Diabetic foot ulcer (DFU) is a major complication of diabetes with high morbidity and mortality rates. The pathogenesis of DFUs is governed by a complex milieu of environmental and host factors. The empirical treatment is initially based on wound severity since culturing and profiling the antibiotic sensitivity of wound-associated microbes is time-consuming. Hence, a thorough and rapid analysis of the microbial landscape is a major requirement toward devising evidence-based interventions. Toward this, 122 wound (100 diabetic and 22 nondiabetic) samples were sampled for their bacterial community structure using both culture-based and next-generation 16S rRNA-based metagenomics approach. Both the approaches showed that the Gram-negative microbes were more abundant in the wound microbiome. The core microbiome consisted of bacterial genera, including Alcaligenes, Pseudomonas, Burkholderia, and Corynebacterium in decreasing order of average relative abundance. Despite the heterogenous nature and extensive sharing of microbes, an inherent community structure was apparent, as revealed by a cluster analysis based on Euclidean distances. Facultative anaerobes (26.5%) were predominant in Wagner grade 5, while strict anaerobes were abundant in Wagner grade 1 (26%). A nonmetric dimensional scaling analysis could not clearly discriminate samples based on HbA1c levels. Sequencing approach revealed the presence of major culturable species even in samples with no bacterial growth in culture-based approach. Our study indicates that (i) the composition of core microbial community varies with wound severity, (ii) polymicrobial species distribution is individual specific, and (iii) antibiotic susceptibility varies with individuals. Our study suggests the need to evolve better-personalized care for better wound management therapies. IMPORTANCE Chronic nonhealing diabetic foot ulcers (DFUs) are a serious complication of diabetes and are further exacerbated by bacterial colonization. The microbial burden in the wound of each individual displays diverse morphological and physiological characteristics with unique patterns of host-pathogen interactions, antibiotic resistance, and virulence. Treatment involves empirical decisions until definitive results on the causative wound pathogens and their antibiotic susceptibility profiles are available. Hence, there is a need for rapid and accurate detection of these polymicrobial communities for effective wound management. Deciphering microbial communities will aid clinicians to tailor their treatment specifically to the microbes prevalent in the DFU at the time of assessment. This may reduce DFUs associated morbidity and mortality while impeding the rise of multidrug-resistant microbes.

Ayurveda has a rich history and its significance woven deeply in the Indian culture. The concept of prakriti (a person’s “nature” or constitutional type determined by the proportion of three doshas, namely - vata , pitta and kapha ) in Ayurveda is deeply rooted in personalized health management. While the attributes of prakriti has been established to have a genomic basis, there is dearth of elaborate evidences linking prakriti with manifestation of diseases. Next generation sequencing studies have provided a causal link between variation in the gut microbiome and its effect on an individual’s fitness. Separately, reports have identified gut microbial patterns associated with several host variables such as geography, age, diet and extreme prakriti phenotypes. Recently, few reports have identified a “core gut microbiome” consisting of Bacteroides, Faecalibacterium, Prevotella and Ruminococcus prevalent across the Indian population; however, a few bacterial genera were specifically enriched in certain prakritis . Hence, in this review we aim to analyse the role of prakriti variations on dysbiosis of the gut microbiome and concomitantly its effect on human health. We suggest that prakriti phenotyping can function as a potential stratifier of the gut microbiome in a given population and may provide evidence for the conceptual framework of personalized medicine in Ayurvedic system of medicine.

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