Table 1 Metagenomic methods: community profiling versus functional metagenomics

DNA obtained directly from a wound sample; culture independent

Marker genes such as 16S rRNA gene from a community of bacteria, or 18S rRNA and internal transcribed spacer (ITS) genes for fungi

Can provide genomic DNA from a community of microorganisms. Applicable to all microorganisms including bacteria, fungi, viruses and archaea

Need to remove human host DNA contamination

PCR primers amplify only marker gene fragments from targeted microbes, excluding DNA from the human host

To avoid biases human DNA must be removed after sequencing through computational methods

Sequenced using high-throughput sequencing technologies

Sequencing errors in highly conserved marker genes can lead to incorrect species assignment

Taxonomic assignment based on multiple genes from genomic DNA can lead to more accurate taxonomic community profiles

Reduction in the overall cost of sequencing

Sequencing is directed at only microbial marker genes, making sequencing more cost effective

Sequencing can be more cost-prohibitive due to human host contamination (approximately 90% of DNA in wound samples)

Data represent a community of microorganisms and reflect organismal diversity and abundance

Community profile is based only on taxonomy

Community profile is based on taxonomy and function, indicating the metabolic potential of a microbial community

Less than 1% of organisms are known, leading to incomplete annotation

Closely-related organisms are indistinguishable based on marker gene sequences alone. Not all bacteria are represented in databases of known 16S rRNA genes or 18S and internal transcribed spacer (ITS) for fungi

Not all microbial genomes exist in databases of known species leading to difficulty in assigning sequences to discrete organisms

Has potential for serendipitous discovery of clinically relevant organisms or function

Novel variations in the hypervariable regions of marker genes can indicate new species

Genomes of unknown organisms can be reconstructed from genomic fragments in metagenomes, providing insights into new species and function

Has potential to find human-microbe interactions

Can find links between microbial community composition and clinical factors or patient outcomes

Can find links between microbial community composition and function and clinical factors or patient outcomes