Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models
With viral sequences being added into common online databases such as NCBI virus and GISAID, the genomic information is growing as sequencing tools advance and this enables more labs to obtain and share viral genomic information. However, sequence information is passive unless we know the patter...
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| Other Authors: | |
| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
| Published: |
Nanyang Technological University
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/161407 |
| _version_ | 1811689151304564736 |
|---|---|
| author | Tan, Zi Hian |
| author2 | Shu Jian Jun |
| author_facet | Shu Jian Jun Tan, Zi Hian |
| author_sort | Tan, Zi Hian |
| collection | NTU |
| description | With viral sequences being added into common online databases such as NCBI
virus and GISAID, the genomic information is growing as sequencing tools
advance and this enables more labs to obtain and share viral genomic
information. However, sequence information is passive unless we know the
patterns and traits of the viral genetic code and the implications on infected
hosts and public health. This thesis presents the work done to extend the
knowledge in using viral sequences to understand the behaviour of viruses.
Viruses do not have to cause a global outbreak or have a high case-fatality ratio
to be of concern. The dengue virus causes mostly subclinical infections;
however, with as many as an estimated 300 million infections and 100million
recorded dengue cases per year it brings about an economic and healthcare
burden. As there is no vaccine available for the dengue virus, managing
dengue infection relies solely on vector (mosquito) management. The first of
three parts of this thesis presents a model for genomic surveillance of the
dengue virus to predict its fitness which results in higher dengue cases. By
analysing the codon usage patterns with historical clinical data, the dengue virus
sequence collected during the month with high reported cases showed fitness
adaptation to human and mosquito hosts. The fitness adaption in the dengue
sequence can be applied to genomic surveillance of mosquitos for an early
indicator of high dengue infection potential.
Next, the second part of this thesis presents on the work to characterise a novel
virus based on its sequence. In the past 2 decades, there have been 3
coronavirus outbreaks with the severe acute respiratory syndrome-related
coronavirus 2 (SARS-CoV-2) causing a global pandemic. The sequences of
SARS-CoV-2 are distinct from SARS-CoV and MERS-CoV, showing a closer
relation to coronaviruses isolated in bats. A novel method of characterising
viruses by studying the distribution pattern of amino acids encoded within
115,582 viral genomes. Viral genomes were determined to exhibit a Quanta
distribution out of 4 functions. These distribution parameters are not random;
the parameters exhibit a linear relation. Upon further analysis, the non-random
behaviour extends to defining viral families or species. By analysing the
sequences, the SARS-CoV-2 parameters lie on the natural linear line and
groups near the SARS virus responsible for the outbreak in 2003. This result
suggests that SARS-CoV-2 is a result of natural evolution. Next, by comparing
the quanta distribution parameters of spike proteins, the model can predict that
Pangolins have a possible role in the current COVID-19 outbreak.
The third and final part of this thesis predicts the susceptible animals to SARSCoV-
2. Transmission from humans to animals cannot be overlooked as SARSCoV-
2 can rapidly spread within farmed and wild animals resulting in a new
strain that can be transmitted back to humans, rendering vaccines ineffective. A
group of animals was determined likely to be susceptible to SARS-CoV-2 and
potentially act as an amplifying host. The model was compared with the similar
closely related SARS virus and found that is it consistent with identifying the
intermediate animal. Additionally, the result matches the recent mink farm
outbreak where the stray cats could have a role in the co-infection with the
minks. Our findings on susceptible animals aid in preventing human-to-animal
transmission and provide insights into the animal origins of SARS-CoV-2. |
| first_indexed | 2024-10-01T05:43:32Z |
| format | Thesis-Doctor of Philosophy |
| id | ntu-10356/161407 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:43:32Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1614072023-03-05T16:35:33Z Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models Tan, Zi Hian Shu Jian Jun Interdisciplinary Graduate School (IGS) Nanyang Institute of Technology in Health and Medicine MJJShu@ntu.edu.sg Science::Biological sciences::Genetics With viral sequences being added into common online databases such as NCBI virus and GISAID, the genomic information is growing as sequencing tools advance and this enables more labs to obtain and share viral genomic information. However, sequence information is passive unless we know the patterns and traits of the viral genetic code and the implications on infected hosts and public health. This thesis presents the work done to extend the knowledge in using viral sequences to understand the behaviour of viruses. Viruses do not have to cause a global outbreak or have a high case-fatality ratio to be of concern. The dengue virus causes mostly subclinical infections; however, with as many as an estimated 300 million infections and 100million recorded dengue cases per year it brings about an economic and healthcare burden. As there is no vaccine available for the dengue virus, managing dengue infection relies solely on vector (mosquito) management. The first of three parts of this thesis presents a model for genomic surveillance of the dengue virus to predict its fitness which results in higher dengue cases. By analysing the codon usage patterns with historical clinical data, the dengue virus sequence collected during the month with high reported cases showed fitness adaptation to human and mosquito hosts. The fitness adaption in the dengue sequence can be applied to genomic surveillance of mosquitos for an early indicator of high dengue infection potential. Next, the second part of this thesis presents on the work to characterise a novel virus based on its sequence. In the past 2 decades, there have been 3 coronavirus outbreaks with the severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) causing a global pandemic. The sequences of SARS-CoV-2 are distinct from SARS-CoV and MERS-CoV, showing a closer relation to coronaviruses isolated in bats. A novel method of characterising viruses by studying the distribution pattern of amino acids encoded within 115,582 viral genomes. Viral genomes were determined to exhibit a Quanta distribution out of 4 functions. These distribution parameters are not random; the parameters exhibit a linear relation. Upon further analysis, the non-random behaviour extends to defining viral families or species. By analysing the sequences, the SARS-CoV-2 parameters lie on the natural linear line and groups near the SARS virus responsible for the outbreak in 2003. This result suggests that SARS-CoV-2 is a result of natural evolution. Next, by comparing the quanta distribution parameters of spike proteins, the model can predict that Pangolins have a possible role in the current COVID-19 outbreak. The third and final part of this thesis predicts the susceptible animals to SARSCoV- 2. Transmission from humans to animals cannot be overlooked as SARSCoV- 2 can rapidly spread within farmed and wild animals resulting in a new strain that can be transmitted back to humans, rendering vaccines ineffective. A group of animals was determined likely to be susceptible to SARS-CoV-2 and potentially act as an amplifying host. The model was compared with the similar closely related SARS virus and found that is it consistent with identifying the intermediate animal. Additionally, the result matches the recent mink farm outbreak where the stray cats could have a role in the co-infection with the minks. Our findings on susceptible animals aid in preventing human-to-animal transmission and provide insights into the animal origins of SARS-CoV-2. Doctor of Philosophy 2022-08-31T02:16:18Z 2022-08-31T02:16:18Z 2022 Thesis-Doctor of Philosophy Tan, Z. H. (2022). Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/161407 https://hdl.handle.net/10356/161407 10.32657/10356/161407 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |
| spellingShingle | Science::Biological sciences::Genetics Tan, Zi Hian Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models |
| title | Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models |
| title_full | Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models |
| title_fullStr | Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models |
| title_full_unstemmed | Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models |
| title_short | Development of viral surveillance for endemic disease, emerging viral characterization and zoonic spill-over spill-back models |
| title_sort | development of viral surveillance for endemic disease emerging viral characterization and zoonic spill over spill back models |
| topic | Science::Biological sciences::Genetics |
| url | https://hdl.handle.net/10356/161407 |
| work_keys_str_mv | AT tanzihian developmentofviralsurveillanceforendemicdiseaseemergingviralcharacterizationandzoonicspilloverspillbackmodels |