Experimental validation of in silico predicted RAD locus frequencies using genomic resources and short read data from a model marine mammal

Genetic variability of the 16S rRNA gene of Nocardia brasiliensis, the most common causative agent of actinomycetoma in Latin America and the Caribbean

Mycetoma is a neglected tropical disease (NTD) declared by the World Health Organization (WHO) in 2016. It is characterized by the progressive growth of nodules and granulomatous lesions on the legs, arms, and trunk. It is potentially disfiguring and causes disability or amputations in working-age people from marginalized areas. The causative agents can be fungi (eumycetoma) or actinobacteria (actinomycetoma), the latter being the most common in America and Asia. Nocardia brasiliensis is the most important causal agent of actinomycetoma in the Americas. Taxonomic problems have been reported when identifying this species, so this study aimed to detect the 16S rRNA gene variations in N. brasiliensis strains using an in silico enzymatic restriction technique. The study included strains from clinical cases of actinomycetoma in Mexico, isolated from humans and previously identified as N. brasiliensis by traditional methods. The strains were characterized microscopically and macroscopically, then subjected to DNA extraction and amplification of the 16S rRNA gene by PCR. The amplification products were sequenced, and consensus sequences were constructed and used for genetic identification and in silico restriction enzyme analysis with the New England BioLabs® NEBcutter program. All study strains were molecularly identified as N. brasiliensis; however, in silico restriction analysis detected a diversity in the restriction patterns that were finally grouped and subclassified into 7 ribotypes. This finding confirms the existence of subgroups within N. brasiliensis. The results support the need to consider N. brasiliensis as a complex species.

Reduced metagenome sequencing for strain-resolution taxonomic profiles

BACKGROUND

Studies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction-associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or not explore the full potential of RMS data.

RESULTS

We suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock community datasets show the potential to clearly separate strains even when the 16S is 100% identical, and genome-wide differences is < 0.02, indicating RMS has a very high resolution. From a simulation study, we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real dataset of infant guts, we show that RMS is capable of detecting a strain diversity gradient for Escherichia coli across time.

CONCLUSION

We find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain level. Like shotgun metagenomics, it requires a good database of reference genomes and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS . Video abstract.