3,341 research outputs found
Prophages are associated with extensive, tolerated CRISPR-Cas auto-immunity
No full textCRISPR–Cas systems require discriminating self from non-self DNA during adaptation and interference. Yet, multiple cases have been reported of bacteria containing self-targeting spacers (STS), i.e. CRISPR spacers targeting protospacers on the same genome. STS has been suggested to reflect potential auto-immunity as an unwanted side effect of CRISPR–Cas defense, or a regulatory mechanism for gene expression. Here we investigated the incidence, distribution, and evasion of STS in over 100 000 bacterial genomes. We found STS in all CRISPR–Cas types and in one fifth of all CRISPR-carrying bacteria. Notably, up to 40% of I-B and I-F CRISPR–Cas systems contained STS. We observed that STS-containing genomes almost always carry a prophage and that STS map to prophage regions in more than half of the cases. Despite carrying STS, genetic deterioration of CRISPR–Cas systems appears to be rare, suggesting a level of escape from the potentially deleterious effects of STS by other mechanisms such as anti-CRISPR proteins and CRISPR target mutations. We propose a scenario where it is common to acquire an STS against a prophage, and this may trigger more extensive STS buildup by primed spacer acquisition in type I systems, without detrimental autoimmunity effects as mechanisms of auto-immunity evasion create tolerance to STS-targeted prophages
Editorial: Computational Methods for Microbiome Analysis
No full textSetubal JC, Stoye J, Dutilh BE. Editorial: Computational Methods for Microbiome Analysis. Frontiers in Genetics. 2020;11: 623897
Computational Methods for Microbiome Analysis
No full textSetubal JC, Stoye J, Dutilh BE, eds. Computational Methods for Microbiome Analysis. Frontiers in Genetics. 2021;Research Topic
Bas-Relief Modeling from Normal Layers
No full textBas-relief is characterized by its unique presentation of intrinsic shape properties and/or detailed appearance using materials raised up in different degrees above a background. However, many bas-relief modeling methods could not manipulate scene details well. We propose a simple and effective solution for two kinds of bas-relief modeling (i.e., structure-preserving and detail-preserving), which is different from the prior tone mapping alike methods. Our idea originates from an observation on typical 3D models which are decomposed into a piecewise smooth base layer and a detail layer in normal field. Proper manipulation of the two layers contributes to both structure-preserving and detail-preserving bas-relief modeling. We solve the modeling problem in a discrete geometry processing setup that uses normal-based mesh processing as a theoretical foundation. Specifically, using the two-step mesh smoothing mechanism as a bridge, we transfer the bas-relief modeling problem into a discrete space, and solve it in a least-squares manner. Experiments and comparisons to other methods show that (i) geometry details are better preserved in the scenario with high compression ratios, and (ii) structures are clearly preserved without shape distortion and interference from details.Accepted author manuscriptMaterials and Manufacturin
A social niche breadth score reveals niche range strategies of generalists and specialists
No full textAbstract
Generalists can survive in many environments whereas specialists are restricted to a single environment. Although a classical concept in ecology, niche breadth has remained challenging to quantify for microbes because it depends on an objective definition of the environmental conditions. Here, by defining the environment of a microbe as the community it resides in, we integrated information from over 22 thousand environmental sequencing samples to derive a quantitative measure of the niche, which we call ‘social niche breadth’. At the level of genera, we explored niche range strategies throughout the prokaryotic tree of life. We found that social generalists include opportunists that stochastically dominate local communities, while social specialists are stable but low in abundance. Social generalists have a more diverse and open pan genome than social specialists, but we found no global correlation between social niche breadth and genome size. Instead, we observed two distinct evolutionary strategies, where specialists have relatively small genomes in habitats with low local diversity, but relatively large genomes in habitats with high local diversity. Together, our analysis shines data-driven light on microbial niche range strategies.
Inside this repository
This is the directory structure and code used to generate all data and figures in the paper "A social niche breadth score reveals niche range strategies of generalists and specialists" by F. A. Bastiaan von Meijenfeldt, Paulien Hogeweg, and Bas E. Dutilh. The code was made by F. A. Bastiaan von Meijenfeldt.
The code inside the ./MGnify directory was used to download the MGnify data.
The code inside the ./niche_breadth directory was used to generate all other data and uses the MGnify data.
The code inside the ./figures directory was used to generate all figures.
Each directory in ./MGnify and ./niche_breadth contains a commands.sh that if run, and if source files are present, will generate all content in that directory. No files are written outside the directory. For example running ./MGnify/commands.sh will generate all files within ./MGnify. The generated files are source files for some of the scripts in ./MGnify/2019-08-20_extra and ./MGnify/2019-08-20_extra/commands.sh can now be run to generate all files within. Source files for the ./niche_breadth subdirectories can be from the ./MGnify directory or from other subdirectories within ./niche_breadth.
The ./figures directory and its subdirectories contain *.ipynb Jupyter Notebook files that if run, and source files are present, will generate the vector files that were used as raw input for the final figures.
The file ./figures/mappings.Figure_to_Notebook.txt contains the mapping of the figure to the notebook that was used to generate the figure. In some cases only part of the notebook output was used in the final figures
Computational function prediction of bacteria and phage proteins
No full textUnderstanding protein functions is crucial for interpreting microbial life; however, reliable function annotation remains a major challenge in computational biology. Despite significant advances in bioinformatics methods, ~30% of all bacterial and ~65% of all bacteriophage (phage) protein sequences cannot be confidently annotated. In this review, we examine state-of-the-art bioinformatics tools and methodologies for annotating bacterial and phage proteins, particularly those of unknown or poorly characterized function. We describe the process of identifying protein-coding regions and the systems to classify protein functionalities. Additionally, we explore a range of protein annotation methods, from traditional homology-based methods to cutting-edge machine learning models. In doing so, we provide a toolbox for confidently annotating previously unknown bacterial and phage proteins, advancing the discovery of novel functions and our understanding of microbial systems.Susanna R. Grigson, George Bouras, Bas E. Dutilh, Robert D. Olson, Robert A. Edward
Molecular and Evolutionary Determinants of Bacteriophage Host Range
No full textThe host range of a bacteriophage is the taxonomic diversity of hosts it can successfully infect. Host range, one of the central traits to understand in phages, is determined by a range of molecular interactions between phage and host throughout the infection cycle. While many well studied model phages seem to exhibit a narrow host range, recent ecological and metagenomics studies indicate that phages may have specificities that range from narrow to broad. There is a growing body of studies on the molecular mechanisms that enable phages to infect multiple hosts. These mechanisms, and their evolution, are of considerable importance to understanding phage ecology and the various clinical, industrial, and biotechnological applications of phage. Here we review knowledge of the molecular mechanisms that determine host range, provide a framework defining broad host range in an evolutionary context, and highlight areas for additional research
Increasing the coverage of a metapopulation consensus genome by iterative read mapping and assembly
No full textDutilh BE, Huynen MA, Strous M. Increasing the coverage of a metapopulation consensus genome by iterative read mapping and assembly. BIOINFORMATICS. 2009;25(21):2878-2881.Motivation: Most microbial species can not be cultured in the laboratory. Metagenomic sequencing may still yield a complete genome if the sequenced community is enriched and the sequencing coverage is high. However, the complexity in a natural population may cause the enrichment culture to contain multiple related strains. This diversity can confound existing strict assembly programs and lead to a fragmented assembly, which is unnecessary if we have a related reference genome available that can function as a scaffold. Results: Here, we map short metagenomic sequencing reads from a population of strains to a related reference genome, and compose a genome that captures the consensus of the population's sequences. We show that by iteration of the mapping and assembly procedure, the coverage increases while the similarity with the reference genome decreases. This indicates that the assembly becomes less dependent on the reference genome and approaches the consensus genome of the multi-strain population
Datasets of the manuscript "Rational design of profile HMMs for sensitive and specific sequence detection with case studies applied to viruses, bacteriophages, and casposons"
No full textDATASETS
Rational design of profile HMMs for sensitive and specific sequence detection with case studies applied to viruses, bacteriophages, and casposons
Liliane S. Oliveira, Alejandro Reyes, Bas E. Dutilh and Arthur Gruber*
* Correspondence: [email protected] (AG); Tel. +55 11 3091 7274
Here we provide different data of Microviridae, Flavivirus and casposons used throughout the work:
Microviridae folder
conserved_HMMs – profile HMMs constructed with TABAJARA in Conservation mode for Microviridae
discriminative_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for Microviridae
sequences – different sequence datasets and respective multiple sequence alignments
Microviridae_113-seq_training_set.fasta - 113 VP1 sequences covering diversity of the Microviridae family
Microviridae_113-seq.aln – multiple sequence alignment of the 113-protein dataset
Microviridae_1836-seq_testset.fasta - 1,836 sequence dataset covering 1,836 sequences of the major capsid protein (VP1) comprising 501 Alpavirinae sequences, 1,040 Gokushovirinae sequences and 295 Pichovirinae sequences
Microviridae_1866-seq.aln - multiple sequence alignment of the 1,866-protein Microviridae dataset used in the experiment of Figure 4
Flavivirus folder
conserved_HMMs – profile HMMs constructed with TABAJARA in Conservation mode for Flavivirus
discriminative_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for Flavivirus
full-length – models constructed from full-length protein sequences
short - models constructed from selected short alignment blocks of the protein sequences
sequences – different sequence datasets and respective multiple sequence alignments
Flavivirus_127-seq_training_set.fasta - 127 polyprotein sequences covering species diversity of the genus Flavivirus
Flavivirus_127-seq.aln – multiple sequence alignment of the 127-protein dataset
Flavivirus_6364-seq_testset.fasta - 6,364 sequence dataset covering species diversity of Flavivirus, including 3,919 of dengue virus (DENV), 327 of Zika virus (ZIKV), 63 of yellow fever virus (YFV), and the remaining 2,055 sequences covering other available flaviviruses
Flavivirus_6364-seq.aln - multiple sequence alignment of the 6,364-protein Flavivirus dataset
Casposons folder
casposon_generic_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for the generic detection of all casposons and discrimination from CRISPRs.
casposon_family_discriminative_HMMs – profile HMMs constructed with TABAJARA in Discrimination mode for the specific discrimination among casposon families and from CRISPRs.
sequences – different sequence datasets and respective multiple sequence alignments
casposons_crisprs.fasta – 106 Cas1 bona fide sequences derived from 52 CRISPRs and 54 casposons
casposon_family_discrimination.aln - multiple sequence alignment of 52 bona fide CRISPR and 54 casposon sequences, with appropriate nomenclature to run TABAJARA for the discrimination of each casposon family.
casposons_crisprs_discrimination.aln - multiple sequence alignment of 52 bona fide CRISPR and 54 casposon sequences, with appropriate nomenclature to run TABAJARA for discrimination of CRISPRs and casposons
Metagenomic Characterisation of the Viral Community of Lough Neagh, the Largest Freshwater Lake in Ireland.
No full textLough Neagh is the largest and the most economically important lake in Ireland. It is also one of the most nutrient rich amongst the world's major lakes. In this study, 16S rRNA analysis of total metagenomic DNA from the water column of Lough Neagh has revealed a high proportion of Cyanobacteria and low levels of Actinobacteria, Acidobacteria, Chloroflexi, and Firmicutes. The planktonic virome of Lough Neagh has been sequenced and 2,298,791 2×300 bp Illumina reads analysed. Comparison with previously characterised lakes demonstrates that the Lough Neagh viral community has the highest level of sequence diversity. Only about 15% of reads had homologs in the RefSeq database and tailed bacteriophages (Caudovirales) were identified as a major grouping. Within the Caudovirales, the Podoviridae and Siphoviridae were the two most dominant families (34.3% and 32.8% of the reads with sequence homology to the RefSeq database), while ssDNA bacteriophages constituted less than 1% of the virome. Putative cyanophages were found to be abundant. 66,450 viral contigs were assembled with the largest one being 58,805 bp; its existence, and that of another 34,467 bp contig, in the water column was confirmed. Analysis of the contigs confirmed the high abundance of cyanophages in the water column
- …
