Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19

Singh, Rachana; Singh, Pradhyumna Kumar; Kumar, Rajnish; Kabir, Md. Tanvir; Kamal, Mohammad Amjad; Rauf, Abdur; Albadrani, Ghadeer M.; Sayed, Amany A.; Mousa, Shaker A.; Abdel-Daim, Mohamed M.

doi:10.3389/fphar.2021.652335

Cited by 22 publications

(10 citation statements)

References 205 publications

(192 reference statements)

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“…One promising method for identifying the factors causing complex diseases is an integrative approach that combines omics technologies, such as microbiomics, transcriptomics, and metabolomics (Hasin et al ., 2017 ). Although this approach has been widely used in studies of human diseases, including cancer (Menyhárt and Győrffy, 2021 ), cardiovascular disease (Leon‐Mimila et al ., 2019 ), and COVID‐19 (Singh et al ., 2021 ), it has rarely been used to study plant diseases. Here, we utilized a multi‐omics approach to identify the bacterial, fungal, and viral communities associated with SGS at the main soybean production site in China, using amplicon (16S and ITS), RNA, and small RNA sequencing approaches.…”

Section: Introductionmentioning

confidence: 99%

Whole‐plant microbiome profiling reveals a novel geminivirus associated with soybean stay‐green disease

Wang

et al. 2022

Plant Biotechnology Journal

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Microbiota colonize every accessible plant tissue and play fundamental roles in plant growth and health. Soybean stay-green syndrome (SGS), a condition that causes delayed leaf senescence (stay-green), flat pods and abnormal seeds of soybean, has become the most serious disease of soybean in China. However, the direct cause of SGS is highly debated, and little is known about how SGS affect soybean microbiome dynamics, particularly the seed microbiome. We studied the bacterial, fungal, and viral communities associated with different soybean tissues with and without SGS using a multi-omics approach, and investigated the possible pathogenic agents associated with SGS and how SGS affects the assembly and functions of plant-associated microbiomes. We obtained a comprehensive view of the composition, function, loads, diversity, and dynamics of soybean microbiomes in the rhizosphere, root, stem, leaf, pod, and seed compartments, and discovered that soybean SGS was associated with dramatically increased microbial loads and dysbiosis of the bacterial microbiota in seeds. Furthermore, we identified a novel geminivirus that was strongly associated with soybean SGS, regardless of plant cultivar, sampling location, or harvest year. This whole-plant microbiome profiling of soybean provides the first demonstration of geminivirus infection associated with microbiota dysbiosis, which might represent a general microbiological symptom of plant diseases.

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Section: Introductionmentioning

confidence: 99%

Whole‐plant microbiome profiling reveals a novel geminivirus associated with soybean stay‐green disease

Wang

et al. 2022

Plant Biotechnology Journal

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“…On the other hand, Singh et al . argued that the multi-omics approaches offered various tools and strategies for identifying potential therapeutic biomolecules for COVID-19, and they explored the available multi-omics approaches [ 156 ]. In addition, Stephenson et al .…”

Section: Resultsmentioning

confidence: 99%

A comprehensive review of the analysis and integration of omics data for SARS-CoV-2 and COVID-19

Zhu

Zhang

Wang

et al. 2021

Briefings in Bioinformatics

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Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, over 100 million people have been infected by COVID-19, millions of whom have died. In the latest year, a large number of omics data have sprung up and helped researchers broadly study the sequence, chemical structure and function of SARS-CoV-2, as well as molecular abnormal mechanisms of COVID-19 patients. Though some successes have been achieved in these areas, it is necessary to analyze and mine omics data for comprehensively understanding SARS-CoV-2 and COVID-19. Hence, we reviewed the current advantages and limitations of the integration of omics data herein. Firstly, we sorted out the sequence resources and database resources of SARS-CoV-2, including protein chemical structure, potential drug information and research literature resources. Next, we collected omics data of the COVID-19 hosts, including genomics, transcriptomics, microbiology and potential drug information data. And subsequently, based on the integration of omics data, we summarized the existing data analysis methods and the related research results of COVID-19 multi-omics data in recent years. Finally, we put forward SARS-CoV-2 (COVID-19) multi-omics data integration research direction and gave a case study to mine deeper for the disease mechanisms of COVID-19.

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“…A study conducted by Müller et al showed that silvestrol inhibits the replication of HCoV-229E and MERS-CoV by suspending cap-dependent viral mRNA translation [ 41 ]. Various studies have shown that silvestrol can inhibit the eIF4A-dependent translation of viral mRNA of EBOV, ZIKV and hepatitis E virus [ 42 , 43 ]. A study by Henss et al also showed that silvestrol can delay protein synthesis of the chikungunya virus and reduce viral RNA replication [ 44 ].…”

Section: Discussionmentioning

confidence: 99%

Molecular Docking and In-Silico Analysis of Natural Biomolecules against Dengue, Ebola, Zika, SARS-CoV-2 Variants of Concern and Monkeypox Virus

Dassanayake

Khoo

Chong

et al. 2022

IJMS

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The emergence and rapid evolution of human pathogenic viruses, combined with the difficulties in developing effective vaccines, underline the need to develop innovative broad-spectrum antiviral therapeutic agents. The present study aims to determine the in silico antiviral potential of six bacterial antimicrobial peptides (AMPs), two phytochemicals (silvestrol, andrographolide), and two bacterial secondary metabolites (lyngbyabellin A, hapalindole H) against dengue virus, Zika virus, Ebola virus, the major variants of SARS-CoV-2 and monkeypox virus. The comparison of docking scores obtained with natural biomolecules was performed with specific neutralizing antibodies (positive controls for ClusPro) and antiviral drugs (negative controls for Autodock Vina). Glycocin F was the only natural biomolecule tested to show high binding energies to all viral surface proteins and the corresponding viral cell receptors. Lactococcin G and plantaricin ASM1 also achieved high docking scores with all viral surface proteins and most corresponding cell surface receptors. Silvestrol, andrographolide, hapalindole H, and lyngbyabellin A showed variable docking scores depending on the viral surface proteins and cell receptors tested. Three glycocin F mutants with amino acid modifications showed an increase in their docking energy to the spike proteins of SARS-CoV-2 B.1.617.2 Indian variant, and of the SARS-CoV-2 P.1 Japan/Brazil variant, and the dengue DENV envelope protein. All mutant AMPs indicated a frequent occurrence of valine and proline amino acid rotamers. AMPs and glycocin F in particular are the most promising biomolecules for the development of broad-spectrum antiviral treatments targeting the attachment and entry of viruses into their target cell.

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Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19

Cited by 22 publications

References 205 publications

Whole‐plant microbiome profiling reveals a novel geminivirus associated with soybean stay‐green disease

Whole‐plant microbiome profiling reveals a novel geminivirus associated with soybean stay‐green disease

A comprehensive review of the analysis and integration of omics data for SARS-CoV-2 and COVID-19

Molecular Docking and In-Silico Analysis of Natural Biomolecules against Dengue, Ebola, Zika, SARS-CoV-2 Variants of Concern and Monkeypox Virus

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