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Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag

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We are currently witnessing a major epidemic caused by the 2019 novel coronavirus (2019- nCoV). The evolution of 2019-nCoV remains elusive. We found 4 insertions in the spike glycoprotein (S) which are unique to the 2019-nCoV and are not present in other coronaviruses. Importantly, amino acid residues in all the 4 inserts have identity or similarity to those in the HIV-1 gp120 or HIV-1 Gag. Interestingly, despite the inserts being discontinuous on the primary amino acid sequence, 3D-modelling of the 2019-nCoV suggests that they converge to constitute the receptor binding site. The finding of 4 unique inserts in the 2019-nCoV, all of which have identity /similarity to amino acid residues in key structural proteins of HIV-1 is unlikely to be fortuitous in nature. This work provides yet unknown insights on 2019-nCoV and sheds light on the evolution and pathogenicity of this virus with important implications for diagnosis of this virus.
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Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120
and Gag
Prashant Pradhan$1,2, Ashutosh Kumar Pandey$1, Akhilesh Mishra$1, Parul Gupta1, Praveen
Kumar Tripathi1, Manoj Balakrishnan Menon1, James Gomes1, Perumal Vivekanandan*1and
Bishwajit Kundu*1
1Kusuma School of biological sciences, Indian institute of technology, New Delhi-110016, India.
2Acharya Narendra Dev College, University of Delhi, New Delhi-110019, India
$Equal contribution
* Corresponding authors- email: bkundu@bioschool.iitd.ac.in
vperumal@bioschool.iitd.ac.in
Abstract:
We are currently witnessing a major epidemic caused by the 2019 novel coronavirus (2019-
nCoV). The evolution of 2019-nCoV remains elusive. We found 4 insertions in the spike
glycoprotein (S) which are unique to the 2019-nCoV and are not present in other coronaviruses.
Importantly, amino acid residues in all the 4 inserts have identity or similarity to those in the HIV-
1 gp120 or HIV-1 Gag. Interestingly, despite the inserts being discontinuous on the primary
amino acid sequence, 3D-modelling of the 2019-nCoV suggests that they converge to constitute
the receptor binding site. The finding of 4 unique inserts in the 2019-nCoV, all of which have
identity /similarity to amino acid residues in key structural proteins of HIV-1 is unlikely to be
fortuitous in nature. This work provides yet unknown insights on 2019-nCoV and sheds light on
the evolution and pathogenicity of this virus with important implications for diagnosis of this virus.
Introduction
Coronaviruses (CoV) are single-stranded positive-sense RNA viruses that infect animals and
humans. These are classified into 4 genera based on their host specificity: Alphacoronavirus,
Betacoronavirus, Deltacoronavirus and Gammacoronavirus (Snijder et al., 2006). There are seven
known types of CoVs that includes 229E and NL63 (Genus Alphacoronavirus), OC43, HKU1,
MERS and SARS (Genus Betacoronavirus). While 229E, NL63, OC43, and HKU1 commonly
infect humans, the SARS and MERS outbreak in 2002 and 2012 respectively occurred when the
virus crossed-over from animals to humans causing significant mortality (J. Chan et al., n.d.; J. F.
W. Chan et al., 2015). In December 2019, another outbreak of coronavirus was reported from
Wuhan, China that also transmitted from animals to humans. This new virus has been temporarily
termed as 2019-novel Coronavirus (2019-nCoV) by the World Health Organization (WHO) (J. F.-
W. Chan et al., 2020; Zhu et al., 2020). While there are several hypotheses about the origin of
2019-nCoV, the source of this ongoing outbreak remains elusive.
The transmission patterns of 2019-nCoV is similar to patterns of transmission documented in the
previous outbreaks including by bodily or aerosol contact with persons infected with the virus.
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Cases of mild to severe illness, and death from the infection have been reported from Wuhan. This
outbreak has spread rapidly distant nations including France, Australia and USA among others.
The number of cases within and outside China are increasing steeply. Our current understanding
is limited to the virus genome sequences and modest epidemiological and clinical data.
Comprehensive analysis of the available 2019- nCoV sequences may provide important clues that
may help advance our current understanding to manage the ongoing outbreak.
The spike glycoprotein (S) of cornonavirus is cleaved into two subunits (S1 and S2). The S1
subunit helps in receptor binding and the S2 subunit facilitates membrane fusion (Bosch et al.,
2003; Li, 2016). The spike glycoproteins of coronoviruses are important determinants of tissue
tropism and host range. In addition the spike glycoproteins are critical targets for vaccine
development (Du et al., 2013). For this reason, the spike proteins represent the most extensively
studied among coronaviruses. We therefore sought to investigate the spike glycoprotein of the
2019-nCoV to understand its evolution, novel features sequence and structural features using
computational tools.
Methodology
Retrieval and alignment of nucleic acid and protein sequences
We retrieved all the available coronavirus sequences (n=55) from NCBI viral genome database
(https://www.ncbi.nlm.nih.gov/) and we used the GISAID (Elbe & Buckland-Merrett,
2017)[https://www.gisaid.org/] to retrieve all available full-length sequences (n=28) of 2019-
nCoV as on 27 Jan 2020. Multiple sequence alignment of all coronavirus genomes was performed
by using MUSCLE software (Edgar, 2004) based on neighbour joining method. Out of 55
coronavirus genome 32 representative genomes of all category were used for phylogenetic tree
development using MEGAX software (Kumar et al., 2018). The closest relative was found to be
SARS CoV. The glycoprotein region of SARS CoV and 2019-nCoV were aligned and visualized
using Multalin software (Corpet, 1988). The identified amino acid and nucleotide sequence were
aligned with whole viral genome database using BLASTp and BLASTn. The conservation of the
nucleotide and amino acid motifs in 28 clinical variants of 2019-nCoV genome were presented by
performing multiple sequence alignment using MEGAX software. The three dimensional structure
of 2019-nCoV glycoprotein was generated by using SWISS-MODEL online server (Biasini et al.,
2014) and the structure was marked and visualized by using PyMol (DeLano, 2002).
Results
Uncanny similarity of novel inserts in the 2019-nCoV spike protein to HIV-1 gp120 and
Gag
Our phylogentic tree of full-length coronaviruses suggests that 2019-nCoV is closely related to
SARS CoV [Fig1]. In addition, other recent studies have linked the 2019-nCoV to SARS CoV.
We therefore compared the spike glycoprotein sequences of the 2019-nCoV to that of the SARS
CoV (NCBI Accession number: AY390556.1). On careful examination of the sequence
alignment we found that the 2019- nCoV spike glycoprotein contains 4 insertions [Fig.2]. To
further investigate if these inserts are present in any other corona virus, we performed a multiple
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sequence alignment of the spike glycoprotein amino acid sequences of all available
coronaviruses (n=55) [refer Table S.File1] in NCBI refseq (ncbi.nlm.nih.gov) this includes one
sequence of 2019-nCoV[Fig.S1]. We found that these 4 insertions [inserts 1, 2, 3 and 4] are
unique to 2019-nCoV and are not present in other coronaviruses analyzed. Another group from
China had documented three insertions comparing fewer spike glycoprotein sequences of
coronaviruses . Another group from China had documented three insertions comparing fewer
spike glycoprotein sequences of coronaviruses (Zhou et al., 2020).
Figure 1: Maximum likelihood genealogy show the evolution of 2019- nCoV: The evolutionary history
was inferred by using the Maximum Likelihood method and JTT matrix-based model. The tree
with the highest log likelihood (12458.88) is shown. Initial tree(s) for the heuristic search were
obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise
distances estimated using a JTT model, and then selecting the topology with superior log likelihood
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value. This analysis involved 5 amino acid sequences. There were a total of 1387 positions in the
final dataset. Evolutionary analyses were conducted in MEGA X.
Figure 2: Multiple sequence alignment between spike proteins of 2019-nCoV and SARS. The
sequences of spike proteins of 2019-nCoV (Wuhan-HU-1, Accession NC_045512) and of SARS
CoV (GZ02, Accession AY390556) were aligned using MultiAlin software. The sites of difference
are highlighted in boxes.
We then analyzed all available full-length sequences (n=28) of 2019-nCoV in GISAID (Elbe &
Buckland-Merrett, 2017) as on January 27, 2020 for the presence of these inserts. As most of these
sequences are not annotated, we compared the nucleotide sequences of the spike glycoprotein of
all available 2019-nCoV sequences using BLASTp. Interestingly, all the 4 insertions were
absolutely (100%) conserved in all the available 2019- nCoV sequences analyzed [Fig.S2, Fig.S3].
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We then translated the aligned genome and found that these inserts are present in all Wuhan 2019-
nCoV viruses except the 2019-nCoV virus of Bat as a host [Fig.S4]. Intrigued by the 4 highly
conserved inserts unique to 2019-nCoV we wanted to understand their origin. For this purpose,
we used the 2019-nCoV local alignment with each insert as query against all virus genomes and
considered hits with 100% sequence coverage. Surprisingly, each of the four inserts aligned with
short segments of the Human immunodeficiency Virus-1 (HIV-1) proteins. The amino acid
positions of the inserts in 2019-nCoV and the corresponding residues in HIV-1 gp120 and HIV-1
Gag are shown in Table 1. The first 3 inserts (insert 1,2 and 3) aligned to short segments of amino
acid residues in HIV-1 gp120. The insert 4 aligned to HIV-1 Gag. The insert 1 (6 amino acid
residues) and insert 2 (6 amino acid residues) in the spike glycoprotein of 2019-nCoV are 100%
identical to the residues mapped to HIV-1 gp120. The insert 3 (12 amino acid residues) in 2019-
nCoV maps to HIV-1 gp120 with gaps [see Table 1]. The insert 4 (8 amino acid residues) maps to
HIV-1 Gag with gaps.
Although, the 4 inserts represent discontiguous short stretches of amino acids in spike glycoprotein
of 2019-nCoV, the fact that all three of them share amino acid identity or similarity with HIV-1
gp120 and HIV-1 Gag (among all annotated virus proteins) suggests that this is not a random
fortuitous finding. In other words, one may sporadically expect a fortuitous match for a stretch of
6-12 contiguous amino acid residues in an unrelated protein. However, it is unlikely that all 4
inserts in the 2019-nCoV spike glycoprotein fortuitously match with 2 key structural proteins of
an unrelated virus (HIV-1).
The amino acid residues of inserts 1, 2 and 3 of 2019-nCoV spike glycoprotein that mapped to
HIV-1 were a part of the V4, V5 and V1 domains respectively in gp120 [Table 1]. Since the 2019-
nCoV inserts mapped to variable regions of HIV-1, they were not ubiquitous in HIV-1 gp120, but
were limited to selected sequences of HIV-1 [ refer S.File1] primarily from Asia and Africa.
The HIV-1 Gag protein enables interaction of virus with negatively charged host surface
(Murakami, 2008) and a high positive charge on the Gag protein is a key feature for the host-virus
interaction. On analyzing the pI values for each of the 4 inserts in 2019-nCoV and the
corresponding stretches of amino acid residues from HIV-1 proteins we found that a) the pI values
were very similar for each pair analyzed b) most of these pI values were 10±2 [Refer Table 1] . Of
note, despite the gaps in inserts 3 and 4 the pI values were comparable. This uniformity in the pI
values for all the 4 inserts merits further investigation.
As none of these 4 inserts are present in any other coronavirus, the genomic region encoding these
inserts represent ideal candidates for designing primers that can distinguish 2019-nCoV from other
coronaviruses.
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Motifs
Virus
Glycoprotein
Motif Alignment
HIV
protein
and
Variable
region
HIV
Genome
Source
Country/
subtype
Total
Char
ge
pI
Valu
e
Insert
1
2019- nCoV (GP)
HIV1(GP120)
71 76
TNGTKR
TNGTKR
404 409
gp120-
V4
Thailand
*/
CRF01_
AE
2
2
11
11
Insert
2
2019- nCoV (GP)
HIV1(GP120)
145 150
HKNNKS
HKNNKS
462 467
gp120-
V5
Kenya*/
G
2
2
10
10
Insert
3
2019- nCoV (GP)
HIV1(GP120)
245 256
RSYL- - - -TPGDSSSG
RTYLFNETRGNSSSG
136 150
gp120-
V1
India*/C
2
1
10.84
8.75
Insert
4
2019- nCoV (Poly
P)
HIV1(gag)
676 684
QTNS-----------------------PRRA
QTNSSILMQRSNFKG PRRA
366 384
Gag
India*/C
2
4
12.00
12.30
Table 1: Aligned sequences of 2019-nCoV and gp120 protein of HIV-1 with their positions
in primary sequence of protein. All the inserts have a high density of positively charged
residues. The deleted fragments in insert 3 and 4 increase the positive charge to surface area
ratio. *please see Supp. Table 1 for accession numbers
The novel inserts are part of the receptor binding site of 2019-nCoV
To get structural insights and to understand the role of these insertions in 2019-nCoV glycoprotein,
we modelled its structure based on available structure of SARS spike glycoprotein (PDB:
6ACD.1.A). The comparison of the modelled structure reveals that although inserts 1,2 and 3 are
at non-contiguous locations in the protein primary sequence, they fold to constitute the part of
glycoprotein binding site that recognizes the host receptor (Kirchdoerfer et al., 2016) (Figure 4).
The insert 1 corresponds to the NTD (N-terminal domain) and the inserts 2 and 3 correspond to
the CTD (C-terminal domain) of the S1 subunit in the 2019-nCoV spike glycoprotein. The insert
4 is at the junction of the SD1 (sub domain 1) and SD2 (sub domain 2) of the S1 subunit (Ou et
al., 2017). We speculate, that these insertions provide additional flexibility to the glycoprotein
binding site by forming a hydrophilic loop in the protein structure that may facilitate or enhance
virus-host interactions.
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Figure 3. Modelled homo-trimer spike glycoprotein of 2019-nCoV virus. The inserts from HIV
envelop protein are shown with colored beads, present at the binding site of the protein.
Evolutionary Analysis of 2019-nCoV
It has been speculated that 2019-nCoV is a variant of Coronavirus derived from an animal source
which got transmitted to humans. Considering the change of specificity for host, we decided to
study the sequences of spike glycoprotein (S protein) of the virus. S proteins are surface proteins
that help the virus in host recognition and attachment. Thus, a change in these proteins can be
reflected as a change of host specificity of the virus. To know the alterations in S protein gene of
2019-nCoV and its consequences in structural re-arrangements we performed in-sillico analysis of
2019-nCoV with respect to all other viruses. A multiple sequence alignment between the S protein
amino acid sequences of 2019-nCoV, Bat-SARS-Like, SARS-GZ02 and MERS revealed that S
protein has evolved with closest significant diversity from the SARS-GZ02 (Figure 1).
Insertions in Spike protein region of 2019-nCoV
Since the S protein of 2019-nCoV shares closest ancestry with SARS GZ02, the sequence coding
for spike proteins of these two viruses were compared using MultiAlin software. We found four
new insertions in the protein of 2019-nCoV- “GTNGTKR” (IS1), “HKNNKS” (IS2), “GDSSSG”
(IS3) and “QTNSPRRA” (IS4) (Figure 2). To our surprise, these sequence insertions were not only
absent in S protein of SARS but were also not observed in any other member of the Coronaviridae
family (Supplementary figure). This is startling as it is quite unlikely for a virus to have acquired
such unique insertions naturally in a short duration of time.
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Insertions share similarity to HIV
The insertions were observed to be present in all the genomic sequences of 2019-nCoV virus
available from the recent clinical isolates (Supplementary Figure 1). To know the source of these
insertions in 2019-nCoV a local alignment was done with BLASTp using these insertions as query
with all virus genome. Unexpectedly, all the insertions got aligned with Human immunodeficiency
Virus-1 (HIV-1). Further analysis revealed that aligned sequences of HIV-1 with 2019-nCoV were
derived from surface glycoprotein gp120 (amino acid sequence positions: 404-409, 462-467, 136-
150) and from Gag protein (366-384 amino acid) (Table 1). Gag protein of HIV is involved in host
membrane binding, packaging of the virus and for the formation of virus-like particles. Gp120
plays crucial role in recognizing the host cell by binding to the primary receptor CD4.This binding
induces structural rearrangements in GP120, creating a high affinity binding site for a chemokine
co-receptor like CXCR4 and/or CCR5.
Discussion
The current outbreak of 2019-nCoV warrants a thorough investigation and understanding of its
ability to infect human beings. Keeping in mind that there has been a clear change in the preference
of host from previous coronaviruses to this virus, we studied the change in spike protein between
2019-nCoV and other viruses. We found four new insertions in the S protein of 2019-nCoV when
compared to its nearest relative, SARS CoV. The genome sequence from the recent 28 clinical
isolates showed that the sequence coding for these insertions are conserved amongst all these
isolates. This indicates that these insertions have been preferably acquired by the 2019-nCoV,
providing it with additional survival and infectivity advantage. Delving deeper we found that these
insertions were similar to HIV-1. Our results highlight an astonishing relation between the gp120
and Gag protein of HIV, with 2019-nCoV spike glycoprotein. These proteins are critical for the
viruses to identify and latch on to their host cells and for viral assembly (Beniac et al., 2006).
Since surface proteins are responsible for host tropism, changes in these proteins imply a change
in host specificity of the virus. According to reports from China, there has been a gain of host
specificity in case 2019-nCoV as the virus was originally known to infect animals and not humans
but after the mutations, it has gained tropism to humans as well.
Moving ahead, 3D modelling of the protein structure displayed that these insertions are present at
the binding site of 2019-nCoV. Due to the presence of gp120 motifs in 2019-nCoV spike
glycoprotein at its binding domain, we propose that these motif insertions could have provided an
enhanced affinity towards host cell receptors. Further, this structural change might have also
increased the range of host cells that 2019-nCoV can infect. To the best of our knowledge, the
function of these motifs is still not clear in HIV and need to be explored. The exchange of genetic
material among the viruses is well known and such critical exchange highlights the risk and the
need to investigate the relations between seemingly unrelated virus families.
Conclusions
Our analysis of the spike glycoprotein of 2019-nCoV revealed several interesting findings: First,
we identified 4 unique inserts in the 2019-nCoV spike glycoprotein that are not present in any
other coronavirus reported till date. To our surprise, all the 4 inserts in the 2019-nCoV mapped to
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short segments of amino acids in the HIV-1 gp120 and Gag among all annotated virus proteins in
the NCBI database. This uncanny similarity of novel inserts in the 2019- nCoV spike protein to
HIV-1 gp120 and Gag is unlikely to be fortuitous. Further, 3D modelling suggests that atleast 3 of
the unique inserts which are non-contiguous in the primary protein sequence of the 2019-nCoV
spike glycoprotein converge to constitute the key components of the receptor binding site. Of note,
all the 4 inserts have pI values of around 10 that may facilitate virus-host interactions. Taken
together, our findings suggest unconventional evolution of 2019-nCoV that warrants further
investigation. Our work highlights novel evolutionary aspects of the 2019-nCoV and has
implications on the pathogenesis and diagnosis of this virus.
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Fig.S1 Multiple sequence alignment of glycoprotein of coronaviridae family, representing all the
four inserts.
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Fig.S2: All four inserts are present in the aligned 28 Wuhan 2019-nCoV virus genomes obtained
from GISAID. The gap in the Bat-SARS Like CoV in the last row shows that insert 1 and 4 is very
unique to Wuhan 2019-nCoV.
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Fig.S3 Phylogenetic tree of 28 clinical isolates genome of 2019-nCoV including one from bat as a host.
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Supplementary Fig 4. Genome alingment of Coronaviridae family. Highlighted black sequences are the
inserts represented here.
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... 10 Nie (2020) recalls how just a "few days after the lockdown of Wuhan in late January 2020, a U.S. newspaper prone to circulating conspiracy theories", the Washington Times (Gertz 2020), linked the origins of SARS-CoV-2 to China's biological weapons programme. Another example cited by Nie is an article from the Indian Institute of Technology, later retracted, reporting findings that were commented by the authors as "unlikely to be fortuitous in nature" (Pradhan et al. 2020). Other studies and investigations analysed how conspiracy theories developed on social media in different countries (e.g., Erokhin et al. 2022). ...
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... Finally, JCPyV seroconversion rates have been reported to be stable during the COVID-19 pandemic, [162], but some data indicate that HIV/AIDS prevalence may increase in the post-COVID-19 period [163][164][165][166][167]. Rare reports describe novel PML manifestations due to SARS-CoV-2 [168]. ...
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... The Covid-19 pandemic emphasizes the speed with which scientific publications are being published, as well as the spread of misleading information in blogs and even scientific papers, giving rise to the problem known as fake news [4]. Prashant Pradhan and his Indian partners released a paper on January 31, 2019 where they offered evidence of unusual parallels in the coronavirus sequence with HIV gp120 and Gag proteins, implying that it was a fabricated virus [5]. ...
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... To accelerate research on this pressing issue, many researchers shared their latest results on the preprint server bioRxiv. On 31 January 2020 a team of researchers from two Indian universities published the preprint 'Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag' (Pradhan et al., 2020, from here: Uncanny Similarity) on bioRxiv. In their preprint, the authors claimed to have identified similarities in the molecular structure of the new coronavirus and HIV. ...
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Many scientists share preprints on social media platforms to gain attention from academic peers, policy-makers, and journalists. In this study we shed light on an unintended but highly consequential effect of sharing preprints: Their contribution to conspiracy theories. Although the scientific community might quickly dismiss a preprint as insubstantial and ‘clickbaity’, its uncertain epistemic status nevertheless allows conspiracy theorists to mobilize the text as scientific support for their own narratives. To better understand the epistemic politics of preprints on social media platforms, we studied the case of a biomedical preprint, which was shared widely and discussed controversially on Twitter in the wake of the coronavirus disease 2019 pandemic. Using a combination of social network analysis and qualitative content analysis, we compared the structures of engagement with the preprint and the discursive practices of scientists and conspiracy theorists. We found that despite substantial engagement, scientists were unable to dampen the conspiracy theorists’ enthusiasm for the preprint. We further found that members from both groups not only tried to reduce the preprint's epistemic uncertainty but sometimes deliberately maintained it. The maintenance of epistemic uncertainty helped conspiracy theorists to reinforce their group's identity as skeptics and allowed scientists to express concerns with the state of their profession. Our study contributes to research on the intricate relations between scientific knowledge and conspiracy theories online, as well as the role of social media platforms for new genres of scholarly communication.
... Finally, in a notable case of incorrect findings having a potential negative impact when released without peer review, a preprint claiming to find "uncanny similarity" between SARS-CoV-2 and HIV was posted to bioRxiv on 31 January 2020. However, it was withdrawn two days later after other scientists posted public comments identifying errors in its analysis (Pradhan, et al., 2020). ...
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Many argue that swift and fundamental interventions in the system of scholarly communication are needed. However, there are substantial disagreements over the short- and long-term benefits of most proposed approaches to changing the practice of science communication, and the lack of systematic, empirically based research in this area makes these controversies difficult to resolve. We argue that experience within public health can be usefully applied to scholarly communication. Starting with the history of DDT (Dichlorodiphenyltrichloroethane) application, we illustrate four ways complex human systems threaten reliable predictions and blunt ad-hoc interventions. We then show how these apply to interventions in scholarly publication – open access based on the article processing charge (APC), and preprints – to yield surprising results. Finally, we offer approaches to help guide the design of future interventions: identifying measures and outcomes, developing infrastructure, incorporating assessment, and contributing to theories of systemic change.
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Background The quality of COVID-19 preprints should be considered with great care, as their contents can influence public policy. Surprisingly little has been done to calibrate the public’s evaluation of preprints and their contents. The PRECHECK project aimed to generate a tool to teach and guide scientifically literate non-experts to critically evaluate preprints, on COVID-19 and beyond. Methods To create a checklist, we applied a four-step procedure consisting of an initial internal review, an external review by a pool of experts (methodologists, meta-researchers/experts on preprints, journal editors, and science journalists), a final internal review, and a Preliminary implementation stage. For the external review step, experts rated the relevance of each element of the checklist on five-point Likert scales, and provided written feedback. After each internal review round, we applied the checklist on a small set of high-quality preprints from an online list of milestone research works on COVID-19 and low-quality preprints, which were eventually retracted, to verify whether the checklist can discriminate between the two categories. Results At the external review step, 26 of the 54 contacted experts responded. The final checklist contained four elements (Research question, study type, transparency and integrity, and limitations), with ‘superficial’ and ‘deep’ evaluation levels. When using both levels, the checklist was effective at discriminating a small set of high- and low-quality preprints. Its usability for assessment and discussion of preprints was confirmed in workshops with Bachelors students in Psychology and Medicine, and science journalists. Conclusions We created a simple, easy-to-use tool for helping scientifically literate non-experts navigate preprints with a critical mind and facilitate discussions within, for example, a beginner-level lecture on research methods. We believe that our checklist has potential to help guide decisions about the quality of preprints on COVID-19 in our target audience and that this extends beyond COVID-19.
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HKU1 is a human betacoronavirus that causes mild yet prevalent respiratory disease, and is related to the zoonotic SARS and MERS betacoronaviruses, which have high fatality rates and pandemic potential. Cell tropism and host range is determined in part by the coronavirus spike (S) protein, which binds cellular receptors and mediates membrane fusion. As the largest known class I fusion protein, its size and extensive glycosylation have hindered structural studies of the full ectodomain, thus preventing a molecular understanding of its function and limiting development of effective interventions. Here we present the 4.0 Å resolution structure of the trimeric HKU1 S protein determined using single-particle cryo-electron microscopy. In the pre-fusion conformation, the receptor-binding subunits, S1, rest above the fusion-mediating subunits, S2, preventing their conformational rearrangement. Surprisingly, the S1 C-terminal domains are interdigitated and form extensive quaternary interactions that occlude surfaces known in other coronaviruses to bind protein receptors. These features, along with the location of the two protease sites known to be important for coronavirus entry, provide a structural basis to support a model of membrane fusion mediated by progressive S protein destabilization through receptor binding and proteolytic cleavage. These studies should also serve as a foundation for the structure-based design of betacoronavirus vaccine immunogens.
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Since the SARS outbreak 18 years ago, a large number of severe acute respiratory syndrome related coronaviruses (SARSr-CoV) have been discovered in their natural reservoir host, bats. Previous studies indicated that some of those bat SARSr-CoVs have the potential to infect humans. Here we report the identification and characterization of a novel coronavirus (nCoV-2019) which caused an epidemic of acute respiratory syndrome in humans, in Wuhan, China. The epidemic, started from December 12th, 2019, has caused 198 laboratory confirmed infections with three fatal cases by January 20th, 2020. Full-length genome sequences were obtained from five patients at the early stage of the outbreak. They are almost identical to each other and share 79.5% sequence identify to SARS-CoV. Furthermore, it was found that nCoV-2019 is 96% identical at the whole genome level to a bat coronavirus. The pairwise protein sequence analysis of seven conserved non-structural proteins show that this virus belongs to the species of SARSr-CoV. The nCoV-2019 virus was then isolated from the bronchoalveolar lavage fluid of a critically ill patient, which can be neutralized by sera from several patients. Importantly, we have confirmed that this novel CoV uses the same cell entry receptor, ACE2, as SARS-CoV.
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The coronavirus spike protein is a multifunctional molecular machine that mediates coronavirus entry into host cells. It first binds to a receptor on the host cell surface through its S1 subunit and then fuses viral and host membranes through its S2 subunit. Two domains in S1 from different coronaviruses recognize a variety of host receptors, leading to viral attachment. The spike protein exists in two structurally distinct conformations, prefusion and postfusion. The transition from prefusion to postfusion conformation of the spike protein must be triggered, leading to membrane fusion. This article reviews current knowledge about the structures and functions of coronavirus spike proteins, illustrating how the two S1 domains recognize different receptors and how the spike proteins are regulated to undergo conformational transitions. I further discuss the evolution of these two critical functions of coronavirus spike proteins, receptor recognition and membrane fusion, in the context of the corresponding functions from other viruses and host cells. Expected final online publication date for the Annual Review of Virology Volume 3 is September 29, 2016. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
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