Protein Sequence Annotation Tool (PSAT): a centralized web-based meta-server for high-throughput sequence annotations

Leung, Elo; Huang, Amy; Cadag, Eithon; Montana, Aldrin; Soliman, Jan Lorenz; Zhou, Carol L. Ecale

doi:10.1186/s12859-016-0887-y

Cited by 6 publications

(3 citation statements)

References 28 publications

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“…2 ). Before any further analysis, both genomes were re-annotated using the RAST (Rapid Annotation using Subsystem Technology) server [ 15 ], the Pseudomonas database (PsDB) [ 16 ] and the Protein Sequence Annotation Tool [ 17 ] (Additional file 1 : Tables S1–S4). The Pae_G1a Affymetrix microarray, designed against the PAO1 genome sequence [ 18 ], was used to supplement RNA-seq data when ATCC 33988 showed high sequence identity to the cDNA probes (Additional file 2 : Tables S5–S8, See Methods for details).…”

Section: Resultsmentioning

confidence: 99%

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes

et al. 2017

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BackgroundExamination of complex biological systems has long been achieved through methodical investigation of the system’s individual components. While informative, this strategy often leads to inappropriate conclusions about the system as a whole. With the advent of high-throughput “omic” technologies, however, researchers can now simultaneously analyze an entire system at the level of molecule (DNA, RNA, protein, metabolite) and process (transcription, translation, enzyme catalysis). This strategy reduces the likelihood of improper conclusions, provides a framework for elucidation of genotype-phenotype relationships, and brings finer resolution to comparative genomic experiments. Here, we apply a multi-omic approach to analyze the gene expression profiles of two closely related Pseudomonas aeruginosa strains grown in n-alkanes or glycerol.ResultsThe environmental P. aeruginosa isolate ATCC 33988 consumed medium-length (C10–C16) n-alkanes more rapidly than the laboratory strain PAO1, despite high genome sequence identity (average nucleotide identity >99%). Our data shows that ATCC 33988 induces a characteristic set of genes at the transcriptional, translational and post-translational levels during growth on alkanes, many of which differ from those expressed by PAO1. Of particular interest was the lack of expression from the rhl operon of the quorum sensing (QS) system, resulting in no measurable rhamnolipid production by ATCC 33988. Further examination showed that ATCC 33988 lacked the entire lasI/lasR arm of the QS response. Instead of promoting expression of QS genes, ATCC 33988 up-regulates a small subset of its genome, including operons responsible for specific alkaline proteases and sphingosine metabolism.ConclusionThis work represents the first time results from RNA-seq, microarray, ribosome footprinting, proteomics, and small molecule LC-MS experiments have been integrated to compare gene expression in bacteria. Together, these data provide insights as to why strain ATCC 33988 is better adapted for growth and survival on n-alkanes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3708-4) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes

et al. 2017

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“…Predicted protein sequences from the MD1149 genome were processed through automated functional annotation using the PSAT metaserver (Leung et al, 2016 ), which ran EFICAz 2.5 (Kumar and Skolnick, 2012 ), blastp against the KEGG, MetaCyc, BRENDA, and STRING databases (Caspi et al, 2014 ; Chang et al, 2015 ; Szklarczyk et al, 2015 ; Kanehisa et al, 2016 ), and Interproscan (Jones et al, 2014 ). Additionally, protein sequences were processed through online servers running SignalP 4.0 (Petersen et al, 2011 ) and TMHMM 2.0 (Krogh et al, 2001 ).…”

Section: Methodsmentioning

confidence: 99%

Prospects for Fungal Bioremediation of Acidic Radioactive Waste Sites: Characterization and Genome Sequence of Rhodotorula taiwanensis MD1149

et al. 2018

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Highly concentrated radionuclide waste produced during the Cold War era is stored at US Department of Energy (DOE) production sites. This radioactive waste was often highly acidic and mixed with heavy metals, and has been leaking into the environment since the 1950s. Because of the danger and expense of cleanup of such radioactive sites by physicochemical processes, in situ bioremediation methods are being developed for cleanup of contaminated ground and groundwater. To date, the most developed microbial treatment proposed for high-level radioactive sites employs the radiation-resistant bacterium Deinococcus radiodurans. However, the use of Deinococcus spp. and other bacteria is limited by their sensitivity to low pH. We report the characterization of 27 diverse environmental yeasts for their resistance to ionizing radiation (chronic and acute), heavy metals, pH minima, temperature maxima and optima, and their ability to form biofilms. Remarkably, many yeasts are extremely resistant to ionizing radiation and heavy metals. They also excrete carboxylic acids and are exceptionally tolerant to low pH. A special focus is placed on Rhodotorula taiwanensis MD1149, which was the most resistant to acid and gamma radiation. MD1149 is capable of growing under 66 Gy/h at pH 2.3 and in the presence of high concentrations of mercury and chromium compounds, and forming biofilms under high-level chronic radiation and low pH. We present the whole genome sequence and annotation of R. taiwanensis strain MD1149, with a comparison to other Rhodotorula species. This survey elevates yeasts to the frontier of biology's most radiation-resistant representatives, presenting a strong rationale for a role of fungi in bioremediation of acidic radioactive waste sites.

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“…The Protein Sequence Annotation Tool (PSAT) is a meta-platform based on the Web for integrated, high-throughput analysis of genomic sequences, demonstrating its usefulness in annotating the gene products of predicted peptides of Herbaspirillum sp. strain RV1423 , import the results into the EC2KEGG, and use the resulting functional comparisons to identify a putative catabolic pathway, highlighting the potential in a genome with limited annotation [16]. Genix is a web-based bacterial genome annotation platform, which stands out for providing results closer to the reference annotation, with a lower number of false-positive proteins and non-annotated functional proteins, being able to enhance the accuracy of bacterial genome annotation steps and provide high-quality results [17].…”

Section: State-of-the-art Related Researchmentioning

confidence: 99%

Pannotator integrated with Medpipe provides immunological and subcellular location features using a microservice

Gonçalves,

Santos

2024

Preprint

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Genome sequencing and assembly are trivial tasks nowadays. After assembling contigs and scaffolds from a genome, the subsequent step is annotation. An annotation evidencing the expected features, like rRNA, tRNA, and CDS, is a signal of the quality of our sequencing and assembly. Different techniques to obtain and reproduce DNA samples, as well as sequencing and assembly of genomes, can impact the quality of a genome's expected features. The Pannotator tool was conceived as an aid annotation tool focusing on the differences between assembling and its reference genome. Some of the key features for bacterial genome annotations are the subcellular location and immunological potential of a CDS. Instead of reimplementing the prediction of these features in Pannotator, we leveraged the capabilities of our microservice to provide them. In the end, Medpipe software was not modified, and Pannotator underwent minor changes to incorporate the subcellular location and immunological potential of all exported proteins annotated by the tool. Moreover, our Medpipe microservice can also be incorporated into other software. The Medpipe microservice is open to anyone, not only to our Pannotator tool. The successful integration of Medpipe to Pannotator, powered by the Medpipe microservice, offers a powerful approach to advanced genomic analysis. The Medpipe microservice, built on Kotlin with the Spring Boot framework, is instrumental in the automation of Medpipe processing. It achieves this using REST endpoints, such as the execution of Medpipe in an asynchronous manner, status retrieval, and prediction generation, which enhance the modularity and scalability of the microservice. The availability of endpoint documentation, detailed request examples, and logs make our microservice user-friendly. The results of this integration demonstrate the value of the information provided by Medpipe, enriching genomic annotation with additional details, such as the density of mature epitopes (MED) and protein subcellular location classification. The Pannotator has evolved beyond basic function annotation and now provides data on immunological potential, structure, and subcellular location after being integrated with our microservice. The Medpipe microservice is available at https://github.com/santosardr/medpipe-ms.git.

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Protein Sequence Annotation Tool (PSAT): a centralized web-based meta-server for high-throughput sequence annotations

Cited by 6 publications

References 28 publications

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes

Prospects for Fungal Bioremediation of Acidic Radioactive Waste Sites: Characterization and Genome Sequence of Rhodotorula taiwanensis MD1149

Pannotator integrated with Medpipe provides immunological and subcellular location features using a microservice

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