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William Bell's Projects

angler icon angler

This is the first version of a library in R to calculate sexual size and shape dimorphism from landmark-based sexual dimorphism data.

assemblies-of-putative-sars-cov2-spike-encoding-mrna-sequences-for-vaccines-bnt-162b2-and-mrna-1273 icon 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 sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.

cv icon cv

My CV and the LaTeX header I used.

data icon data

Data and code behind the articles and graphics at FiveThirtyEight

ea-data icon ea-data

Syberia Projects for EA Data Analysis

fastball icon fastball

The Fastball toolbox for cognitive neuroscience

fortmcmurraywildfire icon fortmcmurraywildfire

Tweets relating to the Fort McMurray wildfire, with some basic sentiment analysis and data visualization.

getoldtweets-python icon getoldtweets-python

A project written in Python to get old tweets, it bypass some limitations of Twitter Official API.

heateq icon heateq

A low-dimensional heat equation solver written in Rcpp for two boundary conditions (Dirichlet, Neumann), this was developed as a method for teaching myself Rcpp.

knnexample icon knnexample

Implementation of k-Nearest Neighbours algorithm for use on geometric morphometric data and a simulated dataset.

macgpa icon macgpa

Convert McMaster's GPA scale to the Four Point System.

oc-bot icon oc-bot

Functional enigine for /u/OC-Bot

oldfaithful icon oldfaithful

Cleaning data entered from the Old Faithful Visitor Center Logs from 2000 so that they're ready for public consumption.

phesd icon phesd

Data repository to store Canadian wastewater and other environmental surveillance data using the Environmental Surveillance for Public Health Open Data Model (ESPH-ODM).

pseudopy icon pseudopy

PseudoPy computes and visualizes the pseudospectrum of a matrix

publiclibrarydata icon publiclibrarydata

This is my attempt to clean up the data provided by the Ontario government in order to prepare it for data analysis.

pyprojection icon pyprojection

Find special projection matrices satisfying certain requirements and study their effect on the pseudospectrum.

r-tutorials icon r-tutorials

These R Tutorials are conceived to be part of a series given for Peace Studies 4G03 on twitter analysis.

rcppnt2 icon rcppnt2

Rcpp integration for the NT2 scientific computing library

rostapack icon rostapack

Tim Mitchell's robustness and stability package.

routines icon routines

A Productivity Package for Personal Use

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