Alterations in intestinal microbiota composition are associated with several chronic conditions, including obesity and inflammatory diseases. The microbiota of older people displays greater inter-individual variation than that of younger adults. Here we show that the faecal microbiota composition from 178 elderly subjects formed groups, correlating with residence location in the community, day-hospital, rehabilitation or in long-term residential care. However, clustering of subjects by diet separated them by the same residence location and microbiota groupings. The separation of microbiota composition significantly correlated with measures of frailty, co-morbidity, nutritional status, markers of inflammation and with metabolites in faecal water. The individual microbiota of people in long-stay care was significantly less diverse than that of community dwellers. Loss of community-associated microbiota correlated with increased frailty. Collectively, the data support a relationship between diet, microbiota and health status, and indicate a role for diet-driven microbiota alterations in varying rates of health decline upon ageing.

Alterations in the human intestinal microbiota are linked to conditions including inflammatory bowel disease, irritable bowel syndrome, and obesity. The microbiota also undergoes substantial changes at the extremes of life, in infants and older people, the ramifications of which are still being explored. We applied pyrosequencing of over 40,000 16S rRNA gene V4 region amplicons per subject to characterize the fecal microbiota in 161 subjects aged 65 y and older and 9 younger control subjects. The microbiota of each individual subject constituted a unique profile that was separable from all others. In 68% of the individuals, the microbiota was dominated by phylum Bacteroides, with an average proportion of 57% across all 161 baseline samples. Phylum Firmicutes had an average proportion of 40%. The proportions of some phyla and genera associated with disease or health also varied dramatically, including Proteobacteria, Actinobacteria, and Faecalibacteria. The core microbiota of elderly subjects was distinct from that previously established for younger adults, with a greater proportion of Bacteroides spp. and distinct abundance patterns of Clostridium groups. Analyses of 26 fecal microbiota datasets from 3-month follow-up samples indicated that in 85% of the subjects, the microbiota composition was more like the corresponding time-0 sample than any other dataset. We conclude that the fecal microbiota of the elderly shows temporal stability over limited time in the majority of subjects but is characterized by unusual phylum proportions and extreme variability.

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Here, we review what is known about the microorganisms present in raw milk, including milk from cows, sheep, goats and humans. Milk, due to its high nutritional content, can support a rich microbiota. These microorganisms enter milk from a variety of sources and, once in milk, can play a number of roles, such as facilitating dairy fermentations (e.g. Lactococcus, Lactobacillus, Streptococcus, Propionibacterium and fungal populations), causing spoilage (e.g. Pseudomonas, Clostridium, Bacillus and other spore-forming or thermoduric microorganisms), promoting health (e.g. lactobacilli and bifidobacteria) or causing disease (e.g. Listeria, Salmonella, Escherichia coli, Campylobacter and mycotoxin-producing fungi). There is also concern that the presence of antibiotic residues in milk leads to the development of resistance, particularly among pathogenic bacteria. Here, we comprehensively review these topics, while comparing the approaches, both culture-dependent and culture-independent, which can be taken to investigate the microbial composition of milk.

High-throughput molecular technologies can profile microbial communities at high resolution even in complex environments like the intestinal microbiota. Recent improvements in next-generation sequencing technologies allow for even finer resolution. We compared phylogenetic profiling of both longer (454 Titanium) sequence reads with shorter, but more numerous, paired-end reads (Illumina). For both approaches, we targeted six tandem combinations of 16S rRNA gene variable regions, in microbial DNA extracted from a human faecal sample, in order to investigate their limitations and potentials. In silico evaluations predicted that the V3/V4 and V4/V5 regions would provide the highest classification accuracies for both technologies. However, experimental sequencing of the V3/V4 region revealed significant amplification bias compared to the other regions, emphasising the necessity for experimental validation of primer pairs. The latest developments of 454 and Illumina technologies offered higher resolution compared to their previous versions, and showed relative consistency with each other. However, the majority of the Illumina reads could not be classified down to genus level due to their shorter length and higher error rates beyond 60 nt. Nonetheless, with improved quality and longer reads, the far greater coverage of Illumina promises unparalleled insights into highly diverse and complex environments such as the human gut.