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NAalytics
Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273
Systems & Infrastructure2021–2022
NAalytics / Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273

Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273

RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some seq

12Distinct people
12Mentions
1Explicit recommenders
3.4KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some seq

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Where it is used

No documented product use was verified in the last source check.

What people are saying

Recently sequences of of the COVID vaccines were released[1]. It's amazing to me how such a short sequence of data will make such an impact on the world. I had the idea to…

connor4312 used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month12 dated mentions

Observed mentions: 2021-03-24 17:08:47 UTC to 2022-09-15 10:04:31 UTC.

0123452021-03-01 00:00:00 UTC to 2021-04-01 00:00:00 UTC (exclusive): 5 mentions; 3 submissions, 2 commentsMar 20212021-04-01 00:00:00 UTC to 2021-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-05-01 00:00:00 UTC to 2021-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-06-01 00:00:00 UTC to 2021-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-07-01 00:00:00 UTC to 2021-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-08-01 00:00:00 UTC to 2021-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-09-01 00:00:00 UTC to 2021-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-10-01 00:00:00 UTC to 2021-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-11-01 00:00:00 UTC to 2021-12-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-12-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsDec 20212022-01-01 00:00:00 UTC to 2022-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-02-01 00:00:00 UTC to 2022-03-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2022-03-01 00:00:00 UTC to 2022-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-04-01 00:00:00 UTC to 2022-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-05-01 00:00:00 UTC to 2022-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-06-01 00:00:00 UTC to 2022-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-07-01 00:00:00 UTC to 2022-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-08-01 00:00:00 UTC to 2022-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-09-01 00:00:00 UTC to 2022-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 2022

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Mar 20212021-03-01 00:00:00 UTC2021-04-01 00:00:00 UTC532
Apr 20212021-04-01 00:00:00 UTC2021-05-01 00:00:00 UTC101
May 20212021-05-01 00:00:00 UTC2021-06-01 00:00:00 UTC101
Jun 20212021-06-01 00:00:00 UTC2021-07-01 00:00:00 UTC000
Jul 20212021-07-01 00:00:00 UTC2021-08-01 00:00:00 UTC000
Aug 20212021-08-01 00:00:00 UTC2021-09-01 00:00:00 UTC000
Sep 20212021-09-01 00:00:00 UTC2021-10-01 00:00:00 UTC000
Oct 20212021-10-01 00:00:00 UTC2021-11-01 00:00:00 UTC000
Nov 20212021-11-01 00:00:00 UTC2021-12-01 00:00:00 UTC101
Dec 20212021-12-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
Jan 20222022-01-01 00:00:00 UTC2022-02-01 00:00:00 UTC000
Feb 20222022-02-01 00:00:00 UTC2022-03-01 00:00:00 UTC202
Mar 20222022-03-01 00:00:00 UTC2022-04-01 00:00:00 UTC000
Apr 20222022-04-01 00:00:00 UTC2022-05-01 00:00:00 UTC000
May 20222022-05-01 00:00:00 UTC2022-06-01 00:00:00 UTC000
Jun 20222022-06-01 00:00:00 UTC2022-07-01 00:00:00 UTC000
Jul 20222022-07-01 00:00:00 UTC2022-08-01 00:00:00 UTC000
Aug 20222022-08-01 00:00:00 UTC2022-09-01 00:00:00 UTC000
Sep 20222022-09-01 00:00:00 UTC2022-10-01 00:00:00 UTC101

What Hacker News says

12 sources
In the US EUAs at the beginning, for me, it was 95% the technology and 5% the manufacturer convinced me mRNA vaccines were superior because of their precisely-targeted nature. It was a gamble between Pfizer and Moderna. Went with Moderna for the first 2 (before the data on "mix-and-match") and Pfizer booster. Btw, sequencing of both mRNA vaccines: https://github.com/NAalytics/Assemblies-of-putative-SARS-CoV...
In J&J tried to get federal judge to block publication of Reuters story
I haven’t searched for the Moderna one, but for the Pfizer I have these two links: Assemblies of putative SARS-CoV2-spike-encoding mRNA sequences for vaccines BNT-162b2 and mRNA-1273 > https://github.com/NAalytics/Assemblies-of-putative-SARS-CoV... Reverse Engineering the source code of the BioNTech/Pfizer SARS-CoV-2 Vaccine > https://berthub.eu/articles/posts/reverse-engineering-source...
In Afrigen has used the public data of Moderna mRNA vaccine to make its own version
They did not use the exact same mRNA sequence: https://github.com/NAalytics/Assemblies-of-putative-SARS-CoV... The different doses were guesses made to balance effectiveness with severity of side effects. (Earlier Moderna trials, at least, had included even higher doses, which could cause pretty severe side effects.) Their choices had to be locked in early, based on very limited preliminary trial data, in order to run their phase 3 trials as quickly as possible, to actually bring the vaccines to market quickly in 2020. They just made somewhat different bets. I think it's as simple as that.
In Pfizer and Biontech provide update on Omicron variant
connor4312·Mar 30, 2021Recommendation phrase
Recently sequences of of the COVID vaccines were released[1]. It's amazing to me how such a short sequence of data will make such an impact on the world. I had the idea to print a couple posters for the occasion, so I made this tool. I linked a redbubble where I uploaded a couple of my favorite designs, but of course you're free to build your own with the tool and print them however you'd like. 1. https://github.com/NAalytics/Assemblies-of-putative-SARS-CoV...
In Show HN: Covid-19 Vaccine Sequence Visualizer
Exactly. FAIR (Findable, Accessible, Interoperable and Reusable) principles are at a loss here [1]. The "Reusable" part seems to be especially problematic as the sequence is buried in a PDF file though all aspects of FAIR are compromised here. Edit: It looks like there is now a PR to address this issue [2] [1] https://www.nature.com/articles/sdata201618 [2] https://github.com/NAalytics/Assemblies-of-putative-SARS-CoV...
In Moderna mRNA sequence released to GitHub [pdf]

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