• Genomics & Informatics
• /
• 제18권4호
• /
• pp.44.1-44.7
• /
• 2020

The severity of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), greatly varies from patient to patient. In the present study, we explored and compared mutation profiles of SARS-CoV-2 isolated from mildly affected and severely affected COVID-19 patients in order to explore any relationship between mutation profile and disease severity. Genomic sequences of SARS-CoV-2 were downloaded from Global Initiative on Sharing Avian Influenza Data (GISAID) database. With the help of Genome Detective Coronavirus Typing Tool, genomic sequences were aligned with the Wuhan seafood market pneumonia virus reference sequence and all the mutations were identified. Distribution of mutant variants was then compared between mildly and severely affected groups. Among the numerous mutations detected, 14408C>T and 23403A>G mutations resulting in RNA-dependent RNA polymerase (RdRp) P323L and spike protein D614G mutations, respectively, were found predominantly in severely affected group (>82%) compared with mildly affected group (<46%, p < 0.001). The 241C>T mutation in the non-coding region of the genome was also found predominantly in severely affected group (p < 0.001). The 3037C>T, a silent mutation, also appeared in relatively high frequency in severely affected group compared with mildly affected group, but the difference was not statistically significant (p = 0.06). We concluded that spike protein D614G and RdRp P323L mutations in SARS-CoV-2 are associated with severity of COVID-19. Further studies will be required to explore whether these mutations have any impact on the severity of disease.

• IMMUNE NETWORK
• /
• 제20권5호
• /
• pp.41.1-41.11
• /
• 2020

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) is a positive-sense single-stranded RNA (+ssRNA) that causes coronavirus disease 2019 (COVID-19). The viral genome encodes twelve genes for viral replication and infection. The third open reading frame is the spike (S) gene that encodes for the spike glycoprotein interacting with specific cell surface receptor - angiotensin converting enzyme 2 (ACE2) - on the host cell membrane. Most recent studies identified a single point mutation in S gene. A single point mutation in S gene leading to an amino acid substitution at codon 614 from an aspartic acid 614 into glycine (D614G) resulted in greater infectivity compared to the wild type SARS-CoV2. We were interested in investigating the mutation region of S gene of SARS-CoV2 from Korean COVID-19 patients. New mutation sites were found in the critical receptor binding domain (RBD) of S gene, which is adjacent to the aforementioned D614G mutation residue. This specific sequence data demonstrated the active progression of SARS-CoV2 by mutations in the RBD of S gene. The sequence information of new mutations is critical to the development of recombinant SARS-CoV2 spike antigens, which may be required to improve and advance the strategy against a wide range of possible SARS-CoV2 mutations.

• Pediatric Infection and Vaccine
• /
• 제31권1호
• /
• pp.83-93
• /
• 2024

목적: 코로나19 판데믹이 시작된 이후, 다양한 주요 변이 바이러스가 출현했다. 코로나 19 판데믹 기간 동안 대표적인 주요 변이 바이러스 유행 시기를 네 가지로 나누고, 네 가지의 주요 변이 바이러스 시기로부터 임상적 그리고 혈액학적 검사의 특징을 파악하고자 하였다. 방법: 코로나19 확진으로 입원한 19세 이하 환자의 의무기록을 후향적으로 분석하였다. 변이전시기(2020년 2월 1일-2020년 9월 30일), 알파와 베타 변이 시기(2020년 10월 1일-2021년 5월 31일), 델타 변이 시기(2021년 6월 1일-2021년 10월 31일), 오미크론 변이 시기(2021년 11월 1일-2022년 5월 31일)를 비교하였다. 결과:대상환자 827명중에서 163명(19.7%)가무증상이었고, 발열과기침의빈도는각각 320명(38.7%), 399명(48.2%)이었다. 38.5℃ 이상의 발열이 있었던 경우는 12세 미만인 경우에 오미크론 변이 시기에 높게 관찰되었다. 혈액학적 검사에서 백혈구 감소증, 임파구 감소증 그리고 호중구 감소증은 각각 33%, 30.2%, 24.9%로 관찰되었다. 결론: 코로나 19의 주요 변이 바이러스 우세 시기에 다른 특징들이 있었다. 델타 변이 시기에 4일 이상의 발열이 지속되는 경우가 더 많았고, 오미크론 변이 시기에는 38.5℃ 이상의 발열을 가지는 경우가 많았다.

• Genomics & Informatics
• /
• 제19권3호
• /
• pp.23.1-23.7
• /
• 2021

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processing (BioNLP) community, so as to retrieve the important information about the mechanism of COVID-19. PubAnnotation is an aligned annotation system which provides an efficient platform for biological curators to upload their annotations or merge other external annotations. Inspired by the integration among multiple useful COVID-19 annotations, we merged three annotations resources to LitCovid data set, and constructed a cross-annotated corpus, LitCovid-AGAC. This corpus consists of 12 labels including Mutation, Species, Gene, Disease from PubTator, GO, CHEBI from OGER, Var, MPA, CPA, NegReg, PosReg, Reg from AGAC, upon 50,018 COVID-19 abstracts in LitCovid. Contain sufficient abundant information being possible to unveil the hidden knowledge in the pathological mechanism of COVID-19.

• IMMUNE NETWORK
• /
• 제21권6호
• /
• pp.38.1-38.8
• /
• 2021

Recently, a new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (B.1.1.529) Omicron variant originated from South Africa in the middle of November 2021. SARS-CoV-2 is also called coronavirus disease 2019 (COVID-19) since SARS-CoV-2 is the causative agent of COVID-19. Several studies already suggested that the SARS-CoV-2 Omicron variant would be the fastest transmissible variant compared to the previous 10 SARS-CoV-2 variants of concern, interest, and alert. Few clinical studies reported the high transmissibility of the Omicron variant but there is insufficient time to perform actual experiments to prove it, since the spread is so fast. We analyzed the SARS-CoV-2 Omicron variant, which revealed a very high rate of mutation at amino acid residues that interact with angiostatin-converting enzyme 2. The mutation rate of COVID-19 is faster than what we prepared vaccine program, antibody therapy, lockdown, and quarantine against COVID-19 so far. Thus, it is necessary to find better strategies to overcome the current crisis of COVID-19 pandemic.

• IMMUNE NETWORK
• /
• 제21권5호
• /
• pp.32.1-32.14
• /
• 2021

Over two hundred twenty-eight million cases of coronavirus disease 2019 (COVID-19) in the world have been reported until the 21^st of September 2021 after the first rise in December 2019. The virus caused the disease called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Over 4 million deaths blame COVID-19 during the last one year and 8 months in the world. Currently, four SARS-CoV-2 variants of concern are mainly focused by pandemic studies with limited experiments to translate the infectivity and pathogenicity of each variant. The SARS-CoV-2 α, β, γ, and δ variant of concern was originated from United Kingdom, South Africa, Brazil/Japan, and India, respectively. The classification of SARS-CoV-2 variant is based on the mutation in spike (S) gene on the envelop of SARS-CoV-2. This review describes four SARS-CoV-2 α, β, γ, and δ variants of concern including SARS-CoV-2 ε, ζ, η, ι, κ, and B.1.617.3 variants of interest and alert. Recently, SARS-CoV-2 δ variant prevails over different countries that have 3 unique mutation sites: E156del/R158G in the N-terminal domain and T478K in a crucial receptor binding domain. A particular mutation in the functional domain of the S gene is probably associated with the infectivity and pathogenesis of the SARS-CoV-2 variant.

• 한국정보통신학회논문지
• /
• 제25권12호
• /
• pp.1756-1761
• /
• 2021

2019년 12월경 후베이 우한시에서 발생한 코로나19 바이러스가 점차 줄어드는 듯 보였으나, 2020년 11월, 2021년 6월 기준으로 점차 늘어나고 있으며, 전세계적으로 총 1억 9천 2백만명, 대한민국 기준 총 확진자는 대략 18만4천명으로 추정된다. 이에 따른 대책으로 중앙재난안전대책본부는 사회적 거리두기 4단계를 시행하면서 강력한 대응책을 내고있지만, 델타바이러스등 전염성이 강한 코로나 변이 바이러스가 기승을 부리면서 국내 일일 확진자 수는 1800명대 까지 증가하게 되었다. 그에따라 코로나바이러스의 심각성을 강조하고자 코로나 누적 확진자 수를 ARIMA 알고리즘을 이용해 예측한다. 그 과정에서 추세와 계절성을 제거하기 위해서 차분을 이용하고, MA, AR, 자기상관함수와 편자기상관함수를 이용해 ARIMA에서 p,d,q값을 결정하고 예측한다. 마지막으로 예측값과 실제값을 비교해 얼마나 잘 예측되었는지 평가한다.

• Journal of Microbiology and Biotechnology
• /
• 제30권7호
• /
• pp.962-966
• /
• 2020

Monitoring the mutation dynamics of human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical in understanding its infectivity, virulence and pathogenicity for development of a vaccine. In an "age of mobility," the pandemic highlights the importance and vulnerability of regionalization and labor market interdependence in Southeast Asia. We intend to characterize the genetic variability of viral populations within the region to provide preliminary information for regional surveillance in the future. By analyzing 142 complete genomes from South East Asian (SEA) countries, we identified three central variants distinguished by nucleotide and amino acid changes.

• 생명과학회지
• /
• 제33권2호
• /
• pp.199-207
• /
• 2023

Post-COVID-19 시대에 다가올 전염병의 위협에 대비하기 위해 인간, 동물, 환경의 건강이 하나라는 One-health 개념에 기반한 연구가 필수적이다. 현재 인간의 SARS-CoV-2의 높은 감염률과 바이러스 부하로 인해 종을 뛰어넘는 감염이 확인되고 있다. 대표적으로 사람에서 밍크로의 전파 가능성이 확인되었고, 밀접 접촉 중에 사람에서 고양이로 전파가 가능할 것으로 추정되고 있다. 현재까지의 자료를 통해 가축류, 가금류에서의 감염 가능성이 낮은 것으로 보여지나 새로운 변이로 인해 감염이 확립된다면 인간의 식량 안보, 경제, 무역 등 다양한 분야에 파급 효과가 클 것으로 예측된다. 또한 SARS-CoV-2의 풍토화 전망과 반려동물로의 접근성이 높다는 점 등이 우려되는 상황이다. 바이러스의 진화는 동물 숙주에서 발생할 가능성이 높고, 다른 종에서 SARS-CoV-2가 확립되면 인간 집단에 바이러스가 다시 출현할 수 있는 중간 숙주 역할을 할 수도 있기 때문이다. SARS-CoV-2의 동물 감염에 대한 연구 데이터를 지속적으로 축적하여 빠른 대응이 필요하다고 생각된다. 또한 동물 감염에 대한 연구는 SARS-CoV-2 백신 및 치료제 연구에 사용되는 동물 모델의 개발 등을 포함한 다방면에서 중요하다. 따라서 본 연구에서는 SARS-CoV-2의 동물 감염에 대해 역학 검토 및 대응 전략을 One-health 관점에서 접근하여 분석하였다.

• 농촌의학ㆍ지역보건
• /
• 제47권2호
• /
• pp.61-66
• /
• 2022

Objectives: In the epidemiology of communicable diseases, the term epidemic period, also referred to as "wave" is often used in the general and academic milieu. A wave refers to a natural pattern of increase in the number of sick individuals, a defined peak, and then a decline in the number of cases. It implies a pattern of peaks and valleys after a particular peak is taken. The idea of epidemic waves is a useful tool for predicting the course as well as helping to accurately describe an epidemic. However, in many domestic and foreign news as well as in various research results in Korea, most of the reports either had no standard, were inaccurate, had a questionable classification of the period of the epidemic, or the basis for classification of a given wave was not presented. Methods: The author reviewed and organized related literature with epidemic wave. The author made several suggestions of an epidemic wave as follows. Results: To start with, it should be based on the number of incident cases in consideration of the size of the outbreak, then the period from the bottom to the peak and then reaching the next bottom; also, the period over a certain scale based on the number of incident cases; and the period according to the change in the major infection type (mutation-dominant species). In addition, according to the period of change in the vaccination rate (formation of herd immunity), as well as the content and duration of the intervention, that is, classification according to the applied quarantine stage. Furthermore, the classification of epidemic periods by the time-dependent reproduction number or time-varying reproduction number (Rt), and lastly the application of mathematical methodology. Conclusions: Therefore, classifying the epidemic period into generally known and accepted time frames is considered to be a very important task for future research analysis and development of intervention strategies.