PCAS – a precomputed proteome annotation database resource

Background  

Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources.     

DraGnET: Software for storing,managing and analyzing annotated draft genome sequence data

Background  

New "next generation" DNA sequencing technologies offer individual researchers the ability to rapidly generate large amounts of genome sequence data at dramatically reduced costs. As a result, a need has arisen for new software tools for storage, management and analysis of genome sequence data. Although bioinformatic tools are available for the analysis and management of genome sequences, limitations still remain. For example, restrictions on the submission of data and use of these tools may be imposed, thereby making them unsuitable for sequencing projects that need to remain in-house or proprietary during their initial stages. Furthermore, the availability and use of next generation sequencing in industrial, governmental and academic environments requires biologist to have access to computational support for the curation and analysis of the data generated; however, this type of support is not always immediately available.     

Proteome sequence features carry signatures of the environmental niche of prokaryotes

Background  

Prokaryotic environmental adaptations occur at different levels within cells to ensure the preservation of genome integrity, proper protein folding and function as well as membrane fluidity. Although specific composition and structure of cellular components suitable for the variety of extreme conditions has already been postulated, a systematic study describing such adaptations has not yet been performed. We therefore explored whether the environmental niche of a prokaryote could be deduced from the sequence of its proteome. Finally, we aimed at finding the precise differences between proteome sequences of prokaryotes from different environments.     

Biochemical and molecular characterisation of Tetrahymena thermophila extracellular cysteine proteases

Background  

Over the last decades molecular biologic techniques have been developed to alter the genome and proteome of Tetrahymena thermophila thereby providing the basis for recombinant protein expression including functional human enzymes. The biotechnological potential of Tetrahymena has been proved in numerous publications, demonstrating fast growth, high biomass, fermentation in ordinary bacterial/yeast equipment, up-scalability, existence of cheap and chemical defined media. For these reasons Tetrahymena offers promising opportunities for the development of a high expression system. Yet optimised high yield strains with protease deficiency such as commonly used in yeast and bacterial systems are not available.     

Kalign – an accurate and fast multiple sequence alignment algorithm

Background  

The alignment of multiple protein sequences is a fundamental step in the analysis of biological data. It has traditionally been applied to analyzing protein families for conserved motifs, phylogeny, structural properties, and to improve sensitivity in homology searching. The availability of complete genome sequences has increased the demands on multiple sequence alignment (MSA) programs. Current MSA methods suffer from being either too inaccurate or too computationally expensive to be applied effectively in large-scale comparative genomics.     

PCR primers for metazoan mitochondrial 12S ribosomal DNA sequences

Background

Assessment of the biodiversity of communities of small organisms is most readily done using PCR-based analysis of environmental samples consisting of mixtures of individuals. Known as metagenetics, this approach has transformed understanding of microbial communities and is beginning to be applied to metazoans as well. Unlike microbial studies, where analysis of the 16S ribosomal DNA sequence is standard, the best gene for metazoan metagenetics is less clear. In this study we designed a set of PCR primers for the mitochondrial 12S ribosomal DNA sequence based on 64 complete mitochondrial genomes and then tested their efficacy.

Methodology/Principal Findings

A total of the 64 complete mitochondrial genome sequences representing all metazoan classes available in GenBank were downloaded using the NCBI Taxonomy Browser. Alignment of sequences was performed for the excised mitochondrial 12S ribosomal DNA sequences, and conserved regions were identified for all 64 mitochondrial genomes. These regions were used to design a primer pair that flanks a more variable region in the gene. Then all of the complete metazoan mitochondrial genomes available in NCBI''s Organelle Genome Resources database were used to determine the percentage of taxa that would likely be amplified using these primers. Results suggest that these primers will amplify target sequences for many metazoans.

Conclusions/Significance

Newly designed 12S ribosomal DNA primers have considerable potential for metazoan metagenetic analysis because of their ability to amplify sequences from many metazoans.     

Computational prediction of CRISPR cassettes in gut metagenome samples from Chinese type-2 diabetic patients and healthy controls

Background

CRISPR has been becoming a hot topic as a powerful technique for genome editing for human and other higher organisms. The original CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats coupled with CRISPR-associated proteins) is an important adaptive defence system for prokaryotes that provides resistance against invading elements such as viruses and plasmids. A CRISPR cassette contains short nucleotide sequences called spacers. These unique regions retain a history of the interactions between prokaryotes and their invaders in individual strains and ecosystems. One important ecosystem in the human body is the human gut, a rich habitat populated by a great diversity of microorganisms. Gut microbiomes are important for human physiology and health. Metagenome sequencing has been widely applied for studying the gut microbiomes. Most efforts in metagenome study has been focused on profiling taxa compositions and gene catalogues and identifying their associations with human health. Less attention has been paid to the analysis of the ecosystems of microbiomes themselves especially their CRISPR composition.

Results

We conducted a preliminary analysis of CRISPR sequences in a human gut metagenomic data set of Chinese individuals of type-2 diabetes patients and healthy controls. Applying an available CRISPR-identification algorithm, PILER-CR, we identified 3169 CRISPR cassettes in the data, from which we constructed a set of 1302 unique repeat sequences and 36,709 spacers. A more extensive analysis was made for the CRISPR repeats: these repeats were submitted to a more comprehensive clustering and classification using the web server tool CRISPRmap. All repeats were compared with known CRISPRs in the database CRISPRdb. A total of 784 repeats had matches in the database, and the remaining 518 repeats from our set are potentially novel ones.

Conclusions

The computational analysis of CRISPR composition based contigs of metagenome sequencing data is feasible. It provides an efficient approach for finding potential novel CRISPR arrays and for analysing the ecosystem and history of human microbiomes.

     

RIPCAL: a tool for alignment-based analysis of repeat-induced point mutations in fungal genomic sequences

Background  

Repeat-induced point mutation (RIP) is a fungal-specific genome defence mechanism that alters the sequences of repetitive DNA, thereby inactivating coding genes. Repeated DNA sequences align between mating and meiosis and both sequences undergo C:G to T:A transitions. In most fungi these transitions preferentially affect CpA di-nucleotides thus altering the frequency of certain di-nucleotides in the affected sequences. The majority of previously published in silico analyses were limited to the comparison of ratios of pre- and post-RIP di-nucleotides in putatively RIP-affected sequences – so-called RIP indices. The analysis of RIP is significantly more informative when comparing sequence alignments of repeated sequences. There is, however, a dearth of bioinformatics tools available to the fungal research community for alignment-based RIP analysis of repeat families.     

A clustering method for repeat analysis in DNA sequences

Background

A computational system for analysis of the repetitive structure of genomic sequences is described. The method uses suffix trees to organize and search the input sequences; this data structure has been used previously for efficient computation of exact and degenerate repeats.

Results

The resulting software tool collects all repeat classes and outputs summary statistics as well as a file containing multiple sequences (multi fasta), that can be used as the target of searches. Its use is demonstrated here on several complete microbial genomes, the entire Arabidopsis thaliana genome, and a large collection of rice bacterial artificial chromosome end sequences.

Conclusions

We propose a new clustering method for analysis of the repeat data captured in suffix trees. This method has been incorporated into a system that can find repeats in individual genome sequences or sets of sequences, and that can organize those repeats into classes. It quickly and accurately creates repeat databases from small and large genomes. The associated software (RepeatFinder), should prove helpful in the analysis of repeat structure for both complete and partial genome sequences.     

IdentiCS – Identification of coding sequence and <Emphasis Type="Italic">in silico</Emphasis> reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence

Background  

A necessary step for a genome level analysis of the cellular metabolism is the in silico reconstruction of the metabolic network from genome sequences. The available methods are mainly based on the annotation of genome sequences including two successive steps, the prediction of coding sequences (CDS) and their function assignment. The annotation process takes time. The available methods often encounter difficulties when dealing with unfinished error-containing genomic sequence.     

Visualization of comparative genomic analyses by BLAST score ratio

Background  

The first microbial genome sequence, Haemophilus influenzae, was published in 1995. Since then, more than 400 microbial genome sequences have been completed or commenced. This massive influx of data provides the opportunity to obtain biological insights through comparative genomics. However few tools are available for this scale of comparative analysis.     

GenomeMatcher: A graphical user interface for DNA sequence comparison

Background  

The number of available genome sequences is increasing, and easy-to-use software that enables efficient comparative analysis is needed.     

2-DE analysis indicates that Acinetobacter baumannii displays a robust and versatile metabolism

Background  

Acinetobacter baumannii is a nosocomial pathogen that has been associated with outbreak infections in hospitals. Despite increasing awareness about this bacterium, its proteome remains poorly characterised, however recently the complete genome of A. baumannii reference strain ATCC 17978 has been sequenced. Here, we have used 2-DE and MALDI-TOF/TOF approach to characterise the proteome of this strain.     

Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

Background  

The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes.     

Altered expression of hypothetical proteins in hippocampus of transgenic mice overexpressing human Cu/Zn-superoxide dismutase 1

Background  

The rapid completion of genome sequences has created an infrastructure of biological information and provided essential information to link genes to gene products, proteins, the building blocks for cellular functions. In addition, genome/cDNA sequences make it possible to predict proteins for which there is no experimental evidence. Clues for function of hypothetical proteins are provided by sequence similarity with proteins of known function in model organisms.     

MetaBinG2: a fast and accurate metagenomic sequence classification system for samples with many unknown organisms

Background

Many methods have been developed for metagenomic sequence classification, and most of them depend heavily on genome sequences of the known organisms. A large portion of sequencing sequences may be classified as unknown, which greatly impairs our understanding of the whole sample.

Result

Here we present MetaBinG2, a fast method for metagenomic sequence classification, especially for samples with a large number of unknown organisms. MetaBinG2 is based on sequence composition, and uses GPUs to accelerate its speed. A million 100 bp Illumina sequences can be classified in about 1 min on a computer with one GPU card. We evaluated MetaBinG2 by comparing it to multiple popular existing methods. We then applied MetaBinG2 to the dataset of MetaSUB Inter-City Challenge provided by CAMDA data analysis contest and compared community composition structures for environmental samples from different public places across cities.

Conclusion

Compared to existing methods, MetaBinG2 is fast and accurate, especially for those samples with significant proportions of unknown organisms.

Reviewers

This article was reviewed by Drs. Eran Elhaik, Nicolas Rascovan, and Serghei Mangul.