Dataset Information

Analysis of SARS-CoV-2 Genomes from West Java, Indonesia.

ABSTRACT: West Java Health Laboratory (WJHL) is one of the many institutions in Indonesia that have sequenced SARS-CoV-2 genome. Although having submitted a large number of sequences since September 2020, however, these submitted data lack advanced analyses. Therefore, in this study, we analyze the variant distribution, hotspot mutation, and its impact on protein structure and function of SARS-CoV-2 from the collected samples from WJHL. As many as one hundred sixty-three SARS-CoV-2 genome sequences submitted by West Java Health Laboratory (WJHL), with collection dates between September 2020 and June 2021, were retrieved from GISAID. Subsequently, the frequency and distribution of non-synonymous mutations across different cities and regencies from these samples were analyzed. The effect of the most prevalent mutations from dominant variants on the stability of their corresponding proteins was examined. The samples mostly consisted of people of working-age, and were distributed between female and male equally. All of the sample sequences showed varying levels of diversity, especially samples from West Bandung which carried the highest diversity. Dominant variants are the VOC B.1.617.2 (Delta) variant, B.1.466.2 variant, and B.1.470 variant. The genomic regions with the highest number of mutations are the spike, NSP3, nucleocapsid, NSP12, and ORF3a protein. Mutation analysis showed that mutations in structural protein might increase the stability of the protein. Oppositely, mutations in non-structural protein might lead to a decrease in protein stability. However, further research to study the impact of mutations on the function of SARS-CoV-2 proteins are required.

SUBMITTER: Fibriani A

PROVIDER: S-EPMC8538575 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Analysis of SARS-CoV-2 Genomes from West Java, Indonesia.

Fibriani Azzania A Stephanie Rebecca R Alfiantie Afifah Alifia AA Siregar Agust Leo Fany ALF Pradani Gusti Ayu Prani GAP Yamahoki Nicholas N Purba William Steflandel WS Alamanda Cut Nur Cinthia CNC Rahmawati Ema E Rachman Rifky Waluyajati RW Robiani Rini R Ristandi Ryan Bayusantika RB

Viruses 20211018 10

West Java Health Laboratory (WJHL) is one of the many institutions in Indonesia that have sequenced SARS-CoV-2 genome. Although having submitted a large number of sequences since September 2020, however, these submitted data lack advanced analyses. Therefore, in this study, we analyze the variant distribution, hotspot mutation, and its impact on protein structure and function of SARS-CoV-2 from the collected samples from WJHL. As many as one hundred sixty-three SARS-CoV-2 genome sequences submit ...[more]

PMID: 34696527

Similar Datasets

Project description:Dengue is an infectious disease caused by infection of dengue virus (DENV) transmitted by Aedes aegypti and Aedes albopictus. In Indonesia, dengue commonly occurs with an increasing incidence rate annually. It is known that early detection of dengue infection is one of the keys to controlling this disease outbreak. Rapid and accurate early detection to diagnose dengue can be achieved by molecular tests, one of which is through a real-time PCR method. However, real-time PCR assay for dengue developed based on Indonesian DENV sequences has not been available. Therefore, we developed in-house dengue real-time PCR (SYBR- and TaqMan-based) assays and evaluated those assays in routine clinical testing in the community. These assays target the 3' UTR region of the four DENV serotypes and was found to be specific for DENV. The most sensitive assay was the TaqMan assay with the LOD95% of 482 copy/ml, followed by the SYBR assay with the LOD95% of 14,398 copy/ml. We recruited dengue suspected patients from three primary health care services in West Java, Indonesia to represent the community testing setting. Dengue infection was examined using the two in-house real-time PCR assays along with NS1, IgM, and IgG rapid diagnostic tests (RDT). In total, as many as 74 clinical specimens of dengue suspected patients were included in this study. Among those patients, 21 were positive for TaqMan assay, 17 were positive for SYBR assay, nine were positive for NS1 test, six were positive for both IgG and IgM tests, and 22 were positive for IgG test only. Compared with our in-house TaqMan assay, the sensitivity of NS1 test, IgM test, and IgG test were 42.86%, 14.29%, and 28.57% respectively. Among these three RDT tests, NS1 showed 100% specificity. Thus, our study confirmed that NS1 test showed high specificity, indicating that a positive result of NS1 can be confidently considered a dengue case. However, NS1, IgM, and IgG tests with RDT are not enough to diagnose a dengue case. We suggest applying the high sensitivity and specificity rRT-PCR test as the gold standard for early detection and antibody test as a follow-up test for rRT-PCR negative cases.

Project description:Larval surveillance is the central approach for monitoring dengue vector populations in Indonesia. However, traditional larval indices are ineffective for measuring mosquito population dynamics and predicting the dengue transmission risk. We conducted a 14-month ovitrap surveillance. Eggs and immature mosquitoes were collected on a weekly basis from an urban village of Bandung, namely Sekejati. Ovitrap-related indices, namely positive house index (PHI), ovitrap index (OI), and ovitrap density index (ODI), were generated and correlated with environmental variables, housing type (terraced or high-density housing), ovitrap placement location (indoor or outdoor; household or public place), and local dengue cases. Our results demonstrated that Aedes aegypti was significantly predominant compared with Aedes albopictus at each housing type and ovitrap placement location. Ovitrap placement locations and rainfall were the major factors contributing to variations in PHI, OI, and ODI, whereas the influences of housing type and temperature were subtle. Indoor site values were significantly positively correlated to outdoor sites' values for both OI and ODI. OI and ODI values from households were best predicted with those from public places at 1- and 0-week lags, respectively. Weekly rainfall values at 4- and 3-week lags were the best predictors of OI and ODI for households and public places, respectively. Monthly mean PHI, OI, and ODI were significantly associated with local dengue cases. In conclusion, ovitrap may be an effective tool for monitoring the population dynamics of Aedes mosquitoes, predicting dengue outbreaks, and serving as an early indicator to initiate environmental clean-up. Ovitrap surveillance is easy for surveyors if they are tasked with a certain number of ovitraps at a designated area, unlike the existing larval surveillance methodology, which entails identifying potential breeding sites largely at the surveyors' discretion. Ovitrap surveillance may reduce the influence of individual effort in larval surveillance that likely causes inconsistency in results.

Dataset Information

Analysis of SARS-CoV-2 Genomes from West Java, Indonesia.

Publications

Analysis of SARS-CoV-2 Genomes from West Java, Indonesia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets