Sequence analysis of the Spike, RNA-dependent RNA polymerase, and protease genes reveals a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia.

During the Covid-19 pandemic, the resurgence of SARS-CoV-2 was due to the development of novel variants of concern (VOC). Thus, genomic surveillance is essential to monitor continuing evolution of SARS-CoV-2 and to track the emergence of novel variants. In this study, we performed phylogenetic, mutation, and selection pressure analyses of the Spike, nsp12, nsp3, and nsp5 genes of SARS-CoV-2 isolates circulating in Yogyakarta and Central Java provinces, Indonesia from May 2021 to February 2022. Various bioinformatics tools were employed to investigate the evolutionary dynamics of distinct SARS-CoV-2 isolates. During the study period, 213 and 139 isolates of Omicron and Delta variants were identified, respectively. Particularly in the Spike gene, mutations were significantly more abundant in Omicron than in Delta variants. Consistently, in all of four genes studied, the substitution rates of Omicron were higher than that of Delta variants, especially in the Spike and nsp12 genes. In addition, selective pressure analysis revealed several sites that were positively selected in particular genes, implying that these sites were functionally essential for virus evolution. In conclusion, our study demonstrated a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia.

Prognostic factors for the outcomes of COVID-19 patients infected with SARS-CoV-2 Omicron and Delta variants.

BACKGROUND: The SARS-CoV-2 Omicron variant has replaced the previously dominant Delta variant because of high transmissibility. However, studies on the impact of the Omicron variant on the severity of COVID-19 are still limited in developing countries. Our study aimed to determine the prognostic factors for the outcomes of patients infected with SARS-CoV-2 Omicron and Delta variants, including age, sex, comorbidities, and smoking. METHODS: In this retrospective cross-sectional study, we involved 352 patients with COVID-19 from Yogyakarta and Central Java provinces, Indonesia, from May 2021 to February 2022, consisting of 164 males and 188 females. We included all patients with the PCR's Ct value of less than 30 for further whole-genome sequencing. RESULTS: Ct value and mean age of COVID-19 patients were not significantly different between both groups (p = 0.146 and 0.273, respectively). Patients infected with Omicron (n = 139) and Delta (n = 213) variants showed similar hospitalization (p = 0.396) and mortality rates (p = 0.565). Multivariate analysis of both groups showed that older age (≥ 65 years) had a higher risk for hospitalization (OR = 3.86 [95% CI = 1.29-11.5]; p = 0.015) and fatalities (OR = 3.91 [95% CI = 1.35-11.42]; p = 0.012). In both groups, patients with cardiovascular disease had a higher risk for hospitalization (OR = 5.36 [95% CI = 1.08-26.52]; p = 0.039), whereas patients with diabetes revealed a higher risk for fatalities (OR = 9.47 [95% CI = 3.23-27.01]; p = < 0.001). CONCLUSIONS: Our study shows that patients infected with Omicron and Delta variants reveal similar clinical outcomes, including hospitalization and mortality. Our findings further confirm that older age, cardiovascular disease, and diabetes are substantial prognostic factors for the outcomes of COVID-19 patients. Our findings imply that COVID-19 patients with older age, cardiovascular disease, or diabetes should be treated comprehensively and cautiously to prevent further morbidity and mortality. Furthermore, incomplete data on vaccination status hampered us from analyzing further its impact on hospitalization and mortality in our patients.

The high mutation rate at the D614G hotspot-furin cleavage site region increases the priming efficiency of the Spike protein by furin protease: analysis of Indonesian SARS-CoV-2 G614 variants obtained during the early COVID-19 pandemic.

D614G mutation plays a significant role in the transmissibility of SARS-CoV-2. Identification of other mutations related to D614G mutation within the Spike protein is pivotal as they might contribute to the pathogenicity of SARS-CoV-2. This study aims to analyze the mutation rate of furin cleavage site (FCS) region of Indonesian origin SARS-CoV-2 and to predict the effect of mutation against Spike priming efficiency by furin. A total of 375 sequences of Indonesian isolates obtained during the early pandemic were used for mutation analysis. Mutation analysis includes mutation pattern, variability, frequency of mutation, amino acid conservation, and mutation rate. The effect of mutation against Spike priming efficiency by furin protease from eight sequences with mutation in the FCS region was analyzed by protein-protein docking. We showed that mutations related to the G614 variant were increasing through time, in contrast to the D614 variant. The FCS region at the position 675-692 contained the most variable (66.67%) as well as the highest mutation frequency (85.92%) and has been observed to be the hotspot mutations linked to the D614G mutation. The D614G hotspot-FCS region (residue 600-700) had the highest amino acid change per site (20.8%) as well as the highest mutation rate as 1.34 × 10-2 substitution per site per year (95% CI 1.79 × 10-3-2.74 × 10-2), compared with other Spike protein regions. Mutations in the FCS region were the most common mutation found after the D614G mutation. These mutations were predicted to increase the Spike priming efficiency by furin. Thus, this study elucidates the importance of D614G mutation to other mutations located in the FCS region and their significance to Spike priming efficiency by furin. Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-023-00827-w.

Facilitators and barriers of preventive behaviors against COVID-19 during Ramadan: A phenomenology of Indonesian adults.

Introduction: Intercity mobility restriction, physical distancing, and mask-wearing are preventive behaviors to reduce the transmission of COVID-19. However, strong cultural and religious traditions become particular challenges in Indonesia. This study uses the Behavior Change Wheel to explore barriers and facilitators for intercity mobility restriction, physical distancing, and mask-wearing during Ramadan. Methods: Semi-structured in-depth interviews with 50 Indonesian adults were conducted between 10 April and 4 June 2020. Having mapped codes into the Capacity, Opportunity, Motivation - Behavior (COM-B), and Theoretical Domain Framework (TDF) model, we conducted summative content analysis to analyze the most identified factors to preventive behaviors and proposed interventions to address those factors. Results: Belief about the consequence of preventive behaviors was the most mentioned facilitator to all preventive behaviors among compliers. However, optimism as a TDF factor was commonly mentioned as a barrier to preventive behaviors among non-compliers, while environmental context and resources were the most commonly mentioned factors for intercity mobility restriction. Conclusions: Public health intervention should be implemented considering the persuasion and involvement of religious and local leaders. Concerning job and economic context, policy related to the intercity mobility restriction should be reconsidered to prevent a counterproductive effect.

Sequence analysis of SARS-CoV-2 Delta variant isolated from Makassar, South Sulawesi, Indonesia.

Introduction: This study aimed to perform mutation and phylogenetic analyses of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Delta variants and analyze the characteristic signs and symptoms of patients infected with SARS-CoV-2 Delta variant originated from Makassar during the Delta outbreak.Methods: We collected samples from patients who were infected with coronavirus disease 2019 (COVID-19) between June and October 2021. We selected the Quantitative Reverse Transcription-Polymerase Chain Reaction (PCR)-positive samples with a cycle threshold value of <30 for whole genome sequencing. Total viral ribonucleic acid (RNA) was isolated from 34 PCR-positive nasopharyngeal swab samples, and whole genome sequencing was performed using the Oxford Nanopore GridlON sequencer. Phylogenetic and maximum clade credibility analyses were performed using the Bayesian Markov chain Monte Carlo method. Results: It was found that 33 patients were infected with the SARS-CoV-2 Delta variant in this cohort study, among whom 63.6% (21) patients were female. According to the clinical data, 24 (72.7%), 7 (21.2%), and 2 (6.1%) patients had mild, moderate, and severe COVID-19 infections. Phylogenetic analysis based on the spike and RNA-dependent RNA polymerase (RdRp) genes showed that the collected samples were clustered in the main lineage of B.1.617.2 (Delta variant). The Delta variants had a high frequency of distinct mutations in the spike protein region, including T19R (94.12%), L452R (88.23%), T478K (91.17%), D614G (97%), P681R (97%), and D950 N (97%). Other unique mutations found in a smaller frequency in our samples were present in the N-terminal domain, including A27T (2.94%) and A222V (14.70%), and in the receptor-binding domain, including Q414K (5.88%), G446V (2.94%), and T470 N (2.94%). Conclusion: This study revealed the unique mutations in the S protein region of Delta variants. T19R, L452R, T478K/T478R, D614G, P681R, and D950 N were the most common substitutions in Makassar's Delta variant.

Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition.

The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach has been widely used to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, instead of using it alone, clinicians often prefer to diagnose the coronavirus disease 2019 (COVID-19) by utilizing a combination of clinical signs and symptoms, laboratory test, imaging measurement (e.g., chest computed tomography scan), and multivariable clinical prediction models, including the electronic nose. Here, we report on the development and use of a low cost, noninvasive method to rapidly sniff out COVID-19 based on a portable electronic nose (GeNose C19) integrating an array of metal oxide semiconductor gas sensors, optimized feature extraction, and machine learning models. This approach was evaluated in profiling tests involving a total of 615 breath samples composed of 333 positive and 282 negative samples. The samples were obtained from 43 positive and 40 negative COVID-19 patients, respectively, and confirmed with RT-qPCR at two hospitals located in the Special Region of Yogyakarta, Indonesia. Four different machine learning algorithms (i.e., linear discriminant analysis, support vector machine, stacked multilayer perceptron, and deep neural network) were utilized to identify the top-performing pattern recognition methods and to obtain a high system detection accuracy (88-95%), sensitivity (86-94%), and specificity (88-95%) levels from the testing datasets. Our results suggest that GeNose C19 can be considered a highly potential breathalyzer for fast COVID-19 screening.

A Comparison of Bioinformatics Pipelines for Enrichment Illumina Next Generation Sequencing Systems in Detecting SARS-CoV-2 Virus Strains.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a newly emerging virus well known as the major cause of the worldwide pandemic due to Coronavirus Disease 2019 (COVID-19). Major breakthroughs in the Next Generation Sequencing (NGS) field were elucidated following the first release of a full-length SARS-CoV-2 genome on the 10 January 2020, with the hope of turning the table against the worsening pandemic situation. Previous studies in respiratory virus characterization require mapping of raw sequences to the human genome in the downstream bioinformatics pipeline as part of metagenomic principles. Illumina, as the major player in the NGS arena, took action by releasing guidelines for improved enrichment kits called the Respiratory Virus Oligo Panel (RVOP) based on a hybridization capture method capable of capturing targeted respiratory viruses, including SARS-CoV-2; therefore, allowing a direct map of raw sequences data to SARS-CoV-2 genome in downstream bioinformatics pipeline. Consequently, two bioinformatics pipelines emerged with no previous studies benchmarking the pipelines. This study focuses on gaining insight and understanding of target enrichment workflow by Illumina through the utilization of different bioinformatics pipelines named as 'Fast Pipeline' and 'Normal Pipeline' to SARS-CoV-2 strains isolated from Yogyakarta and Central Java, Indonesia. Overall, both pipelines work well in the characterization of SARS-CoV-2 samples, including in the identification of major studied nucleotide substitutions and amino acid mutations. A higher number of reads mapped to the SARS-CoV-2 genome in Fast Pipeline and merely were discovered as a contributing factor in a higher number of coverage depth and identified variations (SNPs, insertion, and deletion). Fast Pipeline ultimately works well in a situation where time is a critical factor. On the other hand, Normal Pipeline would require a longer time as it mapped reads to the human genome. Certain limitations were identified in terms of pipeline algorithm, whereas it is highly recommended in future studies to design a pipeline in an integrated framework, for instance, by using NextFlow, a workflow framework to combine all scripts into one fully integrated pipeline.

Full-genome sequencing and mutation analysis of SARS-CoV-2 isolated from Makassar, South Sulawesi, Indonesia.

Introduction: A global surge in SARS-CoV-2 cases is occurring due to the emergence of new disease variants, and requires continuous adjustment of public health measures. This study aims to continuously monitor and mitigate the impact of SARS-CoV-2 through genomic surveillance, to determine the emergence of variants and their impact on public health. Methods: Data were collected from 50 full-genome sequences of SARS-CoV-2 isolates from Makassar, South Sulawesi, Indonesia. Mutation and phylogenetic analysis was performed of SARS-CoV-2 from Makassar, South Sulawesi, Indonesia. Results: Phylogenetic analysis showed that two samples (4%) were of the B.1.319 lineage, while the others (96%) were of the B.1.466.2 lineage. Mutation analysis of the spike (S) protein region showed that the most common mutation was D614G (found in 100% of the sequenced isolates), followed by N439K (98%) and P681R (76%). Several mutations were also identified in other genomes with a high frequency, including P323L (nsp12), Q57H (ns3-orf3a), and T205I (nucleoprotein). Conclusion: Our findings highlight the importance of continuous genomic surveillance to identify new viral mutations and variants with possible impacts on public health.

Co-infection of SARS-CoV-2 with other viral respiratory pathogens in Yogyakarta, Indonesia: A cross-sectional study.

Background: Growing evidence shows that viral co-infection is found repeatedly in patients with Coronavirus Disease-2019 (COVID-19). This is the first report of SARS-CoV-2 co-infection with viral respiratory pathogens in Indonesia. Methods: Over a one month period of April to May 2020, SARS-CoV-2 positive nasopharyngeal swabs in our COVID-19 referral laboratory in Yogyakarta, Indonesia, were tested for viral respiratory pathogens by real-time, reverse transcription polymerase chain reaction (RT-PCR). Proportion of co-infection reported in percentage. Results: Fifty-nine samples were positive for other viral respiratory pathogens among a total of 125 samples. Influenza A virus was detected in 32 samples, Influenza B in 16 samples, Human metapneumovirus in 1 sample, and adenovirus in 10 samples. We did not detect any co-infection with respiratory syncytial virus. Nine (7.2%) patients had co-infection with more than two viruses. Conclusion: Viral co-infection with SARS-CoV-2 is common. These results will provide a helpful reference for diagnosis and clinical treatment of patients with COVID-19.

Evolutionary dynamics of SARS-CoV-2 circulating in Yogyakarta and Central Java, Indonesia: sequence analysis covering furin cleavage site (FCS) region of the spike protein.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new virus responsible for the COVID-19 pandemic. The emergence of the new SARS-CoV-2 has been attributed to the possibility of evolutionary dynamics in the furin cleavage site (FCS) region. This study aimed to analyze the sequence of the FCS region in the spike protein of SARS-CoV-2 isolates that circulated in the Special Region of Yogyakarta and Central Java provinces in Indonesia. The RNA solution extracted from nasopharyngeal swab samples of confirmed COVID-19 patients were used and subjected to cDNA synthesis, PCR amplification, sequencing, and analysis of the FCS region. The sequence data from GISAID were also retrieved for further genome analysis. This study included 52 FCS region sequences. Several mutations were identified in the FCS region, i.e., D614G, Q675H, Q677H, S680P, and silent mutation in 235.57 C > T. The most important mutation in the FCS region is D614G. This finding indicated the G614 variant was circulating from May 2020 in those two provinces. Eventually, the G614 variant totally replaced the D614 variant from September 2020. All Indonesian SARS-CoV-2 isolates during this study and those deposited in GISAID showed the formation of five clade clusters from the FCS region, in which the D614 variant is in one specific cluster, and the G614 variant is dispersed into four clusters. The data indicated there is evolutionary advantage of the D614G mutation in the FCS region of the spike protein of SARS-CoV-2 circulating in the Special Region of Yogyakarta and Central Java provinces in Indonesia.

Is the Infection of the SARS-CoV-2 Delta Variant Associated With the Outcomes of COVID-19 Patients?

Background: Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) Delta variant (B.1.617.2) has been responsible for the current increase in Coronavirus disease 2019 (COVID-19) infectivity rate worldwide. We compared the impact of the Delta variant and non-Delta variant on the COVID-19 outcomes in patients from Yogyakarta and Central Java provinces, Indonesia. Methods: In this cross-sectional study, we ascertained 161 patients, 69 with the Delta variant and 92 with the non-Delta variant. The Illumina MiSeq next-generation sequencer was used to perform the whole-genome sequences of SARS-CoV-2. Results: The mean age of patients with the Delta variant and the non-Delta variant was 27.3 ± 20.0 and 43.0 ± 20.9 (p = 3 × 10-6). The patients with Delta variant consisted of 23 males and 46 females, while the patients with the non-Delta variant involved 56 males and 36 females (p = 0.001). The Ct value of the Delta variant (18.4 ± 2.9) was significantly lower than that of the non-Delta variant (19.5 ± 3.8) (p = 0.043). There was no significant difference in the hospitalization and mortality of patients with Delta and non-Delta variants (p = 0.80 and 0.29, respectively). None of the prognostic factors were associated with the hospitalization, except diabetes with an OR of 3.6 (95% CI = 1.02-12.5; p = 0.036). Moreover, the patients with the following factors have been associated with higher mortality rate than the patients without the factors: age ≥65 years, obesity, diabetes, hypertension, and cardiovascular disease with the OR of 11 (95% CI = 3.4-36; p = 8 × 10-5), 27 (95% CI = 6.1-118; p = 1 × 10-5), 15.6 (95% CI = 5.3-46; p = 6 × 10-7), 12 (95% CI = 4-35.3; p = 1.2 × 10-5), and 6.8 (95% CI = 2.1-22.1; p = 0.003), respectively. Multivariate analysis showed that age ≥65 years, obesity, diabetes, and hypertension were the strong prognostic factors for the mortality of COVID-19 patients with the OR of 3.6 (95% CI = 0.58-21.9; p = 0.028), 16.6 (95% CI = 2.5-107.1; p = 0.003), 5.5 (95% CI = 1.3-23.7; p = 0.021), and 5.8 (95% CI = 1.02-32.8; p = 0.047), respectively. Conclusions: We show that the patients infected by the SARS-CoV-2 Delta variant have a lower Ct value than the patients infected by the non-Delta variant, implying that the Delta variant has a higher viral load, which might cause a more transmissible virus among humans. However, the Delta variant does not affect the COVID-19 outcomes in our patients. Our study also confirms that older age and comorbidity increase the mortality rate of patients with COVID-19.

Association between prognostic factors and the outcomes of patients infected with SARS-CoV-2 harboring multiple spike protein mutations.

The outcome of SARS-CoV-2 infection is determined by multiple factors, including the viral, host genetics, age, and comorbidities. This study investigated the association between prognostic factors and disease outcomes of patients infected by SARS-CoV-2 with multiple S protein mutations. Fifty-one COVID-19 patients were recruited in this study. Whole-genome sequencing of 170 full-genomes of SARS-CoV-2 was conducted with the Illumina MiSeq sequencer. Most patients (47%) had mild symptoms of COVID-19 followed by moderate (19.6%), no symptoms (13.7%), severe (4%), and critical (2%). Mortality was found in 13.7% of the COVID-19 patients. There was a significant difference between the age of hospitalized patients (53.4 ± 18 years) and the age of non-hospitalized patients (34.6 ± 19) (p = 0.001). The patients' hospitalization was strongly associated with hypertension, diabetes, and anticoagulant and were strongly significant with the OR of 17 (95% CI 2-144; p = 0.001), 4.47 (95% CI 1.07-18.58; p = 0.039), and 27.97 (95% CI 1.54-507.13; p = 0.02), respectively; while the patients' mortality was significantly correlated with patients' age, anticoagulant, steroid, and diabetes, with OR of 8.44 (95% CI 1.5-47.49; p = 0.016), 46.8 (95% CI 4.63-472.77; p = 0.001), 15.75 (95% CI 2-123.86; p = 0.009), and 8.5 (95% CI 1.43-50.66; p = 0.019), respectively. This study found the clade: L (2%), GH (84.3%), GR (11.7%), and O (2%). Besides the D614G mutation, we found L5F (18.8%), V213A (18.8%), and S689R (8.3%). No significant association between multiple S protein mutations and the patients' hospitalization or mortality. Multivariate analysis revealed that hypertension and anticoagulant were the significant factors influencing the hospitalization and mortality of patients with COVID-19 with an OR of 17.06 (95% CI 2.02-144.36; p = 0.009) and 46.8 (95% CI 4.63-472.77; p = 0.001), respectively. Moreover, the multiple S protein mutations almost reached a strong association with patients' hospitalization (p = 0.07). We concluded that hypertension and anticoagulant therapy have a significant impact on COVID-19 outcomes. This study also suggests that multiple S protein mutations may impact the COVID-19 outcomes. This further emphasized the significance of monitoring SARS-CoV-2 variants through genomic surveillance, particularly those that may impact the COVID-19 outcomes.

Detection of SARS-CoV-2 spike protein D614G mutation by qPCR-HRM analysis.

OBJECTIVES: Monitoring the spread of the G614 in specific locations is critical as this variant is highly transmissible and can trigger the emergence of other mutations. Therefore, a rapid and accurate method that can reliably detect the D614G mutation will be beneficial. This study aims to analyze the potential use of the two-step Reverse Transcriptase quantitative polymerase chain reaction - high resolution melting analysis (RT-qPCR-HRM) to detect a specific mutation in the SARS-CoV-2 genome. METHODS: Six SARS-CoV-2 RNA samples were synthesized into cDNA and analyzed with the qPCR-HRM method in order to detect the D614G mutation in Spike protein of SARS-CoV-2. The primers are designed to target the specific Spike region containing the D614G mutation. The qPCR-HRM analysis was conducted simultaneously, and the identification of the SARS-CoV-2 variant was confirmed by conventional PCR and Sanger sequencing methods. RESULTS: The results showed that the melting temperature (Tm) of the D614 variant was 79.39 ± 0.03 °C, which was slightly lower than the Tm of the G614 variant (79.62 ± 0.015 °C). The results of the HRM analysis, visualized by the normalized melting curve and the difference curve were able to discriminate the D614 and G614 variant samples. All samples were identified as G614 variants by qPCR-HRM assay, which was subsequently confirmed by Sanger sequencing. CONCLUSIONS: This study demonstrated a sensitive method that can identify the D614G mutation by a simple two-step RT-qPCR-HRM assay procedure analysis, which can be useful for active surveillance of the transmission of a specific mutation.

Molecular epidemiology of SARS-CoV-2 isolated from COVID-19 family clusters.

BACKGROUND: Transmission within families and multiple spike protein mutations have been associated with the rapid transmission of SARS-CoV-2. We aimed to: (1) describe full genome characterization of SARS-CoV-2 and correlate the sequences with epidemiological data within family clusters, and (2) conduct phylogenetic analysis of all samples from Yogyakarta and Central Java, Indonesia and other countries. METHODS: The study involved 17 patients with COVID-19, including two family clusters. We determined the full-genome sequences of SARS-CoV-2 using the Illumina MiSeq next-generation sequencer. Phylogenetic analysis was performed using a dataset of 142 full-genomes of SARS-CoV-2 from different regions. RESULTS: Ninety-four SNPs were detected throughout the open reading frame (ORF) of SARS-CoV-2 samples with 58% (54/94) of the nucleic acid changes resulting in amino acid mutations. About 94% (16/17) of the virus samples showed D614G on spike protein and 56% of these (9/16) showed other various amino acid mutations on this protein, including L5F, V83L, V213A, W258R, Q677H, and N811I. The virus samples from family cluster-1 (n = 3) belong to the same clade GH, in which two were collected from deceased patients, and the other from the survived patient. All samples from this family cluster revealed a combination of spike protein mutations of D614G and V213A. Virus samples from family cluster-2 (n = 3) also belonged to the clade GH and showed other spike protein mutations of L5F alongside the D614G mutation. CONCLUSIONS: Our study is the first comprehensive report associating the full-genome sequences of SARS-CoV-2 with the epidemiological data within family clusters. Phylogenetic analysis revealed that the three viruses from family cluster-1 formed a monophyletic group, whereas viruses from family cluster-2 formed a polyphyletic group indicating there is the possibility of different sources of infection. This study highlights how the same spike protein mutations among members of the same family might show different disease outcomes.

Full-length genome characterization and phylogenetic analysis of SARS-CoV-2 virus strains from Yogyakarta and Central Java, Indonesia.

BACKGROUND: Recently, SARS-CoV-2 virus with the D614G mutation has become a public concern due to rapid dissemination of this variant across many countries. Our study aims were (1) to report full-length genome sequences of SARS-CoV-2 collected from four COVID-19 patients in the Special Region of Yogyakarta and Central Java provinces, Indonesia; (2) to compare the clade distribution of full-length genome sequences from Indonesia (n = 60) from March to September 2020 and (3) to perform phylogenetic analysis of SARS-CoV-2 complete genomes from different countries, including Indonesia. METHODS: Whole genome sequencing (WGS) was performed using next-generation sequencing (NGS) applied in the Illumina MiSeq instrument. Full-length virus genomes were annotated using the reference genome of hCoV-19/Wuhan/Hu-1/2019 (NC_045512.2) and then visualized in UGENE v. 1.30. For phylogenetic analysis, a dataset of 88 available SARS-CoV-2 complete genomes from different countries, including Indonesia, was retrieved from GISAID. RESULTS: All patients were hospitalized with various severities of COVID-19. Phylogenetic analysis revealed that one and three virus samples belong to clade L and GH. These three clade GH virus samples (EPI_ISL_525492, EPI_ISL_516800 and EPI_ISL_516829) were not only located in a cluster with SARS-CoV-2 genomes from Asia but also those from Europe, whereas the clade L virus sample (EPI_ISL_516806) was located amongst SARS-CoV-2 genomes from Asia. Using full-length sequences available in the GISAID EpiCoV Database, 39 of 60 SARS-CoV-2 (65%) from Indonesia harbor the D614G mutation. CONCLUSION: These findings indicate that SARS-CoV-2 with the D614G mutation appears to become the major circulating virus in Indonesia, concurrent with the COVID-19 situation worldwide.

Significance of continuous rotavirus and norovirus surveillance in Indonesia.

BACKGROUND: Diarrhea significantly contributes to the global burden of diseases, particularly in developing countries. Rotavirus and norovirus are the most dominant viral agents responsible for diarrheal disease globally. The aim of this review was to conduct a comprehensive assessment of rotavirus and norovirus study in Indonesia. DATA SOURCES: Articles about rotavirus and norovirus surveillance in Indonesia were collected from databases, including PubMed and Google Scholar. Manual searching was performed to identify additional studies. Furthermore, relevant articles about norovirus diseases were included. RESULTS: A national surveillance of rotavirus-associated gastroenteritis has been conducted for years, resulting in substantial evidence about the high burden of the diseases in Indonesia. In contrast, norovirus infection received relatively lower attention and very limited data are available about the incidence and circulating genotypes. Norovirus causes sporadic and epidemic gastroenteritis globally. It is also emerging as a health problem in immunocompromised individuals. During post-rotavirus vaccination era, norovirus potentially emerges as the most frequent cause of diarrheal diseases. CONCLUSIONS: Our review identifies knowledge gaps in Indonesia about the burden of norovirus diseases and the circulating genotypes. Therefore, there is a pressing need to conduct national surveillance to raise awareness of the community and national health authority about the actual burden of norovirus disease in Indonesia. Continuing rotavirus surveillance is also important to assess vaccine effectiveness and to continue tracking any substantial changes of circulating rotavirus genotypes.

Identification of Rotavirus Strains Causing Diarrhoea in Children under Five Years of Age in Yogyakarta, Indonesia.

BACKGROUND: Rotavirus is an important cause of severe diarrhoea in children. The aims of this study were to identify the rotavirus strains that cause diarrhoea in children in Yogyakarta and to determine the association between rotavirus positivity and its clinical manifestations. METHODS: Clinical data and stool samples were collected from children hospitalised at Kodya Yogyakarta Hospital, Indonesia. Rotavirus was detected in stool samples using an enzyme immunoassay (EIA), which was followed by genotyping using reverse transcriptase polymerase chain reaction (RT-PCR). Electropherotyping was performed for the rotavirus-positive samples. RESULTS: In total, 104 cases were included in the study, 57 (54.8%) of which were rotavirus-positive. Based on a multiple logistic regression analysis, age group, vomiting and stool mucous were associated with rotavirus positivity. Most of the 56 samples subjected to genotyping were classified as G1 (80.36%) and P[8] (69.64%) genotypes. The genotype combination G1P[8] was identified as the most prevalent strain (66.07%). Of the 19 samples subjected to electropherotyping, 17 G1 isolates and 1 G3 isolate had long patterns, and 1 G1 isolate had a short pattern. CONCLUSION: G1P[8] was the most dominant strain of rotavirus causing diarrhoea in children in Yogyakarta. Age group, vomiting and stool mucous were associated with rotavirus positivity.