Practical Data Processing Approach for RNA Sequencing of Microorganisms

The rapid evolvement of sequencing technology has generated huge amounts of DNA/RNA sequences, even with the continuous performance acceleration. Due to the wide variety of basic studies and applications derived from the huge number of species and the microorganism diversity, the targets to be sequenced are also expanding. The huge amounts of data generated by recently developed high-throughput sequencers have required highly efficient data analysis algorithms using recently developed high-performance computers. We have developed a highly accurate and cost-effective mapping strategy that includes the exclusion of unreliable base calls and correction of the reference sequence through provisional mapping of RNA sequencing reads. The use of mapping software tools, such as HISAT and STAR, precisely aligned RNA-Seq reads to the genome of a filamentous fungus considering exon-intron boundaries. The accuracy of the expression analysis through the refinement of gene models was achieved by the results of mapped RNA-Seq reads in combination with ab initio gene finding tools using generalized hidden Markov models (GHMMs). Visualization of the mapping results greatly helps evaluate and improve the entire analysis in terms of both wet experiment and data processing. We believe that at least a portion of our approach is useful and applicable to the analysis of any microorganism

Microbial residence time is a controlling parameter of the taxonomic composition and functional profile of microbial communities.

A remaining challenge within microbial ecology is to understand the determinants of richness and diversity observed in environmental microbial communities. In a range of systems, including activated sludge bioreactors, the microbial residence time (MRT) has been previously shown to shape the microbial community composition. However, the physiological and ecological mechanisms driving this influence have remained unclear. Here, this relationship is explored by analyzing an activated sludge system fed with municipal wastewater. Using a model designed in this study based on Monod-growth kinetics, longer MRTs were shown to increase the range of growth parameters that enable persistence, resulting in increased richness and diversity in the modeled community. In laboratory experiments, six sequencing batch reactors treating domestic wastewater were operated in parallel at MRTs between 1 and 15 days. The communities were characterized using both 16S ribosomal RNA and non-target messenger RNA sequencing (metatranscriptomic analysis), and model-predicted monotonic increases in richness were confirmed in both profiles. Accordingly, taxonomic Shannon diversity also increased with MRT. In contrast, the diversity in enzyme class annotations resulting from the metatranscriptomic analysis displayed a non-monotonic trend over the MRT gradient. Disproportionately high abundances of transcripts encoding for rarer enzymes occur at longer MRTs and lead to the disconnect between taxonomic and functional diversity profiles

Assigning ecological roles to the populations belonging to a phenanthrene-degrading bacterial consortium using omic approaches

The present study describes the behavior of a natural phenanthrene-degrading consortium (CON), a synthetic consortium (constructed with isolated strains from CON) and an isolated strain form CON (Sphingobium sp. AM) in phenanthrene cultures to understand the interactions among the microorganisms present in the natural consortium during phenanthrene degradation as a sole carbon and energy source in liquid cultures. In the contaminant degradation assay, the defined consortium not only achieved a major phenanthrene degradation percentage (> 95%) but also showed a more efficient elimination of the intermediate metabolite. The opposite behavior occurred in the CON culture where the lowest phenanthrene degradation and the highest HNA accumulation were observed, which suggests the presence of positive and also negative interaction in CON. To consider the uncultured bacteria present in CON, a metagenomic library was constructed with total CON DNA. One of the resulting scaffolds (S1P3) was affiliated with the Betaproteobacteria class and resulted in a significant similarity with a genome fragment from Burkholderia sp. HB1 chromosome 1. A complete gene cluster, which is related to one of the lower pathways (meta-cleavage of catechol) involved in PAH degradation (ORF 31–43), mobile genetic elements and associated proteins, was found. These results suggest the presence of at least one other microorganism in CON besides Sphingobium sp. AM, which is capable of degrading PAH through the meta-cleavage pathway. Burkholderiales order was further found, along with Sphingomonadales order, by a metaproteomic approach, which indicated that both orders were metabolically active in CON. Our results show the presence of negative interactions between bacterial populations found in a natural consortium selected by enrichment techniques; moreover, the synthetic syntrophic processing chain with only one microorganism with the capability of degrading phenanthrene was more efficient in contaminant and intermediate metabolite degradation than a generalist strain (Sphingobium sp. AM).Centro de Investigación y Desarrollo en Fermentaciones Industriale

The secondary metabolite bioinformatics portal:Computational tools to facilitate synthetic biology of secondary metabolite production

AbstractNatural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http://www.secondarymetabolites.org) is introduced to provide a one-stop catalog and links to these bioinformatics resources. In addition, an outlook is presented how the existing tools and those to be developed will influence synthetic biology approaches in the natural products field

Sharing of worldwide distributed carbohydrate-related digital resources: online connection of the Bacterial Carbohydrate Structure DataBase and GLYCOSCIENCES.de

Functional glycomics, the scientific attempt to identify and assign functions to all glycan molecules synthesized by an organism, is an emerging field of science. In recent years, several databases have been started, all aiming to support deciphering the biological function of carbohydrates. However, diverse encoding and storage schemes are in use amongst these databases, significantly hampering the interchange of data. The mutual online access between the Bacterial Carbohydrate Structure DataBase (BCSDB) and the GLYCOSCIENCES.de portal, as a first reported attempt of a structure-based direct interconnection of two glyco-related databases is described. In this approach, users have to learn only one interface, will always have access to the latest data of both services, and will have the results of both searches presented in a consistent way. The establishment of this connection helped to find shortcomings and inconsistencies in the database design and functionality related to underlying data concepts and structural representations. For the maintenance of the databases, duplication of work can be easily avoided, and will hopefully lead to a better worldwide acceptance of both services within the community of glycoscienists. BCSDB is available at and the GLYCOSCIENCES.de portal a

COMPUTATIONAL APPROACHES FOR THE PREDICTION OF ANTIMICROBIAL POTENTIAL PEPTIDES FROM OCIMUM TENUIFLORUM.

 Objective: In this study, antimicrobial activity was predicted against novel antimicrobial target 1SDE receptor to understand the structural feature of predicted peptides using machine learning approach from Ocimum tenuiflorum. Methods: Protein sequences from O. tenuiflorum were digested using peptide cutter and further processed for the prediction of antimicrobial peptide (AMP) through AMP predictor tool of CAMP which have multidimensional algorithms such as support vector machine, artificial neural network, random forest, and discriminant analysis. After analyzing various peptides, only four peptides were predicted as antimicrobial in nature. Furthermore, the three-dimensional structure of different potential peptides was generated with the help of Pepfold-3.0 server followed by protein-peptide docking studies with novel target receptor with the help of PatchDock, FireDock webserver, and Hex 8.0 software. Interactions were further visualized using Discovery Studio Client 2.5 software tool.Results: This study revealed that peptide 2 resulted higher score in PatchDock and FireDock and also Hex 8.0 provides E total value of −430.18 which is higher than that of peptide 1 with −381.07, peptide 3 with −416.86, and peptide 4 with −407.94.Conclusion: The peptide predicted in this study has potential to act as effective AMP against target receptor and also utilize other antimicrobial target

Characterization of specificity of bacterial community structure within the burrow environment of the marine polychaete Hediste (Nereis) diversicolor

Bioturbation is known to stimulate microbial communities, especially in macrofaunal burrows where the abundance and activities of bacteria are increased. Until now, these microbial communities have been poorly characterized and an important ecological question remains: do burrow walls harbor similar or specific communities compared with anoxic and surface sediments? The bacterial community structure of coastal sediments inhabited by the polychaete worm Hediste diversicolor was investigated. Surface, burrow wall and anoxic sediments were collected at the Carteau beach (Gulf of Fos, Mediterranean Sea). Bacterial diversity was determined by analyzing small subunit ribosomal RNA (16S rRNA) sequences from three clone libraries (168, 179 and 129 sequences for the surface, burrow wall and anoxic sediments, respectively). Libraries revealed 306 different operational taxonomic units (OTUs) belonging to at least 15 bacterial phyla. Bioinformatic analyses and comparisons between the three clone libraries showed that the burrow walls harbored a specific bacterial community structure which differed from the surface and anoxic environments. More similarities were nevertheless found with the surface assemblage. Inside the burrow walls, the bacterial community was characterized by high biodiversity, which probably results from the biogeochemical heterogeneity of the burrow system

A method for automatically extracting infectious disease-related primers and probes from the literature

BACKGROUND: Primer and probe sequences are the main components of nucleic acid-based detection systems. Biologists use primers and probes for different tasks, some related to the diagnosis and prescription of infectious diseases. The biological literature is the main information source for empirically validated primer and probe sequences. Therefore, it is becoming increasingly important for researchers to navigate this important information. In this paper, we present a four-phase method for extracting and annotating primer/probe sequences from the literature. These phases are: (1) convert each document into a tree of paper sections, (2) detect the candidate sequences using a set of finite state machine-based recognizers, (3) refine problem sequences using a rule-based expert system, and (4) annotate the extracted sequences with their related organism/gene information. RESULTS: We tested our approach using a test set composed of 297 manuscripts. The extracted sequences and their organism/gene annotations were manually evaluated by a panel of molecular biologists. The results of the evaluation show that our approach is suitable for automatically extracting DNA sequences, achieving precision/recall rates of 97.98% and 95.77%, respectively. In addition, 76.66% of the detected sequences were correctly annotated with their organism name. The system also provided correct gene-related information for 46.18% of the sequences assigned a correct organism name. CONCLUSIONS: We believe that the proposed method can facilitate routine tasks for biomedical researchers using molecular methods to diagnose and prescribe different infectious diseases. In addition, the proposed method can be expanded to detect and extract other biological sequences from the literature. The extracted information can also be used to readily update available primer/probe databases or to create new databases from scratch.The present work has been funded, in part, by the European Commission through the ACGT integrated project (FP6-2005-IST-026996) and the ACTION-Grid support action (FP7-ICT-2007-2-224176), the Spanish Ministry of Science and Innovation through the OntoMineBase project (ref. TSI2006-13021-C02-01), the ImGraSec project (ref. TIN2007-61768), FIS/AES PS09/00069 and COMBIOMED-RETICS, and the Comunidad de Madrid, Spain.S

The Methods for Detection of Biofilm and Screening Antibiofilm Activity of Agents

Biofilm producer microorganisms cause nosocomial and recurrent infections. Biofilm that is a sticky exopolysaccharide is the main virulence factor causing biofilm-related infections. Biofilm formation begins with attachment of bacteria to biotic surface such as host cell or abiotic surface such as prosthetic devices. After attachment, aggregation of bacteria is started by cell-cell adhesion. Aggregation continues with the maturation of biofilm. Dispersion is started by certain conditions such as phenol-soluble modulins (PSMs). By this way, sessile bacteria turn back into planktonic form. Bacteria embedded in biofilm (sessile form) are more resistant to antimicrobials than planktonic bacteria. So it is hard to treat biofilm-embedded bacteria than planktonic forms. For this reason, it is important to detect biofilm. There are a few biofilm detection and biofilm production methods on prosthetics, methods for screening antibacterial effect of agents against biofilm-embedded microorganism and antibiofilm effect of agents against biofilm production and mature biofilm. The aim of this chapter is to overview direct and indirect methods such as microscopy, fluorescent in situ hybridization, and Congo red agar, tube method, microtiter plate assay, checkerboard assay, plate counting, polymerase chain reaction, mass spectrometry, MALDI-TOF, and biological assays used by antibiofilm researches