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Review
. 2015 Jan 7:13:2.
doi: 10.1186/s12916-014-0232-0.

Microbiology of diabetic foot infections: from Louis Pasteur to 'crime scene investigation'

Anne Spichler, Bonnie L Hurwitz, David G Armstrong, Benjamin A Lipsky  1
Affiliations
Review

Microbiology of diabetic foot infections: from Louis Pasteur to 'crime scene investigation'

Anne Spichler et al. BMC Med. .

Abstract

Were he alive today, would Louis Pasteur still champion culture methods he pioneered over 150 years ago for identifying bacterial pathogens? Or, might he suggest that new molecular techniques may prove a better way forward for quickly detecting the true microbial diversity of wounds? As modern clinicians faced with treating complex patients with diabetic foot infections (DFI), should we still request venerated and familiar culture and sensitivity methods, or is it time to ask for newer molecular tests, such as 16S rRNA gene sequencing? Or, are molecular techniques as yet too experimental, non-specific and expensive for current clinical use? While molecular techniques help us to identify more microorganisms from a DFI, can they tell us 'who done it?', that is, which are the causative pathogens and which are merely colonizers? Furthermore, can molecular techniques provide clinically relevant, rapid information on the virulence of wound isolates and their antibiotic sensitivities? We herein review current knowledge on the microbiology of DFI, from standard culture methods to the current era of rapid and comprehensive 'crime scene investigation' (CSI) techniques.

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Figures

Figure 1
Figure 1
Overview of methods for community profiling and functional metagenomics. Patient tissue samples contain a mixture of human and microbial DNA. Microbial DNA is derived from a community of bacteria and other organisms present at their relative abundance in the sample, indicated here using different colors. Once DNA has been extracted from the sample, two metagenomic methods can be applied. In functional metagenomics the total DNA is sequenced and analyzed by comparing it to databases of known genomes (for example, NCBI and IMG) and 16S rRNA genes (for example, RDP, Green Genes and Silva) to identify bacterial taxa and their abundance. Sequences are also compared to known proteins (for example, SIMAP, MG-RAST, KEGG) for functional analysis of genes, pathways and relative frequency. In community profiling, hypervariable regions of the 16S rRNA gene from bacteria are amplified and sequenced. Highly similar sequences are binned by operational taxonomic units and compared to databases of 16S rRNA genes from known bacteria (for example, RDP, Green Genes and Silva) to identify bacterial taxa and their frequency. 16S rRNA gene sequences can be used in subsequent analyses of phylogenetic diversity in the sample. IMG: Integrated Microbial Genomes; KEGG: Kyoto Encyclopedia of Genes and Genomes; MG-RAST: Metagenomic Rapid Annotations using Subsystems Technology; NCBI: National Center for Biotechnology Information; OTU: Operational Taxonomic Unit; RDP: Ribosomal Database Project; SIMAP: Similarity Matrix of Proteins.
Figure 2
Figure 2
Proposed algorithm for diabetic foot or other chronic wound infection management using molecular microbiology methodology.
Figure 3
Figure 3
Example of a potential microbiology report produced using the results of 16S rRNA (NGS) data. Example of a potential microbiology report produced using the results of 16S rRNA NGS data from an actual patient specimen from the Southern Arizona Limb Salvage Alliance clinic. A) Patient and specimen information, B) Test description and overview, C) Sample preparation requirements, D) List of any resistance or virulence factors detected (note that this test does not yield these data), E) Bacterial taxonomic profile, F) Antibiotic susceptibility profile based on the bacterial taxa detected in this sample. NGS, next-generation sequencing.
Figure 4
Figure 4
Example of a potential microbiology report based on hypothetical functional metagenomic next generation sequencing (NGS) data. Example of a potential microbiology report based on hypothetical functional metagenomic NGS data from a patient specimen. A) Patient and specimen information, B) Test description and overview, C) Sample preparation requirements, D) List of any resistance or virulence factors detected, E) Bacterial taxonomic profile, F) Antibiotic susceptibility profile based on bacterial taxa detected and antibiotic resistance and virulence factors detected.
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