Mamit-tRNA, a database of mammalian mitochondrial tRNA primary and secondary structures

Mamit-tRNA (http://mamit-tRNA.u-strasbg.fr), a database for mammalian mitochondrial genomes, has been developed for deciphering structural features of mammalian mitochondrial tRNAs and as a helpful tool in the frame of human diseases linked to point mutations in mitochondrial tRNA genes. To accommodate the rapid growing availability of fully sequenced mammalian mitochondrial genomes, Mamit-tRNA has implemented a relational database, and all annotated tRNA genes have been curated and aligned manually. System administrative tools have been integrated to improve efficiency and to allow real-time update (from GenBank Database at NCBI) of available mammalian mitochondrial genomes. More than 3000 tRNA gene sequences from 150 organisms are classified into 22 families according to the amino acid specificity as defined by the anticodon triplets and organized according to phylogeny. Each sequence is displayed linearly with color codes indicating secondary structural domains and can be converted into a printable two-dimensional (2D) cloverleaf structure. Consensus and typical 2D structures can be extracted for any combination of primary sequences within a given tRNA specificity on the basis of phylogenetic relationships or on the basis of structural peculiarities. Mamit-tRNA further displays static individual 2D structures of human mitochondrial tRNA genes with location of polymorphisms and pathology-related point mutations. The site offers also a table allowing for an easy conversion of human mitochondrial genome nucleotide numbering into conventional tRNA numbering. The database is expected to facilitate exploration of structure/function relationships of mitochondrial tRNAs and to assist clinicians in the frame of pathology-related mutation assignments.     

Cyanoseq: A database of cyanobacterial 16S rRNA gene sequences with curated taxonomy

Cyanobacteria are photosynthetic bacteria that occupy various habitats across the globe, playing critical roles in many of Earth's biogeochemical cycles both in both aquatic and terrestrial systems. Despite their well-known significance, their taxonomy remains problematic and is the subject of much research. Taxonomic issues of Cyanobacteria have consequently led to inaccurate curation within known reference databases, ultimately leading to problematic taxonomic assignment during diversity studies. Recent advances in sequencing technologies have increased our ability to characterize and understand microbial communities, leading to the generation of thousands of sequences that require taxonomic assignment. We herein propose CyanoSeq ( https://zenodo.org/record/7569105 ), a database of cyanobacterial 16S rRNA gene sequences with curated taxonomy. The taxonomy of CyanoSeq is based on the current state of cyanobacterial taxonomy, with ranks from the domain to genus level. Files are provided for use with common naive Bayes taxonomic classifiers, such as those included in DADA2 or the QIIME2 platform. Additionally, FASTA files are provided for creation of de novo phylogenetic trees with (near) full-length 16S rRNA gene sequences to determine the phylogenetic relationship of cyanobacterial strains and/or ASV/OTUs. The database currently consists of 5410 cyanobacterial 16S rRNA gene sequences along with 123 Chloroplast, Bacterial, and Vampirovibrionia (formally Melainabacteria) sequences.     

A tool for biomarker discovery in the urinary proteome: a manually curated human and animal urine protein biomarker database

Urine is an important source of biomarkers. A single proteomics assay can identify hundreds of differentially expressed proteins between disease and control samples; however, the ability to select biomarker candidates with the most promise for further validation study remains difficult. A bioinformatics tool that allows accurate and convenient comparison of all of the existing related studies can markedly aid the development of this area. In this study, we constructed the Urinary Protein Biomarker (UPB) database to collect existing studies of urinary protein biomarkers from published literature. To ensure the quality of data collection, all literature was manually curated. The website (http://122.70.220.102/biomarker) allows users to browse the database by disease categories and search by protein IDs in bulk. Researchers can easily determine whether a biomarker candidate has already been identified by another group for the same disease or for other diseases, which allows for the confidence and disease specificity of their biomarker candidate to be evaluated. Additionally, the pathophysiological processes of the diseases can be studied using our database with the hypothesis that diseases that share biomarkers may have the same pathophysiological processes. Because of the natural relationship between urinary proteins and the urinary system, this database may be especially suitable for studying the pathogenesis of urological diseases. Currently, the database contains 553 and 275 records compiled from 174 and 31 publications of human and animal studies, respectively. We found that biomarkers identified by different proteomic methods had a poor overlap with each other. The differences between sample preparation and separation methods, mass spectrometers, and data analysis algorithms may be influencing factors. Biomarkers identified from animal models also overlapped poorly with those from human samples, but the overlap rate was not lower than that of human proteomics studies. Therefore, it is not clear how well the animal models mimic human diseases.     

Polymorphisms of mitochondrially encoded proteins.

Polymorphisms of mitochondrially encoded proteins can be detected in human lymphocytes by sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Using an SDS-polyacrylamide 8 M urea system, 17 mitochondrially encoded proteins are distinguishable. Three of these (ME-6, ME-8, and ME-17) were polymorphic among 92 individuals screened, and these polymorphisms are reported here for the first time. With SDS-polyacrylamide electrophoresis without urea, 18 mitochondrial proteins are detectable. One of these (MV-1) varied in two of 31 individuals tested. This polymorphism has been identified previously in HeLa cells. Maternal inheritance of the ME-8 polymorphism was demonstrated by three informative families.     

Microarray meta-analysis database (M2DB): a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database

Background

With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and apply it to de novo sequencing of new organisms. As an example, this paper demonstrates how such extra information can be used to improve de novo assemblies by augmenting the overlapping step. Finding all pairs of overlapping reads is a key task in many genome assemblers, and to this end, highly efficient algorithms have been developed to find alignments in large collections of sequences. It is well known that due to repeated sequences, many aligned pairs of reads nevertheless do not overlap. But no overlapping algorithm to date takes a rigorous approach to separating aligned but non-overlapping read pairs from true overlaps.

Results

We present an approach that extends the Minimus assembler by a data driven step to classify overlaps as true or false prior to contig construction. We trained several different classification models within the Weka framework using various statistics derived from overlaps of reads available from prior sequencing projects. These statistics included percent mismatch and k-mer frequencies within the overlaps as well as a comparative genomics score derived from mapping reads to multiple reference genomes. We show that in real whole-genome sequencing data from the E. coli and S. aureus genomes, by providing a curated set of overlaps to the contigging phase of the assembler, we nearly doubled the median contig length (N50) without sacrificing coverage of the genome or increasing the number of mis-assemblies.

Conclusions

Machine learning methods that use comparative and non-comparative features to classify overlaps as true or false can be used to improve the quality of a sequence assembly.     

CRlncRNA: a manually curated database of cancer-related long non-coding RNAs with experimental proof of functions on clinicopathological and molecular features

Background

Recent studies demonstrated that long non-coding RNAs (lncRNAs) could be intricately implicated in cancer-related molecular networks, and related to cancer occurrence, development and prognosis. However, clinicopathological and molecular features for these cancer-related lncRNAs, which are very important in bridging lncRNA basic research with clinical research, fail to well settle to integration.

Results

After manually reviewing more than 2500 published literature, we collected the cancer-related lncRNAs with the experimental proof of functions. By integrating from literature and public databases, we constructed CRlncRNA, a database of cancer-related lncRNAs. The current version of CRlncRNA embodied 355 entries of cancer-related lncRNAs, covering 1072 cancer-lncRNA associations regarding to 76 types of cancer, and 1238 interactions with different RNAs and proteins. We further annotated clinicopathological features of these lncRNAs, such as the clinical stages and the cancer hallmarks. We also provided tools for data browsing, searching and download, as well as online BLAST, genome browser and gene network visualization service.

Conclusions

CRlncRNA is a manually curated database for retrieving clinicopathological and molecular features of cancer-related lncRNAs supported by highly reliable evidences. CRlncRNA aims to provide a bridge from lncRNA basic research to clinical research. The lncRNA dataset collected by CRlncRNA can be used as a golden standard dataset for the prospective experimental and in-silico studies of cancer-related lncRNAs. CRlncRNA is freely available for all users at http://crlnc.xtbg.ac.cn.

     

GlycoSuiteDB: a new curated relational database of glycoprotein glycan structures and their biological sources

GlycoSuiteDB is a relational database that curates information from the scientific literature on glyco-protein derived glycan structures, their biological sources, the references in which the glycan was described and the methods used to determine the glycan structure. To date, the database includes most published O:-linked oligosaccharides from the last 50 years and most N:-linked oligosaccharides that were published in the 1990s. For each structure, information is available concerning the glycan type, linkage and anomeric configuration, mass and composition. Detailed information is also provided on native and recombinant sources, including tissue and/or cell type, cell line, strain and disease state. Where known, the proteins to which the glycan structures are attached are reported, and cross-references to the SWISS-PROT/TrEMBL protein sequence databases are given if applicable. The GlycoSuiteDB annotations include literature references which are linked to PubMed, and detailed information on the methods used to determine each glycan structure are noted to help the user assess the quality of the structural assignment. GlycoSuiteDB has a user-friendly web interface which allows the researcher to query the database using mono-isotopic or average mass, monosaccharide composition, glycosylation linkages (e.g. N:- or O:-linked), reducing terminal sugar, attached protein, taxonomy, tissue or cell type and GlycoSuiteDB accession number. Advanced queries using combinations of these parameters are also possible. GlycoSuiteDB can be accessed on the web at http://www.glycosuite.com.     

Nucleotide sequences of three tRNA genes encoded in Tetrahymena mitochondrial DNA.

Nucleotide sequences of three cloned restriction fragments of Tetrahymena mtDNA which showed hybridization with mitochondrial tRNA have been determined. EcoRI fragment 5 (4.1 kbp) contains the tRNAphe gene sequence with anticodon GAA; Hind III fragment 6 (2.0 kbp) the tRNAhis with anticodon GTG; and EcoRI fragment 7 (1.9 kbp) the tRNAtrp with anticodon TCA. The CCA end is not encoded. All three tRNAs show usual features with common invariant and semi-invariant bases and can be folded into a cloverleaf structure with standard loops and regular base pairs in the stems. However, some minor irregular features are present including several GT pairs and an unmatched TT in the stems, and TCC instead of T psi C. All exhibit high G+C contents (about 50%); in contrast, the flanking regions are extremely A+T rich (about 80%). Several short coding frames can be deduced in these sequences, but their significance is not known.     

Compilation of tRNA sequences and sequences of tRNA genes.

Sequences of 3279 sequences of tRNA genes and tRNAs published up to December 1996 are included in the compilation. Alignment of the sequences, which is most compatible with the tRNA phylogeny and known three-dimensional structures of tRNA, is used. Sequences and references are available under http://www.uni-bayreuth. de/departments/biochemie/trna/     

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways’ side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl.gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.     

ConoServer, a database for conopeptide sequences and structures

SUMMARY: ConoServer is a new database dedicated to conopeptides, a large family of peptides found in the venom of marine snails of the genus Conus. These peptides have an exceptional diversity of sequences and chemical modifications and their ability to block ion channels makes them important as drug leads and tools for physiological studies. ConoServer uses standardized names and a genetic and structural classification scheme to present data retrieved from SwissProt, GenBank, the Protein DataBank and the literature. The ConoServer web site incorporates specialized features like the graphic display of post-translational modifications that are extensively present in conopeptides. Currently, ConoServer manages 1214 nucleic sequences (from 54 Conus species), 2258 proteic sequences (from 66 Conus species) and 99 3D structures. AVAILABILITY: http://research1t.imb.uq.edu.au/conoserver/.     

A 7.1 kb linear DNA molecule of Theileria parva has scrambled rDNA sequences and open reading frames for mitochondrially encoded proteins.

Theileria parva, an intralymphocytic protozoan parasite of cattle, contains a linear 7.1 kb DNA element with terminal inverted repeat sequences. The molecule is transcribed into low molecular weight RNA, and both DNA strands encode short stretches of unique sequences, usually < 100 nucleotides, which are similar to large (LSU) or small (SSU) ribosomal subunit RNA. Phylogenetically conserved conformational rRNA domains were assembled from the discontinuous rDNA sequences using comparative secondary structure modelling. For example, a minimum of four predicted sequences, two derived from each DNA strand, is required to assemble domain V of LSU rRNA which participates in peptidyl transferase activity. The discontinuities in the identified rRNA domains fall within regions of no known functional significance. Hence, it is likely that the element encodes fragmented rDNA genes and the mature rRNA is unconventional, consisting of several fragments of RNA, primarily held together by intermolecular and intramolecular base pairing. The element also has ORFs for components of the last two mitochondrial electron transport enzyme complexes. The structure of the parasite DNA element, its protein coding capacity and scrambled rDNA gene sequences, are reminiscent of the mitochondrial genome of Chlamydomonas reinhardtii. We propose that the 7.1 kb element is equivalent to the mitochondrial DNA of T. parva, although a number of its features are unusual for this family of extrachromosomal DNA molecules.     

GlycoSuiteDB: a curated relational database of glycoprotein glycan structures and their biological sources. 2003 update

GlycoSuiteDB is an annotated and curated relational database of glycan structures reported in the literature. It contains information on the glycan type, core type, linkages and anomeric configurations, mass, composition and the analytical methods used by the researchers to determine the glycan structure. Native and recombinant sources are detailed, including species, tissue and/or cell type, cell line, strain, life stage, disease, and if known the protein to which the glycan structures are attached. There are links to SWISS-PROT/TrEMBL and PubMed where applicable. Recent developments include the implementation of searching by 2D structure and substructure, disease and reference. The database is updated twice a year, and now contains over 7650 entries. Access to GlycoSuiteDB is available at http://www.glycosuite.com.     

Analysis of wheat mitochondrially encoded polypeptides by in organello labelling

 The in organello labeling pattern in wheat (Triticum aestivum) mitochondria isolated from imbibed embryos were compared with those from the commonly used starting material, etiolated seedlings. Mitochondria from imbibed embryos proved to be metabolically more active than those from etiolated seedlings and produced a large number of strongly in organello-labeled polypeptides. Immunoprecipitation of the labeled proteins enabled the identification of mitochondrially encoded subunits of the respiratory chain complex I, some of which could not be detected by conventional Western blotting due to their high hydrophobicity. A method for mass isolation of wheat embryos is also presented which allows easy preparation of large amounts of intact and highly active mitochondria suitable for biochemical studies. Received: 9 November 1998 / Revision received: 10 March 1999 / Accepted: 1 April 1999