The Phylogenetic Analysis of 5 SARS-CoV-2 Proteins’ Sequences in

Relation to Time and Geographical Location

Sophia Ying Li

1,†

, Xiayan Li

2,*

, Jiahe Gao

, Kaiyang Pang

and Deyuan Xu

Thomas Jefferson High School for Science and Technology, 6560 Braddock Rd Alexandria, VA 22312, U.S.A.

School of Computer science and Engineering, Baylor University, 1311 S 5th St, Waco, TX 76706, U.S.A.

Qingdao No.2 High School, Qingdao, Shandong, 266061, China

Revelle College, University of California San Diego, 9500 Gilman Drive, La Jolla, 92093, U.S.A.

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150076, China

Keywords: Bioinformatics, Protein Sequence, SARS-Cov-2, Geographical Location, Phylogenetic Analysis, Evolution.

Abstract: After 18 months since the start of the COVID-19 epidemic, the virus continues to plague the world. Learning

more about how SARS-CoV-2 proteins mutate and the relation to spatial location is critical in helping us

predict the spread of variants. We built an MSA and UPGMA phylogenetic tree for each of the 5 crucial ORF

sequences (S, M, E, N, and ORF1ab protein), which were collected by the latest update date for each region,

and based on the results, we are not able to conclude that SARS-CoV-2 protein sequences from different

countries co-evolved with other SARS-CoV-2 protein variants in proximity. However, some highly mutated

regions within those sequences may suggest some evolutionary pattern during this continuing pandemic.

1 INTRODUCTION

1.1 Spread of Coronavirus

The outbreak of severe acute respiratory syndrome

coronavirus (SARS-CoV-2) across the globe has had

devastating impacts on various countries. In

December 2019, the first COVID-19 infection, the

disease caused by SARS-CoV2, was reported in

Wuhan, China (Wang, Horby, Hayden, Gao 2020).

The number of infections reports then increased

rapidly around the world. In March 2020, COVID-19

was declared as a global pandemic by The World

Health Organization (WHO) (“WHO Director-

General’s opening remarks at the media briefing on

COVID-19 - 11 March 2020)

As of September 2021,

the CDC has reported almost 40 million cases and

over 600 thousand deaths in the United States of

America (CDC 2021). There has been a total of

around 218.9 million cases and 4.5 million deaths

(WHO Coronavirus (COVID-19) Dashboard).

Although the epidemic is currently under control,

COVID-19 is still spreading in some countries and

areas, threatening global health systems and health

security. For the foreseeable future, novel coronavirus

outbreaks will continue for several years, and national

and regional prevention measures will continue.

Novel coronavirus, a part of the Coronaviridae

family, causes severe respiratory infections in

mammals. According to the World Health

Organization, based on the accumulated

observations, the most common symptoms of

COVID-19 are fever, dry cough, and fatigue. Less

common symptoms include loss of taste or smell,

nasal congestion, conjunctivitis (also known as red

eyes), sore throat, headache, muscle or joint pain, and

nausea (Coronavirus disease (COVID-19).”). There

have also been many asymptomatic cases, as seen

through a study of healthcare workers by Wilder-

Smith et al (A. Wilder-Smith, M. D. Teleman, B. H.

Heng, A. Earnest, A. E. Ling, and Y. S. Leo 2005).

1.2 Geographical Location and

Mutations of SARS-Cov2

One study by Fan et al. predicted the outbreak to

come from bats and China because of the data from

past SARS-related coronavirus outbreaks. The study

predicts hotspots for the emergence of the virus using

3 factors: recombination from rich gene pools, the

distance between bats and humans, and virus

transmissibility. The researchers found the spread of

many diverse and closely related CoVs between bats

1164

Li, S., Li, X., Gao, J., Pang, K. and Xu, D.

The Phylogenetic Analysis of 5 SARS-CoV-2 Proteins’ Sequences in Relation to Time and Geographical Location.

DOI: 10.5220/0011381500003443

In Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics (ICBEB 2022), pages 1164-1173

ISBN: 978-989-758-595-1

of various provinces in China (Fan, Zhao, Shi, Zhou

2019). Their result indicated a positive relationship

between short spatial distances and bat coronavirus

mutation rate.

1.3 Coronavirus Proteins

Novel coronavirus is a single-stranded RNA virus

that consists of 4 structural proteins: surface or spike

glycoprotein (S), membrane glycoprotein (M),

envelope protein (E), and nucleocapsid

phosphoprotein (N). In the SARS-CoV2 genome,

there are 10 operating reading frames (ORF), and the

first ORF (ORF1ab) encodes for 1-16 non-structural

proteins and phosphoprotein a and b, representing the

biggest gene in the coronavirus’s genome (Satarker,

Nampoothiri 2020). The unique sequences which

ORF1ab contains have been recognized as potential

early detection targets for novel Coronavirus (Corman

et al 2020, Jung et al 2020, Wang et al 2020). The rest

code for the structural and accessory proteins. The M

protein is present in high amounts and helps mediate

the inflammatory response in hosts. The E protein is

a tiny integral membrane protein that enhances viral

pathogenicity and aids in virion assembly by

producing viroporins. The N protein enhances viral

entry and plays a critical part in virus transcription

and assembly (McBride, M. van Zyl, Fielding 2014).

The S protein is also known as surface glycoprotein or

spike protein. It plays an important role in

conformational rearrangement to membrane fusion,

which creates pores on the host transmembrane that

viral genomes can be passed through during the viral

transmission. Specifically, the peptide 353- KGDFR-

357 (H. sapiens ACE2 residue numbering), located on

the surface of the ACE2 molecule, participates in the

binding of the SARS-CoV-2 receptor-binding

domain (RBD) (Huang, Yang, Xu, Xu, Liu 2020).

The ACE2 receptor is expressed in lung, intestine,

kidney, and epithelial alveolar type II cells.

Therefore, the study of mutation patterns within S

protein may be crucial in understanding virus

reproductive adaptability and evolutionary survival in

fast. These proteins are the building blocks of the

virus, and understanding their sequence is crucial in

understanding their function. However, due to the

high mutation capacity of SARS-CoV-2 and its

increasing adaptability to the environment, more

research is still needed to eliminate the effects of the

virus and restore the normal functioning of society. In

particular, the Delta variant has been spreading faster

than other variants due to its reduced sensitivity to

antibodies that target the S proteins (Planas et al

2021). This study focuses on understanding the

evolutionary pattern among the ORF1ab, S, M, E, and

N of SARS-Cov2 from different countries. By

comparing multiple sequence alignment (MSA) and

analyzing phylogenetic trees, this study aims to

discover the correlation between mutation rates and

geographical location. Specifically, this includes the

results suggesting whether specific protein sequences

are conserved or highly mutated depending on the

region of origin.

2 RESULTS

2.1 Minimal Relationship between

Mutation of Different Proteins and

Geographical Location

Based on the 5 protein UPGMA phylogenetic trees

(see Figure 1-2), there is minimal correlation between

specific protein mutation rates and geographical

location. Moreover, there seems to be no relationship

between S, M, E, Orf1ab, and N. Each tree has a

significantly different structure based on which

region each protein sequence came from. This means

these proteins do not evolve with one another.

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(a) UPGMA phylogenetic tree of envelope protein (E)

(b) UPGMA phylogenetic tree of membrane glycoprotein (M)

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(d) UPGMA phylogenetic tree of surface Nucleocapsid protein (N)

Figure 1: UPGMA phylogenetic tree of relatively conserved SARS-CoV-2 proteins’ sequences from various countries.

The Phylogenetic Analysis of 5 SARS-CoV-2 Proteins’ Sequences in Relation to Time and Geographical Location

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2.2 MSAs Indicate There to Be No

Specific Mutation Point

There are no major similarities between where

mutations of amino acids occur in any MSAs of each

protein [see Figure 3-6]. The difference between each

region’s amino acid sequences is relatively random

indicating there are no mutation points within any of

the 5 proteins. However, this does not mean that there

are no differences between the sequences. Each

protein has variations between sequences from

different countries, and S protein evolves and mutates

most of the 5 proteins analyzed.

2.3 M, ORF1ab, N, and E Protein Are

Highly Conserved between

SARS-Cov-2 of Different Countries

The phylogenetic tree of M protein has few branches,

and there are only a few differences between the M

protein sequences of the 89 countries. The one

major variation is at position 82 aa of 222 aa where

16 sequences have threonine, 70 have isoleucine, and

2 have serine. Serine and threonine are polar amino

acids, while isoleucine is nonpolar. This may affect

the structure of the protein. 3D structure prediction is

needed to understand the impact of this variation.

Unlike the other countries’ sequences, the sequence

from Iraq and Cameroon has a long section of

’undetermined or atypical amino acids’ near the

beginning and the end respectively. Overall, the

phylogenetic tree and MSA suggest that the M protein

sequence is highly conserved. For ORF1ab, there is

one highly mutated region observed from the MSA at

3667 aa - 3691 aa, and there is a gap introduced in

Lebanon, Philippines, Venezuela, Ghana, Taiwan,

Djibouti, Cambodia, Poland, Dominican Republic,

Tunisia, Saudi Arabia, South Africa, France, Togo.

However, this region is not fully studied, so it is hard

to draw any conclusion on the contribution of this

region to the evolutionary pattern. Sequences of N

protein were analyzed, and the mutation rate is

relatively high at 503 aa. In most protein sequences,

the amino acid at this position would be asparagine.

However, there are 15 sequences where the amino

acid of this position is tyrosine. By extracting the

table corresponding to the countries of those 15

sequences, it turns out that 13 of those sequences

come from mid-latitude regions if not low-latitude

regions. These countries are mainly under the

influence of tropical climate or subtropical climates.

According to the MSA analysis, sequences of E

protein in different regions are comparatively similar.

Moreover, because there are also only a few branches

in the phylogenetic tree, E protein is likely to have a

highly conserved sequence between different

countries. The most noticeable differences are ones in

a few tropical countries: Somalia, Saudi Arabia, and

Kenya. They follow the highly conserved consistency

and mutate only in particular regions. The biggest

difference is a mismatch at 71 aa, in which 5 countries

have leucine and the rest have proline.

2.4 S Protein Is Highly Mutated

between SARS-Cov-2 of Different

Countries

Figure 2: UPGMA phylogenetic tree of highly mutated

SARS-CoV-2 of surface glycoprotein(S).

There are numerous gaps and mismatches detected

from the MSA outcome of S protein: gaps are detected

from 57 aa - 263 aa and 682 aa - 686 aa (this gap is

mainly caused by the 4 aa insertions from the Russia

sequence), and few mismatches are detected at the

regions close to the gaps. This may suggest these

regions undergo positive evolution. Within the

UPGMA Phylogenetic tree graph, the distance unit,

which is 0.001, for this tree is relatively larger than

the M, N, E, and ORF1ab protein. Surprisingly, the

sequence from Russia has a long-stretched branch at

the beginning of the root tree, which may be caused

by 4 aa insertions from 682 aa - 686 aa, and the other

region sequences which have introduced gaps, also are

at the position close to the root. There are also no

obvious spatial or time relations captured within the

protein S phylogenetic tree.

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Figure 3: Protein S frequency-based difference MSA.

Figure 4: MSA snapshot of protein N.

The Phylogenetic Analysis of 5 SARS-CoV-2 Proteins’ Sequences in Relation to Time and Geographical Location

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Figure 5: Protein M frequency-based difference MSA.

Figure 6: Protein M rasmol amino acid coloring.

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3 DISCUSSION

3.1 Geography and Time Have an

Insignificant Role in SARS-Cov-2

Evolution Pattern

In the UPGMA phylogenetic tree of the 5 proteins, it

is hard to conclude that location and time play a role

in the SARS-CoV-2 evolutionary path. For instance,

the latest sequences for countries in North America on

the S protein phylogenetic tree is scattered: USA is on

branch 17, but Canada is on branch 0. Moreover, the

protein sequence QNT 35432.1, Puerto Rico,

2020/09/18 updated in 2020 is not close to the root,

which may be due to global traveling. Traveling

makes the contact of individuals from non-

neighboring regions easier, so the study of sequences

from a region with less traveling may help eliminate

this factor. Moreover, this introduction of a new

variant may be the reason that unrelated protein

sequences are similar. Further studies are needed to

understand the mechanisms related to the mutation

rates of SARS-CoV-2 proteins. A similar study on

SARS-CoV SNVs (Single nucleotides variations)

also suggests that SNVs frequency across different

regions may be different by geography and time

(Chen, Altschuler, Zhan, Chan, Deverman 2021).

Therefore, there are minimal effects from geography

and time on the small-scale (nucleotide) evolutionary

pattern, and this result may be similar to the minimal

effects of geography and time on a larger scale

(sequences).

3.2 Difference between Highly Mutated

and Conserved Proteins

The phylogenetic tree of the ORF1ab protein has a

smaller scale compared to the phylogenetic tree of

other proteins. Because this protein consists of 2/3 of

the RNA and encodes for the nonstructural proteins,

the results strongly suggest the sequence of this

protein is highly conserved between SARS-CoV-2 of

different countries. Considering the function of N and

E protein have with the virus assembly, the process is

highly vulnerable to the temperature of the

environment. In other words, the difference occurring

at 503 aa of N protein and 71 aa of E protein may be

the adaptivity of the proteins to the climate, further

altering the virus’ survival and spreading under

different climates. More research on the temperature

sensitivity of N protein is needed to understand this

difference. The highly conserved nature of M

proteins is likely related to its function in helping the

virus survive in host cells as it inhibits NFB (Nuclear

Factor Kappa B), which needs to be activated to

produce an immune response to pathogens. This

process is specific because of the direct interaction

between M protein and Iκκβ (I Kappa B Kinase)

(Fang et al 2007). Noticeably, Protein S MSA

outcome reveals two highly mutated regions occurred

from 57 aa - 263 aa and 682 aa - 686 aa in sequence,

and those highly mutated regions are found in the N-

terminal domain (NTD) of the S1 subunit and S1/S2

cleavage regions. The second highly mutated regions

are 6 - 10 aa upstream of the cleavage site, which this

site should be cleaved during virus egress, and highly

mutation pattern captured within this site may suggest

that the variability of this region provide a gain-of-

function to the SARS-CoV-2 for efficient spreading in

the human population compared to other lineage b

beta coronaviruses (Coutard 2020). Since the

comparison made is between countries, it may also

suggest that this virus is highly adaptable within a

changing environment. Additionally, evidence shows

that NTD of the S1 subunit is involved in promoting

cytokine release in immune cells, and this appearance

of cytokines can lead to respiratory failure and a fatal

outcome (Chan et al 2021). Thus, the frequent

mutation within NTD-S1 subunit regions may give

rise to varying severity of immune response across the

different mutant strains and adaptive attack pathways

towards different races of peoples’ immune systems.

In general, the mutation pattern of SARS-CoV-2

Protein S may assist the rapid spreading rate and acute

immune response during the evolution process.

3.3 Future Direction

Combining the study of human immune response

variants towards SARS-CoV-2 may be conse

quential

for understanding how the mutations get selected in the

co-evolution with the host immune

system

mechanisms, and the patient’s record from the

GWAS catalog can be a valuable resource for

analysis. In addition, understanding how these

mutations affect each of the protein structures will be

crucial in finding further therapeutic options and

improving vaccine booster shots.

4 METHODS

4.1 Protein Sequences Collection

The latest sequences of ORF1ab polyprotein, spike

glycoprotein, envelope protein, membrane

glycoprotein, nucleocapsid phosphoprotein were

The Phylogenetic Analysis of 5 SARS-CoV-2 Proteins’ Sequences in Relation to Time and Geographical Location

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collected for each region (“INSDC Country List.) if

the data was present. In this study, these sequences

were collected by a script, which is available at

github repository. Entrez-direct (Kans 2021) an Unix

command-line tool that provides access to the NCBI

interconnected database, was used to collect the

protein ID, regions name and update dates, and

download sequences in FASTA files format. There

were 88 sequences collected for ORF1ab, 91

sequences collected for protein S, 89 sequences

collected for Protein E, 89 sequences collected for

Protein M, and 89 sequences collected for Protein N.

The header for each sequence in the FASTA file was

substituted into the format of “protein id:region name

updateDate” to produce straightforward vi-

sualization for further analysis, and “fixed

sequences.fasta” file stores the fixed header and

amino acids sequence. All sequences for five proteins

were collected on 09/04/2021, and the MSA and

Phylogenetics Tree analyses were made on the same

day.

4.2 MSA Analysis

The five sequences FASTA files were separately

aligned by MUSCLE, a tool for creating multi- ple

alignments of protein sequences in high biological

accuracy and time efficiency (Edgar 2004). No

special parameters were set except the input file and

output file because the alignments were relatively

short and there were few alignments. After running

MUSCLE on a five sequence FASTA file, it

produced the alignments files which insert gaps to

achieve the maximum sum-of-pairs (SP) score. The 5

alignment files were the input of the MEGA X tool to

make the UPGMA phylogenetic trees. Because it was

hard to capture the mismatch and gaps in 5 alignment

files, NCBI Multiple Se- quence Alignment Viewer

(NCBI Multiple Sequence Alignment Viewer) a

graphical display for multiple alignments of

nucleotide and protein sequences, is used to produce a

better graphic visualization of MSA analysis results.

The partial or whole scope of MSA outcome was

captured to show the significant regions.

4.3 UPGMA Phylogenetics Tree

Analysis

Finally, the UPGMA phylogenetic trees were created

by MEGA X (Kumar, Stecher, Li, Knyaz, Tamura

2018) a software that implements tools for

phylogenomic analysis. ‘Bootstrap method’ -> ‘Test

of Phylogeny’, ‘500’ -> ‘No. of Bootstrap

Replication’, ‘Amino Acid’ -> ‘Substitutions Type’,

Poisson model’ -> ‘Model/Method’, ‘Uniform Rates’

-> ‘Rates among sites’, ‘same (Homogeneous)’ ->

‘Pattern among Lineages’, and ‘Pairwise deletion’-

>’Gaps/Missing Data Treatment’ were set for the

progress, and rooted trees were kept in a circle

format.

5 CONCLUSION

By analyzing the UPGMA phylogenetic tree and

MSAs of each protein, the results show that

geographical location has an insignificant impact on

SARS-CoV-2 protein mutations and relationships. A

few potential highly mutated regions among the

sequence of each region may suggest the dynamic

adaptivity to diverse environments and alternative

invading strategies to human immune response.

Because geographical location and time do not have a

direct relationship to SARS-CoV-2 protein

mutations, there may be a more complex underlying

factor to explain the relationships between the

protein sequences of various SARS-CoV-2 which can

be studied in the future. Carriers such as different

animals and humans may be one of the many factors

that contribute to this similarity between protein

sequences. Variability in the human immune system

may also be a fac- tor that causes indirect relations

between temporal, geographical location, and SARS-

CoV-2-point mutation patterns. Therefore, more

studies about how the human immune system evolved

during the pandemic should be analyzed. This could

be done by researching patients’ variants record from

the GWAS catalog to prove the correlation with the

variability of the human immune system.

ACKNOWLEDGMENTS

Author superscripts are ordered by number for

contribution and letter for alphabetical order by

authors’ name. Sophia Ying Li and Xiayan Li are the

first co-authors (marked by plus sign), and Jiahe Gao,

Kaiyang Pang, and Deyuan Xu are the second co-

authors.

LIST OF FIGURES

UPGMA phylogenetic tree of relatively

UPGMA phylogenetic tree of highly mutated

SARS-CoV-2 of surface glycoprotein (S).

MSA Overview of protein S

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MSA snapshot of protein N

Protein M frequency-based difference MSA

Protein M rasmol amino acid coloring

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