Evolution of vacuolar H+-ATPases: immunological relationships of the nucleotide-binding subunits

1989 ◽  
Vol 67 (6) ◽  
pp. 306-310 ◽  
Author(s):  
Morris F. Manolson ◽  
Judith M. Percy ◽  
David K. Apps ◽  
Xiao-Song Xie ◽  
Dennis K. Stone ◽  
...  
Keyword(s):  
Anaerobic Bacterium ◽  
Common Ancestor ◽  
Sequence Data ◽  
Structural Features ◽  
Eukaryotic Cells ◽  
Clostridium Pasteurianum ◽  
Chromaffin Granules ◽  
Α Subunit ◽  
Evolutionary Origins ◽  
Vacuolar Membranes

The evolution of the endomembrane systems of eukaryotic cells can be examined by exploring the evolutionary origins of the endomembrane H+-ATPases. Recent studies suggest that certain polypeptides are common to all H+ pumps of this type. Tonoplast H+ -ATPase from Beta vulgaris L. was purified and antibodies raised to two of its subunits. Each of these antisera reacted with a polypeptide of the corresponding size in bovine chromaffin granules, bovine clathrincoated vesicles, and yeast vacuolar membranes, suggesting common structural features and a common ancestor for endomembrane H+-ATPases of different organelles and different kingdoms. The antiserum raised against the 57-kDa polypeptide of plant tonoplast H+ -ATPase also reacted with subunit "a" of the H+-ATPase from the obligately anaerobic bacterium Clostridium pasteurianum and to the α subunit of the H+ -ATPase from Escherichia coli. There was no reactivity with chloroplast or mitochondrial ATPases. These results are discussed in relation to recent sequence data which suggest that endomembrane H+-ATPases may be evolutionarily related to the F0F1 ATPases.Key words: H+ -ATPase, evolution, immunology, vacuole, endomembrane.

scholarly journals Evolution and diversification of the nuclear pore complex

2021 ◽  
Author(s):  
Alexandr A. Makarov ◽  
Norma E. Padilla-Mejia ◽  
Mark C. Field
Keyword(s):  
Transport System ◽  
Nuclear Pore Complex ◽  
Common Ancestor ◽  
Mrna Export ◽  
Intraflagellar Transport ◽  
Eukaryotic Cells ◽  
Nuclear Pore ◽  
Last Eukaryotic Common Ancestor ◽  
Structural Characterisation ◽  
Evolutionary Origins

The nuclear pore complex (NPC) is responsible for transport between the cytoplasm and nucleoplasm and one of the more intricate structures of eukaryotic cells. Typically composed of over 300 polypeptides, the NPC shares evolutionary origins with endo-membrane and intraflagellar transport system complexes. The modern NPC was fully established by the time of the last eukaryotic common ancestor and, hence, prior to eukaryote diversification. Despite the complexity, the NPC structure is surprisingly flexible with considerable variation between lineages. Here, we review diversification of the NPC in major taxa in view of recent advances in genomic and structural characterisation of plant, protist and nucleomorph NPCs and discuss the implications for NPC evolution. Furthermore, we highlight these changes in the context of mRNA export and consider how this process may have influenced NPC diversity. We reveal the NPC as a platform for continual evolution and adaptation.

scholarly journals Prediction and analysis of multiple protein lysine modified sites based on conditional wasserstein generative adversarial networks

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yingxi Yang ◽  
Hui Wang ◽  
Wen Li ◽  
Xiaobo Wang ◽  
Shizhao Wei ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Sequence Data ◽  
Rapid Development ◽  
Pearson Correlation ◽  
Structural Features ◽  
Generative Adversarial Networks ◽  
Post Translational Modification ◽  
Generative Adversarial Network ◽  
Data Imbalance ◽  
Adversarial Network

Abstract Background Protein post-translational modification (PTM) is a key issue to investigate the mechanism of protein’s function. With the rapid development of proteomics technology, a large amount of protein sequence data has been generated, which highlights the importance of the in-depth study and analysis of PTMs in proteins. Method We proposed a new multi-classification machine learning pipeline MultiLyGAN to identity seven types of lysine modified sites. Using eight different sequential and five structural construction methods, 1497 valid features were remained after the filtering by Pearson correlation coefficient. To solve the data imbalance problem, Conditional Generative Adversarial Network (CGAN) and Conditional Wasserstein Generative Adversarial Network (CWGAN), two influential deep generative methods were leveraged and compared to generate new samples for the types with fewer samples. Finally, random forest algorithm was utilized to predict seven categories. Results In the tenfold cross-validation, accuracy (Acc) and Matthews correlation coefficient (MCC) were 0.8589 and 0.8376, respectively. In the independent test, Acc and MCC were 0.8549 and 0.8330, respectively. The results indicated that CWGAN better solved the existing data imbalance and stabilized the training error. Alternatively, an accumulated feature importance analysis reported that CKSAAP, PWM and structural features were the three most important feature-encoding schemes. MultiLyGAN can be found at https://github.com/Lab-Xu/MultiLyGAN. Conclusions The CWGAN greatly improved the predictive performance in all experiments. Features derived from CKSAAP, PWM and structure schemes are the most informative and had the greatest contribution to the prediction of PTM.

Mammalian mitochondrial translation — revealing consequences of divergent evolution

2019 ◽  
Vol 47 (5) ◽  
pp. 1429-1436 ◽  
Author(s):  
Rawaa A. Z. Al-Faresi ◽  
Robert. N. Lightowlers ◽  
Zofia M. A. Chrzanowska-Lightowlers
Keyword(s):  
Common Ancestor ◽  
Current Knowledge ◽  
Eukaryotic Cells ◽  
Divergent Evolution ◽  
Mitochondrial Translation ◽  
Complete Understanding ◽  
Genetic Origin ◽  
Cryo Electron Microscopy ◽  
Encoded Proteins ◽  
Molecular Aspects

Abstract Mitochondria are ubiquitous organelles present in the cytoplasm of all nucleated eukaryotic cells. These organelles are described as arising from a common ancestor but a comparison of numerous aspects of mitochondria between different organisms provides remarkable examples of divergent evolution. In humans, these organelles are of dual genetic origin, comprising ∼1500 nuclear-encoded proteins and thirteen that are encoded by the mitochondrial genome. Of the various functions that these organelles perform, it is only oxidative phosphorylation, which provides ATP as a source of chemical energy, that is dependent on synthesis of these thirteen mitochondrially encoded proteins. A prerequisite for this process of translation are the mitoribosomes. The recent revolution in cryo-electron microscopy has generated high-resolution mitoribosome structures and has undoubtedly revealed some of the most distinctive molecular aspects of the mitoribosomes from different organisms. However, we still lack a complete understanding of the mechanistic aspects of this process and many of the factors involved in post-transcriptional gene expression in mitochondria. This review reflects on the current knowledge and illustrates some of the striking differences that have been identified between mitochondria from a range of organisms.

Molecular cloning of cDNAs encoding two types of gonadotrophin α subunit from the masu salmon, Oncorhynchus masou: construction of specific oligonucleotides for the α1 and α2 subunits

1993 ◽  
Vol 11 (3) ◽  
pp. 265-273 ◽  
Author(s):  
K Gen ◽  
O Maruyama ◽  
T Kato ◽  
K Tomizawa ◽  
K Wakabayashi ◽  
...  
Keyword(s):  
Amino Acids ◽  
Structural Difference ◽  
Structural Features ◽  
Masu Salmon ◽  
Time Interval ◽  
Oncorhynchus Masou ◽  
Α Subunit ◽  
Polymerase Chain ◽  
Fossil Records ◽  
Masu Salmon Oncorhynchus Masou

ABSTRACT Two types of cDNA (GTHα1 and -α2) encoding the α subunits of masu salmon (Oncorhynchus masou) gonadotrophin were cloned by the reverse transcription-polymerase chain reaction for pituitary mRNAs. The nucleotide sequences showed that the GTHα1 cDNA was 380 bp long, encoding 119 amino acids, and that GTHα2 cDNA was 365 bp long, encoding 114 amino acids. The masu salmon α subunit types had a few differences between the sequences, with homologies of 80% (nucleotide sequence) and 72% (amino acid sequence). The structural difference between the α1 and α2 subunits was predicted using hydropathic analysis. The evolutionary interval between masu and chum salmon was estimated to be 4·0 and 2·3 million years by comparing their GTHα1 and -α2 subunits respectively. These time values are roughly consistent with the evolutionary time interval (3·0 million years) estimated from fossil records and an isozyme study. Specific synthetic oligonucleotide probes were constructed and used for genomic Southern blot analyses. The restriction fragment sizes of the GTHα1 and -α2 genes were similar, and when their patterns were compared with those from four other teleosts, each species showed a different pattern from the others, but no difference between their respective α1 and α2 genes. Therefore, the structural features of the GTHα1 and -α2 genes may have diverged in a similar manner in these five teleosts.

Similarity and Homology

1995 ◽  
Author(s):  
David J. States ◽  
Mark S. Boguski
Keyword(s):  
Sequence Alignment ◽  
Common Ancestor ◽  
Sequence Data ◽  
Sequence Similarity ◽  
Biological Macromolecules ◽  
Clear Understanding ◽  
Molecular Sequence Data ◽  
Molecular Sequence ◽  
Automated Tools ◽  
Similarity Relationships

Properly approached, molecular sequence data is a rich source of knowledge capable of teaching us much about the structure, function, and evolution of biological macromolecules. To effectively realize this potential, however, some understanding of the process of and theoretical basis for sequence comparison is needed as well as a variety of practical tools to access and manipulate the data. The volume of molecular sequence data has long since surpassed human information processing capacity for even simple tasks such as searching for related sequences, and with the ever increasing rate at which new sequences are being produced, the need for computer-assisted analysis becomes more and more acute. Automated tools can extend human capabilities by orders of magnitude in both speed and accuracy. The educated application of these automated tools is an essential part of modern molecular biology research. This chapter considers the theory and practice of analyzing sequence similarity as it applies to database searching and sequence alignment. Five major areas will be examined. First, we describe the use of dot matrix plots to elucidate the structures and features relating a sequence pair. Secondly, we discuss optimal pairwise alignment of sequences using dynamic programming algorithms. Thirdly, we examine fast, approximate techniques for detecting local similarities. Fourthly, the uses of and techniques for multiple sequence alignment are described. Finally, the statistical significance of sequence similarity is considered. In the analysis of molecular sequences, the terms similarity andhomology are often used without a clear understanding of their distinct implications. Similarity is a descriptive term which only implies that two sequences, by some criterion, resemble each other and carries no suggestion as to their origins or ancestry. Homology refers specifically to similarity due to descent from a common ancestor (Patterson, 1988;Reeck etal., 1987). On the basis of similarity relationships among a group of sequences, it may be possible to infer homology, but outside of an explicit laboratory model system, descent from a common ancestor remains hypothetical. There are philosophical issues in the inference of homology as well as practical ones. In classical morphology, conjunction (the occurrence of two traits in a single individual) is considered evidence that they are not homologous (Patterson, 1982).

scholarly journals The First Glimpse of Streptocarpus ionanthus (Gesneriaceae) Phylogenomics: Analysis of Five Subspecies’ Chloroplast Genomes

Plants ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 456 ◽  
Author(s):  
Cornelius M. Kyalo ◽  
Zhi-Zhong Li ◽  
Elijah M. Mkala ◽  
Itambo Malombe ◽  
Guang-Wan Hu ◽  
...  
Keyword(s):  
Phylogenetic Relationships ◽  
Sequence Data ◽  
Structural Features ◽  
Base Pairs ◽  
Protein Coding ◽  
Variable Regions ◽  
Morphological Heterogeneity ◽  
Chloroplast Genomes ◽  
Chloroplast Genome Sequence ◽  
Phylogenomic Analyses

Streptocarpus ionanthus (Gesneriaceae) comprise nine herbaceous subspecies, endemic to Kenya and Tanzania. The evolution of Str. ionanthus is perceived as complex due to morphological heterogeneity and unresolved phylogenetic relationships. Our study seeks to understand the molecular variation within Str. ionanthus using a phylogenomic approach. We sequence the chloroplast genomes of five subspecies of Str. ionanthus, compare their structural features and identify divergent regions. The five genomes are identical, with a conserved structure, a narrow size range (170 base pairs (bp)) and 115 unique genes (80 protein-coding, 31 tRNAs and 4 rRNAs). Genome alignment exhibits high synteny while the number of Simple Sequence Repeats (SSRs) are observed to be low (varying from 37 to 41), indicating high similarity. We identify ten divergent regions, including five variable regions (psbM, rps3, atpF-atpH, psbC-psbZ and psaA-ycf3) and five genes with a high number of polymorphic sites (rps16, rpoC2, rpoB, ycf1 and ndhA) which could be investigated further for phylogenetic utility in Str. ionanthus. Phylogenomic analyses here exhibit low polymorphism within Str. ionanthus and poor phylogenetic separation, which might be attributed to recent divergence. The complete chloroplast genome sequence data concerning the five subspecies provides genomic resources which can be expanded for future elucidation of Str. ionanthus phylogenetic relationships.

scholarly journals Mechanistic and Structural Insights on the IL-15 System through Molecular Dynamics Simulations

Molecules ◽  
2019 ◽  
Vol 24 (18) ◽  
pp. 3261
Author(s):  
Sousa ◽  
Laurent ◽  
Quéméner ◽  
Mortier ◽  
Questel
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Structural Features ◽  
Cellular Functions ◽  
Α Subunit ◽  
X Ray Crystallography ◽  
Receptor Complexes ◽  
Protein Interfaces ◽  
Dynamics Simulations ◽  
Comparison Of The Results

Interleukin 15 (IL-15), a four-helix bundle cytokine, is involved in a plethora of different cellular functions and, particularly, plays a key role in the development and activation of immune responses. IL-15 forms receptor complexes by binding with IL-2Rβ- and common γ(γc)-signaling subunits, which are shared with other members of the cytokines family (IL-2 for IL-2Rβ- and all other γc- cytokines for γc). The specificity of IL-15 is brought by the non-signaling α-subunit, IL-15Rα. Here we present the results of molecular dynamics simulations carried out on four relevant forms of IL-15: its monomer, IL-15 interacting individually with IL-15Rα (IL-15/IL-15Rα), with IL-2Rβ/γc subunits (IL-15/IL-2Rβ/γc) or with its three receptors simultaneously (IL-15/IL-15Rα/IL-2Rβ/γc). Through the analyses of the various trajectories, new insights on the structural features of the interfaces are highlighted, according to the considered form. The comparison of the results with the experimental data, available from X-ray crystallography, allows, in particular, the rationalization of the importance of IL-15 key residues (e.g. Asp8, Lys10, Glu64). Furthermore, the pivotal role of water molecules in the stabilization of the various protein-protein interfaces and their H-bonds networks are underlined for each of the considered complexes.

scholarly journals Widespread nocturnality of living birds stemming from their common ancestor

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yonghua Wu
Keyword(s):  
Positive Selection ◽  
Common Ancestor ◽  
Activity Patterns ◽  
Bright Light ◽  
Night Vision ◽  
Diel Activity ◽  
Divergent Evolution ◽  
Nocturnal Activity ◽  
Evolutionary Origins ◽  
Diel Activity Patterns

Abstract Background Many living birds exhibit some nocturnal activity, but the genetic basis and evolutionary origins of their nocturnality remain unknown. Results Here, we used a molecular phyloecological approach to analyze the adaptive evolution of 33 phototransduction genes in diverse bird lineages. Our results suggest that functional enhancement of two night-vision genes, namely, GRK1 and SLC24A1, underlies the nocturnal adaption of living birds. Further analyses showed that the diel activity patterns of birds have remained relatively unchanged since their common ancestor, suggesting that the widespread nocturnal activity of many living birds may largely stem from their common ancestor rather than independent evolution. Despite this evolutionary conservation of diel activity patterns in birds, photoresponse recovery genes were found to be frequently subjected to positive selection in diverse bird lineages, suggesting that birds generally have evolved an increased capacity for motion detection. Moreover, we detected positive selection on both dim-light vision genes and bright-light vision genes in the class Aves, suggesting divergent evolution of the vision of birds from that of reptiles and that different bird lineages have evolved certain visual adaptions to their specific light conditions. Conclusions This study suggests that the widespread nocturnality of extant birds has a deep evolutionary origin tracing back to their common ancestor.

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