Cross-host evolution of severe acute respiratory syndrome coronavirus in palm civet and human

Article (PDF Available)inProceedings of the National Academy of Sciences 102(7):2430-5 · March 2005with83 Reads
DOI: 10.1073/pnas.0409608102 · Source: PubMed
The genomic sequences of severe acute respiratory syndrome coronaviruses from human and palm civet of the 2003/2004 outbreak in the city of Guangzhou, China, were nearly identical. Phylogenetic analysis suggested an independent viral invasion from animal to human in this new episode. Combining all existing data but excluding singletons, we identified 202 single-nucleotide variations. Among them, 17 are polymorphic in palm civets only. The ratio of nonsynonymous/synonymous nucleotide substitution in palm civets collected 1 yr apart from different geographic locations is very high, suggesting a rapid evolving process of viral proteins in civet as well, much like their adaptation in the human host in the early 2002-2003 epidemic. Major genetic variations in some critical genes, particularly the Spike gene, seemed essential for the transition from animal-to-human transmission to human-to-human transmission, which eventually caused the first severe acute respiratory syndrome outbreak of 2002/2003.
Cross-host evolution of severe acute respiratory
syndrome coronavirus in palm civet and human
Huai-Dong Song
, Chang-Chun Tu
, Guo-Wei Zhang
, Sheng-Yue Wang
, Kui Zheng
, Lian-Cheng Lei
Qiu-Xia Chen
, Yu-Wei Gao
, Hui-Qiong Zhou
, Hua Xiang
, Hua-Jun Zheng
, Shur-Wern Wang Chern
, Feng Cheng
Chun-Ming Pan
, Hua Xuan
, Sai-Juan Chen
, Hui-Ming Luo
, Duan-Hua Zhou
, Yu-Fei Liu
, Jian-Feng He
Peng-Zhe Qin
, Ling-Hui Li
, Yu-Qi Ren
, Wen-Jia Liang
, Ye-Dong Yu
, Larry Anderson
, Ming Wang
, Rui-Heng Xu
Xin-Wei Wu
, Huan-Ying Zheng
, Jin-Ding Chen
, Guodong Liang
, Yang Gao
, Ming Liao
, Ling Fang
, Li-Yun Jiang
Hui Li
, Fang Chen
, Biao Di
, Li-Juan He
, Jin-Yan Lin
, Suxiang Tong
, Xiangang Kong
, Lin Du
, Pei Hao
Hua Tang
, Andrea Bernini
, Xiao-Jing Yu
, Ottavia Spiga
, Zong-Ming Guo
, Hai-Yan Pan
, Wei-Zhong He
Jean-Claude Manuguerra
, Arnaud Fontanet
, Antoine Danchin
, Neri Niccolai
, Yi-Xue Li
, Chung-I Wu
and Guo-Ping Zhao
State Key Laboratory for Medical GenomicsPoˆ le Sino-Franc¸ais de Recherche en Sciences du Vivant et Ge´ nomique, Ruijin Hospital Affiliated to Shanghai
Second Medical University, 197 Rui Jin Road II, Shanghai 200025, China;
Changchun University of Agriculture and Animal Sciences, Changchun 130062,
Chinese National Human Genome Center, 250 Bi Bo Road, Zhang Jiang High Tech Park, Shanghai 201203, China;
Guangdong Center for Disease
Control and Prevention, 176 Xingangxi Road, Guangzhou 510300, Guangdong, China;
Centers for Disease Control and Prevention, 1600 Clifton Road,
Atlanta, GA 30333;
Guangzhou Center for Disease Control and Prevention, 23 Third Zhongshan Road, Guangzhou 510080, Guangdong, China;
Provincial Veterinary Station of Epidemic Prevention and Supervision, Guangzhou 510230, China;
College of Veterinary Medicine, South China Agriculture
University, Guangzhou 510246, China;
National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention,
Beijing 100052, China;
National Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agriculture
Sciences, Harbin 150001, China;
Bioinformation CenterInstitute of Plant Physiology and EcologyHealth Science Center, Shanghai Institutes for Biological
Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China;
Shanghai Center for Bioinformation Technology, 100 Qinzhou Road,
Shanghai 200235, China;
Department of Ecology and Evolution, University of Chicago, 1101 East 57th Street, Chicago, IL 60637;
Biomolecular Structure
Research Center and Department of Molecular Biology, University of Siena, Via A. Fiorentina 1, I-53100 Siena, Italy;
Institut Pasteur, 25, Rue du Docteur
Roux, 75724 Paris Cedex 15, France; and
State Key Laboratory of Genetic EngineeringDepartment of Microbiology, School of Life Science, Fudan
University, 220 Handan Road, Shanghai 200433, China
Communicated by Zhu Chen, Shanghai Institute of Hematology, Shanghai, People’s Republic of China, December 22, 2004 (received for review
November 20, 2004)
The genomic sequences of severe acute respiratory syndrome
coronaviruses from human and palm civet of the 20032004 out-
break in the city of Guangzhou, China, were nearly identical.
Phylogenetic analysis suggested an independent viral invasion
from animal to human in this new episode. Combining all existing
data but excluding singletons, we identified 202 single-nucleotide
variations. Among them, 17 are polymorphic in palm civets only.
The ratio of nonsynonymoussynonymous nucleotide substitution
in palm civets collected 1 yr apart from different geographic
locations is very high, suggesting a rapid evolving process of viral
proteins in civet as well, much like their adaptation in the human
host in the early 2002–2003 epidemic. Major genetic variations in
some critical genes, particularly the Spike gene, seemed essential
for the transition from animal-to-human transmission to human-
to-human transmission, which eventually caused the first severe
acute respiratory syndrome outbreak of 20022003.
he prompt identification of a novel human c oronavir us
(CoV) as the etiologic agent of severe acute respiratory
syndrome (SA RS) demonstrated the power deriving f rom co-
ordinate integration of clinical investigation and molecular
virology (1–4). SA RS-CoV-like virus was isolated from a few
Himalayan palm civets (Paguma larvata) and a rac coon dog
(Nyctereutes procyonoides) at a Shenzhen food market during the
SA RS epidemic of 2002–2003 (May 7 and 8, 2003). Their
genomic sequences displayed 99.8% identit y with that of the
human SARS-CoV (5). Together with the evidence of a signif-
icant high ratio of positive cases bearing the anti-SARS-CoV
antibody in the population with a history of close contact to these
an imals, an imal–human interspecies transmission of SARS-CoV
was first proposed. Meanwhile, molecular epidemiological ap-
proaches were effectively conducted for better understanding
the origin, route of transmission, and evolution of SARS-CoV (6,
7). Characteristic genotypes were identified for viruses of dif-
ferent transmitting lineages, and the disease episodes were
categorized into different epidemiological phases based on the
c ombination of classical epidemiology analysis and molecular
phylogeny analysis using well represented viral genomic se-
quences. It was particularly interesting that critical intermediate
single-nucleotide variations (SNVs) were found among isolates
c ollected between connective phases along with their transmis-
sion paths. It also strongly suggested an an imal origin of the
human SARS-CoV and its viral adaptation to human hosts (7).
However, direct evidence of animal-to-human infection has yet
to be provided, and the molecular mechanism that enabled the
vir us to switch hosts has not been investigated.
Af ter the first epidemic of SA RS ended in July 2003, as
announced by the World Health Organ ization (WHO) (www.
who.intcsrdon20030705en), scattered new cases were re-
ported. Unlike the cases of laboratory infections reported from
Singapore (www.who.intcsrdon20030924 en), Taiwan
(www.who.intcsrdon20031217 en), and Beijing (www.
who.intcsrdon20040518aen), the four confirmed SA RS
patients of the 2003–2004 episode in the cit y of Guangzhou,
China, were all communit y-infected cases without obvious
human-to-human cont act history related to SARS (see Materials
and Methods). In this report, using the sequence data of vir uses
obt ained from these human patients as well as from palm civets
c ollected at the same period in the same region, we were able to
delineate the characteristics of the cross-host evolution of SARS-
Abbreviations: SARS, severe acute respiratory syndrome; CoV, coronavirus; SNV, single-
nucleotide variation; WHO, World Health Organization; CDSs, coding DNA sequences; S,
Spike; MRCA, most recent common ancestor; Ks, number of synonymous substitution per
synonymous site; AS, ratio of nonsynonymoussynonymous substitution numbers.
Data deposition: The sequences reported in this paper have been deposited in the GenBank
database (accession numbers are listed in Table 1, which is published as supporting
information on the PNAS web site).
H.-D.S., C.-C.T., G.-W.Z., S.-Y.W., H.-M.L., D.-H.Z., X.-W.W., H.-Y.Z., J.-D.C., P.H., H.T., and
A.B. contributed equally to this work in performing the research.
H.X., S.-J.C., M.W., R.-H.X., J.-Y.L., S.T., X.K., L.D., N.N., Y.-X.L., and C.-I.W. contributed
equally to this work in organizing the research.
To whom correspondence should be addressed. E-mail:
© 2005 by The National Academy of Sciences of the USA
February 15, 2005
vol. 102
no. 7 www.pnas.orgcgidoi10.1073pnas.0409608102
CoV over a short period. This is an essential step for under-
st anding the genetic process of the adaptation of an animal vir us
to a human host.
Materials and Methods
Epidemiological Investigation and Sample Collection. Official epi-
demiological records about SARS cases oc curring during the
2003–2004 period from both the Guangdong Center for Disease
Control and Prevention and the Guangzhou Center for Disease
Control and Prevention were reviewed. These records were
matched with the information released by WHO (
csrdon20040105en, www.who.intcsrdon20040127en,
and www.who.intcsrdon20040131en).
Human patient samples were collected by the virologists of the
Guangzhou Center for Disease Control and Prevention. Palm
civet samples from the animal cage of the restaurant TDLR were
c ollected by WHO experts, whereas those from the Guangzhou
food market were c ollected by virologists of the SARS Consor-
tium of the Minister of Agriculture of the Chinese Central
Sequencing Strategy and Procedures. The sequencing strategy was
basically the same as described (7). However, all new sequences
we obtained during this study were derived directly from RT-
PCR products of specimens from individual human patients or
an imals (or their cages, as indicated). Another set of nested PCR
primers with shorter genomic fragments being amplified was
used when the regular primer set failed to amplify the corre-
sponding genomic regions. This strategy was successful in ob-
t aining more genomic DNA fragments being amplified for
sequencing. A ll of the International Nucleotide Sequence Da-
t abase CollaborationGenBank accession nos. for SARS-CoV
sequences analyzed in the text are listed in Table 1, which is
published as supporting information on the PNAS web site.
In Silico
Sequence Analysis. Whole-genome sequence alignments
were generated by using
CLUSTALW, Ver. 1.83 (
clustalw) with the default DNA weight matrix for the 96 SARS-
CoV genomic sequences analyzed in this study (91 from human
patients and 5 from palm civets). The same method was used for the
alignment analysis of Spike (S) genes from 14 animal samples (in
addition to the five sequences from palm civet host used in
whole-genome sequence alignment, seven sequences from other
palm civet samples of the Guangzhou food market and two
sequences, SZ1 and SZ13, from palm civet samples of the 2002–
2003 epidemic were added) and 92 human SARS-CoV sequences.
Compared with the 91 sequences used in the whole genome
analysis, the previously sequenced S gene (GD03T13) from the first
patient (GZ03-01) (7) and the newly sequenced S gene from the
third patient (GZ03-03) of the 2003–2004 epidemic were added,
whereas the GZ-D of the 2002–2003 epidemic was deleted due to
the incompleteness of the sequence. The scoring algorithm used to
determine the variant loci characteristic of the SARS-CoV geno-
types and to allow the segregation of the SARS-CoV genotypes into
major groups was previously described (7), and the outcome of this
analysis is listed in Table 2, which is published as supporting
information on the PNAS web site.
For purposes of illustration, we adopted the follow ing
nomenclature as shown in Fig. 1: PC for palm civet and HP for
human patient. Both of them were suf fixed with 03 or 04 to
specif y the 2002–2003 or 2003–2004 epidemics, respectively.
Further more, the HP03 events are followed by E, M, or L,
representing the early, middle, or late phases of the 2002–2003
epidemic (7).
Analysis of the Phylogenetic Relationship Among Different Transmis-
sion Lineages of the Early Samples of SARS-CoV Sequences. The
c onsensus genomic nucleotide sequences for g roups PC04,
HP04, PC03 and individual transmission lineages of HP03E
(GZ, HSZ, and ZS) were used to c onstruct the neighbor-
join ing tree (8). Tajima’s relative rate test (9) was then
perfor med to see whether there is significant dif ference
bet ween the dist ance from PC03 to PC04 and that from PC04
to HP04.
Calculating the Average Number of Nucleotide Difference
Two Sample Groups.
We used n
and n
to denote the sample sizes
for groups 1 and 2. All of the singleton sites were excluded for
the sequences between the two groups. The total number of the
nucleotide difference D
(i 1,...,n
; j 1,...,n
) was then
calculated for two genome sequences, i and j, one from each
group. Therefore,
i, j
Analysis of the Three Most Significantly Variable Protein Coding DNA
Sequences (CDSs), S, sars3a, and nsp3, Among Palm Civets and Human
Patients of the Two Epidemics.
The phylogenetic tree of sequences
in the four groups (PC03, PC04, HP03E, and HP04) of each
gene was first constructed by the neighbor-join ing method (8).
Given the tree, we used maximum-likelihood analysis (10) for
c odon substitutions to estimate the number of nonsynony mous
and synony mous changes in each branch as well as their rate
( dNdS) (10). The codon-substitution model (11)
accounts for the genetic code structure, transition
transversion rate bias, and different base frequencies at
each c odon position. In the likelihood analysis, we applied the
most general model, which implies an independent dNdS
ratio for each branch in the phylogeny (10). A n
value 1
is usually taken as evidence for the signature of positive
selection (12).
Statistical Analysis for Estimation of the Neutral Mutation Rate and
the Date for the Most Recent Common Ancestor (MRCA) and Con-
struction of Rooted Phylogenetic Tree.
The Pamilo–Bianchi–Li
model was used to calculate the number of synony mous
substitutions per synony mous site, Ks, for the c oncatenated
five k nown major c oding sequences (or f1ab, S, E, M, and N)
of SARS-CoV, as we did previously (7). Taking GZ02 (7), the
reference sequence of the HP03 epidemic, as the outgroup, the
Kss were calculated for two PC03 SARS-CoV (SZ16 and SZ3),
three PC04 SARS-CoV (PC4-136, PC4-227, PC4-13), and two
HP04 sequences (GZ03-01 and GZ03-02), to estimate the
neutral mutation rate.
Based on the plot of Fig. 2, the intercept (
) of the fitted line
is 0.0007806, with the c orresponding sampling date 0, which is
the end of year 2002. Let T denote the number of days ahead of
January 1, 2003, for the MRCA of the PC03 and HP03 g roups.
Because we used the GZ02 as an outg roup whose sampling date
is February 11, 2003 (i.e., 42 days after January 1, 2003), the
estimated T will be T(
142)228( days), which is
equivalent to early December 2002.
The Ks between SZ16 and SZ3 is 0.001585. Therefore, the
estimated date of MRCA for PC03 group is around the end of
January 2003. (0.0015850.0000082 99 days ahead of May 7,
2003, which is the sampling date for SZ16 and SZ3).
The Ks between SZ16 and PC4-136, PC4-227, and PC4-13 are
0.003785, 0.003752, and 0.003782, respectively. Therefore, the
estimated date of MRCA for PC03 and PC04 is (0.00378
0.000008-244)2 114 days ahead of May 7, 2003, which
c orresponds to the middle of January 2003.
Based on these estimates, a rooted phylogenetic tree for
Song et al. PNAS
February 15, 2005
vol. 102
no. 7
SA RS-CoV isolates from palm civet (PC03 and PC04) and early
human patients (HP03E and HP04) is constructed (Fig. 3).
Estimating the Coevolution Coefficients Among SARS-CoV Proteins
(Identified and Hypothetical) Based on Amino Acid Substitution Rates.
The value of the linear correlation coefficient (r) of the amino acid
substitution rates between two proteins of SARS-CoV indicates
their level of coevolution (13). We first conducted multiple se-
quence alignment for each of the SARS proteins (among 72
samples with 21 assigned or predicted protein CDSs without gap in
the coding areas) and then used them to build matrices containing
the distances between all possible protein pairs. Distances were
calculated as the average value of the residue similaritie s taken from
the McLachlan amino acid homology matrix (14). The outcome of
this study is listed in Table 3, which is published as supporting
information on the PNAS web site.
Results and Discussion
Contact History and Clinical Symptoms of the Four Confirmed SARS
Patients (2003–2004) Provide Direct Evidence of Animal-to-Human
The epidemiology information collected by the Guang-
dong Center for Disease Control and Prevention and the Guang-
zhou Center for Disease Control and Prevention indicated that
bet ween December 16, 2003, and January 8, 2004, a total of four
patients were independently hospit alized in the city of Guang-
zhou, Guangdong Province, China, with flu-like syndromes later
diagnosed as confirmed SARS cases (see Materials and Meth-
ods). Although none of these patients had a contact history with
the other previously documented SARS cases, they all had direct
or indirect contact history with wild an imals in geographically
restricted areas. The second patient worked in a local restaurant,
TDLR, and the fourth patient dined in the same restaurant
where palm civet and other exotic dishes were served, whereas
Fig. 1. Genotype clustering of SARS-CoV covering the epidemics from 2002 to 2004. It is illustrated by an unrooted phylogenetic tree constructed with complete
SNVs and deletions of 91 sequences from the human patient-derived viruses (HP) and five sequences from the palm civet-derived viruses (PC) (A) and a
neighbor-joining (N-J) tree for the consensus nucleotide sequences of PC and early individual transmission lineages of HP (B). In A, the division of the clusters
and the corresponding nomenclatures was based on both the hosts of the viruses and the phases of the epidemic (7) (Table 2). The map distance between
individual sequences represents the extent of genotypic difference. To highlight the variations between two neighboring clusters, the number of SNVs [total
(synonymous, nonsynonymous causing drastic amino acid changes)] occurring among the genomic sequences of both groups and the average number of
nucleotide difference D between the two sample groups (see Materials and Methods) were shown in the boxes. Besides the SNVs of the whole genome (Total),
those occurring in
ORF1AB (particularly in ORF1A, which is part of Orf1ab), S, and sars3a are listed in the same manner as the total SNVs. These SNVs were present
in at least two independent samples of all the sequences used for this analysis. In B, consensus nucleotide sequences were derived from each PC and HP data set.
For HP03E, consensus nucleotide sequences were individually derived from three primary transmission lineages, based on their direct epidemiological
connections and high genomic sequence similarities, and were represented as HP03EGZ (Guangzhou), HP03EHSZ (Shenzhen), and HP03EZS (Zhongshan). These
six consensus nucleotide sequences were used to construct the N-J tree (8) in
MEGA2 (23), and the Kimura 2-parameter model was assumed. The branch lengths
are the estimates of genetic distances.
www.pnas.orgcgidoi10.1073pnas.0409608102 Song et al.
the third patient dined in a neighboring rest aurant, SJR. These
restaurants are located near two major hospitals in Guangzhou
where many SARS patients were treated in the previous epi-
demic, and the first patient, the only patient with no c ontact with
TDLR or SJR, visited one of the hospitals in February 2003. This
index patient also cont acted house rats in his apartment a few
days before disease onset. It is import ant to emphasize that,
unlike most SARS patients during the 2002–2003 epidemic,
these four new patients clinically presented very mild symptoms,
and neither of them had close cont acts who were infected (15).
Genomic Sequences of SARS-CoV from both the Human Patients and
the Market Palm Civet of the 2003–2004 Outbreak Are Almost Iden-
Among the specimens collected during the 2003–2004
outbreak in Guangzhou (see Materials and Methods), we were
able to sequence nearly completely the SARS-CoV viral genome
f rom the first t wo of the four human patients, the two palm civets
of the Guangzhou food market, and one sample from the palm
civet cage at the restaurant TDLR. These genomic sequences
were characterized and phylogenetically analyzed by comparison
with 89 human SA RS-CoV and two SARS-like-CoV sequences
f rom the Himalayan palm civets available at GenBank as of the
end of September 2004, using the in silico analysis methodolog y
adopted previously. A total of 202 SNVs with multiple occur-
rences were identified, among which 200 were in the CDSs.
Among the 128 nonsynonymous mutations, 89 led to a predicted
radical amino acid changes (Table 2 and Fig. 1 A).
Besides the individual sequence-based analysis, we further
analyzed the data based on comparisons bet ween groups of
samples. A lthough both the nomenclature for sample groups and
the analytical methods are described in Materials and Methods,
an abbreviated nomenclature will be redefined in the text on first
oc currence.
A ll of the HP04 and PC04 (human patient and palm civet,
2003–2004) SARS-CoV isolates ret ained the 29-nt segment
marker in orf8a as in the viruses of PC03 (palm civet 2002–2003)
and the Guangzhou primary transmission lineages of HP03E
(human patient 2002–2003, early phase). The genomes of the
SA RS-CoV from HP04 were almost identical to those of the
SA RS-CoV-like viruses from PC04 (Fig. 1 A). There were 33
SNVs detected among the viral genomic sequences from PC04
and HP04, which accounts for 0.11% of the viral genome. The
average total number of nucleotide differences in the whole
genome bet ween the two groups is 20.33. In contrast, between
genomic sequences of HP03E and PC03, the average number of
nucleotide differences is 39.5, and a total of 77 SNVs was
detected, accounting for nearly 0.26% of the viral genome (Fig.
1 A). A lthough 17 of the 202 SNVs were polymorphic in the palm
civets only, no signature SNVs are shared by all members of palm
civet isolates distinguishable from all members of the human
isolates (Table 2).
The phylogenetic relationship among different transmission
lineages of the early samples of SARS-CoV sequences were also
analyzed on the basis of consensus of each epidemiological
phaseprimary transmission lineage (7) (Fig. 1B). Tajima’s
relative rate test was perfor med based on the phylogenetic
analysis of consensus nucleotide sequence of PC04 as the root,
was 39.72 with one degree of freedom (P 0.000), i.e., the
dist ance between PC04 and PC03 is significantly larger than that
bet ween PC04 and HP04. Thus, structurally, there is little
dif ference to distinguish the genomic sequences of the SARS-
CoV and SARS-CoV-like vir uses and functionally, c oncerning
the animal contact history of the current patients, it is likely that
the same virus can infect both palm civet and human.
The Estimation of the Neutral Mutation Rate and the Date for the
MRCA Illustrated the Evolving SARS-CoV in both Palm Civet and
Human. We used the concatenated five major CDSs (orf1ab, S, E,
M, and N) of SARS-CoV from PC03, PC04, and HP04 to estimate
the neutral mutation rate during SARS-CoV transmission in palm
civets and HP04 (Fig. 2). The total length of the concatenated
sequence accounts for 91.25% of the whole genome. The estimate
turned out to be 8.00 10
, which is almost the same
as that estimated in our previous work based on 10 samples in HP03
group (8.26 10
) (7). These two independent esti-
mates are almost identical, and thus it supports well the previous
conclusion. On the other hand, because samples of PC03, PC04, and
HP04 were collected 1 yr apart from different geographic locations,
this new estimate should be more accurate. This relatively long-
term evolutionary analysis once again strongly suggested that
SARS-CoV evolves at a relatively constant neutral rate both in
human and palm civet. Furthermore, the date estimates of the
MRCAs for PC03, HP03E, PC04, and HP04 were obtained (see
Fig. 2. A plot of the number of synonymous substitutions per synonymous
site, Ks, for the concatenated coding sequences vs. the sampling dates. The Ks
calculation and samples used are described in Materials and Methods. The
sampling dates are measured as the number of days away from Jan. 1, 2003.
The slope (
) of the fitted line from the linear regression model gives the
estimation of the neutral rate, 8.00 10
per site per day.
Fig. 3. A rooted phylogenetic tree for SARS-CoV isolates from palm civet
(PC03 and PC04) and early human patients (HP03E and HP04) based on MRCA
estimations. All data are described in Materials and Methods except that for
HP03E, which was from previous work (7). The branch length is proportional
to the time interval.
Song et al. PNAS
February 15, 2005
vol. 102
no. 7
Materials and Methods), which enabled us to derive a rooted
phylogenetic tree (Fig. 3). It clearly indicated that PC03 and PC04
are not in the same primary transmission lineage. The viral trans-
mission from animal to human occurred independently in these two
instances. PC03 and PC04 further diverged around January 2003,
i.e., after the PC03 and HP03 groups bifurcated. Given the relatively
long divergence time since their MRCA, it is no surprise to observe
an average of 70.83 total nucleotide difference between the viral
genome PC03 and PC04 (Fig. 1A), higher than that observed for
PC03 and HP03E (see above). Because a higher viral load of PC04
was sugge sted in palm civets from Guangzhou food market during
the 2003–2004 outbreak based on the fact that it was much easier
to obtain SARS-CoV samples for genomic sequencing than that
during the 2002–2003 epidemic (laboratory experience; C.-C.T.,
H.X., and J.-D.C.), PC04 might have evolved to be more virulent
in or better adapted to palm civet. This further demonstrated that
SARS is a zoonotic disease from still-unknown origin that has been
evolving not only in human but also in palm civet hosts.
The Three Most Significantly Variable Protein CDSs, S, sars3a, and
nsp3, Evolved Differently Among Palm Civets and Human Patients of
the Two Epidemics.
The phylogeny relationship among palm civets
and human patients of the two epidemics was further analyzed
by using the maximum-likelihood method (10) based on the
three most significantly variable CDSs, S, sars3a, and nsp3 (Fig.
4). In the S gene (Fig. 4A), from the ancestor node of PC03 to
the node of PC04, the ratio of nonsynonymoussynonymous
substitution numbers (AS) is 18.22.1, i.e.,
2.68 (
dNdS: ratio of nonsynonymous and synony mous rates), indi-
cating a positive selection pressure during animal-to-animal
transmission. Furthermore, the ancestor nodes of PC04 and
HP04 in the S gene were the same, indicating that unlike during
the 20022003 epidemic, HP04 viruses did not have a chance to
diverge for enough time, although in the patient GZ03-02, they
already ac cumulated some amino acid changes (AS 61). In
c ontrast, the AS from the ancestor node of PC03 to the node
of HP03E in S gene is 11.80, which corresponds to
synony mous variations). This is consistent with our previous
c onclusion that, during the virus transmission from palm civet to
human, the S gene experienced strong positive selection and
improvement to adapt to its human host. Within the HP03E, in
most branches, we observed a very high AS, again suggesting
that the S gene was still evolving, having not yet reached its
maximum adaptation to human.
It has been shown that the sars3a CDS encodes a minor
str uctural protein associated with the S protein on the surface of
the SA RS-CoV viral envelope (16). Interestingly, the sars3a
CDS evolved in synergy w ith the S protein (Table 3). Therefore,
it is no surprise that it evolved adaptively, as did the S gene, as
a trifurcating tree for the four epidemic groups (Fig. 4B). The
ASis40 bet ween PC03 and HP03E, 40 between PC03 and
PC04 (HP04), and 60 between HP03E and HP04. In contrast,
there is no single variation among palm civets and human beings
of the current epidemic. Although the coevolving process be-
t ween S and sars3a is likely due to the need of maintaining their
necessary interaction, amino acid changes in the sars3a protein
might also be critical, as are those in the S protein, to modulate
the host switch of SARS-CoV.
The phylogenetic tree of nsp3 is largely different from that of
S or sars3a (Fig. 4C). The PC03 is very close to HP03E but
relatively more divergent from those of new cases. This suggests
that nsp3 may be under different evolutionary pressure from that
for the S and sars3a genes. In the lineage connecting the ancestor
node of HP03E and HP04 (or PC04), the AS is only 4.1 6.2
0.227), which does not show any positive selection signa-
ture. It is worth pointing out that in the new cases, there is one
mut ation at nucleotide 6295 leading to a stop codon in the nsp3
CDS of the orf1a. Considering the unique alterations of nsp3
CDS structure in SARS-CoV compared with other CoVs (17),
we propose this special mutation might acc ount for the mild
clin ical symptoms and apparent weak infectivit y of this episode.
Major Genetic Variations in the
Gene Seem Essential for the
Transition from Animal-to-Human Transmission to Human-to-Human
The S protein is responsible for binding to the
angiotensin-converting enzyme 2 (ACE2) receptor (18) and thus is
the fastest-evolving protein of SARS-CoV in the epidemic from
animal to human. Besides the S gene sequences available from
whole-genome data (Table 2, except for GZ-D of the 2002–2004
epidemic, which was deleted due to the incompleteness of the
sequence), we were able to add more S gene sequences for
alignment analysis, one from a human sample (GZ03-03) and seven
from palm civet samples of the Guangzhou food market, all for the
2003–2004 epidemic. Two sequences, SZ1 and SZ13, from palm
civet samples of the 2002–2003 epidemic publicly available were
also included in the analysis. Because the 3D structure of the S
protein was successfully simulated (Protein Data Bank ID code
1T7G) (19), it was used for a better understanding of the molecular
mechanism driving the mutations of the S gene over the course of
the epidemic. Table 4, which is published as supporting information
on the PNAS web site, lists all 49 SNVs observed in 1 of the 103
S CDS sequences, i.e., two more SNVs observed than that using
whole-genome sequences (Table 2), because more sequences were
added for the analysis. One of them (nucleotide 22220) causes
synonymous variation in the amino acid residue 243D, which is
predicted to be partially exposed at the top of the S1 domain,
Fig. 4. Phylogeny of the most variable genes, S (A), sars3a (B), and nsp3 (C) in the SARS-CoV samples from the early cases of the epidemic 2002–2003 and the
new cases of the 2003–2004 outbreak. Samples of the early cases of the 2002–2003 epidemic were selected based on two criteria: the completeness of the
sequences and their representativity in each of the epidemiology lineages. The two numbers shown along each branch are the maximum-likelihood estimates
of the numbers of synonymous and nonsynonymous substitutions for each entire gene along the branch (Materials and Methods). In each tree, a different dNdS
ratio is assumed for each branch. The branch length is proportional to the total number of estimated synonymous and nonsynonymous substitutions occurring
in that branch.
www.pnas.orgcgidoi10.1073pnas.0409608102 Song et al.
although the other (nucleotide 23163) causes a nonsynonymous
variation of amino acid residue 558FI, which is predicted to be
exposed at the side of the S1 domain but not in the predicted
receptor-binding region (20).
Of the 17 SNVs observed in animals, 10 are located in the S gene.
Among them, seven were observed in the current epidemic, one in
the previous epidemic, and two in both. With more S gene
sequences from samples of the third patient of the current epidemic
and of seven palm civets from the Guangzhou food market added
for analysis, no further changes were found in the SNV patterns.
Although mutations are dispersed over the whole protein, the
majority of the mutations are located in the S1 domain (31 of 48
total SNVs), particularly in the region (residue s 318–510) predicted
to constitute the ACE2 receptor-binding site (20), 11 SNVs corre-
sponding to 10 amino acid re sidues. Among them, except for two
synonymous variations, seven of the nine nonsynonymous muta-
tions may cause radical amino acid changes. Two of them (nucle-
otides 22422 and 22549) occurred in HP03 only, whereas the
remaining five fell into three categories. First, mutations at the
second and third nucleotide s (22927 and 22928) of codon 479 may
cause changes corresponding to three different amino acid residues
(K, R, or N). Although all of these codons were found in the palm
civet samples, only the aat codon for N was found in all of the human
samples as well as some 2003–2004 palm civet samples (PC04).
Second, the c3t switch of nucleotide 22570 causing the S3 F
mutation of codon 360 distinguishes the virus of the 2002–2003
epidemic (HP03) from all other viruses isolated from palm civet
(PC03 and PC04) as well as human patients of the 2003–2004
outbreak (HP04). Third, the g3a switch of nucleotide 22930
causing the G3 D mutation of codon 480 distinguishes the virus of
2002–2003 (PC03 and HP03) from those of 2003–2004 (PC04 and
HP04), regardle ss of the source s.
Outside of the predicted receptor-binding peptide, we ob-
served another two-substitution codon (19) 609 (nucleotides
23316 and 23317), which is predicted to be buried at the interface
of the S1 and S2 domains (19). This tt a3gca switch causing an
L3 A mutation is one of a few nonsynony mous mutations that
nearly distinguishes the virus of 2002–2003 from those of 2003–
2004, disregarding either their human or animal sources.
Given such low variations in the SARS-CoV genome among
all available samples, the probability of having a multiple sub-
stitution codon is almost zero, especially for the two-substitution
c odon involving two nonsynonymous changes, codons 479 and
609 for the S gene. The latter event is the more remarkable,
because it also goes in the direction of G C enrichment, a
feature usually extremely rare in viruses, for metabolic reasons
(21). Thus, it is another good represent ative site showing the
signature of positive selection (22).
The unfortunate recurrence of SARS at the end of the year 2003
gave us the opportunity to witness the variationadaptation behav-
ior of the etiological agent of the disease. The new SARS-CoV
derived not from the preceding episode but very likely from a
common ancestor, which does not harbor the 29-nt deletion that
marks most of the virulent forms of SARS-CoV for the 2002–2003
epidemic. The fates of the virus inside the human host and in palm
civets are similar, i.e., the virus has not yet adapted to its new host,
making it evolve fast (and possibly into highly contagious andor
virulent forms), and in general the infection is mild. Therefore,
humans working with wild animals are often seropositive for the
SARS-CoV without noticeable symptoms (5). All of this points to
a common source of disease lingering in the environment, presum-
ably adapted to its nature host that can come in contact with
humans andor animals. It may have a fairly high probability of
mutating under favorable conditions to a form causing SARS in
humans. This situation is expected to yield an unusual epidemic
pattern, because a proportion of humans may have been immunized
against an innocuous form of the virus, so that distribution of the
disease, when it happens, is expected to be highly uneven. This
should prompt support for more research on the discovery of CoVs
in animals, in particular in the Guangdong region.
We are grateful for the critical technical assistance supplied by Yan
Sheng, Yi Chen, Zheng Ruan, Guo-Wen Peng, Ai-Ping Deng, Ji-Ya Dai,
Hao-Jie Zhong, Xin Zhang, Li-Mei Diao, and Yan-Hua Ao. We sincerely
thank Hong-Wei Gao for providing the necessary laboratory facilities
and Zhao-An Xin for providing coordination support. We thank Infor-
Sense (San Diego) for providing KDE BioScience software for data
analysis. We appreciate the strong support of the Ministry of Science and
Technology and the Ministry of Agriculture of the Central Government
of China and the governments of Guangdong Province and Shanghai
Municipality. This work was supported by State High Technolog y
Development Program Grant 2003AA208407, State Key Program for
Basic Research Grants 2003CB514101 and 2003CB715904 (to P.H.), the
Guangdong Provincial Program on SARS Prevention and Treatment
(Project No. 2003FD02-06), and European Commission Grant
EPISARS (no. 511063). H.-D.S., G.-W.Z., F.C., C.-M.P., and S.-J.C. are
partly supported by a SARS Research Grant from the Bank of BNP
PARIBAS. P.H., Z.-M.G., H.-Y.P., W.-Z.H., and Y.-X.L. are partly
supported by the Shanghai Commission of Science and Technology. H.T.
is supported by a National Institutes of Health grant (to C-.I.W.).
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no. 7
    • "raccoon dogs, masked palm civets and hog badger and spilling over to human population through close contact with these animals or their tissues. Later on adaptive mutations in virus genome lead to human to human transmission of virus (Song et al., 2005). The disease potential of a SARS like virus, SHC014-CoV from Chinese horse shoe bat (Rhinolophidae) was studied using reverse genetics system where a chimeric virus was prepared which expressed spikes of bat coronavirus SHC014 in a mouse adapted wild type SARS-CoV backbone (Menachery et al., 2015). "
    Full-text · Dataset · Jun 2016 · Science China. Life sciences
    • "raccoon dogs, masked palm civets and hog badger and spilling over to human population through close contact with these animals or their tissues. Later on adaptive mutations in virus genome lead to human to human transmission of virus (Song et al., 2005). The disease potential of a SARS like virus, SHC014-CoV from Chinese horse shoe bat (Rhinolophidae) was studied using reverse genetics system where a chimeric virus was prepared which expressed spikes of bat coronavirus SHC014 in a mouse adapted wild type SARS-CoV backbone (Menachery et al., 2015). "
    [Show abstract] [Hide abstract] ABSTRACT: Abtract Infectious diseases are one of the greatest threats to animal and human population living in the developing world. These diseases have capacity to instigate in a small area and then open out very fast to the rest of the world and causing a heavy pandemic situation, for example; avian influenza pandemic. Such diseases infect large masses of population and may lead to loss of lives and also incur huge economic losses. Therefore, the best way to control these diseases is by diagnosing it at a very primary level and taking necessary precautionary measures so as to avoid the spread. Since last few years, the diagnostic approach has changed from tedious molecular biological techniques, to easy and rapid diagnostic techniques. Nanotechnology has extended the molecular diagnostics limit to nanoscale. These developed techniques do not require sophisticated laboratories and expert personnel, and hence are a cheap diagnostic approach. These assays can also be performed at the field level where the patient is present and get the results there itself. Hence, they are also called as pen side test or lab on chip diagnostic assays. The biological tests using nanotechnology become quicker, more flexible and more sensitive. These techniques have greatly influenced the diagnostic approach in the veterinary as well as medical field. Especially in the developing countries such as India, where the laboratory services are not available at the village level, these techniques have facilitated the disease diagnosis the most. Nanotechnology also applies the tools and processes for nanofabrication which is used to build devices for studying biosystems. Molecular diagnostics incorporated with nanobiotechnology has improved clinical diagnosis and opened a new area for development of personalized medicine. Nanotechnology has also played a crucial role in designing of diagnostic assays for medical and veterinary use. The nano materials have many versatile optical properties, piezo-electric properties, thermal properties, electro-chemical properties, enzyme mimicking properties etc. By exploiting these properties, the workers have designed different approaches for diagnosis. In this review, different nano-diagnostic approaches for detection of pathogen have been stated.
    Full-text · Article · May 2016 · Science China. Life sciences
    • "GD in M. fuliginosus and BtCoV HKU8 in M. pusillus showed a higher degree of genomic similarity than any of the other CoVs, except in the S region. Phylogenetic analysis of the S protein revealed that BtCoV HKU8 clustered with HB, rather than with GD; indeed the BtCoV HKU8 S protein exhibited higher identity with HB than the other three Lineage 1 CoVs, including GD. Phylogenetic analysis, similarity plots, bootscan analysis, and recombination-breakpoint analysis suggested that recombination occurred around the S region among BtCoV HKU8, GD, and HB (Wu et al., 2015), which may have facilitated adaptation of the virus to a new bat species, finally leading to interspecies transmission (Graham and Baric, 2010; Song et al., 2005). Furthermore, within the complete genome (including the S region), some of the established Lineage 2 CoVs (AH, JX, GD-a, HB-a, and HN-a) showed high similarity to BtCoV 1A found in M. magnater, while other Lineage 2 CoVs (GD-b and HN-b) showed high similarity to BtCoV 1B found in M. pusillus. "
    [Show abstract] [Hide abstract] ABSTRACT: Coronaviruses, such as severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus, pose significant public health threats. Bats have been suggested to act as natural reservoirs for both these viruses, and periodic monitoring of coronaviruses in bats may thus provide important clues about emergent infectious viruses. The Eastern bent-wing bat Miniopterus fuliginosus is distributed extensively throughout China. We therefore analyzed the genetic diversity of coronaviruses in samples of M. fuliginosus collected from nine Chinese provinces during 2011-2013. The only coronavirus genus found was Alphacoronavirus. We established six complete and five partial genomic sequences of alphacoronaviruses, which revealed that they could be divided into two distinct lineages, with close relationships to coronaviruses in Miniopterus magnater and Miniopterus pusillus. Recombination was confirmed by detecting putative breakpoints of Lineage 1 coronaviruses in M. fuliginosus and M. pusillus (Wu et al., 2015), which supported the results of topological and phylogenetic analyses. The established alphacoronavirus genome sequences showed high similarity to other alphacoronaviruses found in other Miniopterus species, suggesting that their transmission in different Miniopterus species may provide opportunities for recombination with different alphacoronaviruses. The genetic information for these novel alphacoronaviruses will improve our understanding of the evolution and genetic diversity of coronaviruses, with potentially important implications for the transmission of human diseases.
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