Study of the human microbiota in relation to human health and disease is a rapidly expanding field. To fully understand the complex relationship between the human gut microbiota and disease risks, study designs that capture the variation within and between human subjects at the population level are required, but this has been hampered by the lack of cost-effective methods to characterize this variation. Illumina sequencing is inexpensive and produces millions of reads per run, but it is unclear whether short reads can adequately represent the microbial community of a human host. In this study, we examined the utility of a profiling method, microbial nucleotide signatures (MNS), focused on low-depth sampling of the human microbiota using Ilumina short reads. This method is intended to aid in human population-based studies where large sample sizes are required to adequately capture variation in disease or phenotype differences. We found that, by calculating the nucleotide diversities along the sequenced 16S rRNA gene region, which did not require assembly or phylogenetic identification, we were able to differentiate the gut microbial nucleotide signatures of 9 healthy individuals. When we further subsampled the reads down to 40,000 reads (51 bp long) per sample, the diversity profiles were relatively unchanged. Applying MNS to a public datasets showed that it could differentiate body site differences. The scalability of our approach offers rapid classification of study participants for studies with the sample sizes required for epidemiological studies. Using MNS to classify the microbiome associated with a disease state followed by targeted in-depth sequencing will give a comprehensive understanding of the role of the microbiome in human health.