuugauaaaagugcuuuuguuaauuuaaaacaauuaccauuuuucuauuacucugacaguccaugugagucucauggaaaacaaguagugucagauauagauuauguaccacuaaagucugcuacguguauaacacguugcaauuuagguggugcugucuguagacaucaugcuaaugaguacagauuguaucucgaugcuuauaacaugaugaucucagcuggcuuuagcuuguggguuuacaaacaauuugauacuuauaaccucuggaacacuuuuacaagacuucag

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.

auggauuuguuuaugagaaucuucacaauuggaacuguaacuuugaagcaaggugaaaucaaggaugcuacuccuucagauuuuguucgcgcuacugcaacgauaccgauacaagccucacucccuuucggauggcuuauuguuggcguugcacuucuugcuguuuuucagagcgcuuccaaaaucauaacccucaaaaagagauggcaacuagcacucuccaaggguguucacuuuguuugcaacuugcuguuguuguuuguaacaguuuacucacaccuuuugcucguugcugcuggccuugaagccccuuuucucuaucuuuaugcuuuagucuacuucuugcagaguauaaacuuuguaagaauaauaaugaggcuuuggcuuugcuggaaaugccguuccaaaaacccauuacuuuaugaugccaacuauuuucuuugcuggcauacuaauuguuacgacuauuguauaccuuacaauaguguaacuucuucaauugucauuacuucaggugauggcacaacaaguccuauuucugaacaugacuaccagauuggugguuauacugaaaaaugggaaucuggaguaaaagacuguguuguauuacacaguuacuucacuucagacuauuaccagcuguacucaacucaauugaguacagacacugguguugaacauguuaccuucuucaucuacaauaaaauuguugaugagccugaagaacauguccaaauucacacaaucgacgguucauccggaguuguuaauccaguaauggaaccaauuuaugaugaaccgacgacgacuacuagcgugccuuuguaagcacaagcugaugaguacgaacuu

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.

auguacucauucguuucggaagagacagguacguuaauaguuaauagcguacuucuuuuucuugcuuucgugguauucuugcuaguuacacuagccauccuuacugcgcuucgauugugugcguacugcugcaauauuguuaacgugagucuuguaaaaccuucuuuuuacguuuacucucguguuaaaaaucugaauucuucuagaguuccugaucuucuggucuaaacgaacuaaauauuauauuaguuuuucuguuuggaacuuuaauuuuagcc

Membrane Protein · M

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

auggcagauuccaacgguacuauuaccguugaagagcuuaaaaagcuccuugaacaauggaaccuaguaauagguuuccuauuccuuacauggauuugucuucuacaauuugccuaugccaacaggaauagguuuuuguauauaauuaaguuaauuuuccucuggcuguuauggccaguaacuuuagcuuguuuugugcuugcugcuguuuacagaauaaauuggaucaccgguggaauugcuaucgcaauggcuugucuuguaggcuugauguggcucagcuacuucauugcuucuuucagacuguuugcgcguacgcguuccauguggucauucaauccagaaacuaacauucuucucaacgugccacuccauggcacuauucugaccagaccgcuucuagaaagugaacucguaaucggagcugugauccuucguggacaucuucguauugcuggacaccaucuaggacgcugugacaucaaggaccugccuaaagaaaucacuguugcuacaucacgaacgcuuucuuauuacaaauugggagcuucgcagcguguagcaggugacucagguuuugcugcauacagucgcuacaggauuggcaacuauaaauuaaacacagaccauuccaguagcagugacaauauugcuuugcuuguacaguaagugacaacag

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.

auguuucaucucguugacuuucagguuacuauagcagagauauuacuaauuauuaugaggacuuuuaaaguuuccauuuggaaucuugauuacaucauaaaccucauaauuaaaaauuuaucuaagucacuaacugagaauaaauauucucaauuagaugaagagcaaccaauggagauugauuaaacgaac

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.

augaaaauuauucuuuucuuggcacugauaacacucgcuacuugugagcuuuaucacuaccaagaguguguuagagguacaacaguacuuuuaaaagaaccuugcucuucuggaacauacgagggcaauucaccauuucauccucuagcugauaacaaauuugcacugacuugcuuuagcacucaauuugcuuuugcuuguccugacggcguaaaacacgucuaucaguuacgugccagaucaguuucaccuaaacuguucaucagacaagaggaaguucaagaacuuuacucuccaauuuuucuuauuguugcggcaauaguguuuauaacacuuugcuucacacucaaaagaaagacagaaugauugaacuuucauuaauugacuucuauuugugcuuuuuagccuuucugcuauuccuuguuuuaauuaugcuuauuaucuuuugguucucacuugaacugcaagaucauaaugaaacuugucacgccuaaacgaac

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.

augaaauuucuuguuuucuuaggaaucaucacaacuguagcugcauuucaccaagaauguaguuuacagucauguacucaacaucaaccauauguaguugaugacccguguccuauucacuucuauucuaaaugguauauuagaguaggagcuagaaaaucagcaccuuuaauugaauugugcguggaugaggcugguucuaaaucacccauucaguacaucgauaucgguaauuauacaguuuccuguuuaccuuuuacaauuaauugccaggaaccuaaauuggguagucuuguagugcguuguucguucuaugaagacuuuuuagaguaucaugacguucguguuguuuuagauuucaucuaaacgaacaaacuaaa

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:

augucugauaauggaccccaaaaucagcgaaaugcaccccgcauuacguuugguggacccucagauucaacuggcaguaaccagaauggagaacgcaguggggcgcgaucaaaacaacgucggccccaagguuuacccaauaauacugcgucuugguucaccgcucucacucaacauggcaaggaagaccuuaaauucccucgaggacaaggcguuccaauuaacaccaauagcaguccagaugaccaaauuggcuacuaccgaagagcuaccagacgaauucgugguggugacgguaaaaugaaagaucucaguccaagaugguauuucuacuaccuaggaacugggccagaagcuggacuucccuauggugcuaacaaagacggcaucauauggguugcaacugagggagccuugaauacaccaaaagaucacauuggcacccgcaauccugcuaacaaugcugcaaucgugcuacaacuuccucaaggaacaacauugccaaaaggcuucuacgcagaagggagcagaggcggcagucaagccucuucucguuccucaucacguagucgcaacaguucaagaaauucaacuccaggcagcaguaggggaacuucuccugcuagaauggcuggcaauggcggugaugcugcucuugcuuugcugcugcuugacagauugaaccagcuugagagcaaaaugucugguaaaggccaacaacaacaaggccaaacugucacuaagaaaucugcugcugaggcuucuaagaagccucggcaaaaacguacugccacuaaagcauacaauguaacacaagcuuucggcagacgugguccagaacaaacccaaggaaauuuuggggaccaggaacuaaucagacaaggaacugauuacaaacauuggccgcaaauugcacaauuugcccccagcgcuucagcguucuucggaaugucgcgcauuggcauggaagucacaccuucgggaacgugguugaccuacacaggugccaucaaauuggaugacaaagauccaaauuucaaagaucaagucauuuugcugaauaagcauauugacgcauacaaaacauucccaccaacagagccuaaaaaggacaaaaagaagaaggcugaugaaacucaagccuuaccgcagagacagaagaaacagcaaacugugacucuucuuccugcugcagauuuggaugauuucuccaaacaauugcaacaauccaugagcagugcugacucaacucaggccuaaacucaugcagaccacacaaggcag

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

caaucuuuaaucaguguguaacauuagggaggacuugaaagagccaccacauuuucaccgaggccacgcggaguacgaucgaguguacagugaacaaugcuagggagagcugccuauauggaagagcccuaauguguaaaauuaauuuuaguagugcuauccccaugugauuuuaauagcuucuuaggagaaugacaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa

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 »

Extracellular RNA and their carriers in disease diagnosis and therapy, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

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/

 

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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

4.1.3

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, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 4: Single Cell Genomics

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, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

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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Regulatory MicroRNAs in Aberrant Cholesterol Transport and Metabolism

Curator: Marzan Khan, B.Sc

Aberrant levels of lipids and cholesterol accumulation in the body lead to cardiometabolic disorders such as atherosclerosis, one of the leading causes of death in the Western World(1). The physical manifestation of this condition is the build-up of plaque along the arterial endothelium causing the arteries to constrict and resist a smooth blood flow(2). This obstructive deposition of plaque is merely the initiation of atherosclerosis and is enriched in LDL cholesterol (LDL-C) as well foam cells which are macrophages carrying an overload of toxic, oxidized LDL(2). As the condition progresses, the plaque further obstructs blood flow and creates blood clots, ultimately leading to myocardial infarction, stroke and other cardiovascular diseases(2). Therefore, LDL is referred to as “the bad cholesterol”(2).

Until now, statins are most widely prescribed as lipid-lowering drugs that inhibit the enzyme 3-hydroxy-3methylgutaryl-CoA reductase (HMGCR), the rate-limiting step in de-novo cholesterol biogenesis (1). But some people cannot continue with the medication due to it’s harmful side-effects(1). With the need to develop newer therapeutics to combat cardiovascular diseases, Harvard University researchers at Massachusetts General Hospital discovered 4 microRNAs that control cholesterol, triglyceride, and glucose homeostasis(3)

MicroRNAs are non-coding, regulatory elements approximately 22 nucleotides long, with the ability to control post-transcriptional expression of genes(3). The liver is the center for carbohydrate and lipid metabolism. Stringent regulation of endogenous LDL-receptor (LDL-R) pathway in the liver is crucial to maintain a minimal concentration of LDL particles in blood(3). A mechanism whereby peripheral tissues and macrophages can get rid of their excess LDL is mediated by ATP-binding cassette, subfamily A, member 1 (ABCA1)(3). ABCA1 consumes nascent HDL particles- dubbed as the “good cholesterol” which travel back to the liver for its contents of triglycerides and cholesterol to be excreted(3).

Genome-wide association studies (GWASs) meta-analysis carried out by the researchers disclosed 4 microRNAs –(miR-128-1, miR-148a, miR-130b, and miR-301b) to lie close to single-nucleotide polymorphisms (SNPs) associated with abnormal metabolism and transport of lipids and cholesterol(3) Experimental analyses carried out on relevant cell types such as the liver and macrophages have proven that these microRNAs bind to the 3’ UTRs of both LDL-R and ABCA1 transporters, and silence their activity. Overexpression of miR-128-1 and miR148a in mice models caused circulating HDL-C to drop. Corroborating the theory under investigation further, their inhibition led to an increased clearance of LDL from the blood and a greater accumulation in the liver(3).

That the antisense inhibition of miRNA-128-1 increased insulin signaling in mice, propels us to hypothesize that abnormal expression of miR-128-1 might cause insulin resistance in metabolic syndrome, and defective insulin signaling in hepatic steatosis and dyslipidemia(3)

Further examination of miR-148 established that Liver-X-Receptor (LXR) activation of the Sterol regulatory element-binding protein 1c (SREBP1c), the transcription factor responsible for controlling  fatty acid production and glucose metabolism, also mediates the expression of miR-148a(4,5) That the promoter region of miR-148 contained binding sites for SREBP1c was shown by chromatin immunoprecipitation combined with massively parallel sequencing (ChIP-seq)(4). More specifically, SREBP1c attaches to the E-box2, E-box3 and E-box4 elements on miR-148-1a promoter sites to control its expression(4).

Earlier, the same researchers- Andres Naars and his team had found another microRNA called miR-33 to block HDL generation, and this blockage to reverse upon antisense targeting of miR-33(6).

These experimental data substantiate the theory of miRNAs being important regulators of lipoprotein receptors and transporter proteins as well as underscore the importance of employing antisense technologies to reverse their gene-silencing effects on LDL-R and ABCA1(4). Such a therapeutic approach, that will consequently lower LDL-C and promote HDL-C seems to be a promising strategy to treat atherosclerosis and other cardiovascular diseases(4).

References:

1.Goedeke L1,Wagschal A2,Fernández-Hernando C3, Näär AM4. miRNA regulation of LDL-cholesterol metabolism. Biochim Biophys Acta. 2016 Dec;1861(12 Pt B):. Biochim Biophys Acta. 2016 Dec;1861(12 Pt B):2047-2052

https://www.ncbi.nlm.nih.gov/pubmed/26968099

2.MedicalNewsToday. Joseph Nordgvist. Atherosclerosis:Causes, Symptoms and Treatments. 13.08.2015

http://www.medicalnewstoday.com/articles/247837.php

3.Wagschal A1,2, Najafi-Shoushtari SH1,2, Wang L1,2, Goedeke L3, Sinha S4, deLemos AS5, Black JC1,6, Ramírez CM3, Li Y7, Tewhey R8,9, Hatoum I10, Shah N11, Lu Y11, Kristo F1, Psychogios N4, Vrbanac V12, Lu YC13, Hla T13, de Cabo R14, Tsang JS11, Schadt E15, Sabeti PC8,9, Kathiresan S4,6,8,16, Cohen DE7, Whetstine J1,6, Chung RT5,6, Fernández-Hernando C3, Kaplan LM6,10, Bernards A1,6,16, Gerszten RE4,6, Näär AM1,2. Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis. . Nat Med.2015 Nov;21(11):1290

https://www.ncbi.nlm.nih.gov/pubmed/26501192

4.Goedeke L1,2,3,4, Rotllan N1,2, Canfrán-Duque A1,2, Aranda JF1,2,3, Ramírez CM1,2, Araldi E1,2,3,4, Lin CS3,4, Anderson NN5,6, Wagschal A7,8, de Cabo R9, Horton JD5,6, Lasunción MA10,11, Näär AM7,8, Suárez Y1,2,3,4, Fernández-Hernando C1,2,3,4. MicroRNA-148a regulates LDL receptor and ABCA1 expression to control circulating lipoprotein levels. Nat Med. 2015 Nov;21(11):1280-9.

https://www.ncbi.nlm.nih.gov/pubmed/26437365

5.Eberlé D1, Hegarty B, Bossard P, Ferré P, Foufelle F. SREBP transcription factors: master regulators of lipid homeostasis. Biochimie. 2004 Nov;86(11):839-48.

https://www.ncbi.nlm.nih.gov/pubmed/15589694

6.Harvard Medical School. News. MicoRNAs and Metabolism.

https://hms.harvard.edu/news/micrornas-and-metabolism

7. MGH – Four microRNAs identified as playing key roles in cholesterol, lipid metabolism

http://www.massgeneral.org/about/pressrelease.aspx?id=1862

 

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

 

  • Cardiovascular Diseases, Volume Three: Etiologies of Cardiovascular Diseases: Epigenetics, Genetics and Genomics,

on Amazon since 11/29/2015

http://www.amazon.com/dp/B018PNHJ84

 

HDL oxidation in type 2 diabetic patients

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/27/hdl-oxidation-in-type-2-diabetic-patients/

 

HDL-C: Target of Therapy – Steven E. Nissen, MD, MACC, Cleveland Clinic vs Peter Libby, MD, BWH

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/11/07/hdl-c-target-of-therapy-steven-e-nissen-md-macc-cleveland-clinic-vs-peter-libby-md-bwh/

 

High-Density Lipoprotein (HDL): An Independent Predictor of Endothelial Function & Atherosclerosis, A Modulator, An Agonist, A Biomarker for Cardiovascular Risk

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/03/31/high-density-lipoprotein-hdl-an-independent-predictor-of-endothelial-function-artherosclerosis-a-modulator-an-agonist-a-biomarker-for-cardiovascular-risk/

 

Risk of Major Cardiovascular Events by LDL-Cholesterol Level (mg/dL): Among those treated with high-dose statin therapy, more than 40% of patients failed to achieve an LDL-cholesterol target of less than 70 mg/dL.

Reporter: Aviva Lev-Ari, PhD., RN

https://pharmaceuticalintelligence.com/2014/07/29/risk-of-major-cardiovascular-events-by-ldl-cholesterol-level-mgdl-among-those-treated-with-high-dose-statin-therapy-more-than-40-of-patients-failed-to-achieve-an-ldl-cholesterol-target-of-less-th/

 

LDL, HDL, TG, ApoA1 and ApoB: Genetic Loci Associated With Plasma Concentration of these Biomarkers – A Genome-Wide Analysis With Replication

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/12/18/ldl-hdl-tg-apoa1-and-apob-genetic-loci-associated-with-plasma-concentration-of-these-biomarkers-a-genome-wide-analysis-with-replication/

 

Two Mutations, in the PCSK9 Gene: Eliminates a Protein involved in Controlling LDL Cholesterol

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/04/15/two-mutations-in-a-pcsk9-gene-eliminates-a-protein-involve-in-controlling-ldl-cholesterol/

Artherogenesis: Predictor of CVD – the Smaller and Denser LDL Particles

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/11/15/artherogenesis-predictor-of-cvd-the-smaller-and-denser-ldl-particles/

 

A Concise Review of Cardiovascular Biomarkers of Hypertension

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/04/25/a-concise-review-of-cardiovascular-biomarkers-of-hypertension/

 

Triglycerides: Is it a Risk Factor or a Risk Marker for Atherosclerosis and Cardiovascular Disease ? The Impact of Genetic Mutations on (ANGPTL4) Gene, encoder of (angiopoietin-like 4) Protein, inhibitor of Lipoprotein Lipase

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

https://pharmaceuticalintelligence.com/2016/03/13/triglycerides-is-it-a-risk-factor-or-a-risk-marker-for-atherosclerosis-and-cardiovascular-disease-the-impact-of-genetic-mutations-on-angptl4-gene-encoder-of-angiopoietin-like-4-protein-that-in/

 

Excess Eating, Overweight, and Diabetic

Larry H Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/15/excess-eating-overweight-and-diabetic/

 

Obesity Issues

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/12/obesity-issues/

 

Read Full Post »

Dr. Doudna: RNA synthesis capabilities of Synthego’s team represent a significant leap forward for Synthetic Biology, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Dr. Doudna: RNA synthesis capabilities of Synthego’s team represent a significant leap forward for Synthetic Biology

Reporter: Aviva Lev-Ari, PhD, RN

 

Synthego Raises $41 Million From Investors, Including a Top Biochemist

Synthego also drew in Dr. Doudna, who had crossed paths with the company’s head of synthetic biology at various industry conferences. According to Mr. Dabrowski, the money from her trust represents the single-biggest check from a non-institutional investor that the start-up has raised.

Synthego’s new funds will help the company take its products to a more global customer base, as well as broaden its offerings. The longer-term goal, Mr. Dabrowski said, is to help fully automate biotech research and take care of much of the laboratory work that scientists currently handle themselves.

The model is cloud technology, where companies rent out powerful remote server farms to handle their computing needs rather than rely on their own hardware.

“We’ll be able to do their full research workflow,” he said. “If you look at how cloud computing developed, it used to be that every company handled their server farm. Now it’s all handled in the cloud.”

SOURCE

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

UPDATED – Status “Interference — Initial memorandum” – CRISPR/Cas9 – The Biotech Patent Fight of the Century: UC, Berkeley and Broad Institute @MIT

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/06/status-interference-initial-memorandum-crisprcas9-the-biotech-patent-fight-of-the-century/

 

Read Full Post »

The Complex Business Model for of the mRNA Therapeutics Sector of the Biotech Industry

Curator & Reporter: Aviva Lev-Ari, PhD, RN

 

On its way for an IPO: mRNA platform, Moderna, Immune Oncology is recruiting 100 new Life Scientists in Cambridge, MA

Curator: Aviva Lev-Ari, PhD, RN

 

Moderna Therapeutics Deal with Merck: Are Personalized Vaccines here?

Curator & Reporter: Stephen J. Williams, Ph.D.

 

at #JPM16 – Moderna Therapeutics turns away an extra $200 million: with AstraZeneca (collaboration) & with Merck ($100 million investment)

Reporter: Aviva Lev-Ari, PhD, RN

 

Licensing Agreements for CRISPR/Cas9 Genome Editing Technology Patent

Curator: Aviva Lev-Ari, PhD, RN

 

Gritstone Oncology

 

 

Neon Therapeutics

 

Genentech dives into mRNA, betting $310M on BioNTech’s personalized cancer vaccine tech

 

The complexity of the technologies involved in development of mRNA Therapies is demonstrated by the Platform components and the ecosystem put in place by Moderna Therapeutics Inc., the leading venture in the mRNA Therapeutics Sector of the Biotech Industry

 

Moderna Therapeutics Inc.Corporate Facts

The Moderna Ecosystem

Messenger RNA (mRNA) Therapeutics™ hold the potential to transform medicine across multiple drug modalities and therapeutic areas. As the first mover and leading company in the space, our responsibility is to simultaneously advance promising internal development programs, while also mobilizing an entire ecosystem capable of propelling the field forward for patients.

Moderna Ventures

We form wholly-owned ventures to focus dedicated resources and staff in key disease areas where high unmet medical needs demand safe, efficacious and innovative therapies.

  • Onkaido, the first of Moderna’s ventures, formed as a wholly-owned subsidiary to develop mRNA drugs in oncology, is utilizing all of the tools and modalities developed at Moderna.
  • Valera, Moderna’s second venture, is focused on the advancement of vaccines and therapeutics for the prevention and treatment of viral and bacterial infectious diseases.
  • Elpidera, Moderna’s third venture, is focused exclusively on the advancement of mRNA-based treatments for rare diseases.
  • Caperna, Moderna’s fourth venture, is focused exclusively on the advancement of personalized vaccines for the treatment of cancer.

We are incubating additional ventures in diverse therapeutic areas, leveraging a cross-section of relevant modalities.

External Partnerships

Moderna is working with world leaders in key therapeutic areas where our mRNA Therapeutics™ can potentially have a profound impact on patients’ lives. We enjoy close and productive strategic agreements with:

  • AstraZeneca — mRNA Therapeutics focused on cardiovascular, metabolic and renal diseases as well as cancer;
  • Alexion Pharmaceuticals — mRNA Therapeutics for rare diseases;
  • Merck — mRNA-based vaccines and passive immunity treatments against viral diseases, as well as mRNA-based personalized cancer vaccines for multiple types of cancer;
  • Vertex — mRNA Therapeutics for the treatment of cystic fibrosis;
  • DARPA (the Defense Advanced Research Projects Agency) — mRNA-based antibody-producing drugs to protect against known and unknown emerging infectious diseases and engineered biological threats;
  • Bill & Melinda Gates Foundation — Combination of mRNA-based antibody therapeutics to help prevent HIV;
  • Karolinska Institutet and Karolinska University Hospital — mRNA Therapeutics to treat serious diseases; and
  • Institut Pasteur — mRNA-based drugs and vaccines to fight infectious diseases.

SOURCE

http://www.modernatx.com/our-business-model

Drug Modalities

Building from our mRNA core expression platform, we have created a new scale of drug discovery and development that enables a series of new drug modalities. Each modality represents a distinct approach to using the mRNA platform to encode proteins that achieve a therapeutic benefit, enabling us to develop numerous drug candidates across a wide array of therapeutic areas.

Vaccines

Vaccines are substances that teach the immune system to rapidly recognize and destroy invading pathogens such as bacteria or viruses, preparing the body’s adaptive immunity for future exposure to the pathogen. Historically, vaccines have introduced immune-activating markers from pathogens into the body. Conversely, Moderna is developing mRNA-based vaccines that enable the body to produce and present immunogenic proteins to the immune system.

Moderna is also developing mRNA-based personalized cancer vaccines to prime the immune system to recognize cancer cells and mount a strong, tailored response to each individual patient’s cancer. Moderna’s technology allows for a rapid turn-around time in production of these unique mRNA vaccines.

Intracellular/Transmembrane

Many diseases are caused by defects in proteins that function inside cells. Existing methods of protein-based therapy do not allow for proteins to reach the intracellular space, and as such are unable to replace the defective, disease-causing proteins within cells. Moderna’s platform allows for the development of mRNA therapies that can stimulate production of intracellular proteins as well as transmembrane proteins. This could potentially lead to a novel approach to treating a vast array of rare genetic and other diseases caused by intracellular protein defects.

Intratumoral

Many targets for the treatment of cancer have been identified but their therapeutic potential has been limited by either the inability to access these targets, or by systemic toxicities. Moderna’s platform allows for localized expression of therapeutic proteins within the tumor microenvironment.

Secreted antibodies

Antibodies are secreted proteins that bind to and inhibit specific targets. Moderna’s platform has the potential to stimulate the body’s own cells to produce specific antibodies that can bind to cellular targets.

Secreted proteins

Proteins are large, complex molecules that have many critical functions both inside and outside of cells. Moderna’s platform stimulates cells to produce and secrete proteins that can have a therapeutic benefit through systemic exposure.

SOURCE

http://www.modernatx.com/about-our-pipeline/drug-modalities

Moderna’s mRNA Platform

At Moderna, we are pioneering the development of a new class of drugs made of messenger RNA (mRNA). This novel drug platform builds on the discovery that modified mRNA can direct the body’s cellular machinery to produce nearly any protein of interest, from native proteins to antibodies and other entirely novel protein constructs that can have therapeutic activity inside and outside of cells.

Our efforts are helping Moderna and the industry to flatten the mRNA learning curve across the full breadth of competencies needed to drive the platform forward, including chemistry, mRNA biology, formulation, process development, automation and high-throughput production, quality, and Good Manufacturing Practice (GMP) manufacturing.

SOURCE

http://www.modernatx.com/our-mrna-platform

Read Full Post »

miRNA Therapeutic Promise

Curator: Larry H. Bernstein, MD, FCAP

 

MicroRNA Expression Could Be Key to Leukemia Treatment

http://www.genengnews.com/gen-news-highlights/microrna-expression-could-be-key-to-leukemia-treatment/81252662/

MicroRNA Expression Could Be Key to Leukemia Treatment

Generalized gene regulation mechanisms of miRNAs. [NIH]

 

Increasingly, cancer researchers are discovering novel biological pathways that regulate the expression of various genes that are often strongly associated with tumorigenesis. These new molecular mechanisms represent important potential therapeutic targets for aggressive and difficult-to-treat cancers. In particular, microRNAs (miRNAs)—small, noncoding genetic material that regulates gene expression—have steadily become implicated in the progression of some cancers.

Now, researchers at the University of Cincinnati (UC) have found a particular signaling route for a microRNA, miR-22, that they believe leads to targets for acute myeloid leukemia (AML), the most common type of fast-growing cancer of the blood and bone marrow.

The findings from this study were published recently in Nature Communications in an article entitled “miR-22 Has a Potent Anti-Tumour Role with Therapeutic Potential in Acute Myeloid Leukaemia.”

Structure of mi-22 miccroRNA. [Ppgardne at el., via Wikimedia Commons]

Increasingly, cancer researchers are discovering novel biological pathways that regulate the expression of various genes that are often strongly associated with tumorigenesis. These new molecular mechanisms represent important potential therapeutic targets for aggressive and difficult-to-treat cancers. In particular, microRNAs (miRNAs)—small, noncoding genetic material that regulates gene expression—have steadily become implicated in the progression of some cancers.

Now, researchers at the University of Cincinnati (UC) have found a particular signaling route for a microRNA, miR-22, that they believe leads to targets for acute myeloid leukemia (AML), the most common type of fast-growing cancer of the blood and bone marrow.

The findings from this study were published recently in Nature Communications in an article entitled “miR-22 Has a Potent Anti-Tumour Role with Therapeutic Potential in Acute Myeloid Leukaemia.”

“MicroRNAs make up a class of small, noncoding internal RNAs that control a gene’s job, or expression, by directing their target messaging RNAs, or mRNAs, to inhibit or stop. Cellular organisms use mRNA to convey genetic information,” explained senior study author Jianjun Chen, Ph.D., associate professor in the department of cancer biology at the UC College of Medicine. “Previous research has shown that microRNA miR-22 is linked to breast cancer and other blood disorders which sometimes turn into AML, but we found in this study that it could be an essential anti-tumor gatekeeper in AML when it is down-regulated, meaning its function is minimized.”

AML—most common type of acute leukemia—arises when the bone marrow begins to make blasts, cells that have not yet completely matured. These blast cells typically develop into white blood cells; however, in AML the cells do not develop and are unable to aid in warding off infections. In the current study, the UC team describes how altering the expression of miR-22 affected AML pathogenesis.

“When we forced miR-22 expression, we saw difficulty in leukemia cells developing, growing, and thriving. miR-22 targets multiple cancer-causing genes (CRTC1, FLT3, and MYCBP) and blocks certain pathways (CREB and MYC),” Dr. Chen noted. “The downregulation, or decreased output, of miR-22 in AML, is caused by the loss of the number of DNA being copied and/or stopping their expression through a pathway called TET1/GFI1/EZH2/SIN3A. Also, nanoparticles carrying miR-22 DNA oligonucleotides (short nucleic acid molecules) prevented leukemia advancement.”

The investigators conducted the study using bone marrow transplant samples and animal models. The researchers showed that the ten-eleven translocation proteins (TET1/2/3) in mammals helped to control genetic expression in normal developmental processes. This was in sharp contrast to mutations that cause function loss and tumor-slowing with TET2, which has been observed previously in blood and stem cell cancers.

“We recently reported that TET1 plays an essential cancer generating role in certain AML where it activates expression of homeobox genes, which are a large family of similar genes that direct the formation of many body structures during early embryonic development,” remarked Dr. Chen. “However, it is unknown whether TET1 can also function as a repressor for cellular function in cancer, and its role in microRNA expression has rarely been studied.”

Dr. Chen added that these findings are important in targeting a cancer that is both common and fatal, stating that “the majority of patients with ALM usually don’t survive longer than 5 years, even with chemotherapy, which is why the development of new effective therapies based on the underlying mechanisms of the disease is so important.”

“Our study uncovers a previously unappreciated signaling pathway (TET1/GFI1/EZH2/SIN3A/miR-22/CREB-MYC) and provides new insights into genetic mechanisms causing and progressing AML and also highlights the clinical potential of miR-22-based AML therapy. More research on this pathway and ways to target it are necessary,” Dr. Chen concluded.

 

miR-22 has a potent anti-tumour role with therapeutic potential in acute myeloid leukaemia

Xi JiangChao HuStephen ArnovitzJason BugnoMiao YuZhixiang ZuoPing Chen, et al.
Nature Communications 26 Apr 2016; 7(11452).    http://dx.doi.org:/doi:10.1038/ncomms11452

MicroRNAs are subject to precise regulation and have key roles in tumorigenesis. In contrast to the oncogenic role of miR-22 reported in myelodysplastic syndrome (MDS) and breast cancer, here we show that miR-22 is an essential anti-tumour gatekeeper in de novo acute myeloid leukaemia (AML) where it is significantly downregulated. Forced expression of miR-22 significantly suppresses leukaemic cell viability and growth in vitro, and substantially inhibits leukaemia development and maintenance in vivo. Mechanistically, miR-22 targets multiple oncogenes, including CRTC1, FLT3 and MYCBP, and thus represses the CREB and MYC pathways. The downregulation of miR-22 in AML is caused by TET1/GFI1/EZH2/SIN3A-mediated epigenetic repression and/or DNA copy-number loss. Furthermore, nanoparticles carrying miR-22 oligos significantly inhibit leukaemia progression in vivo. Together, our study uncovers a TET1/GFI1/EZH2/SIN3A/miR-22/CREB-MYC signalling circuit and thereby provides insights into epigenetic/genetic mechanisms underlying the pathogenesis of AML, and also highlights the clinical potential of miR-22-based AML therapy.

 

As one of the most common and fatal forms of hematopoietic malignancies, acute myeloid leukaemia (AML) is frequently associated with diverse chromosome translocations (for example t(11q23)/MLL-rearrangements, t(15;17)/PML-RARA and t(8;21)/AML1-ETO) and molecular abnormalities (for example, internal tandem duplications of FLT3 (FLT3-ITD) and mutations in nucleophosmin (NPM1c+))1. Despite intensive chemotherapies, the majority of patients with AML fail to survive longer than 5 years2, 3. Thus, development of effective therapeutic strategies based on a better understanding of the molecular mechanisms underlying the pathogenesis of AML is urgently needed.

MicroRNAs (miRNAs) are a class of small, non-coding RNAs that post-transcriptionally regulate gene expression4. Individual miRNAs may play distinct roles in cancers originating from different tissues or even from different lineages of hematopoietic cells4. It is unclear whether a single miRNA can play distinct roles between malignancies originating from the same hematopoietic lineage, such as de novo AML and myelodysplastic syndrome (MDS). Although around 30% of MDS cases transform to AML, the genetic and epigenetic landscapes of MDS or MDS-derived AML are largely different from those of de novo AML5, 6. MDS and MDS-derived AML are more responsive to hypomethylating agents than de novo AML7. The molecular mechanisms underlying the distinct pathogenesis and drug response between MDS (or MDS-derived AML) and de novo AML remain unclear.

The ten-eleven translocation (Tet1/2/3) proteins play critical transcriptional regulatory roles in normal developmental processes as activators or repressors8, 9, 10. In contrast to the frequent loss-of-function mutations and tumour-suppressor role of TET2 observed in hematopoietic malignancies11, 12, 13, we recently reported that TET1 plays an essential oncogenic role in MLL-rearranged AML where it activates expression of homeobox genes14. However, it is unknown whether TET1 can also function as a transcriptional repressor in cancer. Moreover, Tet1-mediated regulation of miRNA expression has rarely been studied10.

In the present study, we demonstrate that miR-22, an oncogenic miRNA reported in breast cancer and MDS15, 16, is significantly downregulated in most cases of de novo AML due to TET1/GFI1/EZH2/SIN3A-mediated epigenetic repression and/or DNA copy-number loss. miR-22 functions as an essential anti-tumour gatekeeper in various AML and holds great therapeutic potential to treat AML.

 

The downregulation of miR-22 in de novo AML

Through Exiqon miRNA array profiling, we previously identified a set of miRNAs, such as miR-150, miR-148a, miR-29a, miR-29b, miR-184, miR-342, miR-423 and miR-22, which are significantly downregulated in AML compared with normal controls17. Here we showed that among all the above miRNAs, miR-150 and especially miR-22 exhibited the most significant and consistent inhibitory effect on MLL-AF9-induced cell immortalization in colony-forming/replating assays (CFA) (Supplementary Fig. 1a). In contrast to the reported upregulation of miR-22 in MDS16, our original microarray data17 (Fig. 1a,b) and new quantitative PCR-independent validation data (Supplementary Fig. 1b) demonstrated a significant and global downregulation of miR-22 in de novo AML relative to normal controls. Notably, miR-22 is significantly downregulated in AML samples (P<0.05) compared with all three sub-populations of normal control cells, that is, normal CD34+ hematopoietic stem/progenitor cells (HSPCs), CD33+ myeloid progenitor cells, or mononuclear cells (MNCs) (Fig. 1a). Expression of miR-22 is significantly downregulated in all or the majority of individual subsets of AML samples than in the normal CD33+ or CD34+ cell samples (Fig. 1b).

Figure 1: miR-22 inhibits AML cell transformation and leukemogenesis.

miR-22 inhibits AML cell transformation and leukemogenesis.

(a,b) Exiqon microRNA profiling assay showed that miR-22 is significantly (P<0.05) downregulated in the entire set of AML set (n=85) (a) or each individual subset (b), relative to normal controls. The expression data were log(2) transformed and mean-centred. Mean±s.e.m. values were shown. (c) Comparison of effects of in-house miR-22, miR-22_Song16 and miR-22 mutant (miR-22mut; see the mutation sequence at the top) on MLL-AF9-induced colony forming. CFAs were performed using mouse BM progenitor (Lin) cells transduced with MSCV-neo+MSCV-PIG (Ctrl), MSCV-neo-MLL-AF9+MSCV-PIG (MLL-AF9), or MSCV-neo-MLL-AF9+MSCV-PIG-miR-22/miR-22_Song/miR-22mut. (d) Effects of miR-22 on the colony forming induced by multiple fusion genes. CFA was performed using wild-type BM progenitor cells co-transduced with MSCV-neo-MLL-AF9 (MA9), -MLL-AF10 (MA10), -PML-RARA (PR) or –AML1-ETO9a(AE9a)19, together with MSCV-PIG (Ctrl) or MSCV-PIG-miR-22 (+miR-22), as well as miR-22−/− BM progenitors co-transduced with individual fusion genes and MSCV-PIG. Colony counts (mean±s.d.) of the second round of plating are shown. *P<0.05; **P<0.01. (e,f) Effect of miR-22 on MLL-AF9-induced primary leukemogenesis. Kaplan–Meier curves are shown for six cohorts of transplanted mice including MSCVneo+MSCV-PIG (Ctrl; n=5), MSCVneo+MSCV-PIG-miR-22 (miR-22; n=5), MSCVneo-MLL-AF9+MSCV-PIG (MA9; n=8), MSCVneo-MLL-AF9+MSCV-PIG-miR-150 (MA9+miR-150, n=6), MSCVneo-MLL-AF9+MSCV-PIG-miR-22 (MA9+miR-22; n=10) and MSCVneo-MLL-AF9+MSCV-PIG-miR-22mutant (MA9+miR-22mut; n=5) (e); Wright–Giemsa stained PB and bone marrow (BM), and hematoxylin and eosin (H&E) stained spleen and liver of the primary BMT recipient mice at the end point are shown (f). (g) Effect of miR-22 on MLL-AF10-induced primary leukemogenesis. Kaplan–Meier curves are shown for two cohorts of transplanted mice including MSCVneo-MLL-AF10+MSCV-PIG (MA10; n=5) and MSCVneo-MLL-AF10+MSCV-PIG-miR-22 (MA10+miR-22; n=5). (h) miR-22 knockout promotes AE9a-induced leukemogenesis. Kaplan–Meier curves are shown for mice transplanted with wild-type or miR-22−/− BM progenitor cells transduced MSCV-PIG-AE9a (n=5 for each group). The P values were generated by t-test (ad) or log-rank test (e,g,h).

To rule out the possibility that the inhibitory effect of miR-22 shown in Supplementary Fig. 1a was due to a non-specific effect of our miR-22 construct, we included the MSCV-PIG-miR-22 construct from Song et al.16 in a repeated CFA. Both miR-22 constructs dramatically inhibited MLL-AF9-induced colony formation (Fig. 1c). As the ‘seed’ sequences at the 5′ end of individual miRNAs are essential for the miRNA-target binding18, we also mutated the 6-bases ‘seed’ sequence of miR-22 and found that the miR-22 mutant did not inhibit colony formation anymore (Fig. 1c). In human AML cells, forced expression of miR-22, but not miR-22 mutant, significantly inhibited cell viability and growth/proliferation, while promoting apoptosis (Supplementary Fig. 1c,d).

Furthermore, as miR-22 is globally downregulated in all major types of AML (Fig. 1b), we also investigated the role of miR-22 in colony formation induced by other oncogenic fusion genes, including MLL-AF10/t(10;11), PML-RARA/t(15;17) and AML1-ETO9a/t(8;21) (ref. 19). As expected, forced expression of miR-22 significantly inhibited colony formation induced by all individual oncogenic fusions; conversely, miR-22 knockout20 significantly enhanced colony forming (Fig. 1d). These results suggest that miR-22 likely plays a broad anti-tumour role in AML.

In accordance with the potential anti-tumour function of miR-22 in AML, miR-22 was expressed at a significantly higher level (P<0.05) in human normal CD33+ myeloid progenitor cells than in more immature CD34+ HSPCs or MNC cells (a mixed population containing both primitive progenitors and committed cells) (Fig. 1a,b), implying that miR-22 is upregulated during normal myelopoiesis. Similarly, we showed that miR-22 was also expressed at a significantly higher level in mouse normal bone marrow (BM) myeloid (Gr-1+/Mac-1+) cells, relative to lineage negative (Lin) progenitor cells, long-term hematopoietic stem cells (LT-HSCs), short-term HSCs (ST-HSCs), and committed progenitors (CPs) (Supplementary Fig. 1e), further suggesting that miR-22 is upregulated in normal myelopoiesis.

The anti-tumour effect of miR-22 in the pathogenesis of AML

Through bone marrow transplantation (BMT) assays, we showed that forced expression of miR-22 (but not miR-22 mutant) dramatically blocked MLL-AF9 (MA9)-mediated leukemogenesis in primary BMT recipient mice, with a more potent inhibitory effect than miR-150 (Fig. 1e;Supplementary Fig. 2a). All MA9+miR-22 mice exhibited normal morphologies in peripheral blood (PB), BM, spleen and liver tissues (Fig. 1f), with a substantially reduced c-Kit+ blast cell population in BM (Supplementary Fig. 2b). Forced expression of miR-22 also almost completely inhibited leukemogenesis induced by MLL-AF10 (Fig. 1g; Supplementary Fig. 2a). Conversely, miR-22 knockout significantly promoted AML1-ETO9a (AE9a)-induced AML (Fig. 1h). Thus, the repression of miR-22 is critical for the development of primary AML. Notably, forced expression of miR-22 inMLL-AF9 and MLL-AF10 leukaemia mouse models caused only a 2–3-fold increase in miR-22 expression level (Supplementary Fig. 2a), in a degree comparable to the difference in miR-22 expression levels between human AML samples and normal controls (Fig. 1a), suggesting that a 2–3-fold change in miR-22 expression level appears to be able to exert significant physiological or pathological effects.

To examine whether the maintenance of AML is also dependent on the repression of miR-22, we performed secondary BMT assays. Forced expression of miR-22 remarkably inhibited progression of MLL-AF9-, AE9a– or FLT3-ITD/NPM1c+-induced AML in secondary recipient mice (Fig. 2a–d), resulting in largely normal morphologies in PB, BM, spleen and liver tissues (Fig. 2b;Supplementary Fig. 2c). Collectively, our findings demonstrate that miR-22 is a pivotal anti-tumour gatekeeper in both development and maintenance of various AML.

Figure 2: Effect of miR-22 on the maintenance of AML in vivo.

Effect of miR-22 on the maintenance of AML in vivo.

(a,b) Effect of miR-22 on the maintenance of MLL-AF9-induced AML in secondary BMT recipient mice. The secondary BMT recipients were transplanted with BM blast cells from the primary MLL-AF9 AML mice retrovirally transduced with MSCV-PIG+MSCVneo (MA9-AML+Ctrl; n=7) or MSCV-PIG+MSCVneo-miR-22 (MA9-AML+miR-22; n=10). Kaplan–Meier curves (a) and Wright–Giemsa or H&E-stained PB, BM, spleen and liver (b) of the secondary leukaemic mice are shown. (c,d) Effect of miR-22 on the maintenance/progression of AML1-ETO9a (AE9a)-induced AML (c) or FLT3-ITD/NPM1c+-induced AML (d) in secondary BMT recipient mice (n=5 for each group). Kaplan–Meier curves and P values (log-rank test) are shown.

 

Identification of critical target genes of miR-22 in AML

To identify potential targets of miR-22 in AML, we performed a series of data analysis. Analysis of In-house_81S (ref. 21) and TCGA_177S (ref. 22) data sets revealed a total of 999 genes exhibiting significant inverse correlations with miR-22 in expression. Of them, 137 genes, including 21 potential targets of miR-22 as predicted by TargetScan18 (Supplementary Table 1), were significantly upregulated in both human and mouse AML compared with normal controls as detected in two additional in-house data sets14, 23. Among the 21 potential targets, CRTC1, ETV6and FLT3 are known oncogenes24, 25, 26, 27, 28, 29. We then focused on these three genes, along with MYCBP that encodes the MYC-binding protein and is an experimentally validated target of miR-22 (ref. 30) although due to a technical issue it was not shown in the 21-gene list (Supplementary Table 1), for further studies.

As expected, all four genes were significantly downregulated in expression by ectopic expression of miR-22 in human MONOMAC-6/t(9;11) cells (Fig. 3a). The coincidence of downregulation of those genes and upregulation of miR-22 was also observed in mouse MLL-ENL-ERtm cells, a leukaemic cell line with an inducible MLL-ENL derivative31, when MLL-ENL was depleted by 4-hydroxy-tamoxifen (4-OHT) withdrawal (Fig. 3b; Supplementary Fig. 3a). While MLL-AF9 remarkably promoted expression of those four genes in mouse BM progenitor cells, co-expressed miR-22 reversed the upregulation (Fig. 3c). In leukaemia BM blast cells of mice with MLL-AF9-induced AML, the expression of Crtc1, Flt3 and Mycbp, but not Etv6, was significantly downregulated by co-expressed miR-22 (but not by miR-22 mutant) (Fig. 3d). Because miR-22-mediated downregulation of Etv6 could be observed only in the in vitro models (Fig. 3a–c), but not in the in vivo model (Fig. 3d), which was probably due to the difference between in vitro and in vivo microenvironments, we decided to focus on the three target genes (that is, Crtc1, Flt3 and Mycbp) that showed consistent patterns between in vitro and in vivo for further studies. The repression of Crtc1, Flt3 and Mycbpwas also found in leukaemia BM cells of mice with AE9a or FLT3-ITD/NPM1c+-induced AML (Fig. 3e,f). As Mycbp is already a known target of miR-22 (ref. 30), here we further confirmed that FLT3and CRTC1 are also direct targets of miR-22 (Fig. 3g,h). The downregulation of CRTC1, FLT3 and MYCBP by miR-22 at the protein level was confirmed in both human and mouse leukaemic cells (Supplementary Fig. 3b,c). Overexpression of miR-22 had no significant influence on the level of leukaemia fusion genes (Supplementary Fig. 3d).

Figure 3: miR-22 targets multiple oncogenes.

miR-22 targets multiple oncogenes.

(a) Downregulation of CRTC1, FLT3, MYCBP and ETV6 by forced expression of miR-22 in MONOMAC-6 cells. Expression of these genes was detected 48h post transfection of MSCV-PIG (Ctrl) or MSCV-PIG-miR-22 (miR-22). (b) Crtc1, Flt3, Mycbp and Etv6 levels in MLL-ENL-ERtm cells after withdrawal of 4-OHT for 0, 7 or 10 days. (c) Expression levels of Crtc1, Flt3, Mycbp and Etv6 in mouse BM progenitor cells retrovirally transduced with MSCV-PIG+MSCV-neo (Ctrl), MSCV-PIG-miR-22+MSCV-neo (miR-22), MSCV-PIG+MSCV-neo-MLL-AF9 (MLL-AF9) or MSCV-PIG-miR-22+MSCV-neo-MLL-AF9 (MLL-AF9+miR-22). (d) Expression levels of Crtc1, Flt3, Mycbp and Etv6 in BM blast cells of leukaemic mice transplanted with MLL-AF9, MLL-AF9+miR-22 or MLL-AF9+miR-22mut primary leukaemic cells. (e,f) Expression levels of Crtc1, Flt3 and Mycbp in BM blast cells of leukaemic mice transplanted with MSCV-PIG or MSCV-PIG-miR-22-retrovirally transduced AE9a (e) or FLT3-ITD/NPM1c+ (f) primary leukaemic cells. (g) Putative miR-22 target sites and mutants in the 3′UTRs of CRTC1 (upper panel) and FLT3(lower panel). (h) Effects of miR-22 on luciferase activity of the reporter gene bearing wild type or mutant 3′UTRs of CRTC1 or FLT3 in HEK293T cells. The mean±s.d. values from three replicates are shown.*P<0.05, t-test.

Co-expression of the coding region (CDS) of each of the three target genes (that is, CRTC1, FLT3and MYCBP) largely reversed the effects of miR-22 on cell viability, apoptosis and proliferation (Fig. 4a–e). More importantly, in vivo BMT assays showed that co-expressing CRTC1, FLT3 orMYCBP largely rescued the inhibitory effect of miR-22 on leukemogenesis (Fig. 4f,g;Supplementary Fig. 3e). Our data thus suggest that CRTC1, FLT3 and MYCBP are functionally important targets of miR-22 in AML.

Figure 4: Multiple onocgenes are functionally important targets of miR-22 in AML.

Multiple onocgenes are functionally important targets of miR-22 in AML.

(a,b) Relative viability (a) and apoptosis (b) levels of MONOMAC-6 cells transfected with MSCV-PIG-CRTC1, -FLT3 or –MYCBP alone, or together with MSCVneo-miR-22. Values were detected 48h post transfection. (c–e) Rescue effects of CRTC1 (c), FLT3 (d) and MYCBP (e) on the inhibition of MONOMAC-6 growth mediated by miR-22. Cell counts at the indicated time points are shown. Mean±s.d. values are shown. *P<0.05, t-test. (f) In vivo rescue effects of CRTC1, FLT3 and MYCBP on the inhibition of MLL-AF9-induced leukemogenesis mediated by miR-22. The secondary recipients were transplanted with BM blast cells of the primary MLL-AF9 leukaemic mice retrovirally transduced with MSCVneo+MSCV-PIG (MA9-AML+Ctrl; n=7), MSCVneo-miR-22+MSCV-PIG (MA9-AML+miR-22; n=10), MSCVneo-miR-22+MSCV-PIG-CRTC1 (MA9-AML+miR-22+CRTC1; n=5), MSCVneo-miR-22+MSCV-PIG-FLT3 (MA9-AML+miR-22+FLT3; n=6) or MSCVneo-miR-22+MSCV-PIG-MYCBP (MA9-AML+miR-22+MYCBP; n=6). Kaplan–Meier curves for all the five groups of transplanted mice are shown. MA9-AML+Ctrl versus MA9-AML+miR-22, P<0.001 (log-rank test); MA9-AML+Ctrl versus any other groups,P>0.05 (log-rank test). (g) Wright–Giemsa stained PB and BM, and H&E stained spleen and liver of the secondary leukaemic mice.

miR-22 represses both CREB and MYC signalling pathways

DNA copy-number loss of miR-22 gene locus in AML

Expression of miR-22 is epigenetically repressed in AML

 

Figure 5: Transcriptional correlation between miR-22 and TET1.

http://www.nature.com/ncomms/2016/160426/ncomms11452/images_article/ncomms11452-f5.jpg

(a) Correlation between the expression levels of miR-22 and TET1 in three independent AML patient databases. All expression data were log(2) transformed; the data in In-house_81S were also mean-centred. The correlation coefficient (r) and P values were detected by ‘Pearson Correlation’, and the correlation regression lines were drawn with the ‘linear regression’ algorithm. (b) Expression of pri-, pre- and mature miR-22, and Tet1/2/3 in colony-forming cells of wild-type mouse BM progenitors retrovirally transduced with MSCVneo (Ctrl), MSCVneo-MLL-AF9 (MLL-AF9), MSCVneo-MLL-AF10 (MLL-AF10) or MSCVneo-AE9a (AE9a), or of FLT3-ITD/NPM1c+ mouse BM progenitors transduced with MSCVneo (FLT3-ITD+/NPM1c+). (c) Expression of miR-22 and Tet1/2/3 in MLL-ENL-ERtm cells. Expression levels were detected at the indicated time points post 4-OHT withdrawal. (d) Effect of miR-22 overexpression onTet1 expression in colony-forming cells with MLL-AF9, AE9a or FLT3-ITD/NPM1c+. (e) Expression ofTet1 in BM progenitor cells of 6-weeks old miR-22−/− or wild-type mice. (f) Effect of miR-22 overexpression on TET1 expression in THP-1 and KOCL-48 AML cells 48h post transfection. (g) Expression of pri-, pre- and mature miR-22 in BM progenitor cells of 6-weeks old Tet1−/− or wild-type mice. Mean±s.d. values are shown. *P<0.05, t-test.

http://www.nature.com/ncomms/2016/160426/ncomms11452/images_article/ncomms11452-f6.jpg

(a) Tet1 targets miR-22 promoter region (−1,100/+55bp), as detected by luciferase reporter assay 48h post transfection in HEK293T cells. (b) Expression of TET1/2/3, EZH2, SIN3A, GFI1 and miR-22 in THP-1 cells 72h post treatment with 1μM ATRA or DMSO control. (c) Co-immunoprecipitation assay showing the binding of endogenous GFI1 and TET1 in THP1 cells. (d) ChIP-qPCR analyses of the promoter region of miR-22 in THP-1 cells 72h post treatment with 1μM ATRA or DMSO. Upper panel: PCR site on the CpG-enriched region of miR-22 gene locus. Note: miR-22 is coded within the second exon of a long non-coding RNA (MIR22HG), which represents the primary transcript of miR-22. Lower panels: enrichment of MLL-N terminal (for both wild-type MLL and MLL-fusion proteins), MLL-C terminal (for wild-type MLL), TET1, EZH2, SIN3A, GFI1, H3K27me3, H3K4me3 or RNA pol II at miR-22 promoter region. (e) Expression levels of TET1, EZH2, SIN3A and miR-22 in GFI1 knockdown cells. (f) ChIP-qPCR analyses of the promoter region of miR-22 in THP-1 cells transduced with GFI1 shRNA or control shRNA. Enrichment of GFI1, TET1, EZH2 and SIN3A are shown. (g) Effects of knockdown of TET1, EZH2 and/orSIN3A on miR-22 expression. The expression level of miR-22 was detected in THP-1 cells 72h post transfection with siRNAs targeting TET1, EZH2 and/or SIN3A. Mean±s.d. values are shown. *P<0.05;**P<0.01 (t-test). (h) Schematic model of the regulatory pathway involving miR-22 in AML and ATRA treatment.

 

The miR-22-associated regulatory circuit in AML

         Restoration of miR-22 expression and function to treat AML

 

Figure 7: Therapeutic effect of miR-22-nanoparticles in treating AML.

http://www.nature.com/ncomms/2016/160426/ncomms11452/images_article/ncomms11452-f7.jpg

(a,b) Primary leukaemia BM cells bearing MLL-AF9 (a) or AE9a (b) were transplanted into sublethally irradiated secondary recipient mice. After the onset of secondary AML (usually 10 days post transplantation), the recipient mice were treated with PBS control, or 0.5mgkg−1 miR-22 or miR-22 mutant RNA oligos formulated with G7 PAMAM dendrimer nanoparticles, i.v., every other day, until the PBS-treated control group all died of leukaemia. (c) NSGS mice49 were transplanted with MV4;11/t(4;11) AML cells. Five days post transplantation, these mice started to be treated with PBS control, miR-22 or miR-22 mutant nanoparticles at the same dose as described above. Kaplan–Meier curves are shown; the drug administration period and frequency were indicated with yellow arrows. The P values were detected by log-rank test. (d) Wright–Giemsa stained PB and BM, and H&E stained spleen and liver of the MLL-AF9-secondary leukaemic mice treated with PBS control, miR-22 or miR-22 mutant nanoparticles.

We then tested the miR-22 nanoparticles in a xeno-transplantation model49. Similarly, the nanoparticles carrying miR-22 oligos, but not miR-22 mutant, significantly delayed AML progression induced by human MV4;11/t(4;11) cells (Fig. 7c). The miR-22-nanoparticle administration also resulted in less aggressive leukaemic pathological phenotypes in the recipient mice (Supplementary Fig. 6e). Thus, our studies demonstrated the therapeutic potential of using miR-22-based nanoparticles to treat AML.

 

It remains poorly understood how TET proteins mediate gene regulation in cancer. Here we show that in de novo AML, it is TET1, but not TET2 (a reported direct target of miR-22 in MDS and breast cancer15, 16), that inversely correlates with miR-22 in expression and negatively regulates miR-22 at the transcriptional level. Likely together with GFI1, TET1 recruits polycomb cofactors (for example, EZH2/SIN3A) to the miR-22 promoter, leading to a significant increase in H3K27me3 occupancy and decrease in RNA pol II occupancy at that region, and thereby resulting in miR-22 repression in AML cells; such a repression can be abrogated by ATRA treatment. Thus, our study uncovers a novel epigenetic regulation mechanism in leukaemia involving the cooperation between TET1/GFI1 and polycomb factors.

Besides GFI1, it was reported that LSD1 is also a binding partner of TET1 (ref. 50). Interestingly, LSD1 is known as a common binding partner shared by TET1 and GFI1, and mediates the effect of GFI1 on hematopoietic differentiation51, 52. Thus, it is possible that LSD1 might also participate in the transcriptional repression of miR-22 as a component of the GFI1/TET1 repression complex.

We previously reported that TET1 cooperates with MLL fusions in positively regulating their oncogenic co-targets in MLL-rearranged AML14. Here we show that TET1 can also function as a transcriptional repressor (of a miRNA) in cancer. The requirement of TET1-mediated regulation on expression of its positive (for example, HOXA/MEIS1/PBX3)14 or negative (for example, miR-22) downstream effectors in leukemogenesis likely explains the rareness of TET1 mutations in AML53, and highlights its potent oncogenic role in leukaemia.

The aberrant activation of both CREB and MYC signalling pathways has been shown in AML24, 25,26, 54, 55, but the underlying molecular mechanisms remain elusive. Our data suggest that the activation of these two signalling pathways in AML can be attributed, at least in part, to the repression of miR-22, which in turn, results in the de-repression of CRTC1 (CREB pathway), FLT3and MYCBP (MYC pathway), and leads to the upregulation of oncogenic downstream targets (for example, CDK6, HOXA7, BMI1, FASN and HMGA1) and downregulation of tumour-suppressor downstream targets (for example, RGS2).

In summary, we uncover a TET1/GFI1/EZH2/SIN3A⊣miR-22⊣CREB-MYC signalling circuit in de novo AML, in which miR-22 functions as a pivotal anti-tumour gate-keeper, distinct from its oncogenic role reported in MDS or MDS-derived AML16. Thus, our study together with the study of Song et al.16 highlight the complexity and functional importance of miR-22-associated gene regulation and signalling pathways in hematopoietic malignancies, and may provide novel insights into the genetic/epigenetic differences between de novo AML and MDS.

Our findings also highlight the possibility of using miR-22-based therapy to treat AML patients. Our proof-of-concept studies demonstrate that the nanoparticles carrying miR-22 oligos significantly inhibit AML progression and prolong survival of leukaemic mice in both BMT and xeno-transplantation models. Notably, miRNA-based nanoparticles have already entered clinical trials56. It would be important, in the future, to further test the combination of miR-22-carrying nanoparticles (or small-molecule compounds that can induce endogenous expression of miR-22) with standard chemotherapy agents (cytosine arabinoside and anthracycline), or with the emerging small molecule inhibitors against MYC and/or CREB pathway effectors, to achieve optimal anti-leukaemia effect with minimal side effects. Overall, our results suggest that restoration of miR-22 expression/function (for example, using miR-22-carrying nanoparticles or small-molecule compounds) holds great therapeutic potential to treat AML, especially those resistant to current therapies.

 

MicroRNAs: A Gene Silencing Mechanism with Therapeutic Implications  

Wed, July 13, 2016   The New York Academy of Sciences    Presented by the Biochemical Pharmacology Discussion Group
http://www.nyas.org/Events/Detail.aspx?cid=787a5d77-8354-4df7-92d5-91db18b2ce49

MicroRNAs (miRNAs) are single-stranded RNAs about 22 nucleotides in length that repress the expression of specific proteins by annealing to complementary sequences in the 3′ untranslated regions (UTRs) of target mRNAs. Apart from their posttranscriptional expression, or silencing, miRNAs may also direct mRNA destabilization and cleavage. Moreover, rather than targeting a single disease-associated protein target as many small molecule drugs and antibodies do, each miRNA may serve to repress the expression of numerous proteins involved in the pathogenesis and progression of various diseases and could therefore potentially interfere with multiple disease-promoting signal transduction pathways. Because aberrant expression of miRNAs has been implicated in numerous disease states, miRNA-based therapies have sparked much interest for the treatment of a variety of diseases. The objective of this symposium is to bring together investigators who have led the field in describing what miRNAs do and their potential in treating diseases, as well as those who are translating these findings into promising drug candidates, some of which have already advanced into early stage clinical trials.

Call for Poster Abstracts

Abstract submissions are invited for a poster session. For complete submission instructions, please send an email to miRNA@nyas.org with the words “Abstract Information” in the subject line. The deadline for abstract submission is May 13, 2016.

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

Reporter: Stephen J Williams, PhD

 

UPDATED on 8/8/2020

A Hybrid Deep Clustering Approach for Robust Cell Type Profiling Using Single-cell RNA-seq Data

  1. Suhas Srinivasan1,
  2. Anastasia Leshchyk1,
  3. Nathan J Johnson2 and
  4. Dmitry Korkin1,3

+Author Affiliations

  1. 1 Worcester Polytechnic Institute;
  2. 2 Harvard Medical School and Dana Farber Cancer Institute
  1. * Corresponding author; email: korkin@korkinlab.org

Abstract

Single-cell RNA sequencing (scRNA-seq) is a recent technology that enables fine-grained discovery of cellular subtypes and specific cell states. It routinely uses machine learning methods, such as feature learning, clustering, and classification, to assist in uncovering novel information from scRNA-seq data. However, current methods are not well suited to deal with the substantial amounts of noise that is created by the experiments or the variation that occurs due to differences in the cells of the same type. Here, we develop a new hybrid approach, Deep Unsupervised Single-cell Clustering (DUSC), that integrates feature generation based on a deep learning architecture with a model-based clustering algorithm, to find a compact and informative representation of the single-cell transcriptomic data generating robust clusters. We also include a technique to estimate an efficient number of latent features in the deep learning model. Our method outperforms both classical and state-of-the-art feature learning and clustering methods, approaching the accuracy of supervised learning. We applied DUSC to single-cell transcriptomics dataset obtained from a triple-negative breast cancer tumor to identify potential cancer subclones accentuated by copy-number variation and investigate the role of clonal heterogeneity. Our method is freely available to the community and will hopefully facilitate our understanding of the cellular atlas of living organisms as well as provide the means to improve patient diagnostics and treatment.

Keywords

  • Received January 3, 2020.
  • Accepted May 22, 2020.

This article is distributed exclusively by the RNA Society for the first 12 months after the full-issue publication date (see http://rnajournal.cshlp.org/site/misc/terms.xhtml). After 12 months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

 

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

SOURCE

http://ki.se/en/news/new-subgroups-of-ilc-immune-cells-discovered-through-single-cell-rna-sequencing?elqTrackId=f79885cef36049e281109c02da213910&elq=ac700a4d4374478b9d6e10e301ae6b90&elqaid=14707&elqat=1&elqCampaignId=14

Updated on 2016-02-15. Published on 2016-02-15Denna sida på svenska

Jenny Mjösberg and Rickard Sandberg are principal investigators at Karolinska Institutet’s Department of Medicine, Huddinge and Department of Cell and Molecular Biology, respectively. Credit: Stefan Zimmerman.

A relatively newly discovered group of immune cells known as ILCs have been examined in detail in a new study published in the journal Nature Immunology. By analysing the gene expression in individual tonsil cells, scientists at Karolinska Institutet have found three previously unknown subgroups of ILCs, and revealed more about how these cells function in the human body.

Innate lymphoid cells (ILCs) are a group of immune cells that have only relatively recently been discovered in humans. Most of current knowledge about ILCs stems from animal studies of e.g. inflammation or infection in the gastrointestinal tract. There is therefore an urgent need to learn more about these cells in humans.

Previous studies have shown that ILCs are important for maintaining the barrier function of the mucosa, which serves as a first line of defence against microorganisms in the lungs, intestines and elsewhere. However, while there is growing evidence to suggest that ILCs are involved in diseases such as inflammatory bowel disease, asthma and intestinal cancer, basic research still needs to be done to ascertain exactly what part they play.

Two research groups, led by Rickard Sandberg and Jenny Mjösberg, collaborated on a study of ILCs from human tonsils. To date, three main groups of human ILCs are characterized. In this present study, the teams used a novel approach that enabled them to sort individual tonsil cells and measure their expression across thousands of  genes. This way, the researchers managed to categorise hundreds of cells, one by one, to define the types of ILCs found in the human tonsils.

Unique gene expression profiles

Rickard Sandberg, credit: Stefan Zimmerman,

“We used cluster analyses to demonstrate that ILCs congregate into ILC1, ILC2, ILC3 and NK cells, based on their unique gene expression profiles,” says Professor Sandberg at Karolinska Institutet’sDepartment of Cell and Molecular Biology, and the Stockholm branch of Ludwig Cancer Research. “Our analyses also discovered the expression of numerous genes of previously unknown function in ILCs, highlighting that these cells are likely doing more than what we previously knew.”

By analysing the gene expression profiles (or transcriptome) of individual cells, the researchers found that one of the formerly known main groups could be subdivided.

Jenny Mjösberg, credit: Stefan Zimmerman.

“We’ve identified three new subgroups of ILC3s that evince different gene expression patterns and that differ in how they react to signalling molecules and in their ability to secrete proteins,” says Dr Mjösberg at Karolinska Institutet’s Department of Medicine in Huddinge, South Stockholm. “All in all, our study has taught us a lot about this relatively uncharacterised family of cells and our data will serve as an important resource for other researchers.”

The study was financed by grants from a number of bodies, including the Swedish Research Council, the Swedish Cancer Society, the EU Framework Programme for Research and Innovation, the Swedish Society for Medical Research, the Swedish Foundation for Strategic Research and Karolinska Institutet.

Publication

The heterogeneity of human CD127+ innate lymphoid cells revealed by single-cell RNA sequencing
Åsa K. Björklund, Marianne Forkel, Simone Picelli, Viktoria Konya, Jakob Theorell, Danielle Friberg, Rickard Sandberg, Jenny Mjösberg
Nature Immunology, online 15 February 2016, doi:10.1038/ni.3368

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