MetCap: a bioinformatics probe design pipeline for large-scale targeted metagenomics

Mycobacterium marinum cutanous infection misdiagnosed as sporotrichosis in a patient with systemic lupus erythematosus: A case report

Mycobacterium marinum(M. marinum ), a slow-growing bacterium in freshwater and seawater, can cause cutanous and extracutaneous infections. A fisher-woman with systemic lupus erythematosus (SLE) presented with chronic polymorphic rashes in a lymphangitic pattern was initially misdiagnosed as sporotrichosis. The final diagnosis of M. marinum and Candida dubliniensis co-infection was confirmed based on the skin histopathology, pustule culture, MetaCAP sequencing and effective antibiotic combination treatments.

ProbeTools: designing hybridization probes for targeted genomic sequencing of diverse and hypervariable viral taxa

BACKGROUND

Sequencing viruses in many specimens is hindered by excessive background material from hosts, microbiota, and environmental organisms. Consequently, enrichment of target genomic material is necessary for practical high-throughput viral genome sequencing. Hybridization probes are widely used for enrichment in many fields, but their application to viral sequencing faces a major obstacle: it is difficult to design panels of probe oligo sequences that broadly target many viral taxa due to their rapid evolution, extensive diversity, and genetic hypervariability. To address this challenge, we created ProbeTools, a package of bioinformatic tools for generating effective viral capture panels, and for assessing coverage of target sequences by probe panel designs in silico. In this study, we validated ProbeTools by designing a panel of 3600 probes for subtyping the hypervariable haemagglutinin (HA) and neuraminidase (NA) genome segments of avian-origin influenza A viruses (AIVs). Using in silico assessment of AIV reference sequences and in vitro capture on egg-cultured viral isolates, we demonstrated effective performance by our custom AIV panel and ProbeTools' suitability for challenging viral probe design applications.

RESULTS

Based on ProbeTool's in silico analysis, our panel provided broadly inclusive coverage of 14,772 HA and 11,967 NA reference sequences. For each reference sequence, we calculated the percentage of nucleotide positions covered by our panel in silico; 90% of HA and NA references sequences had at least 90.8 and 95.1% of their nucleotide positions covered respectively. We also observed effective in vitro capture on a representative collection of 23 egg-cultured AIVs that included isolates from wild birds, poultry, and humans and representatives from all HA and NA subtypes. Forty-two of forty-six HA and NA segments had over 98.3% of their nucleotide positions significantly enriched by our custom panel. These in vitro results were further used to validate ProbeTools' in silico coverage assessment algorithm; 89.2% of in silico predictions were concordant with in vitro results.

CONCLUSIONS

ProbeTools generated an effective panel for subtyping AIVs that can be deployed for genomic surveillance, outbreak prevention, and pandemic preparedness. Effective probe design against hypervariable AIV targets also validated ProbeTools' design and coverage assessment algorithms, demonstrating their suitability for other challenging viral capture applications.

Syotti: scalable bait design for DNA enrichment

MOTIVATION

Bait enrichment is a protocol that is becoming increasingly ubiquitous as it has been shown to successfully amplify regions of interest in metagenomic samples. In this method, a set of synthetic probes ('baits') are designed, manufactured and applied to fragmented metagenomic DNA. The probes bind to the fragmented DNA and any unbound DNA is rinsed away, leaving the bound fragments to be amplified for sequencing. Metsky et al. demonstrated that bait-enrichment is capable of detecting a large number of human viral pathogens within metagenomic samples.

RESULTS

We formalize the problem of designing baits by defining the Minimum Bait Cover problem, show that the problem is NP-hard even under very restrictive assumptions, and design an efficient heuristic that takes advantage of succinct data structures. We refer to our method as Syotti. The running time of Syotti shows linear scaling in practice, running at least an order of magnitude faster than state-of-the-art methods, including the method of Metsky et al. At the same time, our method produces bait sets that are smaller than the ones produced by the competing methods, while also leaving fewer positions uncovered. Lastly, we show that Syotti requires only 25 min to design baits for a dataset comprised of 3 billion nucleotides from 1000 related bacterial substrains, whereas the method of Metsky et al. shows clearly super-linear running time and fails to process even a subset of 17% of the data in 72 h.

AVAILABILITY AND IMPLEMENTATION

https://github.com/jnalanko/syotti.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Methanogenic archaea in peatlands

Methane emission feedbacks in wetlands are predicted to influence global climate under climate change and other anthropogenic stressors. Herein, we review the taxonomy and physiological ecology of the microorganisms responsible for methane production in peatlands. Common in peat soils are five of the eight described orders of methanogens spanning three phyla (Euryarchaeota, Halobacterota and Thermoplasmatota). The phylogenetic affiliation of sequences found in peat suggest that members of the thus-far-uncultivated group Candidatus Bathyarchaeota (representing a fourth phylum) may be involved in methane cycling, either anaerobic oxidation of methane and/or methanogenesis, as at least a few organisms within this group contain the essential gene, mcrA, according to metagenomic data. Methanogens in peatlands are notoriously challenging to enrich and isolate; thus, much remains unknown about their physiology and how methanogen communities will respond to environmental changes. Consistent patterns of changes in methanogen communities have been reported across studies in permafrost peatland thaw where the resulting degraded feature is thermokarst. However much remains to be understood regarding methanogen community feedbacks to altered hydrology and warming in other contexts, enhanced atmospheric pollution (N, S and metals) loading and direct anthropogenic disturbances to peatlands like drainage, horticultural peat extraction, forestry and agriculture, as well as post-disturbance reclamation.

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

High-throughput DNA sequencing techniques enable time- and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.

The microbiome in respiratory medicine: current challenges and future perspectives

The healthy lung has previously been considered to be a sterile organ because standard microbiological culture techniques consistently yield negative results. However, culture-independent techniques report that large numbers of microorganisms coexist in the lung. There are many unknown aspects in the field, but available reports show that the lower respiratory tract microbiota: 1) is similar in healthy subjects to the oropharyngeal microbiota and dominated by members of the Firmicutes, Bacteroidetes and Proteobacteria phyla; 2) shows changes in smokers and well-defined differences in chronic respiratory diseases, although the temporal and spatial kinetics of these changes are only partially known; and 3) shows relatively abundant non-cultivable bacteria in chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, cystic fibrosis and bronchiectasis, with specific patterns for each disease. In all of these diseases, a loss of diversity, paralleled by an over-representation of Proteobacteria (dysbiosis), has been related to disease severity and exacerbations. However, it is unknown whether dysbiosis is a cause or a consequence of the damage to bronchoalveolar surfaces.Finally, little is known about bacterial functionality and the interactions between viruses, fungi and bacteria. It is expected that future research in bacterial gene expressions, metagenomics longitudinal analysis and host-microbiome animal models will help to move towards targeted microbiome interventions in respiratory diseases.

Design and evaluation of primers targeting genes encoding NO-forming nitrite reductases: implications for ecological inference of denitrifying communities

The detection of NO-forming nitrite reductase genes (nir) has become the standard when studying denitrifying communities in the environment, despite well-known amplification biases in available primers. We review the performance of 35 published and 121 newly designed primers targeting the nirS and nirK genes, against sequences from complete genomes and 47 metagenomes from three major habitats where denitrification is important. There were no optimal universal primer pairs for either gene, although published primers targeting nirS displayed up to 75% coverage. The alternative is clade-specific primers, which show a trade-off between coverage and specificity. The test against metagenomic datasets showed a distinct performance of primers across habitats. The implications of clade-specific nir primers choice and their performance for ecological inference when used for quantitative estimates and in sequenced-based community ecology studies are discussed and our phylogenomic primer evaluation can be used as a reference along with their environmental specificity as a guide for primer selection. Based on our results, we also propose a general framework for primer evaluation that emphasizes the testing of coverage and phylogenetic range using full-length sequences from complete genomes, as well as accounting for environmental range using metagenomes. This framework serves as a guideline to simplify primer performance comparisons while explicitly addressing the limitations and biases of the primers evaluated.

Captured metagenomics: large-scale targeting of genes based on 'sequence capture' reveals functional diversity in soils

Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances.