Literature DB >> 27008566

Vertebrate bacterial gut diversity: size also matters.

Jean-Jacques Godon1, Pugazhendi Arulazhagan2,3, Jean-Philippe Steyer2, Jérôme Hamelin2.   

Abstract

BACKGROUND: One of the central issues in microbial ecology is to understand the parameters that drive diversity. Among these parameters, size has often been considered to be the main driver in many different ecosystems. Surprisingly, the influence of size on gut microbial diversity has not yet been investigated, and so far in studies reported in the literature only the influences of age, diet, phylogeny and digestive tract structures have been considered. This study explicitly challenges the underexplored relationship connecting gut volume and bacterial diversity.
RESULTS: The bacterial diversity of 189 faeces produced by 71 vertebrate species covering a body mass range of 5.6 log. The animals comprised mammals, birds and reptiles. The diversity was evaluated based on the Simpson Diversity Index extracted from 16S rDNA gene fingerprinting patterns. Diversity presented an increase along with animal body mass following a power law with a slope z of 0.338 ± 0.027, whatever the age, phylogeny, diet or digestive tract structure.
CONCLUSIONS: The results presented here suggest that gut volume cannot be neglected as a major driver of gut microbial diversity. The characteristics of the gut microbiota follow general principles of biogeography that arise in many ecological systems.

Entities:  

Keywords:  Biodiversity; Biogeography; Fingerprint; Gut; Species-area relationship

Mesh:

Year:  2016        PMID: 27008566      PMCID: PMC4804487          DOI: 10.1186/s12898-016-0071-2

Source DB:  PubMed          Journal:  BMC Ecol        ISSN: 1472-6785            Impact factor:   2.964


Background

Among a number of parameters, the ‘size’ of an ecosystem is often assumed to have a key impact on the management of diversity. In fact, the species-area relationship is central to the ecological theory [1] and was first described for macro-organisms [2]. For bacteria, the species-area relationship is generally expressed in terms of habitat volume (i.e., volume-area relationship) and has been illustrated in liquid sump tanks of metal-cutting machines [3], membrane bioreactors [4] and tree holes (i.e., rainwater accumulated in holes at the base of large trees) [5]. However, until present, the microbial species-volume relationship has never yet been studied for gut or body size, even though vertebrate gut size covers a wide range of magnitudes. There is a 106 body mass factor between a tiny bird or a shrew and an elephant. The vertebrate gut hosts a microbial community that fulfils many vital functions for the host: it enhances resistance to infection, stimulates mucosal immune defences, synthesizes essential vitamins and promotes caloric uptake by hydrolysing complex carbohydrates. The bacterial populations inhabiting the gut are complex, varying considerably from individual to individual and from species to species. However, gut microbial ecosystems are not a random association of microbes but are shaped by the host. A transfer occurs vertically from mothers to offspring or horizontally between individuals within a specific group. Such transfers have given rise to the long-standing co-evolution of microbiota and their hosts [6]. The benefit of bacterial diversity in the human gut has often been highlighted [7] and driving factors such as age [8], diverse lifestyles [9] and diet variations [10] have already been explored. Despite such an interest, the relationship between body mass and gut microbiota has never been explored whereas, in contrast, the positive links between the abundance of parasitic organisms or protozoal faunas and animal body size have been thoroughly referenced [11] [12]. The aim of the present study is to analyse a large bacterial dataset, comprising faeces collected from 71 different vertebrate species, in order to examine the effect of the volume-microbial diversity relationship in animal digestive tracts.

Methods

Sampling

All the animal samples were obtained from domesticated or captive populations in France (zoo, farm, aquarium, recreative farm or individual keeper). There is non-experimental research dedicated for this study, faeces samples were collected on ground with the animal keeper or animal owner without stresses for the animals. We obtained permissions from Lunaret zoo, Montpellier; Océanopolis, Brest; Réserve Africaine, Sigean; Mini Ferme Zoo, Cessenon sur Orb and consent from the animal owners (Jean-Philippe Steyer, Anais Bonnafous, Jean-Jacques Godon). Animal were living alone or in small groups (1 to 5). Furthermore, their food (meat, seeds, fruits or hay) were more standardized in comparison to wild diets. Human stool specimens used in the present study were from infant and adult subjects included in international multicentric studies. Samples were collected between 2001 to 2005 and used on previous published studies. Infants samples were collected in the frame of the European project INFABIO (http://www.gla.ac.uk/departments/infabio/), ethical permission was obtained from Yorkhill Research Ethics Committee P16/03 and parents gave written informed consent [13]. Adults samples were collected in the frame of the European project Crownalife, the studies were approved by the Ethics Committee of Versailles Hospital Centre and written informed consent was obtained from all participants [14]. Approval for Institut National de la Recherche Agronomique to manage human-derived biological samples in accordance with Articles L.1243-3, R.1243-49 of “Code de la Santé Publique” was granted by the Ministry of Research and Education under number DC-2012-1728. Faeces from 189 individuals belonging to 71 vertebrate species (31 mammals, 37 birds and 3 reptiles) were collected (Table 1). They were sub-divided into 80 categories according to species or to body mass (i.e., age (young–adult), sex (female–male), breed size (small–big–domesticated–wild), see Table 1). Body masses were provided by the breeder for large animals or obtained from literature for small animals. Body masses, along with diversity, were displayed with a logarithmic scale in order to highlight the linear shape of the power-law relationship. Except for the distinct dimorphism of male and female turkey samples, an average value of male and female body mass values was used. Dwarf or young individuals from the same species were also classified in specific body mass categories. For example, human samples were divided into two body mass categories: babies between 1 and 10 months old (mean of 5.8 kg) and adults between 29 and 61 years old (set at 70 kg). Composite faeces samples were avoided except for those that could not provide enough material for DNA extraction (less than 0.5 g).
Table 1

Animal data ranked by body mass

Name (common name)PhylogenyBody mass (kg)Feeding typeType of digestive tractSize of animal husbandry groupDiversitySDNumber of samples
Taeniopygia guttata (zebra finch)Aves, Passeriformes0.012GranivorousHindgut colonLarge1.20.13
Serinus canaria (canary)Aves, Passeriformes0.024GranivorousHindgut colonLarge1.60.52
Ramphocelus bresilius (brazilian tanager)Aves, Passeriformes0.035FrugivorousHindgut colonSmall3.40.44
Melopsittacus undulatus (budgerigar)Aves, Psittaciformes0.04GranivorousHindgut colonLarge1.93.03
Ploceus cucullatus (village weaver)Aves, Passeriformes0.04GranivorousHindgut colonSmall2.30.02
Agapornis fischeri (Fischer’s lovebird)Aves, Psittaciformes0.05GranivorousHindgut colonLarge1.51
Agapornis roseicollis (rosy-faced lovebird)Aves, Psittaciformes0.05GranivorousHindgut colonLarge2.10.02
Amblyramphus holosericeus (scarlet-headed blackbird)Aves, Passeriformes0.08CarnivorousHindgut colonSmall3.40.22
Nymphicus hollandicus (cockatiel)Aves, Psittaciformes0.08GranivorousHindgut colonSmall1.40.32
Guira guira (guira cuckoo)Aves, Cuculiformes0.14CarnivorousHindgut colonSmall2.90.54
Poicephalus senegalus (senegal parrot)Aves, Psittaciformes0.14GranivorousHindgut colonSmall2.61
Streptopelia decaocto (eurasian collard dove)Aves, Columbidae0.19GranivorousHindgut colonLarge2.40.53
Corvus monedula (eurasian jackdaw)Aves, Passeriformes0.22OmnivorousHindgut colonSmall1.81
Psarocolius decumanus (crested oropendola)Aves, Passeriformes0.3OmnivorousHindgut colonSmall3.80.33
Columba livia (pigeon)Aves, Columbidae0.3GranivorousHindgut colonLarge1.91
Gallus gallus (dwarf chicken)a Aves, Galliformes0.3GranivorousHindgut caecumLarge2.10.52
Tauraco erythrolophus (red-crested turaco)Aves, Cuculiformes0.35FrugivorousHindgut colonSmall3.81
Agamia agami (agami heron)Aves, Ciconiiformes0.46PiscivorousHindgut colonSmall3.61
Coracopsis vasa (vasa parrot)Aves, Psittaciformes0.5FrugivorousHindgut colonSmall2.41
Chinchilla laniger xChinchilla brevicaudata (chinchilla)Mammalia, Rodentia0.6HerbivorousHindgut caecumSmall4.20.12
Ramphastos tucanus (white-throated toucan)Aves, Piciformes0.675FrugivorousHindgut colonSmall3.60.43
Chrysolophus pictus (golden pheasant)Aves, Galliformes0.700GranivorousHindgut caecumSmall3.41
Cavia porcellus (domestic guinea pig)Mammalia, Rodentia0.8HerbivorousHindgut caecumLarge5.00.23
Anas acuta (northern pintail)Aves, Anatidae0.9GranivorousHindgut caecumSmall3.61
Elaphe guttata (corn snake)Sauropsida, Serpentes0.9CarnivorousHindgut colonSmall4.11
Lampropeltis getula (common kingsnake) Sauropsida, Serpentes1CarnivorousHindgut colonSmall3.31
Ara ararauna (blue-and-yellow macaw)Aves, Psittaciformes1GranivorousHindgut colonSmall2.80.12
Anas platyrhynchos (wild type duck)a Aves, Anatidae1.1GranivorousHindgut caecumLarge3.11
Neochen jubata (orinoco goose)Aves, Anatidae1.25GranivorousHindgut caecumSmall3.51
Gallus gallus (chicken)a Aves, Galliformes1.5GranivorousHindgut caecumLarge1.70.56
Numida meleagris (guinea-fowl)Aves, Galliformes2GranivorousHindgut caecumLarge3.00.73
Branta sandvicensis (nene)Aves, Anatidae2GranivorousHindgut caecumSmall2.61
Oryctolagus cuniculus (domestic rabbit)Mammalia, Lagomorpha2.2HerbivorousHindgut caecumLarge4.50.73
Anas platyrhynchos (domestic duck)a Aves, Anatidae2.3GranivorousHindgut colonSmall2.31.43
Eudyptes chrysocome (western rockhopper penguin)Aves, Sphenisciformes2.6PiscivorousHindgut colonLarge1.60.63
Testudo hermanni boettgeri (Hermann’s tortoise)Sauropsida, Testudines3HerbivorousHindgut colonLarge5.61
Meleagris gallopavo (turkey female)a Aves, Galliformes3GranivorousHindgut caecumSmall2.21
Thylogale sp. (pademelon)Mammalia, Marsupials3.5HerbivorousHindgut colonSmall4.31
Cairina moschata (muscovy duck)Aves, Anatidae4GranivorousHindgut colonLarge3.32
Chauna torquata (southern screamer) Aves, Anseriformes4HerbivorousHindgut caecumSmall3.41
Canis lupus familiaris (puppy)a Mammalia, Carnivora4CarnivorousHindgut colonSmall2.61
Pavo cristatus (blue peafowl)Aves, Galliformes5GranivorousHindgut caecumSmall3.70.12
Anser anser domesticus (domestic goose)Aves, Anatidae5GranivorousHindgut caecumSmall3.50.12
Homo sapiens (baby human caucasian)a Mammalia, Primates6OmnivorousHindgut colonSmall3.20.715
Meleagris gallopavo (turkey male)a Aves, Galliformes8GranivorousHindgut caecumSmall3.81
Wallabia bicolor (black wallaby)Mammalia, Marsupials9HerbivorousHindgut colonSmall4.81
Hylobates lar (gibbon)Mammalia, Primates10FrugivorousHindgut colonSmall5.51
Aptenodytes patagonicus (king penguin)Aves, Sphenisciformes13PiscivorousHindgut colonSmall2.81.14
Capra hircus (dwarf goat)Mammalia, Ruminantia15HerbivorousRuminants foregutSmall5.21.12
Canis lupus familiaris (medium size dog)a Mammalia, Carnivora20CarnivorousHindgut colonSmall3.21.12
Ovis aries (dwarf sheep)a Mammalia, Ruminantia20HerbivorousRuminants foregutSmall5.70.72
Hippotragus equinus (roan antelope)Mammalia, Ruminantia20HerbivorousRuminants foregutSmall5.71
Tragelaphus streps (greater kudu)Mammalia, Ruminantia20HerbivorousRuminants foregutSmall5.51
Hystrix cristata (crested porcupine)Mammalia, Rodentia25HerbivorousHindgut caecumSmall5.71
Rhea americana (greater rhea)Aves, Rheiformes31GranivorousHindgut caecumLarge4.00.54
Ovis aries (sheep)a Mammalia, Ruminantia40HerbivorousRuminants foregutSmall5.01
Canis lupus familiaris (big size dog)a Mammalia, Carnivora40CarnivorousHindgut colonSmall3.11
Pan troglodytes (chimpanzee)Mammalia, Primates40OmnivorousHindgut colonSmall5.31
Dromaius novaehollandiae (emu)Aves, Casuariiformes40GranivorousHindgut colonSmall3.91
Capra hircus (goat)Mammalia, Ruminantia50HerbivorousRuminants foregutSmall7.01
Sus scrofa (dwarf pig)a Mammalia, Suina55OmnivorousHindgut colonSmall5.40.42
Lama glama (llama)Mammalia, Tylopoda55HerbivorousRuminants foregutSmall5.41
Homo sapiens (adult human caucasian)a Mammalia, Primates70OmnivorousHindgut colonLarge4.40.834
Sus scrofa (pig)a Mammalia, Suina100OmnivorousHindgut colonSmall5.81.14
Tragelaphus spekei (sitatunga)Mammalia, Ruminantia100HerbivorousRuminants foregutSmall7.51
Struthio camelus (ostrich)Aves, Struthioniformes120HerbivorousHindgut colonSmall4.40.23
Equus asinus (donkey)Mammalia, Equidae150HerbivorousHindgut caecumSmall5.30.42
Ammotragus lervia (aoudad)Mammalia, Ruminantia150HerbivorousRuminants foregutSmall6.11
Equus caballus (pony)Mammalia, Equidae160HerbivorousHindgut caecumSmall5.60.12
Panthera leo (african lion)Mammalia, Carnivora160CarnivorousHindgut colonSmall4.41
Equus zebra hartmannae (mountain zebra)Mammalia, Equidae350HerbivorousHindgut caecumSmall5.41
Syncerus caffer nanus (forest buffalo)Mammalia, Ruminantia450HerbivorousRuminants foregutSmall2.91
Camelus dromedarius (arabian Camel)Mammalia, Tylopoda500HerbivorousRuminants foregutSmall3.21
Bos grunniens (yak)Mammalia, Ruminantia600HerbivorousRuminants foregutSmall5.31
Tragelaphus oryx (eland antelope)Mammalia, Ruminantia600HerbivorousRuminants foregutSmall6.21
Bos taurus (cow)Mammalia, Ruminantia750HerbivorousRuminants foregutLarge6.20.74
Giraffa camelopardalis reticulata (somali giraffe)Mammalia, Ruminantia1100HerbivorousRuminants foregutSmall6.41
Giraffa camelopardalis peralta (nigerian giraffe)Mammalia, Ruminantia1100HerbivorousRuminants foregutSmall6.61
Ceratotherium simum (white rhinoceros)Mammalia, Rhinocerotidae2500HerbivorousHindgut colonSmall5.61
Elephas maximus (asian elephant)Mammalia, Proboscidea3500HerbivorousHindgut colonSmall4.91

SD standard deviation

a species with different sizes (young-adult, female-male, small-big or domesticated-wild)

Animal data ranked by body mass SD standard deviation a species with different sizes (young-adult, female-male, small-big or domesticated-wild)

DNA extraction, PCR amplification and Capillary Electrophoresis Single Strand Conformation Polymorphism (CE-SSCP) fingerprinting

Genomic DNAs were extracted from 0.5 g of raw material using the procedure described by Godon et al. [15]. The V3 region of the 16S rRNA gene was amplified with Bacteria-specific primers and PCR products were analysed by CE-SSCP analysis using an ABI3130 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA) in accordance with a previously described method [16]. All raw CE-SSCP data are available on Additional file 4.

Calculation of diversity and statistical computing

Diversity was estimated by the Simpson Diversity Index from CE-SSCP fingerprinting patterns. The Simpson Diversity Index was expressed as where is the relative abundance of each CE-SSCP peak p. This index was directly calculated from each CE-SSCP fingerprint [17] using the R StatFingerprints library [18]. Preference was given to the Simpson Diversity Index from CE-SSCP fingerprinting rather than the Richness estimation because: (1) neither fingerprinting nor sequencing data can provide a robust estimation of richness [19]; (2) the Simpson Diversity Index can be estimated accurately with CE-SSCP fingerprinting [17, 20]. A generalized linear model was applied to fit the relationship between body mass and diversity. ANOVA followed by Tukey post hoc tests were used for determining the statistical difference between (sub-) categories and body mass or diversity, both expressed in a logarithmic scale. All statistics were performed under R software (version 3.1.2) [21]. The calculation of the slope z was based on the exponent of the power-law relationship as follows: diversity = c weight

Results and discussion

The bacterial diversity of faeces from 189 vertebrates belonging to 71 species (31 mammals, 37 birds and 3 reptiles) was analysed (Table 1; Fig. 1). Analysis was only focused on diversity (Simpson Diversity Index), which can be accurately measured according to CE-SSCP fingerprinting patterns [15] (see the “Methods” section and Additional file 1). Apart from their phylogenetic position, animals can also be classified according to: (1) their diet (herbivorous, granivorous, omnivorous, carnivorous, piscivorous and frugivorous); (2) their metabolic body mass (from 12 g (zebra finch) to 3500 kg (Asian elephant)); (3) the structure of their digestive tracts; (4) and the size of the animal husbandry group (small and large). The present study focused on bacterial diversity, although changes within the structure of the bacterial communities were not taken into account. This study is also based on two assumptions: (1) the gut size should be proportional to the animal body mass, as has been demonstrated for herbivores [22] and birds [23]; and (2) the microbial diversity of faeces should be similar to that in the gut [24].
Fig. 1

Relationship between the animal body mass and the Simpson Diversity Index for gut microbiota. Diamonds, circles and triangles correspond to birds, mammals and reptiles, respectively. Small, medium and large sizes correspond to 1, 2–5, >10 individuals, respectively. Green, brown, grey, red, blue and yellow colors correspond to herbivorous, granivorous, omnivorous, carnivorous, piscivorous and frugivorous diets, respectively. Bold fonts make reference to the animals mentioned in the text

Relationship between the animal body mass and the Simpson Diversity Index for gut microbiota. Diamonds, circles and triangles correspond to birds, mammals and reptiles, respectively. Small, medium and large sizes correspond to 1, 2–5, >10 individuals, respectively. Green, brown, grey, red, blue and yellow colors correspond to herbivorous, granivorous, omnivorous, carnivorous, piscivorous and frugivorous diets, respectively. Bold fonts make reference to the animals mentioned in the text Results point to a correlation between animal body mass and microbial diversity (linear regression with a slope z of 0.338 ± 0.027; p value <2.2 × 10−16), irrespective of the diet, phylogeny or structure of the digestive tracts (Fig. 1). Consequently, the use of a greater amount of samples over a wider size range confirms previous works on unrelated bacterial communities that have suggested the existence of a link between volume and diversity in tree holes [5], membrane bioreactors [4] and metal-cutting fluid sump tanks [3]. In the present results, the Simpson Diversity Index ranges between 3.3 and 1789.5, thus corresponding to a 5.6 log body mass range (Fig. 1). A wide variability in the diversity between individuals for a given species was observed. However the average diversity value for species that were represented by several individuals was close to the regression line (Fig. 1). For example, the average diversity value for adult human microbiota (34 samples) was 80.8 with a standard deviation of 294.2, and 23.7 ± 20.3 for the 15 baby human microbiota. As a matter of comparison, Trosvik et al. [25] observed a similar range of diversity (over 2 log-units of Shannon index) when analysing a time-series of 332 sequencings over 443 days, on a single male adult individual. Animal gut microbiota covered a broad range of diversity ranging from 2.2 to 1808.0. This was comparable to the values found in various types of environment, like drinking water, raw milk, plant roots, activated sludge in wastewater treatment plants, compost or soil (Additional file 2). On one hand, the lowest diversity in gut microbiota varied around 2, similarly to those found in drinking water. On the other hand, the highest diversity in gut microbiota reaching about 1808 resembled the values found in soils (Additional file 2). This vast range of variations in gut diversity is often associated with factors that are different to the body mass: diet [10], phylogeny [26], digestive tract structure [27], age [8] [28], way of life [29], ethnic origin [30], state of health (immune system, pregnancy, obesity) [31] [32], or genetic background [32]. Among these parameters, age has been well documented as the major one to explain these variations and the diversity or richness between human baby microbiota and those of adults [33] [34]. However the size of the gut also varies during infant growth. In this case, a difference in the microbial diversity between infant (29.9 ± 20.3) and adults (106.6 ± 76.0) was observed, concomitantly with changes in body mass when comparing human babies (6.5 ± 1.9) and adults (70 kg). The same observation was made for young and adult dog samples (Table 1). Furthermore, when comparing two penguin species that only differ in their body mass (only adult specimens, with the same diet and living in the same location), the relationship between microbial diversity and body mass still remain valid. The correlation between body mass and diversity has been assessed for homogenous sub-categories (Table 2 and Additional file 3), thus excluding the potential effects of the different parameters. Indeed, the 189 samples could also be analysed according to phylogeny (reptile, bird, and mammal), diet (carnivorous, herbivorous, granivorous, omnivorous and piscivorous), gut structure (hindgut caecum, hindgut colon and foregut ruminant), age (baby and adult), and size of the animal husbandry group (small and large). Except for the latter category, all of them depended on the body mass (e.g. body mass was related to phylogeny, related to age or to ruminants). Significantly positive body mass/diversity correlations were observed for each sub-category, provided that a sufficient amount of data was available (over 50 samples minimum per sub-category) (Table 2; Additional file 3). The significant slopes z of the mass-diversity relationships generally ranged from 0.202 ± 0.043 to 0.380 ± 0.039. As the herbivorous group only contained 44 samples, the interestingly weak body mass diversity correlation with a z value of 0.137 could not be correctly interpreted.
Table 2

Bacterial diversity and animal weight within sub-categories, correlation between diversity and weight, and slope of the relationship of the diversity versus log-weight

Category Number of samplesSimpson diversity mean (SD)Weight in kg mean (SD)Pearson correlation between diversity and weightPower law relationship diversity = c weightz
corp valueSlope z Confidence interval
Sub-categories
 Diet
  Carnivorous1332.0 (23.4)19.0 (44.1)0.2770.359 (NS)0.075 (NS)
  Frugivorous1055.2 (68.5)1.3 (3.1)0.5330.113 (NS)0.234 (NS)
  Granivorous5420.4 (21.7)4.4 (9.4)0.6673.7e−08 (***)0.298 (***)0.205–0.391
  Herbivorous44301.6 (342.3)354.5 (668.1)0.3380.025 (*)0.137 (*)0.018–0.256
  Omnivorous60111.3 (149.0)50.5 (32.4)0.5427.7e−06 (***)0.361 (***)0.214– 0.508
  Piscivorous820.4 (20.8)7.5 (5.9)0.0300.944 (NS)0.029 (NS)
 Phylogeny
  Bird8525.1 (23.6)7.8 (23.0)0.4561.1e−05 (***)0.202 (***)0.116–0.288
  Mammal101194.9 (268.8)183.3 (464.0)0.4151.6e−05 (***)0.272 (***)0.153–0.391
  Reptile3119.3 (131.9)1.6 (1.2)0.9640.172 (NS)1.686 (NS)
 Gut structure
  Caecum4670.4 (80.6)26.1 (65.3)0.5281.7e−04 (***)0.397 (***)0.203–0.591
  Colon12478.5 (122.5)79.0 (382.7)0.678<2.2e−16 (***)0.293 (***)0.236–0.350
  Rumen19484.9 (449.7)411.8 (384.5)−0.0360.883 (NS)−0.031 (NS)
 Group size
  Large8593.1 (151.0)65.8 (156.4)0.7341.3e−15 (***)0.380 (***)0.303–0.457
  Small104137.2 (253.7)130.6 (449.1)0.6326.6e−13 (***)0.300 (***)0.227–0.372
 Age
  Adult173125.6 (222.2)110.3 (364.6)0.687<2.2e−16 (***)0.337 (***)0.283–0.391
   Baby1628.9 (20.1)6.3 (2.0)0.2050.446 (NS)0.427 (NS)
 All189117.4 (214.3)101.5 (350.0)0.675<2.2e−16 (***)0.338 (***)0.284–0.391

NS not significant

* low significance, *** high significance

Bacterial diversity and animal weight within sub-categories, correlation between diversity and weight, and slope of the relationship of the diversity versus log-weight NS not significant * low significance, *** high significance The observed slope z was similar to that reported for ‘island’ patterns of bacterial diversity such as metal-cutting fluid sump tanks (z = 0.245–0.295) [3] and tree holes (z = 0.26) [5] and varied within a similar range to that reported for plants and animals from discrete islands (z = 0.25–0.35). The slope z-values reported for continuous patterns (such as marsh sediment [35] with z-values between 0.02 and 0.04) are generally much lower than those reported for discrete habitats. According to these results, which confirm the assumption that species and volume are related, guts can compared to an archipelago, where microbes originating from feed tend to colonise the available niches provided by the gut. This is also in line with the MacArthur and Wilson biogeography theory [1]. Size, similarly to island environments appears to reflect the heterogeneity of the environment. Hence, a large gut size should provide more space, enabling a large microbial diversity to settle in [36].

Conclusions

The aim of this study was not to explain the genesis of bacterial diversity in vertebrate guts but was rather focused on producing evidence on the role of gut size in the maintenance of a level of microbial diversity. This work highlights the hitherto unexplored relationship between volume and diversity in the case of gut microbiota. Gut volume should henceforth be taken into account along with other parameters to explain the level of diversity. Finally, this work confirms the relevance of the microbial world when addressing ecological issues such as the relationship between species diversity and the size of the habitat [37].

Availability of supporting data

Our data are provided in the electronic supplementary materials (Additional file 4).
  31 in total

1.  Larger islands house more bacterial taxa.

Authors:  Thomas Bell; Duane Ager; Ji-Inn Song; Jonathan A Newman; Ian P Thompson; Andrew K Lilley; Christopher J van der Gast
Journal:  Science       Date:  2005-06-24       Impact factor: 47.728

2.  Differences in fecal microbiota in different European study populations in relation to age, gender, and country: a cross-sectional study.

Authors:  Susanne Mueller; Katiana Saunier; Christiana Hanisch; Elisabeth Norin; Livia Alm; Tore Midtvedt; Alberto Cresci; Stefania Silvi; Carla Orpianesi; Maria Cristina Verdenelli; Thomas Clavel; Corinna Koebnick; Hans-Joachim Franz Zunft; Joël Doré; Michael Blaut
Journal:  Appl Environ Microbiol       Date:  2006-02       Impact factor: 4.792

Review 3.  A case of non-scaling in mammalian physiology? Body size, digestive capacity, food intake, and ingesta passage in mammalian herbivores.

Authors:  Marcus Clauss; Angela Schwarm; Sylvia Ortmann; W Jürgen Streich; Jürgen Hummel
Journal:  Comp Biochem Physiol A Mol Integr Physiol       Date:  2007-06-07       Impact factor: 2.320

Review 4.  What determines species richness of parasitic organisms? A meta-analysis across animal, plant and fungal hosts.

Authors:  Tsukushi Kamiya; Katie O'Dwyer; Shinichi Nakagawa; Robert Poulin
Journal:  Biol Rev Camb Philos Soc       Date:  2013-06-20

5.  Molecular microbial diversity of an anaerobic digestor as determined by small-subunit rDNA sequence analysis.

Authors:  J J Godon; E Zumstein; P Dabert; F Habouzit; R Moletta
Journal:  Appl Environ Microbiol       Date:  1997-07       Impact factor: 4.792

6.  Robust estimation of microbial diversity in theory and in practice.

Authors:  Bart Haegeman; Jérôme Hamelin; John Moriarty; Peter Neal; Jonathan Dushoff; Joshua S Weitz
Journal:  ISME J       Date:  2013-02-14       Impact factor: 10.302

7.  Diet is a major factor governing the fecal butyrate-producing community structure across Mammalia, Aves and Reptilia.

Authors:  Marius Vital; Jiarong Gao; Mike Rizzo; Tara Harrison; James M Tiedje
Journal:  ISME J       Date:  2015-03-17       Impact factor: 10.302

8.  Molecular fingerprinting of the fecal microbiota of children raised according to different lifestyles.

Authors:  Johan Dicksved; Helen Flöistrup; Anna Bergström; Magnus Rosenquist; Göran Pershagen; Annika Scheynius; Stefan Roos; Johan S Alm; Lars Engstrand; Charlotte Braun-Fahrländer; Erika von Mutius; Janet K Jansson
Journal:  Appl Environ Microbiol       Date:  2007-02-09       Impact factor: 4.792

9.  Richness of human gut microbiome correlates with metabolic markers.

Authors:  Emmanuelle Le Chatelier; Trine Nielsen; Junjie Qin; Edi Prifti; Falk Hildebrand; Gwen Falony; Mathieu Almeida; Manimozhiyan Arumugam; Jean-Michel Batto; Sean Kennedy; Pierre Leonard; Junhua Li; Kristoffer Burgdorf; Niels Grarup; Torben Jørgensen; Ivan Brandslund; Henrik Bjørn Nielsen; Agnieszka S Juncker; Marcelo Bertalan; Florence Levenez; Nicolas Pons; Simon Rasmussen; Shinichi Sunagawa; Julien Tap; Sebastian Tims; Erwin G Zoetendal; Søren Brunak; Karine Clément; Joël Doré; Michiel Kleerebezem; Karsten Kristiansen; Pierre Renault; Thomas Sicheritz-Ponten; Willem M de Vos; Jean-Daniel Zucker; Jeroen Raes; Torben Hansen; Peer Bork; Jun Wang; S Dusko Ehrlich; Oluf Pedersen
Journal:  Nature       Date:  2013-08-29       Impact factor: 49.962

10.  Gut microbiome of the Hadza hunter-gatherers.

Authors:  Stephanie L Schnorr; Marco Candela; Simone Rampelli; Manuela Centanni; Clarissa Consolandi; Giulia Basaglia; Silvia Turroni; Elena Biagi; Clelia Peano; Marco Severgnini; Jessica Fiori; Roberto Gotti; Gianluca De Bellis; Donata Luiselli; Patrizia Brigidi; Audax Mabulla; Frank Marlowe; Amanda G Henry; Alyssa N Crittenden
Journal:  Nat Commun       Date:  2014-04-15       Impact factor: 14.919

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  19 in total

1.  Insect anal droplets contain diverse proteins related to gut homeostasis.

Authors:  Tianzhong Jing; Fuxiao Wang; Fenghui Qi; Zhiying Wang
Journal:  BMC Genomics       Date:  2018-10-30       Impact factor: 3.969

2.  Maintenance of Distal Intestinal Structure in the Face of Prolonged Fasting: A Comparative Examination of Species From Five Vertebrate Classes.

Authors:  Marshall D McCue; Celeste A Passement; David K Meyerholz
Journal:  Anat Rec (Hoboken)       Date:  2017-10-05       Impact factor: 2.064

3.  The Intestinal Microbiota of Tadpoles Differs from Those of Syntopic Aquatic Invertebrates.

Authors:  Mariana L Lyra; Molly C Bletz; Célio F B Haddad; Miguel Vences
Journal:  Microb Ecol       Date:  2017-11-20       Impact factor: 4.552

4.  Dispersal limitation promotes the diversification of the mammalian gut microbiota.

Authors:  Andrew H Moeller; Taichi A Suzuki; Dana Lin; Eileen A Lacey; Samuel K Wasser; Michael W Nachman
Journal:  Proc Natl Acad Sci U S A       Date:  2017-12-11       Impact factor: 11.205

5.  Rates of gut microbiome divergence in mammals.

Authors:  Alex H Nishida; Howard Ochman
Journal:  Mol Ecol       Date:  2018-01-31       Impact factor: 6.185

6.  Drivers of symbiont diversity in freshwater snails: a comparative analysis of resource availability, community heterogeneity, and colonization opportunities.

Authors:  Keegan McCaffrey; Pieter T J Johnson
Journal:  Oecologia       Date:  2016-12-30       Impact factor: 3.225

7.  Comparative Analysis of Microbiome Metagenomics in Reintroduced Wild Horses and Resident Asiatic Wild Asses in the Gobi Desert Steppe.

Authors:  Liping Tang; Yunyun Gao; Liping Yan; Huiping Jia; Hongjun Chu; Xinping Ma; Lun He; Xiaoting Wang; Kai Li; Defu Hu; Dong Zhang
Journal:  Microorganisms       Date:  2022-06-07

8.  The gut microbiota and Bergmann's rule in wild house mice.

Authors:  Taichi A Suzuki; Felipe M Martins; Megan Phifer-Rixey; Michael W Nachman
Journal:  Mol Ecol       Date:  2020-06-04       Impact factor: 6.185

Review 9.  Towards an ecosystem model of infectious disease.

Authors:  James M Hassell; Tim Newbold; Andrew P Dobson; Yvonne-Marie Linton; Lydia H V Franklinos; Dawn Zimmerman; Katrina M Pagenkopp Lohan
Journal:  Nat Ecol Evol       Date:  2021-05-17       Impact factor: 15.460

10.  Does the Composition of the Gut Bacteriome Change during the Growth of Tuna?

Authors:  Elsa Gadoin; Lucile Durand; Aurélie Guillou; Sandrine Crochemore; Thierry Bouvier; Emmanuelle Roque; Laurent Dagorn; Jean-Christophe Auguet; Antoinette Adingra; Christelle Desnues; Yvan Bettarel
Journal:  Microorganisms       Date:  2021-05-27
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