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Mitogenome-wise codon usage pattern from comparative analysis of the first mitogenome of Blepharipa sp. (Muga uzifly) with other Oestroid flies. Sci Rep 2022; 12:7028. [PMID: 35487927 PMCID: PMC9054809 DOI: 10.1038/s41598-022-10547-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 03/21/2022] [Indexed: 11/08/2022] Open
Abstract
Uziflies (Family: Tachinidae) are dipteran endoparasites of sericigenous insects which cause major economic loss in the silk industry globally. Here, we are presenting the first full mitogenome of Blepharipa sp. (Acc: KY644698, 15,080 bp, A + T = 78.41%), a dipteran parasitoid of Muga silkworm (Antheraea assamensis) found in the Indian states of Assam and Meghalaya. This study has confirmed that Blepharipa sp. mitogenome gene content and arrangement is similar to other Tachinidae and Sarcophagidae flies of Oestroidea superfamily, typical of ancestral Diptera. Although, Calliphoridae and Oestridae flies have undergone tRNA translocation and insertion, forming unique intergenic spacers (IGS) and overlapping regions (OL) and a few of them (IGS, OL) have been conserved across Oestroidea flies. The Tachinidae mitogenomes exhibit more AT content and AT biased codons in their protein-coding genes (PCGs) than the Oestroidea counterpart. About 92.07% of all (3722) codons in PCGs of this new species have A/T in their 3rd codon position. The high proportion of AT and repeats in the control region (CR) affects sequence coverage, resulting in a short CR (Blepharipa sp.: 168 bp) and a smaller tachinid mitogenome. Our research unveils those genes with a high AT content had a reduced effective number of codons, leading to high codon usage bias. The neutrality test shows that natural selection has a stronger influence on codon usage bias than directed mutational pressure. This study also reveals that longer PCGs (e.g., nad5, cox1) have a higher codon usage bias than shorter PCGs (e.g., atp8, nad4l). The divergence rates increase nonlinearly as AT content at the 3rd codon position increases and higher rate of synonymous divergence than nonsynonymous divergence causes strong purifying selection. The phylogenetic analysis explains that Blepharipa sp. is well suited in the family of insectivorous tachinid maggots. It's possible that biased codon usage in the Tachinidae family reduces the effective number of codons, and purifying selection retains the core functions in their mitogenome, which could help with efficient metabolism in their endo-parasitic life style and survival strategy.
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Wan D, Du T, Hong W, Chen L, Que H, Lu S, Peng X. Neurological complications and infection mechanism of SARS-COV-2. Signal Transduct Target Ther 2021; 6:406. [PMID: 34815399 PMCID: PMC8609271 DOI: 10.1038/s41392-021-00818-7] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 09/27/2021] [Accepted: 11/02/2021] [Indexed: 02/05/2023] Open
Abstract
Currently, SARS-CoV-2 has caused a global pandemic and threatened many lives. Although SARS-CoV-2 mainly causes respiratory diseases, growing data indicate that SARS-CoV-2 can also invade the central nervous system (CNS) and peripheral nervous system (PNS) causing multiple neurological diseases, such as encephalitis, encephalopathy, Guillain-Barré syndrome, meningitis, and skeletal muscular symptoms. Despite the increasing incidences of clinical neurological complications of SARS-CoV-2, the precise neuroinvasion mechanisms of SARS-CoV-2 have not been fully established. In this review, we primarily describe the clinical neurological complications associated with SARS-CoV-2 and discuss the potential mechanisms through which SARS-CoV-2 invades the brain based on the current evidence. Finally, we summarize the experimental models were used to study SARS-CoV-2 neuroinvasion. These data form the basis for studies on the significance of SARS-CoV-2 infection in the brain.
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Affiliation(s)
- Dandan Wan
- Laboratory of Aging Research and Cancer Drug Target, State Key Laboratory of Biotherapy, National Clinical Research Center for Geriatricts, West China Hospital, Sichuan University, No. 17, Block 3, Southern Renmin Road, 610041, Chengdu, Sichuan, PR China
| | - Tingfu Du
- National Kunming High-level Biosafety Primate Research Center, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan, China
| | - Weiqi Hong
- Laboratory of Aging Research and Cancer Drug Target, State Key Laboratory of Biotherapy, National Clinical Research Center for Geriatricts, West China Hospital, Sichuan University, No. 17, Block 3, Southern Renmin Road, 610041, Chengdu, Sichuan, PR China
| | - Li Chen
- Laboratory of Aging Research and Cancer Drug Target, State Key Laboratory of Biotherapy, National Clinical Research Center for Geriatricts, West China Hospital, Sichuan University, No. 17, Block 3, Southern Renmin Road, 610041, Chengdu, Sichuan, PR China
| | - Haiying Que
- Laboratory of Aging Research and Cancer Drug Target, State Key Laboratory of Biotherapy, National Clinical Research Center for Geriatricts, West China Hospital, Sichuan University, No. 17, Block 3, Southern Renmin Road, 610041, Chengdu, Sichuan, PR China
| | - Shuaiyao Lu
- National Kunming High-level Biosafety Primate Research Center, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan, China.
| | - Xiaozhong Peng
- National Kunming High-level Biosafety Primate Research Center, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan, China.
- State Key Laboratory of Medical Molecular Biology, Department of Molecular, Biology and Biochemistry, Institute of Basic Medical Sciences, Medical Primate Research Center, Neuroscience Center, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.
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Sanclemente-Alaman I, Moreno-Jiménez L, Benito-Martín MS, Canales-Aguirre A, Matías-Guiu JA, Matías-Guiu J, Gómez-Pinedo U. Experimental Models for the Study of Central Nervous System Infection by SARS-CoV-2. Front Immunol 2020; 11:2163. [PMID: 32983181 PMCID: PMC7485091 DOI: 10.3389/fimmu.2020.02163] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 08/10/2020] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION The response to the SARS-CoV-2 coronavirus epidemic requires increased research efforts to expand our knowledge of the disease. Questions related to infection rates and mechanisms, the possibility of reinfection, and potential therapeutic approaches require us not only to use the experimental models previously employed for the SARS-CoV and MERS-CoV coronaviruses but also to generate new models to respond to urgent questions. DEVELOPMENT We reviewed the different experimental models used in the study of central nervous system (CNS) involvement in COVID-19 both in different cell lines that have enabled identification of the virus' action mechanisms and in animal models (mice, rats, hamsters, ferrets, and primates) inoculated with the virus. Specifically, we reviewed models used to assess the presence and effects of SARS-CoV-2 on the CNS, including neural cell lines, animal models such as mouse hepatitis virus CoV (especially the 59 strain), and the use of brain organoids. CONCLUSION Given the clear need to increase our understanding of SARS-CoV-2, as well as its potential effects on the CNS, we must endeavor to obtain new information with cellular or animal models, with an appropriate resemblance between models and human patients.
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Affiliation(s)
- Inmaculada Sanclemente-Alaman
- Laboratory of Neurobiology, Department of Neurology, Institute of Neurosciences, San Carlos Institute for Health Research, Universidad Complutense de Madrid, Madrid, Spain
| | - Lidia Moreno-Jiménez
- Laboratory of Neurobiology, Department of Neurology, Institute of Neurosciences, San Carlos Institute for Health Research, Universidad Complutense de Madrid, Madrid, Spain
| | - María Soledad Benito-Martín
- Laboratory of Neurobiology, Department of Neurology, Institute of Neurosciences, San Carlos Institute for Health Research, Universidad Complutense de Madrid, Madrid, Spain
| | - Alejandro Canales-Aguirre
- Preclinical Evaluation Unit, Medical and Pharmaceutical Biotechnology, CIATEJ-CONACYT, Guadalajara, Mexico
| | - Jordi A. Matías-Guiu
- Laboratory of Neurobiology, Department of Neurology, Institute of Neurosciences, San Carlos Institute for Health Research, Universidad Complutense de Madrid, Madrid, Spain
| | - Jorge Matías-Guiu
- Laboratory of Neurobiology, Department of Neurology, Institute of Neurosciences, San Carlos Institute for Health Research, Universidad Complutense de Madrid, Madrid, Spain
| | - Ulises Gómez-Pinedo
- Laboratory of Neurobiology, Department of Neurology, Institute of Neurosciences, San Carlos Institute for Health Research, Universidad Complutense de Madrid, Madrid, Spain
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