Anne L. McCartney, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6AP, Berkshire, UK. E-mail: firstname.lastname@example.org
Aims: Aim of the study was to investigate the faecal microbiota of geriatric cats, as aging affects the nutrient digestibility and metabolic function of the feline intestine.
Methods and Results: Twenty geriatric cats were randomly assigned to two groups that were fed different foods. Coriobacteriaceae, Clostridium cluster XIV, bifidobacteria and lactic acid bacteria were the dominant faecal bacterial groups, accounting for c. 40% of total bacteria. Clostridium cluster IX was less predominant (0·5% of total bacteria), while the remaining bacterial populations enumerated only accounted for 0·2% of total bacteria. Highly diverse microbial profiles were demonstrated for geriatric cats with denaturing gradient gel electrophoresis, although a few common bands were evident. Some differences were seen in the feline faecal microbiota between animal groups at the same time or over time for individual animals. However, no obvious clustering based on animal group or sample time was indicated.
Conclusions: Geriatric cats harboured a complex faecal microbiota and c. 41% of total bacteria have been detected with the probes employed.
Significance and Impact of the Study: First molecular-based study examining faecal microbiota of geriatric felines. Knowledge of the microbiota associated with ageing in cats may allow improved development of foods specific for the needs of senior cats.
Ageing has been reported to be associated with a number of changes in the digestive tract of companion animals. Geriatric cats have been shown to have reduced ability to digest fat and protein (Taylor et al. 1995; Perez-Camargo 2004; Laflamme 2005) and increased daily food intake (Taylor et al. 1995). This might indicate that older cats with compromised digestive function increase their daily food intake to compensate for reduced ability to digest macronutrients (Harper 1998). Limited information is currently available on the gastrointestinal (GI) microbiota of senior cats, although faecal Bifidobacterium levels were shown to be significantly lower in elderly cats compared with young and adult cats (Patil et al. 2000). Data from humans, however, have shown that significant microbiological changes are associated with ageing, with both numerical changes and species alteration of the predominant microbiota seen in the elderly population compared with the adult population (Blaut et al. 2002; Hopkins et al. 2002). Metabolic differences have also been reported in elderly people, with reduced amylolytic activity and total short-chain fatty acid levels and increased proteolytic activity (Woodmansey 2007).
Nutritional requirements are known to change with age. Feeding senior cats an optimal diet could compensate for declining functional systems of some organs during ageing, and thus improve the quality, and possibly length, of life. One recent study reported that cats eating a diet containing a nutritional blend of antioxidants, prebiotic fibre and polyunsaturated fatty acids lived significantly longer and showed significantly slower deterioration in some clinical health characteristics (e.g. haematology, serum, skin thickness and activity levels) compared with cats fed a control diet (Cupp et al. 2008). Understanding the changes in the microbiota associated with ageing in cats may afford development of foods specific for the needs of senior cats. The aim of this study was to investigate the predominant faecal microbiota of geriatric cats.
Materials and methods
Unless otherwise stated, all chemicals were supplied by Sigma-Aldrich (Gillingham, UK).
Twenty geriatric shorthair cats (8–14 years of age) were included in the study. The study protocol was reviewed and approved by the Institutional Animal Care and Use Committee. All cats were immunized against feline panleukopenia, calici and herpes viruses, and rabies and none had chronic systemic disease on the basis of results of physical examination, complete blood count determination, serum biochemical analyses, urinalysis and negative faecal examination for parasites. Cats were housed individually, had free access to water, and food was continuously available throughout the day until their daily caloric requirements were consumed. Cats experienced behavioural enrichment through interactions with each other, by daily interaction and play time with caretakers, and access to toys. Two faecal samples were collected from each cat, 3 months apart. Stools were collected following defecation (within 15 min), immediately stored in anaerobic pouches and frozen at −20°C. Ten of the animals were on diet A and ten on diet B (Table 1). In general, the two foods had similar protein, carbohydrate and fibre content, but food B contained higher fat content, DHA, vitamin E and methionine compared with food A. Total, soluble and insoluble fibre and crude fibre were analysed according to the methods described by the Association of Official Analytical Chemists (AOAC 991.43; AOAC 962.09).
Table 1. Composition of the geriatric feline foods (% dry matter unless shown otherwise)
*Diet A, Purina O.N.E. Feline Sr Protection (Purina).
†Diet B, Hill’s Experimental Food (Hill’s Pet Nutrition).
Vitamin E, IU g−1
Analysis of the faecal microbiota
Analysis of the faecal microbiota was performed using fluorescence in situ hybridization (FISH) and denaturing gradient gel electrophoresis (DGGE) as described previously (Jia et al. 2010). Briefly, cells were fixed in paraformaldehyde and stored at −20°C in phosphate-buffered saline (PBS, 1 mol l−1, pH 7·2; Oxoid, Basingstoke, UK)/ethanol (50 : 50, v/v) prior to hybridization with a range of oligonucleotide probes. The probes used in this study were Ato291 (Harmsen et al. 2000), Bif164 (Langendijk et al. 1995), CFB719 (Weller et al. 2000), Chis150 (Franks et al. 1998), Clit135 (Franks et al. 1998), DSV687 (Devereux et al. 1992), EC1531 (Poulsen et al. 1995), Erec482 (Franks et al. 1998), Lab158 (Harmsen et al. 1999) and Prop853 (Walker et al. 2005) (50 ng μl−1), specific for most members of the family Coriobacteriaceae, Bifidobacterium ssp., most members of the class Bacteroidetes, Clostridium clusters I and II, Clostridium lituseburense group, Desulfovibrionales, Escherichia coli, Clostridium cluster XIV, lactic acid bacteria and Clostridium cluster IX. The nucleic acid stain 4′, 6′-diamidino-2-phenylindole (DAPI) was used for total bacterial counts. DNA was also extracted from the faecal samples (using the QIAmp® DNA Stool Mini Kit; Qiagen, Crawley, UK) and used for universal PCR-DGGE using the primers P2 and P3 (Muyzer et al. 1993). DGGE was then performed with a 30–70% gradient of denaturant and gels were silver-stained and scanned prior to analysis of the DGGE profiles using TotalLab TL120 and TotalLab TL120DM.
FISH data. Unpaired Student’s t-test was used to determine significant differences in the bacterial counts between geriatric cats fed food A and those fed food B at the same time point. Paired Student’s t-test was used to determine significant differences in the bacterial counts within each geriatric feline group over time. Statistical significance was accepted at P <0·05.
DGGE gel analysis. Statistical differences in the number of bands in profiles within each group were analysed by Student’s t-test. Cluster analysis and calculation of similarity indices between DGGE profiles were performed with Pearson correlation coefficient and the unweighted pair group method with arithmetic mean (UPGMA) dendrogram type. spss 14.0 (SPSS Inc., Chicago, IL) was used to determine whether the similarity data were normally distributed. Student’s t-test was performed with normally distributed data; Wilcoxon’s test was performed with non-normally distributed data for the paired test and Mann–Whitney U-test for the unpaired test with non-normally distributed data. P <0·05 was considered statistically significant.
Composition of the faecal microbiota
Ato291 counts (Coriobacteriaceae) were significantly higher in the second faecal samples of all cats, compared with sample 1 (Table 2). Whilst Bif164 and Erec482 counts (Bifidobacterium species and Clostridium cluster XIV, respectively) were significantly higher in the second faecal sample of geriatric cats fed food A. Sample 2 Bif164 counts were significantly lower and Lab158 counts (lactic acid bacteria) significantly higher for group B, compared with sample 2 counts for group A.
Table 2. Investigation of the faecal microbiota of geriatric cats fed different diets using fluorescence in situ hybridization analysis
Food A (n =10)
Food B (n =10)
Data are expressed as means ± standard deviations. *Significantly (P <0·01) different to sample 1 for same animal group; **significantly (P <0·01) different to sample 2 from geriatric cats on food A; ***significantly (P <0·05) different to sample 1 for same animal group; †significantly (P <0·05) different to sample 2 from geriatric cats on food A.
9·65 ± 0·20
9·94 ± 0·21*
9·70 ± 0·22
9·97 ± 0·18*
8·76 ± 0·42
9·61 ± 0·61*
8·50 ± 0·30
8·82 ± 0·52**
6·77 ± 0·43
6·76 ± 0·55
6·82 ± 0·48
6·78 ± 0·43
7·14 ± 0·24
7·11 ± 0·53
7·32 ± 0·52
7·43 ± 0·47
7·12 ± 0·17
7·13 ± 0·47
6·91 ± 0·48
7·11 ± 0·38
10·46 ± 0·12
10·53 ± 016
10·46 ± 0·07
10·52 ± 0·23
6·29 ± 0·28
6·33 ± 0·19
6·35 ± 0·17
6·29 ± 0·22
6·40 ± 0·47
6·59 ± 0·31
6·75 ± 0·25
6·53 ± 0·25
8·90 ± 0·55
9·42 ± 0·32***
9·30 ± 0·43
9·32 ± 0·40
8·03 ± 0·67
8·39 ± 1·02
9·06 ± 0·92
9·04 ± 0·99†
7·30 ± 0·36
7·87 ± 0·94
7·78 ± 0·71
7·86 ± 0·83
Overall, bacteria detected by probes Ato291 and Erec482 were the predominant populations in this study, making up c. 21 and 7% of DAPI counts (total bacteria), respectively. The relative predominance of Bif164 and Lab158 counts varied between the two animal groups and between samples (i.e. over time), with Bif164 forming 3 and 15% of DAPI counts for cats on food A (sample 1 and 2, respectively) and 2% of DAPI counts for cats on food B (both samples); whilst Lab158 predominance was 1 and 4% for cats on food A (sample 1 and 2, respectively) and 9% for cats on food B (both samples).
Biodiversity of the faecal microbiota
On the basis of DGGE analysis, each animal seemed to have its own unique and complex microbiota, although some common bands were evident (Fig. 1). The number of bands in each sample varied from 13 to 34, with a total of 79 different bands detected across the study. Approximately 5% of the bands were common (present in more than 90% of samples), whilst c. 8% were unique bands (only seen in one sample). The bacterial diversity, determined as number of bands within a profile, was significantly lower for the second faecal sample of cats on food B (18 ± 4) compared with both sample 1 from the same animals (24 ± 5) and sample 2 from cats on food A (25 ± 6). Comparison of the profiles of each animal within each group at each sampling time demonstrated that significantly greater similarity was seen between the sample 1 profiles of group B animals, compared with sample 1 profiles of group A (74·24 ± 8·43% and 67·18 ± 11·21%, respectively). However, the similarity indices were significantly higher between sample 2 profiles of group A (70·67 ± 9·80%) than was seen for profiles from sample 1 of the same animals. No significant difference was observed between the similarity indices of sample 2 DGGE profiles from group A and group B. UPGMA algorithm analysis did not identify any obvious clustering based on animal group (i.e. food) or sample time (Fig. 2).
To date, feline GI microbial ecology studies have mainly focused on healthy adults and data on senior cats are scarce. Changes of dominant microbiota associated with ageing is also lacking in feline studies. The present data indicated that Actinobacteria (i.e. Bifidobacterium and Coriobacteriaceae) and Firmicutes (i.e. Clostridium, Eubacterium and lactic acid bacteria) were the predominant bacterial members of the faecal community seen in geriatric cats. This is consistent with the results of other feline studies within our laboratory (Jia 2009; Abecia et al. 2010). In addition, Ritchie et al. (2008) recently demonstrated that Actinobacteria and Clostridium clusters XIV and IV were predominantly isolated from colonic samples of healthy adult cats.
In combination with the previous kitten study (Jia 2009), which applied the same methodology and probes as the current study, the results have indicated that kittens and geriatric cats generally harboured c. 10·5 log10 total bacteria per gram of faeces (wet weight). Coriobacteriaceae (Ato291) was the most abundant bacterial group with relatively similar counts in kittens and geriatric cats (9·6 log10 and 9·8 log10 cells per g faeces, respectively), making up 16 and 22% of total bacteria in kittens and geriatric cats, respectively. Erec482 counts (Clostridium cluster XIV) were also similar between kittens and geriatric cats, 9·3 and 9·2 log10 cells per g faeces, respectively. In contrast, notable variation was shown in Lab158 (lactic acid bacteria) counts within each geriatric feline group at both sampling times, and thus it was not feasible to compare with those of kittens.
Age-related changes of dominant GI microbiota have been reported in a few human studies (Hopkins et al. 2002; Woodmansey et al. 2004) and reductions in numbers of bacteroides and bifidobacteria in elderly groups were accompanied by reduced species diversity compared with healthy young adults, although total anaerobe numbers remained relatively constant in old people (Woodmansey et al. 2004). Higher proportions of enterobacteria were also found in elderly people compared with adults (Mueller et al. 2006). A number of studies have also shown that the Bifidobacterium population was significantly lower in elderly animals compared with adult and/or young animals in both feline and canine studies (Benno et al. 1992; Patil et al. 2000). The Bifidobacterium counts obtained during this study, and the previous kitten study both demonstrated that this bacterial population may not be stable in cats, with significantly different counts found between multiple samples from the same animals. However, we did not observe a significant difference between the averaged Bifidobacterium levels from kittens and geriatric cats. Interestingly, however, the current data demonstrate that diet can affect faecal Bifidobacterium levels (as well as those of other groups of bacteria) of geriatric cats and thus could be employed to modulate the faecal microbiota (in this case Bifidobacterium content) of senior cats.
Age is known to affect the gut microbiota, gut morphology and immunity, and nutrient digestibility (e.g. energy, protein, carbohydrates and lipids) in companion animals, yet relatively few data are available on mineral absorption/metabolism and vitamin nutrition in dogs and cats with ageing (Fahey et al. 2008). A 7-year follow-up study with senior cats demonstrated that cats fed a diet supplemented with vitamin E, β-carotene, dried chicory root and a blend of omega-3 and omega-6 fatty acids lived c. 1 year longer with positive effects on health characteristics (e.g. body weight, skin thickness and activity levels) compared with the control group (Cupp et al. 2008). In the current study, dynamic changes were qualitatively and quantitatively shown in the faecal microbiota of senior cats over time with notable variations seen with respect to the food-induced microbial changes of the two geriatric cat groups (A and B). Food A appeared to have a greater effect on the feline faecal microbiota than food B, which differed from food A only in relation to a few components (such as fat, DHA, manganese and methionine content). Further studies are required to examine the importance of dietary modulation of the faecal microbiota of geriatric cats and the relevance of different components of these complete foods (alone or in combination) on microbiological changes. For example, investigating the correlation between significantly higher Bifidobacterium counts and food A [which had notably lower fat (% dry content), manganese (ppm) and vitamin E (IU g−1) and higher protein (% dry content) than food B]. Indeed, to fully elucidate the effects of nutrition on the feline gut microbiota and health, future studies should employ diets formulated such that the effects of individual (and/or clearly defined combinations of) components may be examined.
In summary, this study demonstrated that geriatric cats harboured a highly complex and diverse faecal microbial profile, with c. 10·5 log10 bacteria per g faeces. Coriobacteriaceae, Clostridium cluster XIV, Bifidobacterium sp. and lactic acid bacteria were the predominant bacterial groups in geriatric feline faecal samples. The current study also indicated food-related changes in the predominant faecal microbiota of geriatric cats. Understanding age-related changes in the feline GI microbiota and the associated microbial metabolic activity, together with the effect(s) of different dietary components on said microbiota, is essential to defining optimal diet(s) for geriatric cats to enhance their quality of life.
This study was supported by grants from Hill’s Pet Nutrition, Topeka, Kansas, USA, which requested publication of the work.