scholarly journals Complete Genomic Sequence of Noni mosaic virus (NoMV), a Novel Potyvirus Associated with a Mosaic Disease in Morinda citrifolia L.

2019 ◽  
Author(s):  
Nai-Tong Yu ◽  
Zhi-Ying Cai ◽  
Zhongguo Xiong ◽  
Yan Yang ◽  
Zhi-Xin Liu
Keyword(s):  
Amino Acid ◽  
Mosaic Virus ◽  
Complete Genome ◽  
De Novo ◽  
Genomic Sequence ◽  
Mosaic Disease ◽  
Amino Acid Sequences ◽  
Morinda Citrifolia ◽  
Mosaic Symptom ◽  
Amino Acid Sequence Similarity

An outbreak of a virus-like disease has caused severe damage to noni plants (Morinda citrifolia L.) in Xishuangbanna area of China's southwestern Yunnan province since 2015. The diseased plants displayed typical mosaic symptom with light and dark green patches on leaves. Flexuous filamentous virus particles of about 800 nm in length were observed from the leaf saps by transmission electron microscope. Illumina transcriptomic sequencing further revealed the presence of a potyvirus and its near complete genome was obtained from de novo assembly. The complete genome of 9,659 nts was obtained by Sanger sequencing of eight amplicons generate by RT-PCR and 5’ and 3’ RACE. BLASTp analysis of the polyprotein sequence showed that the virus was most closely related to Tobacco vein banding mosaic virus (TVBMV), but these two viruses only shared 50.7% amino acid sequence similarity. Both phylogenetic analyses of the polyprotein and CP amino acid sequences indicated that this virus is a member of genus Potyvirus. However, the low sequence homology with all known potyviruses established this virus as a new species in the genus, tentatively named as Noni mosaic virus (NoMV). Our field surveys showed that 100% of the symptomatic samples and 28.57% of the asymptomatic samples were infected with this novel potyvirus. Aphids collected from diseased leaves were also detected carrying the virus. In summary, our data indicated that a novel species of potyvirus, NoMV, is prevalent in Yunnan, China and is associated with an emerging mosaic disease on M. citrifolia.

scholarly journals IDENTIFIKASI MOLEKULER BEAN COMMON MOSAIC VIRUS YANG BERASOSIASI DENGAN PENYAKIT MOSAIK KUNING KACANG PANJANG

2016 ◽  
Vol 15 (2) ◽  
pp. 132
Author(s):  
Melinda . ◽  
Tri Asmira Damayanti ◽  
Sri Hendrastuti Hidayat
Keyword(s):  
Amino Acid ◽  
Mosaic Virus ◽  
Bean Common Mosaic Virus ◽  
Mosaic Disease ◽  
Amino Acid Sequences ◽  
Yellow Mosaic Disease ◽  
West Java ◽  
Central Java ◽  
Cp Gene ◽  
Dna Fragment

Molecular identification of bean common mosaic virus associated with yellow mosaic disease on yard long bean. Bean common mosaic virus (BCMV) has been reported as one of the causal agents of yellow mosaic disease on yard long bean in West Java and Central Java. Infected plants showed mosaic, yellowing, and mixture of yellow mosaic. The research was conducted to identify the diversity of BCMV associated with yellow mosaic disease based on coat protein (CP) gene sequences. Symptomatic leaf samples were collected from yard long bean growing areas in several districts in West Java (Bogor, Cirebon, Subang, and Indramayu), and several districts in Central Java (Tegal, Klaten, Solo, Yogjakarta, Sleman, and Magelang). Molecular detection using RT-PCR method was carried out by using specific primer to BCMV which will amplify the CP gene. DNA fragment, + 860 bp in size, was successfully amplified from 8 out of 13 leaf samples, i.e samples from three villages in Bogor District (Cangkurawok, Bubulak, Bojong), and five samples from District of Cirebon, Subang, Solo, Sleman, and Tegal. Sequence analysis of those DNA fragment showed that 4 isolates (Bogor-Cangkurawok, Subang, Solo and Sleman) had the highest homology to BCMV-BlC from Taiwan, whereas 2 isolates (Cirebon and Tegal) had the highest homology to BCMVNL1 from England. Further, phyllogenetic analysis revealed that those of 4 isolates were closely related to BCMV-BlC from Taiwan based on nucleotide as well as amino acid sequences; while those other 2 isolates were closely related to BCMV-NL1 from England based on nucleotide sequences but closely related to BCMV-BlC Y from China based on amino acid sequences. Phyllogenetic analysis showed that those of 6 BCMV isolates separated in two different clusters; 4 isolates (Bogor- Cangkurawok, Subang, Solo, and Sleman) in cluster 1 together with BCMV-BlC from Taiwan, while other 2 isolates (Cirebon and Tegal) in cluster 2 together with BCMV-NL1.

scholarly journals Complete Genome Sequence of a Distinct Isolate of Cassava common mosaic virus (CsCMV) Infecting Cassava in Hainan, China

2020 ◽  
Author(s):  
Nai-tong Yu ◽  
Yi Yang ◽  
Jun-hua Li ◽  
Wei-li Li ◽  
Zhi-xin Liu
Keyword(s):  
Mosaic Virus ◽  
Genome Sequence ◽  
Complete Genome ◽  
Genomic Sequence ◽  
Triple Gene Block ◽  
Open Reading Frames ◽  
Mosaic Symptom ◽  
Post Inoculation ◽  
Manihot Esculenta Crantz ◽  
Gene Block

The complete genomic sequence of a Cassava common mosaic virus Linggao isolate (CsCMV-LG) was determined from cassava (Manihot esculenta Crantz) with mild leafy mosaic symptom to no symptom in China. Excluding the poly(A) tail, the CsCMV-LG genome (GenBank accession No. MT038420) is 6374 nucleotides (nts) in length, with five major open reading frames encoding a 1450-amino acids (aa) RNA-dependent RNA polymerase (RdRp), three triple gene block (TGB) proteins (231-aa, 110-aa and 95-aa), and a 229-aa coat protein (CP). Phylogenetic analysis indicated that the complete genome of the CsCMV-LG is closely related to that of CsCMV-Brazilian which has been assigned to the genus Potexvirus, but the sequence identity shared only 88.0%. Notable, the mild CsCMV-LG isolate can also infect Nicotiana benthamiana in laboratory through rub inoculation causing mild vein yellowing at 15-day post inoculation. This is the first full-length genome sequence of a distinct isolate of Cassava common mosaic virus (CsCMV) infecting cassava in Hainan, China.

Die primäre Proteinstruktur von Stämmen des Tabakmosaikvirus

1963 ◽  
Vol 18 (12) ◽  
pp. 1032-1049 ◽  
Author(s):  
B. Wittmann-Liebold ◽  
H. G. Wittmann
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Tobacco Mosaic Virus ◽  
Mosaic Virus ◽  
Amino Acid Sequences ◽  
Tryptic Peptides

The amino acid sequence of dahlemense, a naturally occuring strain of tobacco mosaic virus, has been determined and compared with that of the strain vulgare (Fig. 7). In this communication the experimental details are given for the elucidation of the amino acid sequences within two tryptic peptides with 65 amino acids.

scholarly journals FIND: Identifying Functionally and Structurally Important Features in Protein Sequences with Deep Neural Networks

2019 ◽  
Author(s):  
Ranjani Murali ◽  
James Hemp ◽  
Victoria Orphan ◽  
Yonatan Bisk
Keyword(s):  
Neural Networks ◽  
Amino Acid ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Genomic Sequence ◽  
Hidden Markov ◽  
Amino Acid Sequences ◽  
Homologous Proteins ◽  
Biological Studies ◽  
Insight Into

AbstractThe ability to correctly predict the functional role of proteins from their amino acid sequences would significantly advance biological studies at the molecular level by improving our ability to understand the biochemical capability of biological organisms from their genomic sequence. Existing methods that are geared towards protein function prediction or annotation mostly use alignment-based approaches and probabilistic models such as Hidden-Markov Models. In this work we introduce a deep learning architecture (FunctionIdentification withNeuralDescriptions orFIND) which performs protein annotation from primary sequence. The accuracy of our methods matches state of the art techniques, such as protein classifiers based on Hidden Markov Models. Further, our approach allows for model introspection via a neural attention mechanism, which weights parts of the amino acid sequence proportionally to their relevance for functional assignment. In this way, the attention weights automatically uncover structurally and functionally relevant features of the classified protein and find novel functional motifs in previously uncharacterized proteins. While this model is applicable to any database of proteins, we chose to apply this model to superfamilies of homologous proteins, with the aim of extracting features inherent to divergent protein families within a larger superfamily. This provided insight into the functional diversification of an enzyme superfamily and its adaptation to different physiological contexts. We tested our approach on three families (nitrogenases, cytochromebd-type oxygen reductases and heme-copper oxygen reductases) and present a detailed analysis of the sequence characteristics identified in previously characterized proteins in the heme-copper oxygen reductase (HCO) superfamily. These are correlated with their catalytic relevance and evolutionary history. FIND was then applied to discover features in previously uncharacterized members of the HCO superfamily, providing insight into their unique sequence features. This modeling approach demonstrates the power of neural networks to recognize patterns in large datasets and can be utilized to discover biochemically and structurally important features in proteins from their amino acid sequences.Author summary

scholarly journals Evolutionary Algorithms for Improving De Novo Peptide Sequencing

2021 ◽  
Author(s):  
◽  
Samaneh Azari
Keyword(s):  
Amino Acid ◽  
De Novo ◽  
Peptide Identification ◽  
Peptide Sequencing ◽  
De Novo Sequencing ◽  
Amino Acid Sequences ◽  
Full Length ◽  
Multi Objective ◽  
De Novo Peptide Sequencing ◽  
De Novo Peptide

<p>De novo peptide sequencing algorithms have been developed for peptide identification in proteomics from tandem mass spectra (MS/MS), which can be used to identify and discover novel peptides and proteins that do not have a database available. Despite improvements in MS instrumentation and de novo sequencing methods, a significant number of CID MS/MS spectra still remain unassigned with the current algorithms, often leading to low confidence of peptide assignments to the spectra. Moreover, current algorithms often fail to construct the completely matched sequences, and produce partial matches. Therefore, identification of full-length peptides remains challenging. Another major challenge is the existence of noise in MS/MS spectra which makes the data highly imbalanced. Also missing peaks, caused by incomplete MS fragmentation makes it more difficult to infer a full-length peptide sequence. In addition, the large search space of all possible amino acid sequences for each spectrum leads to a high false discovery rate. This thesis focuses on improving the performance of current methods by developing new algorithms corresponding to three steps of preprocessing, sequence optimisation and post-processing using machine learning for more comprehensive interrogation of MS/MS datasets. From the machine learning point of view, the three steps can be addressed by solving different tasks such as classification, optimisation, and symbolic regression. Since Evolutionary Algorithms (EAs), as effective global search techniques, have shown promising results in solving these problems, this thesis investigates the capability of EAs in improving the de novo peptide sequencing. In the preprocessing step, this thesis proposes an effective GP-based method for classification of signal and noise peaks in highly imbalanced MS/MS spectra with the purpose of having a positive influence on the reliability of the peptide identification. The results show that the proposed algorithm is the most stable classification method across various noise ratios, outperforming six other benchmark classification algorithms. The experimental results show a significant improvement in high confidence peptide assignments to MS/MS spectra when the data is preprocessed by the proposed GP method. Moreover, the first multi-objective GP approach for classification of peaks in MS/MS data, aiming at maximising the accuracy of the minority class (signal peaks) and the accuracy of the majority class (noise peaks) is also proposed in this thesis. The results show that the multi-objective GP method outperforms the single objective GP algorithm and a popular multi-objective approach in terms of retaining more signal peaks and removing more noise peaks. The multi-objective GP approach significantly improved the reliability of peptide identification. This thesis proposes a GA-based method to solve the complex optimisation task of de novo peptide sequencing, aiming at constructing full-length sequences. The proposed GA method benefits the GA capability of searching a large search space of potential amino acid sequences to find the most likely full-length sequence. The experimental results show that the proposed method outperforms the most commonly used de novo sequencing method at both amino acid level and peptide level. This thesis also proposes a novel method for re-scoring and re-ranking the peptide spectrum matches (PSMs) from the result of de novo peptide sequencing, aiming at minimising the false discovery rate as a post-processing approach. The proposed GP method evolves the computer programs to perform regression and classification simultaneously in order to generate an effective scoring function for finding the correct PSMs from many incorrect ones. The results show that the new GP-based PSM scoring function significantly improves the identification of full-length peptides when it is used to post-process the de novo sequencing results.</p>

Expression of intermediate filament proteins during development of Xenopus laevis. I. cDNA clones encoding different forms of vimentin

Development ◽  
1989 ◽  
Vol 105 (2) ◽  
pp. 279-298
Author(s):  
H. Herrmann ◽  
B. Fouquet ◽  
W.W. Franke
Keyword(s):  
Amino Acid ◽  
Xenopus Laevis ◽  
Intermediate Filament ◽  
De Novo ◽  
Mesenchymal Cell ◽  
Amino Acid Sequences ◽  
Cytoskeletal Proteins ◽  
Cdna Clones ◽  
Mammalian Development ◽  
Intermediate Filament Proteins

To provide a basis for studies of the expression of genes encoding the diverse kinds of intermediate-filament (IF) proteins during embryogenesis of Xenopus laevis we have isolated and characterized IF protein cDNA clones. Here we report the identification of two types of Xenopus vimentin, Vim1 and Vim4, with their complete amino acid sequences as deduced from the cloned cDNAs, both of which are expressed during early embryogenesis. In addition, we have obtained two further vimentin cDNAs (Vim2 and 3) which are sequence variants of closely related Vim1. The high evolutionary conservation of the amino acid sequences (Vim1: 458 residues; Mr approximately 52,800; Vim4: 463 residues; Mr approximately 53,500) to avian and mammalian vimentin and, to a lesser degree, to desmin from the same and higher vertebrate species, is emphasized, including conserved oligopeptide motifs in their head domains. Using these cDNAs in RNA blot and ribonuclease protection assays of various embryonic stages, we observed a dramatic increase of vimentin RNA at stage 14, in agreement with immunocytochemical results obtained with antibody VIM-3B4. The significance of very weak mRNA signals detected in earlier stages is discussed in relation to negative immunocytochemical results obtained in these stages. The first appearance of vimentin has been localized to a distinct mesenchymal cell layer underlying the neural plate or tube, respectively. The results are discussed in relation to programs of de novo synthesis of other cytoskeletal proteins in amphibian and mammalian development.

History, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19)

Coronaviruses ◽  
2021 ◽  
Vol 02 ◽  
Author(s):  
Amaresh Mishra ◽  
Nisha Nair ◽  
Vishwas Tripathi ◽  
Yamini Pathak ◽  
Jaseela Majeed
Keyword(s):  
Amino Acid ◽  
Severe Acute Respiratory Syndrome ◽  
Sequence Similarity ◽  
Neurological Complications ◽  
Amino Acid Sequences ◽  
World Health ◽  
Amino Acid Sequence Similarity ◽  
Effective Prevention ◽  
Short Period ◽  
The World

: The Coronavirus Disease 2019 (COVID-19), also known as a novel coronavirus (2019-nCoV), reportedly originated from Wuhan City, Hubei Province, China. Coronavirus Disease 2019 rapidly spread all over the world within a short period. On January 30th, 2020, the World Health Organization (WHO) declared it a global epidemic. COVID-19 is a severe acute respiratory syndrome coronavirus (SARS-CoV) virus that evolves to respiratory, hepatic, gastrointestinal, and neurological complications, and eventually death. SARS-CoV and the Middle East Respiratory Syndrome coronavirus (MERS-CoV) genome sequences similar identity with 2019-nCoV or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, few amino acid sequences of 2019-nCoV differ from SARS-CoV and MERS-CoV. COVID-19 shares about 90% amino acid sequence similarity with SARS-CoV. Effective prevention methods should be taken in order to control this pandemic situation. Till now, there are no effective treatments available to treat COVID-19. This review provides information regarding COVID-19 history, epidemiology, pathogenesis, and molecular diagnosis. Also, we focus on the development of vaccines in the management of this COVID-19 pandemic and limiting the spread of the virus.

scholarly journals Unevolved De Novo Proteins Have Innate Tendencies to Bind Transition Metals

Life ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 8 ◽  
Author(s):  
Michael S. Wang ◽  
Kenric J. Hoegler ◽  
Michael H. Hecht
Keyword(s):  
Amino Acid ◽  
Transition Metals ◽  
Metal Binding ◽  
Combinatorial Library ◽  
De Novo ◽  
Protein Sequences ◽  
Amino Acid Sequences ◽  
Ancestral Sequences ◽  
Wide Range ◽  
Catalytic Functions

Life as we know it would not exist without the ability of protein sequences to bind metal ions. Transition metals, in particular, play essential roles in a wide range of structural and catalytic functions. The ubiquitous occurrence of metalloproteins in all organisms leads one to ask whether metal binding is an evolved trait that occurred only rarely in ancestral sequences, or alternatively, whether it is an innate property of amino acid sequences, occurring frequently in unevolved sequence space. To address this question, we studied 52 proteins from a combinatorial library of novel sequences designed to fold into 4-helix bundles. Although these sequences were neither designed nor evolved to bind metals, the majority of them have innate tendencies to bind the transition metals copper, cobalt, and zinc with high nanomolar to low-micromolar affinity.

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