Intestinal microbiota profiles associated with low and high residual feed intake in chickens across two geographical locations
Siegerstetter, S-C., Schmitz-Esser, S., Magowan, E., Wetzels, S. U., Zebeli, Q., Lawlor, P., O'Connell, N., & Metzler-Zebeli, B. (2017). Intestinal microbiota profiles associated with low and high residual feed intake in chickens across two geographical locations. PLoS ONE, 12(11), 1-23. https://doi.org/10.1371/journal.pone.0187766 Published in: PLoS ONE
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Download date:27. Sep. 2021 1 Intestinal microbiota profiles associated with low and high
2 residual feed intake in chickens across two geographical
3 locations
4
5 Sina-Catherine Siegerstetter1,2, Stephan Schmitz-Esser2,3#a, Elizabeth Magowan4,
6 Stefanie Urimare Wetzels1,2#b, Qendrim Zebeli1,2, Peadar G. Lawlor5, Niamh E.
7 O´Connell6, and Barbara U. Metzler-Zebeli1,2*
8
9 1Institute of Animal Nutrition and Functional Plant Compounds, Department for Farm
10 Animals and Veterinary Public Health, University of Veterinary Medicine, Vienna, Austria,
11 2Research Cluster “Animal Gut Health”, Department for Farm Animals and Veterinary Public
12 Health, University of Veterinary Medicine, Vienna, Austria,
13 3Institute of Milk Hygiene, Milk Technology and Food Science, Department for Farm
14 Animals and Veterinary Public Health, University of Veterinary Medicine, Vienna, Austria,
15 4Agri-Food and Biosciences Institute, Agriculture Branch, Large Park, Co. Down,
16 Hillsborough, Northern Ireland, United Kingdom,
17 5Teagasc Pig Development Department, Animal & Grassland Research & Innovation Centre,
18 Moorepark, Fermoy, Co. Cork, Ireland,
19 6Institute for Global Food Security, Queen´s University Belfast, University Road Belfast, BT7
20 1NN, Northern Ireland, United Kingdom,
21 #aCurrent Address: Department of Animal Science, College of Agriculture and Life Science,
22 IOWA State University, Ames, Iowa, USA,
23 #bCurrent Address: Institute of Milk Hygiene, Milk Technology and Food Science,
24 Department for Farm Animals and Veterinary Public Health, University of Veterinary
25 Medicine, Vienna, Austria
26
27 *Corresponding author: Tel.: +43 1 25077 3209. Fax: +43 1 25077 5297; e-mail:
29
30 Short Title: Intestinal microbiome, feed efficiency and chickens
31
32 Abstract
33 Intestinal microbe-host interactions can affect the feed efficiency (FE) of chickens. As
34 inconsistent findings for FE-associated bacterial taxa were reported across studies, the present
35 objective was to identify whether bacterial profiles and predicted metabolic functions that
36 were associated with residual feed intake (RFI) and performance traits in female and male
37 chickens were consistent across two different geographical locations. At six weeks of life, the
38 microbiota in ileal, cecal and fecal samples of low (n = 34) and high (n = 35) RFI chickens
39 were investigated by sequencing the V3-5 region of the 16S rRNA gene. Location-associated
40 differences in α-diversity and relative abundances of several phyla and genera were detected.
41 RFI-associated bacterial abundances were found at the phylum and genus level, but differed
42 among the three intestinal sites and between males and females. Correlation analysis
43 confirmed that, of the taxonomically classifiable bacteria, Lactobacillus (5% relative
44 abundance) and two Lactobacillus crispatus-OTUs in feces were indicative for high RFI in
45 females (P < 0.05). In males, Ruminococcus in cecal digesta (3.1% relative abundance) and
46 Dorea in feces (<0.1% relative abundance) were best indicative for low RFI, whereas
47 Acinetobacter in feces (<1.5% relative abundance) related to high RFI (P < 0.05). Predicted
48 metabolic functions in feces of males confirmed compositional relationships as functions
49 related to amino acid, fatty acid and vitamin metabolism correlated with low RFI, whereas an
50 increasing abundance of bacterial signaling and interaction (i.e. cellular antigens) genes
51 correlated with high RFI (P < 0.05). In conclusion, RFI-associated bacterial profiles could be
52 identified across different geographical locations. Results indicated that consortia of low-
53 abundance taxa in the ileum, ceca and feces may play a role for FE in chickens, whereby only
54 bacterial FE-associations found in ileal and cecal digesta may serve as useful targets for
55 dietary strategies.
56 Keywords: chicken, intestinal microbiota, geographical location, residual feed intake
57 Introduction
58 Chicken’s intestinal microbiota are an important “metabolic organ” which plays a vital
59 role in feed digestibility, nutrient absorption and immune competence [1]. Differences in
60 microbial energy-harvesting from feed can influence energy retention, weight gain and hence
61 chicken’s feed efficiency (FE) [1,2]. An improvement in FE reduces the feed costs and
62 concurrently the environmental impact of broiler production [3]. Within one chicken
63 population from the same breed, a considerable variation in FE can be found [4]. Therefore,
64 elucidating the FE-associated intestinal microbiota composition may allow for the
65 characterization of an optimal microbial profile for good FE. Correspondingly, bacteria
66 belonging to Bacteroides, Enterobacteriaceae, Clostridium, Ruminococcus, Faecalibacterium
67 and Lactobacillus have been previously positively or negatively associated with FE in
68 chickens [5-8]. However, the high hygiene levels in modern commercial hatcheries have an
69 unwanted side effect of causing highly variable bacterial colonization of chicken’s intestine
70 [9]. This may be one reason for the inconsistent findings for cecal and fecal microbial profiles
71 associated with good FE among studies [2,5,7,8] and the batch-to-batch variability within one
72 study [7]. Other sources of variation are the dietary composition, the chicken line used and the
73 encountered environmental microbes [2,5,7,10]. Bacteria associated with good FE, however,
74 should be detectable across different chicken batches within the same rearing environment,
75 but also across multiple production settings, irrespective of the origin of the chickens and
76 dietary effects. If unique bacterial FE-associations can be characterized across batches and
77 geographical environments, those can serve as targets for dietary approaches in the future to
78 improve chicken’s FE. Also, previous research mainly focused on male chickens [2,5,7] and
79 adult hens [8],whereas FE-related bacterial profiles were hardly investigated simultaneously
80 in broiler chickens of both sexes.
4
81 So far, most studies on the FE-associated intestinal microbiota in chickens have been
82 conducted using feed conversion ratio (FCR) or apparent metabolizable energy (AME) as
83 metrics for FE [2,5,7]. In being independent of production traits (e.g., body weight gain), the
84 residual feed intake (RFI) is another metric of choice to investigate the biological mechanisms
85 contributing to varying FE in livestock animals including poultry, pigs and cattle [11,12]. The
86 objective of this study was therefore to identify whether bacterial profiles and predicted
87 metabolic functions that were associated with RFI or performance traits in female and male
88 chickens were consistent across two geographical locations. This was based on the hypothesis
89 that the ileal, cecal and fecal microbiota in chickens of good FE raised in different
90 environments would be characterized by mutual FE-associated bacteria and microbial
91 functions. Because batch-to-batch variation in FE-associated bacterial profiles were reported
92 before [2,5,7,8], we designed the chicken experiments to be carried out in three batches at
93 each geographical location in order to reduce the impact of batch-associated differences when
94 identifying bacterial profiles across the two locations. Other sources of variation in the FE-
95 related microbial profiles among studies may be associated with the methods of DNA
96 extraction, sequencing and bioinformatic analyses of the samples [13]. In order to reduce the
97 analytical bias, ileal and cecal digesta and fecal samples underwent the same analytical
98 procedures and were processed together at one geographical location in the present study.
99
100 Materials and Methods
101 Animals, housing and experimental design
102 To reduce the impact of experimental procedures on the study outcome, two chicken
103 experiments using common protocols comprising the experimental design, diet formulations,
104 data and sample collection were conducted at two different geographical locations [L1:
105 Institute of Animal Nutrition and Functional Plant Compounds, University of Veterinary 5
106 Medicine Vienna, Austria; and L2: Agri-Food and Biosciences Institute (AFBI),
107 Hillsborough, Northern Ireland]. In order to account for the previously reported variation in
108 the intestinal microbiota composition among chicken batches [2,5,7,8], each of the two
109 experiments was planned to consist of three consecutive replicate batches. The two
110 experiments were run in parallel at the two geographical locations within a six month period.
111 In Austria, the animal procedures including animal handling and treatment were approved by
112 the institutional ethics committee of the University of Veterinary Medicine Vienna and the
113 Austrian national authority according to paragraph 26 of Law for Animal Experiments,
114 Tierversuchsgesetz 2012 – TVG 2012 (GZ 68.205/0131-II/3b/2013). In Northern Ireland,
115 animal procedures were conducted in line with the requirements of the ‘Animals (Scientific
116 Procedures) Act 1986’ (PPL 2781, Department of Health, Social Services and Public Safety,
117 Northern Ireland, UK) and were approved by AFBI’s internal ethics committee.
118 In order to mimic commercial production conditions, different local hatcheries delivered
119 the chickens to the two geographical locations and the feed was prepared at local feed mills
120 according to the same dietary specifications (S1 Table). A total of 157 (n = 78 females, n = 79
121 males) and 192 (n = 96 females, n = 96 males) day-old Cobb 500FF broiler chickens were
122 used at L1 and L2, respectively. Within each replicate batch, equal numbers of females and
123 males, except for one batch with one more male at L1, were used. Day-old chickens were
124 group-housed for six days and then randomly allocated to individual cages on day 7 of life
125 until day 42 of life. Chickens had free access to starter (day 1-10), grower (day 11-21) and
126 finisher (day 22-42) corn-soybean meal based diets (S1 Table) and demineralized water. Diets
127 were free of anti-microbial growth promoters and coccidiostats. At each location, starter,
128 grower and finisher diets for the three replicate batches came from the same batch of
129 commercially prepared crumbles (starter diet) and pellets (grower and finisher diets), which
130 were stored in cool (<15°C) and dry conditions for a duration of no longer than six months.
131 6
132 Determination of FE and selection of chickens
133 Feed leftovers and spills were collected before recording feed intake on days 14, 21, 28,
134 35, 36 and 38 of life. Chickens were weighed accordingly upon arrival, weekly and on the last
135 experimental day. In the present study, we used the RFI to rank the chickens according to
136 their FE [14]. The final RFI at the two geographical locations were determined two days apart
137 due to the slower growth of the chickens at L2 than those at L1. For this, total FI (TFI), total
138 BW gain (TBWG) and metabolic mid weight were calculated between days 7 and 36 of life
139 and days 7 and 38 of life at L1 and L2, respectively. Regression analysis was performed for
140 each batch and geographical location individually. A nonlinear mixed model (SAS Stat Inc.,
141 version 9.2; Cary, NC, USA) was used to estimate chicken’s RFI value as the residual
142 according to the following equations [14]. The mid metabolic weight (MMW) was calculated
143 as MMW = {[BW at d 7 of life (g) + BW at d 36 or 38 of life, respectively (g)]/2}0.75. The
144 RFI was calculated as RFI (g) = TFI − (a1 + b1 × MMW + b2 × TBWG), in which a1 is the
145 intercept and b1 and b2 are partial regression coefficients of MMW and TBWG on TFI,
146 respectively. In each replicate, it was aimed to select the three chickens with the lowest RFI
147 (low RFI chickens) and the three chickens with the highest RFI (high RFI chickens),
148 separately for female and male chickens. A total of 34 low RFI and 35 high RFI chickens
149 were finally selected at both geographical locations (L1, n = 9/sex and RFI; L2, n = 6 low RFI
150 females, n = 8 high RFI females, and n = 10 low RFI males, n = 9 high RFI males). For those
151 chickens, the RFI as well as TFI and TBWG between days 7 and 36 of life will be presented.
152 In addition, the individual FCR value of the low and high RFI chickens was calculated.
153
154 Sample collection
155 Fresh fecal samples for microbiota analysis were collected on day 36 of life at both
156 geographical locations. To facilitate the collection of feces, parchment paper was laid out on
7
157 the tray under each cage. The gastrointestinal origin of the chicken feces determines the fecal
158 bacterial composition [15]; therefore, feces of a paste-like texture without the uric acid-
159 containing white part were predominantly collected. Within 5 to 10 min after defecation, feces
160 were aseptically collected, placed into sterile 2-ml cryotubes (Sarstedt, Nümbrecht,
161 Germany), snap frozen in liquid N2 and stored at -80°C until DNA extraction. Selected
162 chickens were humanely killed on days 37 to 42 of life with an overdose of sodium
163 pentobarbital (450 mg/kg, Release, WTD-Wirtschaftsgenossenschaft Deutscher Tierärzte,
164 Garbsen, Germany) by i.v. injection into the caudal tibial vein from day 37 of life with three
165 to six chickens per day, whereas at L2 selected chickens were sacrificed on days 41 and 42 of
166 life. After exsanguination, the abdominal cavity was opened and the whole gastrointestinal
167 tract was removed. Digesta from the ileum (end of mesentery arteries to ileo-cecal junction)
168 and both ceca were aseptically collected, homogenized, placed into sterile 2-ml cryotubes
169 (Sarstedt), snap-frozen in liquid N2 and stored at -80°C until further analysis. Before
170 homogenization, the content of both ceca was pooled together.
171
172 DNA extraction
173 The DNA was extracted from all intestinal and fecal samples of both geographical
174 locations together at L1. Total DNA was extracted from 250 mg of fecal, ileal and cecal
175 samples using the PowerSoil DNA extraction kit (MoBio Laboratories Inc., Carlsbad, CA,
176 USA) with some modifications [16, 17]. After addition of buffer C1, a heating step at 70°C
177 for 10 min was included. The DNA concentration was measured using the Qubit 2.0
178 Fluorometer (Life Technologies, Carlsbad, CA, USA) with the Qubit dsDNA HS Assay Kit
179 (Life Technologies). The identical DNA sample was used for 16S rRNA gene amplicon
180 sequencing and qPCR analysis of total bacteria. For the qPCR, DNA sample volumes were
8
181 adjusted to achieve similar DNA concentrations across samples to avoid an impact of the
182 DNA concentration on the amplification results.
183
184 16S rRNA gene amplicon sequencing
185 The 16S rRNA gene was amplified using the primer set 341F
186 (CCTACGGGRSGCAGCAG) and 909R (TTTCAGYCTTGCGRCCGTAC) targeting the
187 V3-5 hypervariable regions of the 16S rRNA gene to generate an approximate amplicon size
188 of 568 bp. The 16S rRNA gene PCR, library preparation as well as DNA sequencing of
189 samples was performed by a commercial provider (Microsynth AG, Balgach, Switzerland).
190 The 16S rRNA gene was amplified using the KAPA HiFi HotStart PCR Kit (Roche, Baden,
191 Switzerland) including a high-fidelity DNA polymerase. Libraries were constructed by
192 ligating sequencing adapters and indices onto purified PCR products using the Nextera XT
193 sample preparation kit (Illumina Inc., San Diego, CA, USA) according to the manufacturer’s
194 protocol. For each of the libraries, equimolar amounts were pooled and sequenced on an
195 Illumina MiSeq Personal Sequencer using a 300 bp read length paired-end protocol. All
196 sample libraries were sequenced in the same sequencing run. The resultant overlapping
197 paired-end reads were demultiplexed, trimmed using cutadapt
198 (http://code.google.com/p/cutadapt/) and stitched using Fast Length Adjustment of SHort
199 reads (FLASH; http://www.cbcb.umd.edu/software/flash) [18] by Microsynth.
200 Further sequence processing was performed using the Quantitative Insights Into
201 Microbial Ecology (QIIME) package, version 1.9.1 [19]. Samples from all three intestinal
202 sites and both geographical locations were analyzed together at L1. Fastq files were quality
203 trimmed using the “split_libraries_fastq“ script for non-multiplexed Illumina fastq data with
204 the phred offset 33. The UCHIME method using the 64-bit version of USEARCH and GOLD
205 database (drive5.com) was used to detect and remove chimeric sequences [20,21]. Open-
9
206 reference operational taxonomic unit (OTU) picking was done at 97% similarity level using
207 UCLUST [20]. OTU taxonomy was assigned against the Greengenes database and QIIME
208 1.9.1 defaults (http://qiime.org/home_static/dataFiles.html) [22]. Rare OTUs containing less
209 than 10 sequences were removed. Community metrics (coverage, α- and β-diversity) analysis
210 was done in QIIME. For α- and ß-diversity analyses a rarefaction depth of 10,000 sequences
211 per sample was used, excluding samples with fewer reads. Beta-diversity was determined
212 using unweighted and weighted UniFrac distance [23,24]. Unweighted UniFrac is a
213 qualitative measurement, taking into account the presence/absence of taxa and measures the
214 distance between two communities by calculating the fraction of the branch length in a
215 phylogenetic tree that is unique to any of the two communities [23]. Weighted UniFrac is a
216 quantitative measurement accounting for differences in the relative abundance of OTUs
217 between different communities by weighting the branches in the phylogenetic tree based on
218 the relative abundance of sequences in the communities [23,25]. The resulting distance
219 matrices were visualized using principal coordinates analysis (PCoA). To compare the overall
220 intestinal microbial community structures of the individual chickens between the two
221 geographical locations and intestinal sites, Venn diagrams, including all OTUs generated by
222 the OTU picking step, were calculated using the software mothur (version 1.34.0) [26].
223 Individual high abundance OTUs that correlated with RFI were additionally classified by
224 using the Greengenes 16S rRNA gene database (http://greengenes.lbl.gov/). Raw sequencing
225 data are available in NCBI’s BioProject SRA database under accession no. PRJNA375981.
226
227 Quantitative PCR
228 Quantification of 16S rRNA gene copies of total bacteria in all DNA samples was
229 performed on a Stratagene Mx3000P QPCR System (Agilent Technologies, Santa Clara, CA)
230 using the Fast-Plus EvaGreen Master Mix with Low ROX (Biotium, Hayward, CA, USA
10
231 Technologies) and the primer set 341-357F and 518-534R in 20 µl reaction mixtures at L1
232 [16,17]. Each standard and sample reaction contained 10 µl of master mix, forward and
233 reverse primers (62.5 pmol) and 1 ng of DNA template. The amplification program included
234 an initial denaturation step at 95°C for 5 min, followed by 40 cycles of 95°C for 15 s, primer
235 annealing at 60°C for 30 s and elongation at 72°C for 30 s. Fluorescence was measured at the
236 last step of each cycle. The dissociation of PCR products were monitored by slow heating
237 with an increment of 0.5°C/s from 55 to 95°C to determine the specificity of the
238 amplification. Correct PCR product length was additionally verified by horizontal gel
239 electrophoresis. Amplification efficiency was calculated according to: E = -1 + 10-1/slope. The
240 standard was created from the purified and quantified PCR products generated by standard
241 PCR using DNA from chicken intestinal digesta and feces of the present experiment and the
242 total bacterial primer set [16,17]. Ten-fold standard serial dilutions (107 to 103 molecules/µl)
243 were run on each 96-well plate, with amplification efficiencies ranging from 1.95 to 2.00 and
244 R2 = 0.99 to 1.00.
245
246 Microbial function prediction
247 Microbial function prediction for each ileal, cecal and fecal sample based on 16S rRNA
248 gene sequencing data was determined using Pylogenetic Investigation of Communities by
249 Reconstruction of Unobserved States (PICRUSt) according to RFI rank, geographical location
250 and the intestinal site [27]. Closed-reference OTU picking was performed at 97% similarity
251 level against the Greengenes database (downloaded from
252 http://greengenes.secondgenome.com/downloads/database/13_5), and processed in the online
253 Galaxy PICRUSt interface (http://galaxyproject.org/) with a workflow described by the
254 developers (http://picrust.github.com/picrust/tutorials/quickstart.html#quickstartguide).
255 Sequences were categorized by function based on Kyoto Encyclopedia of Genes and
11
256 Genomes (KEGG) pathways in PICRUSt. Non-bacteria related KEGG orthology functions
257 and functions <0.01% relative abundance were dismissed.
258
259 Statistical analyses
260 Sequencing data were included in the statistical analysis that were detected in more than
261 50% of the chickens, separate per location, gut site and sex. Feed efficiency and microbiota
262 variables were first analyzed for normality using Shapiro-Wilk test with the PROC
263 UNIVARIATE method in SAS, version 9.4. The Cook’s distance (Cook’s D) test was used to
264 determine any influential observation on the model. Absolute 16S rRNA gene copies and
265 sequencing data including α-diversity indices and relative abundances of individual phyla,
266 families, genera and OTUs were analyzed by ANOVA using two different models and the
267 MIXED procedure in SAS. The first model accounted for the fixed effects of sex, intestinal
268 site, batch, geographical location and RFI group. Because chickens were sacrificed at
269 different days of life and to consider that chickens were consecutively sampled, the first
270 model included the random effects of chicken nested within day of life and chicken order at
271 sacrifice. Sex as fixed effect was significant for most parameters; therefore, variables were
272 analyzed separately for female and male chickens using the second model. This model was
273 fitted to take into account the fixed effect of RFI group and geographical location and their
274 two-way-interaction, separately per intestinal site. As previously reported in the literature
275 [7,9], batch affected many bacterial taxa. Therefore, the random effect considered the chicken
276 nested within batch, day of life and chicken order at slaughter. Degrees of freedom were
277 approximated by the method of Kenward-Roger. The rigorous statistical tests applied in SAS
278 allow a False Discovery Rate of less than 5%. Least squares means were computed using the
279 pdiff statement and significance was declared at P ≤ 0.05. A trend was considered at 0.05 < P
280 ≤ 0.10.
12
281 To characterize relationships between FE and performance traits and bacterial taxa and
282 predicted metabolic functions that were similarly directed at both locations and to distinguish
283 whether relationships were more predominant with bacterial taxa of high or low abundance,
284 Pearson’s correlation analysis (CORR procedure of SAS) was used to identify individual
285 genera, OTUs and KEGG pathways that were associated with RFI, TFI TBWG and FCR
286 across locations, separately for female and male chickens, and to quantify their relationships
287 in ileal and cecal digesta and feces. Moreover, Pearson’s correlations between KEGG
288 pathways and bacterial genera that were associated with RFI were calculated to relate RFI-
289 associated differences in the predicted metabolic functions back to bacterial abundances.
290 Correlations between OTUs and RFI, FCR and performance traits were only calculated for
291 individual OTUs, which occurred at a relative abundance >0.01% of all sequences at each
292 intestinal site, sex and geographical location. Descriptive statistics was performed using the
293 MEANS procedure of SAS (SAS Inst. Inc., version 9.4). In the following, the term cross-
294 locational association will be used to describe similar effects across the two geographical
295 locations.
296
297 Results
298 Feed efficiency
299 The RFI values and TFI of chickens within the same RFI rank were similar between
300 geographical locations (Table 1). The RFI increased (P < 0.001) by 292 and 499 g from low
301 (good FE) to high RFI (poor FE) in females and by 486 and 442 g from low to high RFI in
302 males from L1 and L2, respectively (Table 1). By contrast, TBWG was equal for low and
303 high RFI ranks, but it was lower in chickens from L2 who gained about 350 to 400 g less
304 compared to chickens from L1 (P < 0.001). Chicken’s FCR values corresponded to those of
13
305 the RFI values in low and high RFI groups. However, the location effect showed that chickens
306 from L2 had higher FCR values and thus poorer FE than chickens from L1 (P < 0.001).
307
308 Table 1. Performance and feed efficiency data of low and high residual feed intake (RFI)
309 broiler chickens raised at two geographical locations (L).
L1a L2a P-Value Low High Low High Item RFI RFI RFI RFI SEM RFI L RFI × L Females TFI, d 7-36 of life (g) 3334 3751 3559 3797 127.1 0.027 0.479 0.566 TBWG, d 7-36 of life (g) 2251 2279 1966 1856 69.9 0.647 <0.001 0.643 RFI (g) -195 97 -267 232 28.4 <0.001 0.412 0.201 FCR (g/g) 1.46 1.62 1.65 1.89 0.027 <0.001 <0.001 0.108
Males TFI, d 7-36 of life (g) 3682 4185 3823 4321 99.1 <0.001 0.340 0.573 TBWG, d 7-36 of life (g) 2573 2615 2228 2214 77.1 0.582 <0.001 0.560 RFI (g) -183 303 -211 231 30.9 <0.001 0.149 0.610 FCR (g/g) 1.41 1.61 1.58 1.79 0.028 <0.001 <0.001 0.774 310 Data are presented as least-square means and pooled standard error of the mean (SEM).
311 a L1, University of Veterinary Medicine Vienna (Vienna, Austria); L2, Agri-Food and Biosciences Institute
312 (Hillsborough, Northern Ireland, UK). TFI, total feed intake; TBWG, total body weight gain; FCR, feed
313 conversion ratio.
314
315 Absolute 16S rRNA gene abundance
316 Total bacterial 16S rRNA gene copy numbers in intestinal and fecal samples were
317 affected by intestinal site, geographical location and RFI (Table 2). Cecal digesta comprised
318 1.5 and 1 log units more bacterial 16S rRNA log10 gene copies compared to ileal digesta and
319 feces, respectively (P < 0.001, Table 2). In addition, females and males at L1 contained 1.1
320 and 1.3 log units more gene copies in the ileum and 0.2 and 0.4 log units more in the ceca,
321 respectively, compared to L2 (P < 0.05), whereas 16S rRNA log10 gene copies in feces were
322 similar. Small, but physiologically not relevant, RFI-related differences in the total bacterial 14
323 gene copies were observed in the ceca of males (P < 0.05) and feces of females (P < 0.10),
324 with low RFI chickens having 0.2 and 0.4 log units more gene copies compared to high RFI
325 animals, respectively.
326
327 Table 2. Total bacterial gene copy numbers (log10 16S rRNA gene copies/g fresh matter)
328 in intestinal digesta and feces of low and high residual feed intake (RFI) broiler chickens
329 raised at two geographical locations (L).
L1a L2a P-Valueb Item Low RFI High RFI Low RFI High RFI SEM RFI L RFI × L Females Ileum 10.1 9.9 8.7 9.2 0.21 0.581 <0.001 0.177 Ceca 11.2 11.2 11.1 10.9 0.09 0.153 0.012 0.497 Feces 10.3 9.9 10.0 9.7 0.17 0.068 0.214 0.985
Males Ileum 10.2 10.3 8.8 9.1 0.23 0.440 <0.001 0.726 Ceca 11.3 11.0 10.8 10.7 0.07 0.012 <0.001 0.460 Feces 10.3 10.2 10.0 10.1 0.13 0.659 0.124 0.405 330 Data are presented as least-square means and pooled standard error of the mean (SEM).
331 a L1, University of Veterinary Medicine Vienna (Vienna, Austria); L2, Agri-Food and Biosciences Institute
332 (Hillsborough, Northern Ireland, UK).
333 b Intestinal site affected total bacterial gene copy numbers (P < 0.001).
334
335 Bacterial community composition related to intestinal site
336 From the 8,600,328 stitched reads for the 68 ileal, 68 cecal and 69 fecal samples (mean
337 Phred score of 29 to 36) obtained from the commercial provider, 7,726,361 reads remained
338 after quality control, with a mean of 37,690 reads per sample (min: 145, max: 175,973) and a
339 mean read length of 557 ± 16 bp, which were classified into 6,404 OTUs.
15
340 For all intestinal sites, the Venn diagram (Fig. 1A) showed that 67.9% of all OTUs
341 (4,351 OTUs) were shared among both geographical locations, whereas 12.3% and 19.8% of
342 the OTUs were specifically associated with L1 and L2, respectively. Thereby, the shared
343 OTUs represented 97.8% of all reads and comprised the high-abundance OTUs, whereas only
344 low-abundance OTUs were specific for the geographical location. Moreover, 39.3% of all
345 OTUs (2,518 OTUs) were shared among all three intestinal sites, whereby they corresponded
346 to 98.1% of all reads (Fig. 1B). In addition, more OTUs were shared between ceca and feces
347 (74.9%) than between ileum and feces (52.8%). Despite the shared OTUs, β-diversity analysis
348 using weighted UniFrac showed a clear separation of the community in cecal digesta from
349 those in feces and ileal digesta (Fig. 1C), which was confirmed by intestinal-site specific
350 relative abundances at phylum and genus level (P < 0.05; Fig. 2; S2 Table). This was also
351 visible when comparing the taxonomical composition. Particularly, bacteria belonging to the
352 phylum Firmicutes were 20 to 35% more abundant in cecal digesta compared to ileal digesta
353 and feces, respectively, whereas in ileal digesta and feces more Proteobacteria were present
354 (P < 0.05; Fig. 2). Moreover, the ileal community was predominated by the genera
355 Lactobacillus (31.2%), Escherichia/Hafnia/Shigella (26.4%) and Turicibacter (24.0%; S2
356 Table). In cecal digesta, an unclassified Clostridiales genus (55.7%) and an unclassified
357 Ruminococcaceae (15.8%) predominated, whereas in feces an Escherichia/Hafnia/Shigella
358 (39.1%), Turicibacter (14.0%) and an unclassified Clostridiales genus (13.8%) were highly
359 abundant.
360
361 Changes in bacterial community related to geographical location
362 Beta-diversity analysis using weighted UniFrac did not show specific clustering based
363 on the different batches and the different geographical locations (Fig. 1D). Nevertheless,
364 effects of the geographical location were detectable when comparing species richness and α-
16
365 diversity (Table 3) as well as the relative abundance of several phyla (Table 4) and genera
366 (Table 5 and 6) across the two locations. In males from L1, the cecal community had a lower
367 α-diversity as indicated by the Shannon and Simpson indices (P < 0.05) compared to males at
368 L2 (Table 3). For the fecal community in females, in contrast, the Chao1 (P < 0.05) and
369 Shannon (P < 0.10) indices showed higher species richness and diversity in animals at L1
370 compared to L2.
371
372 Table 3. Differences in α-diversity indices in intestinal digesta and feces of low and high
373 residual feed intake (RFI) broiler chickens raised at two geographical locations (L).
L1c L2c P-Valued,e Item Low RFI High RFI Low RFI High RFI SEM RFI L RFI × L Females Ileum Shannon 2.34 2.80 2.39 3.05 0.453 0.231 0.748 0.830 Simpson 0.53 0.64 0.59 0.71 0.089 0.220 0.475 0.998 Chao1 449 421 315 450 61.2 0.398 0.406 0.200 Ceca Shannon 5.28b 5.28b 4.78b 6.41a 0.299 0.012 0.311 0.012 Simpson 0.93a 0.92a 0.83b 0.96a 0.026 0.020 0.295 0.014 Chao1 1076bA 1084bA 807bB 1365a 96.0 0.007 0.951 0.008 Feces Shannon 3.60 3.21 2.78 2.44 0.413 0.389 0.065 0.954 Simpson 0.72 0.66 0.57 0.59 0.068 0.730 0.134 0.605 Chao1 772 594 525 437 87.8 0.142 0.030 0.613
Males Ileum Shannon 2.16 2.79 2.42 3.11 0.320 0.048 0.378 0.919 Simpson 0.55 0.67 0.62 0.69 0.061 0.128 0.447 0.708 Chao1 310 347 305 457 63.0 0.145 0.414 0.370 Ceca Shannon 5.49 5.39 6.21 6.13 0.205 0.664 0.001 0.974 Simpson 0.93 0.91 0.96 0.94 0.014 0.180 0.044 0.957 Chao1 1152 1050 1191 1260 90.0 0.856 0.174 0.348 Feces
17
Shannon 3.83 3.65 4.13 3.38 0.420 0.280 0.966 0.504 Simpson 0.79 0.77 0.79 0.72 0.045 0.338 0.562 0.559 Chao1 729 526 801 633 97.5 0.066 0.365 0.858 374 Data are presented as least-square means and pooled standard error of the mean (SEM).
375 a,b Different superscript letters within a row indicate significant difference (P ≤ 0.05).
376 A,B Different superscript capital letters within a row indicate a tendency (P ≤ 0.10).
377 c L1, University of Veterinary Medicine Vienna (Vienna, Austria); L2. Agri-Food and Biosciences Institute
378 (Hillsborough, Northern Ireland, UK).
379 d Rarefaction depth of 10,000 sequences per sample removed 9 samples from the dataset. L1, n = 9/sex, RFI and
380 intestinal site, except for ileum where n = 8 high RFI females, and n = 8 low RFI males, and for feces where n =
381 8 low RFI females; L2, for ileum, n = 5 low RFI females, n = 5 high RFI females, and n = 9 low RFI males, n =
382 8 high RFI males; for ceca, n = 4 low RFI females, n = 8 high RFI females, and n = 10 low RFI males, n = 9
383 high RFI males; for feces, n = 6 low RFI females, n = 8 low RFI females, and n = 10 low RFI males, n = 9 high
384 RFI males.
385 e Intestinal site affected all diversity indices (P < 0.001).
386
387 The phyla with the most pronounced differences for geographical location included
388 Tenericutes and Actinobacteria in the ceca of both sexes and Firmicutes in cecal digesta of
389 males (P < 0.001; Table 4). At genus level, strong effects for geographical location were
390 found for the genera Ruminococcus in cecal digesta and an unclassified Clostridiaceae 2 in
391 the feces of females (P < 0.001; Table 5) as well as for unclassified Ruminococcaceae,
392 Anaerotruncus, Ruminococcus, Faecalibacterium and Streptococcus in cecal digesta of males
393 (P < 0.001; Table 6).
394
395 Changes in the bacterial community related to RFI
396 Although the β-diversity analysis did not show RFI-associated clustering (Fig. 1E),
397 comparison of the microbiota composition between RFI ranks demonstrated that RFI-related
398 differences in bacterial abundances were evident, whereby RFI × location interactions
18
399 suggested that many RFI effects were specific for the geographical location (Tables 4-6).
400 Although sex-related clustering of intestinal samples was not observed when using weighted
401 UniFrac analysis (Fig. 1F), RFI effects and RFI × location interactions differed between
402 sexes.
403 Specifically, the ceca of low RFI females comprised lower species richness (Chao1) and
404 evenness (Shannon and Simpson) compared to high RFI females, but only at L2 but not at L1
405 (P < 0.05; Table 3). Low RFI males contained an ileal microbiota of lower evenness as
406 indicated by the Shannon index (P < 0.05) and a fecal community of greater species richness
407 (Chao1, P < 0.10) compared to high RFI males at both geographical locations.
408 Differences in the bacterial abundances that were associated with low and high RFI
409 chickens were detectable at the phylum (Table 4) and genus level but differed for males and
410 females (Tables 5 and 6). In females, a trend for cross-locational association with low RFI
411 was found for a low-abundance unclassified Lachnospiraceae genus in feces (P < 0.1; Table
412 5). In contrast, in males, taxa that were enriched in low RFI animals across geographical
413 locations were Ruminococcus (3.1% relative abundance) and the Lachnospiraceae genus
414 Coprococcus (0.2% relative abundance) in cecal digesta, and, also belonging to the
415 Lachnospiraceae family, Dorea in feces (<0.05% relative abundance; P < 0.05; Table 6).
416 Cross-locational association with high RFI was observed for the most abundant genus, an
417 unclassified Clostridiales genus, which was less abundant with low RFI compared to high
418 RFI in cecal digesta of males (P < 0.05; Table 6).
419
420 Table 4. Differences in the relative abundance (%) of bacterial phyla in intestinal digesta
421 and feces of low and high residual feed intake (RFI) broiler chickens raised at two
422 geographical locations (L).
L1c L2c P-Valued Low High Low High Phylum RFI RFI RFI RFI SEM RFI L RFI × L 19
Females Ileum Firmicutes 81.93a 53.50b 56.66ab 72.91ab 10.370 0.563 0.781 0.041 Proteobacteria 17.57b 46.28a 41.47ab 25.64ab 10.372 0.541 0.877 0.042 Cyanobacteria 0.004 0.02 0.95 0.42 0.366 0.485 0.079 0.460 Actinobacteria 0.01 0.03 0.74 0.37 0.277 0.541 0.063 0.497 Unclassified 0.10A 0.04 0.01B 0.08 0.032 0.901 0.466 0.066 Ceca Firmicutes 94.86 90.67 84.36 80.50 3.516 0.267 0.007 0.963 Tenericutes 1.60b 1.28b 2.25b 7.94a 0.911 0.007 <0.001 0.003 Bacteroidetes 0 0 1.16 1.63 0.354 0.519 <0.001 0.520 Actinobacteria 0 0 0.38 0.23 0.071 0.331 <0.001 0.332 Unclassified 0.11abB 0.11abB 0.05b 0.22aA 0.041 0.044 0.627 0.054 Feces Unclassified 0.34 0.26 0.10 0.18 0.083 0.999 0.075 0.337 Actinobacteria 0.008b 0.06b 0.23aA 0.06abB 0.057 0.284 0.062 0.060 Bacteroidetes 0b 0b 0.08a 0.02b 0.012 0.011 <0.001 0.014 Cyanobacteria 0.008b 0.009b 0.07a 0.005b 0.018 0.092 0.122 0.084
Males Ileum Cyanobacteria 0.003 0.01 0.38 0.27 0.152 0.724 0.042 0.708 Actinobacteria 0.06 0.09 0.26 0.21 0.092 0.903 0.089 0.686 Ceca Firmicutes 93.10 95.13 85.42 86.73 1.870 0.379 <0.001 0.849 Tenericutes 1.10 2.42 7.34 6.09 1.043 0.972 <0.001 0.226 Bacteroidetes 0 0 1.44 1.26 0.430 0.837 0.004 0.838 Actinobacteria 0 0 0.37 0.26 0.056 0.361 <0.001 0.359 Unclassified 0.11 0.12 0.16 0.20 0.036 0.536 0.065 0.610 Feces Tenericutes 0.45 0.01 3.58 0.51 0.873 0.058 0.051 0.130 Bacteroidetes 0 0 0.23 0.10 0.071 0.478 0.042 0.271 423 Data are presented as least-square means and pooled standard error of the mean (SEM).
424 a,b Different superscript letters within a row indicate significant difference (P ≤ 0.05).
425 A,B Different superscript capital letters within a row indicate a tendency (P ≤ 0.10).
426 c L1, University of Veterinary Medicine Vienna (Vienna, Austria); L2. Agri-Food and Biosciences Institute
427 (Hillsborough, Northern Ireland, UK).
428 d Intestinal site affected Firmicutes, Proteobacteria, Tenericutes, Bacteroidetes, unclassified phylum (P <
429 0.001), and Cyanobacteria (P < 0.05).
20
430
431 Changes in bacterial genera that were associated with low RFI only at L1 included the
432 high-abundance genus Turicibacter in ileal digesta of females (P < 0.10; Table 5) and males
433 (P < 0.05; Table 6). Also in both sexes at L1, feces contained less Acinetobacter phylotypes
434 with low RFI compared to high RFI (P < 0.05; Table 5 and 6). In addition, in females, high-
435 abundance Escherichia/Hafnia/Shigella and Streptococcus were less abundant with low RFI
436 in ileal digesta (P < 0.05; Table 5), whereas in males, the cecal community comprised more
437 Streptococcus with low RFI compared to high RFI at L1 (P < 0.05; Table 6).
438
439 Table 5. Differences in the relative abundance (%) of bacterial genera in intestinal digesta
440 and feces of low and high residual feed intake (RFI) female broiler chickens raised at two
441 geographical locations (L).
L1d L2d P-Value Low High Low High RFI × Genusc RFI RFI RFI RFI SEM RFI L L Ileum Turicibacter 55.37aA 24.78abB 9.32b 21.94abB 12.281 0.472 0.058 0.091 Escherichia/Hafnia/Shigella 15.91b 44.98a 35.49ab 14.85b 9.923 0.675 0.601 0.019 Lactobacillus 12.05 4.68 35.29 39.11 11.225 0.876 0.016 0.623 Streptococcus 0.69b 8.05a 0.46b 0.30b 1.548 0.029 0.016 0.023 Unclassified Clostridiaceae 2 0.16 0.31 0.80 1.08 0.364 0.551 0.064 0.864 Methylobacterium 0.004 0.01 1.22 0.65 0.509 0.584 0.081 0.573 Bacillus 0.006 0.02 0.46 0.16 0.173 0.412 0.096 0.371 Clostridium 0 0 0.07 0.06 0.021 0.849 0.020 0.503 Corynebacterium 0 0 0.02 0.07 0.016 0.059 0.025 0.169 Ceca Unclassified Ruminococcaceae 21.46 19.20 18.73 10.59 3.238 0.123 0.094 0.377 Anaerotruncus 7.29 8.39 0.63 1.75 2.016 0.590 0.003 0.999 Unclassified RF39 1.60b 1.28b 2.25b 7.94a 0.911 0.007 <0.001 0.003 Ruminococcus 1.92 2.15 4.60 4.32 0.529 0.967 <0.001 0.633 Unclassified Lachnospiraceae 2 0.63 0.56 2.36 1.29 0.545 0.311 0.034 0.370 Faecalibacterium 0.21 0.18 0.84 1.82 0.339 0.180 0.003 0.152 Bacillus 0.47 0.61 0.08 0.39 0.176 0.216 0.096 0.636 Streptococcus 0.32 0.64 0 0 0.160 0.061 0.059 0.980
21
Unclassified Clostridiaceae 2 0.004 0.005 0.23 0.03 0.069 0.157 0.079 0.150 Clostridium 0.03 0.04 0.004 0.009 0.011 0.441 0.020 0.744 Feces Turicibacter 7.99 3.39 17.16 32.19 7.653 0.503 0.020 0.212 Unclassified Clostridiales 1 18.18 12.73 4.11 0.89 5.337 0.426 0.022 0.837 Unclassified Ruminococcaceae 9.65 9.28 1.88 0.23 4.229 0.814 0.058 0.882 Streptococcus 4.12 5.88 0.45 1.29 1.853 0.491 0.035 0.807 Unclassified Clostridiales 2 0.15b 0.67b 6.57a 0.77b 1.817 0.159 0.085 0.094 Unclassified Clostridiaceae 2 0.09 0.17 2.79 1.30 0.514 0.185 <0.001 0.139 Ruminococcus 1.51 1.48 0.74 0.07 0.483 0.480 0.033 0.510 Acinetobacter 0.02b 1.74a 0.15b 0.12b 0.511 0.111 0.158 0.099 Oscillospira 0.82 0.76 0.29 0.04 0.272 0.566 0.028 0.731 Anaerotruncus 0.44 0.76 0.05 0.01 0.304 0.653 0.074 0.557 Unclassified Lachnospiraceae 2 0.28 0.19 0.41 0.02 0.124 0.060 0.883 0.243 Unclassified Peptostreptococcaceae 0.002 0.005 0.06 0.15 0.050 0.374 0.060 0.401 Pseudomonas 0.005b 0.004b 0.02a 0.003b 0.003 0.037 0.091 0.042 442 Data are presented as least-square means and pooled standard error of the mean (SEM).
443 a,b Different superscript letters within a row indicate significant difference (P ≤ 0.05).
444 A,B Different superscript capital letters within a row indicate a tendency (P ≤ 0.10).
445 c The coverage of analyzed bacterial genera accounted for 99.02% of all sequences.
446 d L1, University of Veterinary Medicine Vienna (Vienna, Austria); L2. Agri-Food and Biosciences Institute
447 (Hillsborough, Northern Ireland, UK).
448
449 Genera associated with low RFI at L2 differed from those at L1 and were an
450 unclassified Clostridiales genus and Pseudomonas in feces of female chickens (P < 0.05;
451 Table 5). Moreover, in females, high RFI was associated with the abundance of an
452 unclassified RF39 genus in cecal digesta (P < 0.05; Table 5). In males, in turn, low-
453 abundance Faecalibacterium in cecal digesta and an unclassified Clostridiaceae genus in
454 feces were enriched with low RFI (P < 0.05; Table 6).
455
22
456 Table 6. Differences in the relative abundance (%) of bacterial genera in intestinal
457 digesta and feces of low and high residual feed intake (RFI) male broiler chickens raised
458 at two geographical locations (L).
L1d L2d P-Value Low High Low High RFI × Genusc RFI RFI RFI RFI SEM RFI L L Ileum Lactobacillus 16.78b 48.70ab 57.13a 34.36ab 13.658 0.740 0.348 0.054 Turicibacter 37.96a 7.51b 6.22b 28.58ab 9.499 0.673 0.578 0.009 Streptococcus 3.88 5.04 0.08 0.71 1.835 0.631 0.034 0.886 Klebsiella 1.88a 0.19b 0.05b 0.57ab 0.559 0.302 0.206 0.056 Methylobacterium 0.006 0.003 0.40 0.39 0.225 0.976 0.091 0.985 Pseudomonas 0 0 0.08 0.06 0.036 0.713 0.091 0.844 Ceca Unclassified Clostridiales 1 45.62 59.38 60.66 63.48 3.878 0.040 0.019 0.168 Unclassified Ruminococcaceae 23.01a 15.99bA 9.66bB 10.59b 2.327 0.199 <0.001 0.097 Anaerotruncus 8.72 11.32 1.36 1.26 2.010 0.538 <0.001 0.506 Unclassified RF39 1.10 2.42 7.34 6.09 1.043 0.972 <0.001 0.226 Ruminococcus 2.83 1.47 4.28 3.57 0.460 0.031 <0.001 0.479 Faecalibacterium 0c 0c 2.29a 1.06b 0.313 0.120 <0.001 0.026 Bacillus 1.20 0.83 0.15 0.21 0.296 0.594 0.008 0.466 Streptococcus 1.05a 0.35b 0b 0b 0.165 0.024 <0.001 0.074 Unclassified Christensenellaceae 0.26 0.20 0.64 0.48 0.101 0.280 0.002 0.653 Coprococcus 0.24 0.16 0.17 0.12 0.032 0.050 0.131 0.626 Unclassified Clostridiales 2 0.24 0.17 0.11 0.12 0.031 0.358 0.006 0.190 Clostridium 0.03 0.04 0.006 0.03 0.009 0.142 0.076 0.361 Feces Lactobacillus 10.09 16.10 7.39 28.56 7.918 0.096 0.542 0.346 Unclassified Ruminococcaceae 8.53 5.45 2.55 1.88 2.563 0.471 0.072 0.642 Acinetobacter 0.51b 4.51a 0.12b 0.12b 0.955 0.044 0.018 0.044 Unclassified RF39 0.45 0.10 3.60 0.51 0.873 0.058 0.051 0.130 Klebsiella 2.10 2.18 0.04 0.05 1.089 0.967 0.063 0.973 Unclassified Clostridiales 2 0.19 0.09 1.30 1.91 0.509 0.618 0.007 0.488 Unclassified Clostridiaceae 2 0.20b 0.05b 0.16b 1.11a 0.272 0.154 0.070 0.050 Faecalibacterium 0 0 0.74 0.61 0.300 0.967 0.046 0.704 Anaerotruncus 0.57 0.53 0.12 0.08 0.193 0.844 0.025 0.993 Unclassified Lachnospiraceae 1 0.42 0.12 0.41 0.23 0.131 0.078 0.700 0.668 Blautia 0.04 0.02 0.14 0.16 0.067 0.994 0.087 0.747 Dorea 0.04 0.02 0.07 0.02 0.017 0.026 0.277 0.527
23
Unclassified Peptostreptococcaceae 0 0 0.01 0.03 0.006 0.493 0.009 0.169 459 Data are presented as least-square means and pooled standard error of the mean (SEM).
460 a,b Different superscript letters within a row indicate significant difference (P ≤ 0.05).
461 A,B Different superscript capital letters within a row indicate a tendency (P ≤ 0.10).
462 c The coverage of analyzed bacterial genera accounted for 99.02% of all sequences.
463 d L1, University of Veterinary Medicine Vienna (Vienna, Austria); L2. Agri-Food and Biosciences Institute
464 (Hillsborough, Northern Ireland, UK).
465
466 Relationships among bacteria and RFI and performance across
467 geographical locations
468 Correlation analysis was performed between bacterial taxa at genus and species level,
469 and the FE and performance variables (RFI, TFI, TBWG and FCR; Tables 7, S3 and S4
470 Tables). From the bacteria that could be taxonomically assigned at family level, most
471 relationships were with members of Turicibacteraceae, Lactobacillaceae, Enterococcaceae,
472 Ruminococcaceae, Lachnospiraceae and several families from the Proteobacteria phylum.
473 Correlation analysis confirmed our results for common variation in RFI-associated bacterial
474 genera across geographical locations, whereby more correlations with high-abundance and
475 low-abundance genera and species were found for TFI, TBWG and FCR than for RFI across
476 all intestinal sites and both sexes (Table 7, S3 and S4 Tables). There were 5, 11, 11 and 12
477 significant correlations between bacterial genera and chicken’s RFI, TFI, TBWG and FCR (P
478 < 0.05), respectively, irrespective of the sex. At species level, we found 12 positive and 12
479 negative correlations between RFI and OTUs across all intestinal sites and both sexes (S3 and
480 S4 Tables). However, most correlations were with OTUs that showed only low similarity to
481 their closest type strain by using the Greengenes 16S rRNA gene database
482 (http://greengenes.lbl.gov/). Correspondingly, only eight OTUs could be taxonomically
483 assigned to their closest type strain with >95% similarity. Those were, in females, one
24
484 Enterobacter-OTU (OTU212, relative abundance <0.5%) in ileal digesta that correlated
485 negatively with chicken’s RFI and two Lactobacillus crispatus-OTUs (OTU4 and OTU8,
486 relative abundance >0.5%) in feces that correlated positively with chicken’s RFI (P < 0.05).
487 In males, two Eubacterium-OTUs (OTU84 and OTU574) and one Clostridium leptum-OTU
488 (OTU281) in cecal digesta correlated positively with chicken’s RFI, whereas one Clostridium
489 hylemonae-OTU (OTU215) and one Turicibacter-OTU (OTU288) in feces correlated
490 negatively with RFI (<0.5% relative abundance; P < 0.05). By contrast, 30 positive and 63
491 negative correlations between FCR and OTUs were observable across sexes and intestinal
492 sites (S3 and S4 Tables).
493
25
494 Table 7. Selected genera correlating to feed efficiency and performance traits in low and high residual feed intake (RFI) female and male
495 chickens (P < 0.05) across geographical locations and by intestinal site.
Genusa RFI TFI TBWG FCR n Mean SE Lower 95% CI Upper 95% CI 5th Pctl 95th Pctl Females Ileum Turicibacter ns -0.53 ns -0.40 31 30.02 6.55 16.64 43.40 0.03 97.15 Escherichia/Hafnia/Shigella ns 0.37 0.36 ns 31 27.90 5.25 17.18 38.62 0.06 83.90 Streptococcus ns ns 0.40 ns 31 2.70 0.96 0.74 4.65 0 14.42 Enterococcus ns 0.41 ns ns 31 0.15 0.06 0.02 0.28 0 1.12 Ceca Unclassified Ruminococcaceae ns ns ns -0.42 31 17.56 1.69 14.10 21.01 6.52 37.33 Anaerotruncus ns ns 0.41 ns 31 5.11 1.11 2.84 7.37 0.22 20.93 Unclassified RF39 ns ns ns 0.56 31 3.25 0.66 1.90 4.60 0.03 9.81 Ruminococcus ns ns ns 0.60 31 3.04 0.33 2.37 3.71 1.02 6.78 Unclassified Lachnospiraceae 1 ns 0.38 ns ns 31 1.72 0.37 0.96 2.49 0.08 8.64 Faecalibacterium ns ns ns 0.49 31 0.72 0.20 0.31 1.13 0 2.77 Dorea ns 0.38 ns ns 31 0.25 0.05 0.16 0.35 0.009 0.97 Feces Unclassified Clostridiales 1 ns ns ns -0.40 32 9.69 2.80 3.97 15.40 0.14 55.18 Unclassified Ruminococcaceae ns ns ns ns 32 5.73 2.13 1.38 10.08 0.03 26.07 Lactobacillus 0.36 ns ns 0.47 32 4.94 1.61 1.66 8.23 0.009 27.70 Unclassified Clostridiales 2 -0.33 ns -0.05 ns 32 1.65 0.96 -0.30 3.60 0.006 8.53 Ruminococcus ns ns 0.33 -0.36 32 1.00 0.25 0.49 1.51 0.01 4.57 Unclassified Clostridiaceae 1 ns ns -0.35 ns 32 0.77 0.54 -0.33 1.87 0 4.16
26
Males Ileum Enterococcus ns -0.33 -0.36 ns 37 0.72 0.37 -0.04 1.48 0 8.68 Unclassified Clostridiaceae 2 ns ns ns 0.34 37 0.37 0.12 0.13 0.61 0 2.52 Ceca Unclassified Clostridiales1 ns ns ns 0.36 37 57.38 2.18 52.96 61.79 31.96 79.33 Ruminococcus -0.34 ns ns ns 37 3.07 0.28 2.50 3.64 0.82 6.37 Coprococcus ns ns ns -0.36 37 0.17 0.02 0.14 0.21 0.05 0.39 Feces Unclassified Clostridiales 1 ns -0.33 ns ns 37 17.66 3.95 9.65 25.67 0.08 67.48 Lactobacillus ns 0.33 ns ns 37 15.31 4.02 7.15 23.48 0.006 95.03 Acinetobacter 0.34 0.34 0.45 ns 37 1.28 0.55 0.17 2.40 0 11.86 Proteus ns ns -0.41 0.35 37 0.52 0.39 -0.26 1.30 0 2.02 Pseudomonas ns 0.36 0.34 ns 37 0.46 0.34 -0.23 1.15 0 4.78 Enterococcus ns -0.32 -0.35 ns 37 0.32 0.13 0.06 0.59 0 2.57 Dorea -0.41 ns ns ns 37 0.04 0.01 0.02 0.06 0 0.20 496 a ns, not significant; RFI, residual feed intake; TFI, total feed intake; TBWG, total body weight gain; FCR, feed conversion ratio; SE, standard error; CI, confidence interval; Pctl,
497 percentile.
27
498 Predicted microbial functions related to FE
499 In order to identify whether relationships between bacterial taxa and FE would be
500 reflected in FE-associated variation in metabolic functions, predicted metagenome
501 functionality of the ileal, cecal and fecal microbiota was inferred using the PICRUSt package
502 and the KEGG database. Because our focus was on cross-locational FE- and performance-
503 associated variation in predicted metabolic functions, data were only analyzed by correlation
504 analysis. Across sexes, 24 significant correlations between RFI and KEGG pathway
505 abundances existed mainly in cecal digesta and feces, particularly in feces of males, whereas
506 they were absent in ileal digesta of both sexes (Fig. 3A and 3B; S5 and S6 Tables). Those
507 correlated pathways included amino acid, fatty acid and vitamin metabolism, cellular
508 signaling and interaction and cell metabolism. However, 86 relationships between FCR and
509 KEGG pathways could be established especially in cecal digesta and fewer in ileal digesta
510 and feces of both sexes (S5 and S6 Tables). In cecal digesta, the FCR correlated with
511 pathways especially in relation to amino acid, carbohydrate and lipid metabolism, vitamin
512 synthesis as well as to the bacterial cell metabolism. Moreover, TFI and TBWG showed
513 positive and negative correlations to amino acid, carbohydrate, vitamin and xenobiotics
514 metabolism mainly in ileal digesta of females, whereas in males most correlations were found
515 in feces (S5 and S6 Tables).
516 When correlating KEGG pathways with bacterial genera abundances that were both
517 associated with RFI, one positive relation in cecal digesta of males (S8 Table) as well as in
518 feces 21 negative and 24 positive associations in males (S9 Table) and six negative and three
519 positive associations in females (S10 Table) were found across geographical locations.
520
521 Discussion
28
522 Previous studies demonstrated associations between chicken’s intestinal microbiota
523 composition and FE, but similar inter- and intra-study FE-associated bacterial profiles were
524 hardly discernible [5,7,8]. Here, the ileal, cecal and fecal bacterial profiles of chickens ranked
525 on RFI from two geographical locations were characterized together in order to expand our
526 knowledge on RFI-associated microbiota profiles as targets for nutritional intervention. The
527 latter can be only successful if bacteria associated with good FE (low RFI or FCR) are
528 identifiable for multiple environments. Despite using different hatcheries, six different
529 batches and preparing our diets locally, the intestinal microbiota was mostly similar at both
530 geographical locations and only differed in very-low abundance bacteria in the present study.
531 This finding differed from previous observations of different underlying microbiota when
532 chickens were raised in different environments [7,9,10]. Nevertheless, differences in the
533 bacterial structure and abundances at six weeks of age existed, indicating that the
534 geographical location had modified the actual bacterial abundances.
535 RFI-associated variation in the ileal, cecal and fecal microbiota and predicted metabolic
536 functions was detectable at both geographical locations. However, cross-locational
537 relationships with chicken’s RFI could be mainly established with low-abundance OTUs. In
538 contrast to hens where relationships between RFI and bacteria emphasized an important role
539 of the cecum for chicken’s FE [8], we found more cross-locational RFI-relationships between
540 RFI and OTUs and predicted metabolic functions in feces than in ileal or cecal digesta. The
541 ceca are the site of the greatest intestinal fermentation in chickens [28] and more efficient
542 fermentation may yield more energy for the host [29]. Due to the short transit time in the
543 colon, the identified bacterial FE-associations were therefore likely less important for host
544 nutrient and energy assimilation and the intestinal immune response compared to the FE-
545 assocations found in ileal or cecal digesta. The fecal microbiota composition is mainly
546 determined by the periodic emptying of the microbiota from the ileum and ceca [15].
547 Therefore, the intestinal origin is a main determinant for the chicken fecal microbiota 29
548 composition and likely explains the absence of clear clustering of fecal samples from ileal and
549 cecal samples in the PCoA plot [15]. Nevertheless, our results also support that the cecal and
550 fecal RFI-associated microbiota cannot be applied to the bacterial community in the upper
551 digestive tract of chickens [8]. Likewise, RFI-associated bacteria were different in males and
552 females, indicating that FE-associated bacterial profiles cannot be transferred from one sex to
553 the other.
554 Irrespective of the sex, more cross-locational associations between bacteria of low and
555 high abundance and TFI, TBWG and FCR were observed in the present study, supporting
556 interactions between the bacterial community and the host in the small and large intestines.
557 Accordingly, negative relationships between FCR and predicted functions for amino acid,
558 carbon and fatty acid metabolism may indicate a role of the ileal microbiota in nutrient
559 acquisition for the host. As simple ratio trait, the FCR accounted for the slower growth of
560 chickens from L2 compared to chickens from L1, which was apparent throughout all replicate
561 batches and for both sexes. As per definition, the RFI was independent of the differences in
562 growth performance between the two geographical locations. This led to our observation that
563 low RFI chickens from L2 had a comparable FCR value as high RFI chickens from L1.
564 Therefore, our data illustrate the importance to carefully select the FE metric when aiming to
565 characterize FE-related microbiota profiles. For the present chicken populations, the FCR may
566 have better reflected cross-locational physiological and microbial differences than the RFI.
567 Because different selection strategies for FE (e.g. FCR, AME or RFI) were previously applied
568 [5,7,8,30], this may have contributed to the inter-study variation in FE-associated bacterial
569 taxa. This assumption is supported by findings in cattle where correlations between efficiency
570 parameters and bacterial genera abundances differed depending on the FE metric used (i.e.,
571 FCR vs. RFI) [31].
572 Most bacteria showing cross-locational RFI-associations belonged to the two
573 predominating phyla Firmicutes and Proteobacteria, which is in general accordance with 30
574 previous findings [7,8,32]. Nevertheless, one important bacterial phylum for energy-
575 harvesting, the Bacteroidetes, was almost absent in the current chicken populations. Its fecal
576 abundance has been previously linked to high FCR and high RFI phenotypes in chickens
577 [5,8]. We detected high numbers of Bacteroidetes bacteria in intestinal digesta using the same
578 DNA extraction procedure in the past [16,17]. Since also others reported a lack of Bacteroides
579 bacteria in the intestine of chickens [33], the present observation may be due to the
580 experimental surroundings and the missing contact with the maternal microbiota [9].
581 Simply due to their dominance, taxonomic groups of high abundance may have a
582 greater impact on nutrient assimilation of the host and host physiology than single low-
583 abundance phylotypes [34]. However, low-abundance bacteria should not be seen
584 individually, but as an integral part of the bacterial community, which interacts with the host
585 [8]. Evidence from other ecological habitats corroborates that low-abundance microorganisms
586 can markedly shape the ecosystem which they inhabit [35]. Furthermore, the absolute
587 bacterial abundance will affect chicken’s digestive efficiency [34]. For this reason, the greater
588 abundance of bacteria in ileal digesta of chickens from L1 compared to chickens from L2 may
589 have yielded more energy from fermentation for the host and may help explaining the cross-
590 locational variation in growth performance. Though, RFI-associated differences in bacterial
591 numbers in ileum, ceca and feces played a negligible role in the present study. When
592 comparing the relative microbiota composition between RFI ranks, separately for females and
593 males, only the Lactobacillus genus and two Lactobacillus crispatus-OTUs in feces were
594 indicative for high RFI in females at both geographical locations. Moreover, the relative
595 abundances of the two Lactobacillus crispatus-OTUs in cecal digesta and feces were also
596 indicative for low TBWG and high FCR values, respectively, again only in females, thereby
597 confirming previous findings [30,33]. Lactobacillus have been shown the ability to activate
598 both innate defense mechanisms and adaptive immune responses in chicken’s intestine
599 [29,36,37]. Despite these potential benefits for intestinal health, activation of the immune 31
600 system is generally energetically costly to the host and may alter partitioning of energy and
601 nutrients away from growth towards processes that support the immune system response,
602 which, in turn, may decrease chicken’s FE [38]. This may be supported by the positive
603 correlation between Lactobacillus and predicted cellular antigens in feces of male chickens.
604 Moreover, despite the short transit time in chicken’s intestine, fermentation of dietary
605 residuals by Lactobacillus in the distal intestinal regions may have reduced SCFA generation
606 as indicated by the negative association between this genus and predicted carbon fixation and
607 fatty acid biosynthesis pathways in feces.
608 By contrast, other high-abundance genera, such as Turicibacter and
609 Escherichia/Hafnia/Shigella, in ileal digesta showed no or contrasting RFI-associations
610 between the two geographical locations and might indicate that both genera may inhabit
611 similar intestinal niches. Nevertheless, correlations between Turicibacter and
612 Escherichia/Hafnia/Shigella and TFI suggested that these two genera probably affected the
613 host physiology or the feeding behavior of the host. Previous findings were inconsistent on
614 the relationship between Escherichia/Shigella and chicken’s growth performance. Some
615 authors reported a negative association between ileal Escherichia/Shigella and nutrient
616 digestibility and weight gain [39], whereas others found positive associations between
617 Escherichia/Shigella in feces and chicken’s FCR [2,5]. This discrepancy may be linked to the
618 actual strains colonizing chicken’s intestine. Accordingly, some strains of Escherichia coli
619 may confer beneficial physiological activities by reducing intestinal inflammation,
620 increasing host innate immune functions or protecting the intestinal barrier against
621 pathogens [40], which may have consequences for TBWG. Due to their predominance in
622 ileal digesta and despite the short transit time in chicken’s small intestine,
623 Escherichia/Hafnia/Shigella probably contributed to SCFA production in the distal small
624 intestine of our chickens, thereby affecting host physiology and feeding behavior [37].
625 Overall, the ileal abundance of Turicibacter was unusually high in the current chicken 32
626 populations as opposed to previous studies showing that the ileal community is dominated by
627 Lactobacillus spp. [41]. These inconsistent findings may be related to the specific housing
628 conditions and the lack of maternal microbiota transfer post-hatch [9] in the present study.
629 In males, mainly RFI-associations with low-abundance bacterial taxa existed in the
630 present study. Accordingly, Ruminococcus in cecal digesta and Dorea in feces were indicative
631 for good FE. The genus Ruminococcus is known for its ability to degrade complex
632 carbohydrates and thus may have contributed to an improved degradation of dietary fiber
633 [42]. In addition, metabolic cross-feeding of fermentation metabolites (e.g., hydrogen, lactate
634 and substrate degradation products) is a widespread feature of various Clostridiales bacteria
635 [42] and may have indirectly promoted the abundance of the Ruminococcus and Dorea. Both
636 genera produce butyrate, which is the preferred energy source of colonocytes and has anti-
637 inflammatory properties [29]. Furthermore, in males, gram-negative Acinetobacter in feces
638 was indicative for high RFI and thus for poor FE. Since gram-negative bacteria express
639 cellular antigens, e.g. lipopolysaccharides, recognition of these antigens can lead to an
640 enhanced innate immune activation with release of cytokines from mast cells [29]. Increased
641 production of pro-inflammatory cytokines can impair the intestinal integrity and epithelial
642 function and subsequently reduce animal’s FE [43, 44]. The RFI-associated predicted
643 microbial functions agreed with the compositional relationships in feces of males indicating
644 that genes related to carbohydrate, energy and amino acid metabolism were related to low
645 RFI, whereas a high abundance of genes for bacterial signaling and interaction (i.e. cellular
646 antigens) increased chicken’s RFI. When relating the RFI-associated predicted metabolic
647 functions to RFI-associated bacterial taxa, those were mainly correlated with genera
648 belonging to the family Lachnospiraceae in feces of males and female chickens and
649 Ruminococcus in the ceca of males. Accordingly, those genera appeared to have promoted the
650 FE of their host, by stimulating fatty acid, amino acid and vitamin synthesis. Although these
33
651 RFI-associations were observed in feces, due to the short intestinal transit time in chickens it
652 is more likely that these associations reflected the situation in chicken’s colon.
653 In cattle, a less diverse, but more specialized rumen microbiome was proposed to
654 promote the energy acquisition of the host, thereby improving animal´s FE [45]. Consistently,
655 low RFI males and females had a less diverse microbiota in the ileum and ceca, respectively.
656 By contrast, communities with higher species richness are thought to use limiting resources
657 more efficiently [46] which may explain the current cross-locational association between
658 increased species richness in feces and low RFI in males. These findings also coincide with
659 the greater number of cross-locational relationships between chicken’s RFI and fecal bacteria
660 and predicted metabolic functions. As a result of the lower feed intake, the decreased
661 intestinal filling probably slowed down the intestinal passage, which may have promoted the
662 establishment of a more species rich community in the colon. Concurrently, undigested
663 fibrous feed particles may have been degraded more efficiently, thereby improving chicken’s
664 FE. Previous studies also reported lower diversity and increased species richness for the
665 intestinal and fecal microbiota, but the affected intestinal sites differed from the present study
666 [7,8].
667 In conclusion, the present results showed that RFI-associated bacterial profiles could be
668 identified across different geographical locations, whereby consortia of mostly low-
669 abundance taxa in the ileum, ceca and feces may play a role for FE in chickens. Although
670 more RFI-related taxa were found in chicken feces, those may be less important for host
671 metabolism and immunity. Therefore, mainly bacterial FE-associations found in ileal and
672 cecal digesta may serve as useful targets for dietary strategies. Different RFI-associated
673 profiles in the microbiota between sexes further suggested that data from one sex could not
674 reflect the RFI-associations of the other sex. Moreover, the low similarity of many OTUs to
675 reference phylotypes especially in the ceca, however, often impeded the prediction of their
676 specific role in energy homeostasis and interaction with the host. Present correlations also 34
677 suggested that FCR may better mirror physiological and microbial FE-associated differences
678 across geographical locations.
679
680 Supporting Information
681 S1 Table. Dietary ingredients and chemical composition of diets (on as-fed basis).
682 S2 Table. Differences in the relative abundance (%) of most abundant genera in ileal
683 and cecal digesta and feces of broiler chickens raised at two geographical locations.
684 S3 Table. Most abundant operational taxonomic units (OTU) correlating to feed
685 efficiency and performance traits in female chickens across two geographical locations
686 and by intestinal site.
687 S4 Table. Most abundant operational taxonomic units (OTU) correlating to feed
688 efficiency and performance traits in male chickens across two geographical locations
689 and by intestinal site.
690 S5 Table. Selected KEGG pathways correlating to feed efficiency and performance
691 traits in female chickens across two geographical locations and by intestinal site.
692 S6 Table. Selected KEGG pathways correlating to feed efficiency and performance
693 traits in male chickens across two geographical locations and by intestinal site.
694 S7 Table. BLAST search results for most abundant operational taxonomic units (OTU)
695 correlated to feed efficiency and performance traits in intestinal digesta and feces of
696 broiler chickens raised at two geographical locations.
697 Table S8. Pearson’s correlations between selected bacterial genera and KEGG pathways
698 in cecal digesta associated with the residual feed intake in male and female chickens
699 across two geographical locations.
35
700 Table S9. Pearson’s correlations between selected bacterial genera and KEGG pathways
701 in feces associated with the residual feed intake in male chickens across two
702 geographical locations.
703 Table S10. Pearson’s correlations between selected bacterial genera and KEGG
704 pathways in feces associated with the residual feed intake in female chickens across two
705 geographical locations.
706
707 Acknowledgements
708 The technical staff at the Institute of Animal Nutrition and Functional Plant Compounds
709 (University of Veterinary Medicine Vienna) and at the Agri-Food and Biosciences Institute
710 are gratefully thanked for their care of the animals and expertise when conducting the
711 experiment and for laboratory assistance.
712
713 Financial Disclosure
714 This project (ECO-FCE) has received funding from the European Union’s Seventh
715 Framework Programme for research, technological development and demonstration (grant no.
716 311794). The funders had no role in study design, data collection and analysis, decision to
717 publish, or preparation of the manuscript.
718
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858 Figure captions
859 Fig. 1. Venn diagrams and β-diversity plot. (A) Venn diagram showing the number of
860 shared operational taxonomic units between two geographical locations (L1 and L2); (B)
861 Venn diagram showing the number of shared operational taxonomic units between ileum,
862 ceca and feces; principal coordinate analysis plots of weighted UniFrac analysis colored by
863 (C) intestinal site; D) batch and geographical location; E) RFI ranks; and F) sex. Rarefaction
864 depth of 10,000 sequences per sample removed 9 samples from the dataset; for ileum, n = 31
865 low RFI chickens and n = 30 high RFI chickens; for ceca, n = 32 low RFI chickens and n = 35
866 high RFI chickens; for feces, n = 33 low RFI chickens and n = 35 high RFI chickens.
867
868 Fig. 2. Relative abundance (%) of the most abundant phyla in ileal and cecal digesta and
869 feces of broiler chickens raised at two geographical locations.
870
871 Fig. 3. Selected KEGG pathways correlating to residual feed intake (RFI) in chickens
872 across two geographical locations and by intestinal site; A) females and B) males.
43
Table S1. Dietary ingredients and analyzed chemical composition of experimental diets at the two geographical different locations.
Starter (day 1-10 Grower (day 11- Finisher (day 22-42 Item of life) 21 of life) of life) Ingredient, g/kg as-fed Corn 612 660 679 Soybean meal 331 282 260 Soybean oil 17.5 20.6 27.7 Limestone flour 11.0 9.8 7.0 Salt 2.0 2.0 2.3 Dicalcium phosphate 16.1 15.0 13.4 Premixa-c 11.0 11.0 10.0 Total 1000 1000 1000 Analyzed chemical composition, g/kg DM, at L1d Dry matter 926 923 914 Crude protein 243 223 216 Crude ash 69 62 55 Analyzed chemical composition, g/kg DM, at L2d Dry matter 908 902 902 Crude protein 221 219 209 Crude ash 94 81 72 a Provided per kilogram of starter diet: vitamin A as retinyl acetate, 13,000 IU; vitamin D3 as cholecalciferol,
5,000 IU; vitamin E as alpha-tocopherol-acetate, 80 IU; vitamin K, 3 mg; thiamin, 3 mg; riboflavin, 9 mg; pyridoxine, 4 mg; vitamin B12, 20 µg; biotin, 0.15 mg; calcium pantothenate, 15 mg; nicotinic acid, 60 mg; folic acid, 2 mg; 500 mg choline chloride; methionine, 3,405 mg; threonine, 745 mg; lysine, 2,812 mg; I, 1 mg as calcium iodate; Se, 0.35 mg as sodium selenite; Fe, 40 mg as ferrous sulphate; Mo, 0.5 mg as sodium molybdate;
Mn, 100 mg as manganous oxide; Cu, 15 mg as copper sulfate; Zn, 100 mg as zinc oxide. b Provided per kilogram of grower diet: vitamin A as retinyl acetate, 10,000 IU; vitamin D3 as cholecalciferol,
5,000 IU; vitamin E as alpha-tocopherol-acetate, 50 IU; vitamin K, 3 mg; thiamin, 2 mg; riboflavin, 8 mg; pyridoxine, 3 mg; vitamin B12, 15 µg; biotin, 0.12 mg; calcium pantothenate, 12 mg; nicotinic acid, 50 mg; folic acid, 2 mg; 400 mg choline chloride; methionine, 3,018 mg; threonine, 726 mg; lysine, 2,831 mg; I, 1 mg as calcium iodate; Se, 0.35 mg as sodium selenite; Fe, 40 mg as ferrous sulphate; Mo, 0.5 mg as sodium molybdate;
Mn, 100 mg as manganous oxide; Cu, 15 mg as copper sulfate; Zn, 100 mg as zinc oxide. c Provided per kilogram of finisher diet: vitamin A as retinyl acetate, 10,000 IU; vitamin D3 as cholecalciferol,
5,000 IU; vitamin E as alpha-tocopherol-acetate, 50 IU; vitamin K, 3 mg; thiamin, 2 mg; riboflavin, 6 mg; pyridoxine, 3 mg; vitamin B12, 15 µg; biotin, 0.12 mg; calcium pantothenate, 10 mg; nicotinic acid, 50 mg; folic acid, 1 mg; 350 mg choline chloride; methionine, 2,514 mg; threonine, 361 mg; lysine, 1,779 mg; I, 1 mg as calcium iodate; Se, 0.35 mg as sodium selenite; Fe, 40 mg as ferrous sulphate; Mo, 0.5 mg as sodium molybdate;
Mn, 100 mg as manganous oxide; Cu, 15 mg as copper sulfate; Zn, 100 mg as zinc oxide. d L1, University of Veterinary Medicine Vienna (Vienna, Austria); L2. Agri-Food and Biosciences Institute
(Hillsborough, Northern Ireland, UK). Table S2. Differences in the relative abundance (%) of most abundant genera in ileal and cecal digesta and feces of broiler chickens raised at two geographical locations.
Genus Relative abundance (%)d SEM P-Value
Ileum Ceca Feces Unclassified Clostridiales1 3.0c 55.7a 13.8b 1.82 <0.001 Escherichia/Hafnia/Shigella 26.4b 6.4c 39.1a 2.95 <0.001 Lactobacillus 31.16a 0.13c 10.15b 2.945 <0.001 Turicibacter 24.04a 1.39c 14.01b 2.647 <0.001 Unclassified Ruminococcaceae 1.43c 15.84a 5.02b 0.930 <0.001 Streptococcus 2.39a 0.35b 3.20a 0.581 0.003 Anaerotruncus 0.07b 5.10a 0.31b 0.404 <0.001 Unclassified RF39 0.20c 3.92a 0.88b 0.270 <0.001 Unclassified Clostridiales 2 3.23a 0.18b 1.32b 0.639 0.003 Ruminococcus 0.28c 3.13a 0.99b 0.143 <0.001 Klebsiella 0.70abB 0.08b 1.59aA 0.384 0.013 Oscillospira 0.19c 1.49a 0.49b 0.083 <0.001 Unclassified Lachnospiraceae 1 0.12b 1.56a 0.32b 0.119 <0.001 Staphylococcus 0B 0B 1.52A 0.584 0.115 Acinetobacter 0.52ab 0b 0.89a 0.249 0.035 Faecalibacterium 0.12b 0.90a 0.29b 0.097 <0.001 Unclassified Lachnospiraceae 2 0.06bB 0.90a 0.26bA 0.085 <0.001 Unclassified Clostridiaceae 1 0.23ab 0 b 0.89a 0.291 0.075 Unclassified Clostridiaceae 2 0.47a 0.08b 0.66a 0.108 <0.001 Bacillus 0.20b 0.49a 0.09b 0.088 0.004 Enterococcus 0.46a 0b 0.22ab 0.125 0.018 Unclassified Christensenellaceae 0b 0.42a 0.05b 0.028 <0.001 Proteus 0.04B 0B 0.33A 0.123 0.148 Corynebacterium 0.03 0 0.38 0.172 0.211 Blautia 0.02bB 0.26a 0.08bA 0.025 <0.001 Pseudomonas 0.04 0 0.23 0.105 0.237 Methylobacterium 0.31a 0b 0.02b 0.074 0.004 Coprococcus 0c 0.17a 0.09b 0.018 <0.001 Dorea 0b 0.22a 0.05b 0.016 <0.001 Clostridium 0.13A 0.02B 0.11 0.052 0.130 Unclassified Peptostreptococcaceae 0.21A 0B 0.03 0.077 0.129 Data are presented as least-square means and pooled standard error of the mean (SEM).
For ileum and ceca, n = 31 females, and n = 37 males; for feces, n = 32 females, and n = 37 males. a,b,c Different superscript letters within the row indicate significant difference (P ≤ 0.05).
A,B Different superscript capital letters within the row indicate a tendency (P ≤ 0.10). d The most abundant genera accounted for 99.02% of all sequences. Table S3. Most abundant operational taxonomic units (OTU) correlating to feed efficiency and performance traits in female chickens across two geographical locations and by intestinal site.
a-c d,e OTU Taxonomy (Genus) n RFI TFI TBWG FCR Mean SE Lower 95% CI Upper 95% CI 5th Pctl 95th Pctl Commented [s1]: einige OTUs noch abgeändert, Ileum damit alle einheitlich der BLAST Taxonomy entsprechen OTU1 Escherichia/Hafnia/Shigella 31 ns 0.36 ns ns 23.90 4.56 14.58 33.22 0.05 75.43 OTU2 Turicibacter 31 ns -0.53 ns -0.40 27.05 5.90 15.01 39.09 0.03 85.74
OTU11 Streptococcus 31 ns ns 0.42 ns 1.83 0.62 0.56 3.10 0 9.60 Qiime hatte diese teilweise als andere Genera OTU15 Escherichia/Hafnia/Shigella 31 ns ns 0.36 ns 1.36 0.25 0.84 1.87 0 4.31 klassifiziert OTU35 Turicibacter 31 ns -0.55 ns -0.38 0.85 0.18 0.48 1.23 0 2.76 OTU40 Turicibacter 31 ns -0.52 ns -0.47 0.88 0.31 0.24 1.51 0 5.30 OTU62 Streptococcus 31 ns ns 0.42 ns 0.27 0.09 0.09 0.44 0 1.25 OTU81 Enterobacter 31 ns 0.38 ns ns 0.20 0.04 0.12 0.28 0 0.69 OTU138 Escherichia/Hafnia/Shigella 31 ns ns 0.38 ns 0.06 0.01 0.04 0.08 0 0.17 OTU148 Escherichia/Hafnia/Shigella 31 ns ns 0.39 ns 0.06 0.01 0.03 0.08 0 0.22 OTU166 Turicibacter 31 ns -0.40 ns ns 0.08 0.02 0.04 0.11 0 0.23 OTU174 Turicibacter 31 ns -0.51 ns -0.42 0.07 0.02 0.04 0.10 0 0.24 OTU209 Turicibacter 31 ns -0.49 ns -0.43 0.06 0.01 0.03 0.08 0 0.20 OTU212 Enterobacter 31 -0.40 ns ns ns 0.02 0.01 0.002 0.04 0 0.19 OTU220 Escherichia/Hafnia/Shigella 31 ns ns 0.36 ns 0.03 0.01 0.01 0.04 0 0.09 OTU253 Turicibacter 31 ns -0.51 ns -0.36 0.04 0.01 0.02 0.06 0 0.14 OTU276 Turicibacter 31 ns -0.49 ns ns 0.03 0.01 0.02 0.05 0 0.10 OTU298 Escherichia/Hafnia/Shigella 31 ns 0.30 0.38 ns 0.02 0.003 0.01 0.02 0 0.06 OTU323 Turicibacter 31 ns -0.52 ns ns 0.02 0.01 0.01 0.04 0 0.08 OTU352 Turicibacter 31 ns -0.42 ns ns 0.03 0.01 0.01 0.04 0 0.09 Ceca OTU4 Lactobacillus 31 ns ns -0.40 ns 0.08 0.03 0.02 0.15 0 0.60 OTU5 [Clostridium] 31 ns ns ns -0.36 5.27 1.09 3.04 7.49 0.11 17.18 OTU6 [Acetanaerobacterium] 31 ns ns ns -0.53 6.58 1.24 4.05 9.12 0.004 20.85 OTU7 Anaerotruncus 31 ns ns 0.43 -0.36 4.48 1.07 2.30 6.66 0.03 19.70 OTU8 Lactobacillus 31 ns ns -0.40 ns 0.05 0.02 0.01 0.08 0 0.38 OTU17 [Clostridium] 31 0.41 ns ns 0.49 3.10 0.66 1.74 4.45 0 9.06 OTU19 [Clostridium] 31 ns -0.43 ns ns 1.77 0.39 0.97 2.57 0.002 6.00 OTU22 [Clostridium] 31 ns ns ns -0.40 1.71 0.59 0.51 2.91 0 4.76 OTU23 [Clostridium] 31 ns 0.38 ns 0.61* 1.01 0.39 0.22 1.80 0.002 5.02 OTU32 [Clostridium] 31 0.38 0.39 ns 0.68* 0.65 0.24 0.15 1.14 0 3.31 OTU33 [Ethanologenbacterium] 31 ns ns ns -0.47 1.24 0.22 0.79 1.69 0.02 4.08 OTU46 Faecalibacterium 31 ns ns ns 0.51 0.62 0.20 0.22 1.03 0 2.64 OTU61 Unclassified Clostridiaceae 31 ns ns ns -0.39 0.45 0.17 0.09 0.80 0 2.40 OTU69 [Clostridium] 31 ns -0.48 ns ns 0.24 0.06 0.12 0.36 0 1.16 OTU73 [Acetanaerobacterium] 31 ns ns ns 0.38 0.28 0.06 0.17 0.39 0.004 0.96 OTU75 Ruminococcus[Clostridium] 31 ns ns ns 0.59* 0.29 0.05 0.18 0.39 0 1.02 OTU94 Clostridium 31 ns ns 0.47 -0.40 0.21 0.05 0.11 0.31 0.004 0.80 OTU108 [Clostridium] 31 ns -0.38 ns -0.37 0.17 0.04 0.08 0.25 0.004 0.54 OTU117 Clostridium 31 ns ns 0.50 ns 0.19 0.06 0.06 0.32 0 0.87 OTU131 Oscillospira[Oscillibacter] 31 ns ns ns 0.36 0.13 0.02 0.09 0.18 0.004 0.37 OTU141 Clostridium 31 ns ns -0.36 0.47 0.14 0.03 0.07 0.21 0.01 0.61 OTU142 [Clostridium] 31 ns ns ns -0.39 0.11 0.04 0.03 0.19 0 0.30 OTU150 Clostridium 31 ns ns ns 0.37 0.13 0.02 0.08 0.18 0 0.42 OTU161 Unclassified Clostridiaceae 31 ns ns -0.53 0.49 0.05 0.02 0.005 0.10 0 0.25 OTU164 Clostridium 31 ns ns 0.39 ns 0.09 0.02 0.06 0.13 0 0.22 OTU165 [Spiroplasma] 31 ns ns -0.41 0.47 0.09 0.03 0.03 0.14 0 0.49 OTU167 [Dehalobacterium] 31 ns ns 0.44 ns 0.09 0.01 0.07 0.12 0.004 0.23 OTU173 Ruminococcus[Clostridium] 31 ns 0.36 ns 0.48 0.09 0.02 0.06 0.12 0.01 0.33 OTU179 [Clostridium] 31 ns -0.36 ns ns 0.07 0.02 0.04 0.10 0 0.26 OTU182 Clostridium 31 ns ns ns 0.36 0.08 0.03 0.02 0.14 0 0.60 OTU188 [Clostridium] 31 0.40 ns ns 0.60* 0.06 0.02 0.02 0.09 0 0.30 OTU190 Eubacterium 31 ns ns ns 0.42 0.07 0.02 0.03 0.10 0.002 0.29 OTU192 [Clostridium] 31 ns ns ns 0.38 0.06 0.01 0.04 0.08 0 0.15 OTU205 CoprococcusHespellia 31 ns ns ns -0.39 0.04 0.01 0.02 0.05 0.002 0.13 OTU210 [Acetanaerobacterium] 31 ns -0.39 ns -0.63* 0.06 0.01 0.04 0.08 0 0.19 OTU217 [Clostridium] 31 ns ns ns -0.37 0.04 0.01 0.02 0.07 0 0.23 OTU224 [Clostridium] 31 ns ns -0.54 0.48 0.06 0.02 0.01 0.10 0 0.48 OTU228 [Spiroplasma] 31 0.37 ns ns ns 0.07 0.02 0.03 0.11 0 0.29 OTU233 [Clostridium] 31 -0.40 ns ns ns 0.05 0.01 0.02 0.07 0 0.20 OTU295 [Clostridium] 31 ns -0.39 ns -0.37 0.03 0.01 0.02 0.04 0 0.07 OTU308 [Clostridium] 31 ns ns ns -0.51 0.03 0.01 0.02 0.04 0 0.11 OTU325 [Clostridium] 31 ns ns ns -0.40 0.03 0.004 0.02 0.03 0 0.06 OTU329 Clostridium 31 ns 0.38 ns ns 0.04 0.01 0.02 0.06 0 0.12 OTU341 Clostridium 31 ns ns ns 0.45 0.03 0.007 0.02 0.04 0.002 0.13 OTU343 Anaerotruncus 31 ns ns 0.46 -0.39 0.03 0.01 0.02 0.04 0 0.09 OTU348 Ruminococcus 31 ns ns 0.43 ns 0.03 0.01 0.02 0.04 0 0.07 OTU349 Sporobacter 31 ns 0.37 ns 0.53 0.02 0.003 0.02 0.03 0.004 0.05 OTU362 [Clostridium] 31 ns -0.54 ns -0.63* 0.02 0.005 0.01 0.03 0 0.08 OTU415 [Clostridium] 31 ns 0.38 ns ns 0.02 0.005 0.01 0.03 0 0.10 OTU437 [Clostridium] 31 ns ns 0.39 -0.38 0.02 0.004 0.01 0.03 0 0.09 OTU456 [Photorhabdus] 31 ns ns -0.38 0.38 0.01 0.003 0.004 0.02 0 0.05 OTU459 [Clostridium] 31 ns -0.51 ns ns 0.01 0.003 0.01 0.02 0 0.05 OTU466 [Clostridium] 31 ns ns 0.37 ns 0.02 0.01 0.004 0.03 0 0.10 OTU469 [Clostridium] 31 ns ns ns -0.40 0.01 0.003 0.01 0.02 0 0.05 OTU500 [Clostridium] 31 ns ns ns -0.37 0.02 0.004 0.01 0.02 0 0.04 OTU504 DoreaClostridium 31 ns 0.42 ns ns 0.02 0.004 0.01 0.03 0 0.08 OTU519 BlautiaRuminococcus 31 ns 0.46 ns ns 0.01 0.003 0.005 0.02 0 0.04 OTU520 [Clostridium] 31 ns -0.65* ns -0.46 0.01 0.003 0.01 0.02 0 0.05 OTU553 [Clostridium] 31 0.48 ns -0.39 0.66* 0.02 0.004 0.01 0.02 0 0.09 OTU610 Ruminococcus[Clostridium] 31 ns ns ns 0.44 0.02 0.005 0.01 0.03 0 0.08 OTU634 [Clostridium] 31 ns ns ns -0.37 0.01 0.002 0.01 0.02 0 0.04 OTU725 DoreaClostridium 31 ns 0.38 ns ns 0.01 0.002 0.01 0.02 0 0.04
Feces OTU4 Lactobacillus 32 0.42 ns -0.37 0.50 1.17 0.65 -0.16 2.49 0 7.80 OTU5 [Clostridium] 32 ns ns ns -0.44 1.41 0.53 0.34 2.48 0.006 7.40 OTU8 Lactobacillus 32 0.40 ns -0.39 0.51 0.59 0.32 -0.06 1.24 0 3.58 OTU18 [Blautia] 32 ns ns ns -0.36 0.35 0.10 0.13 0.56 0 2.02 OTU19 [Clostridium] 32 ns ns ns -0.39 0.38 0.15 0.08 0.68 0 2.42 OTU22 [Clostridium] 32 ns ns 0.43 -0.47 0.56 0.16 0.23 0.88 0 2.52 OTU25 [Clostridium] 32 ns ns 0.45 ns 0.28 0.09 0.09 0.47 0 1.91 OTU38 [Clostridium] 32 -0.37 ns ns ns 0.13 0.06 0.01 0.24 0 0.92 OTU40 Turicibacter 32 ns -0.36 ns -0.38 0.10 0.05 -0.002 0.20 0 0.93 OTU52 [Clostridium] 32 ns ns ns -0.43 0.05 0.01 0.02 0.08 0 0.24 OTU99 [Clostridium] 32 ns -0.37 ns ns 0.04 0.02 -0.003 0.08 0 0.27 OTU173 [Clostridium]Ruminococcus 32 ns ns ns -0.40 0.02 0.01 0.01 0.03 0 0.10 OTU259 [Escherichia/Hafnia/Shigella] 32 ns -0.37 ns ns 0.03 0.01 0.01 0.05 0 0.13 OTU294 [Escherichia/Hafnia/Shigella] 32 ns ns ns -0.36 0.02 0.004 0.01 0.03 0 0.07 a Statistical comparisons were made for those OTUs that showed a relative abundance > 0.01% per intestinal site. Commented [s2]: noch extra erwähnen, dass nur die OTUs der meist abundanten OTUs, die in mehr b Only significant (P ≤ 0.05) correlations are presented. * P ≤ 0.001. als der Hälfte der Tiere in beiden Locations per gut site vorkamen analysiert wurden? cns, not significant; RFI, residual feed intake; TFI, total feed intake; TBWG, total body weight gain; FCR, feed conversion ratio; SE, standard error; CI, confidence interval; Pctl, percentile. dTaxonomic classification based on the Greengenes 16S rRNA gene database (greengenes.lbl.gov/cgi-bin/nph-index.cgi). eSequences not distinguishable between Escherichia, Hafnia and Shigella.
Table S4. Most abundant operational taxonomic units (OTU) correlating to feed efficiency and performance traits in male chickens across two geographical locations and by intestinal site.
OTUa-c Taxonomy (Genus)d,e n RFI TFI TBWG FCR Mean SE Lower 95% CI Upper 95% CI 5th Pctl 95th Pctl Ileum OTU18 [Blautia] 37 ns ns ns 0.35 0.09 0.04 0.01 0.17 0 0.92 OTU54 Enterobacter 37 ns ns -0.40 ns 1.08 0.72 -0.38 2.54 0 13.13 OTU125 Enterococcus 37 ns ns -0.36 ns 0.56 0.37 -0.19 1.30 0 8.56 OTU619 Pseudidiomarina 37 ns ns -0.40 ns 0.01 0.01 0.002 0.02 0 0.04
Ceca OTU7 Anaerotruncus 37 ns ns 0.37 ns 4.80 1.15 2.46 7.13 0.06 19.46 OTU14 [Clostridium] 37 ns -0.34 ns ns 1.94 0.45 1.02 2.86 0.002 6.16 OTU29 [Clostridium] 37 ns ns ns 0.47 1.93 0.75 0.41 3.45 0 12.93 OTU32 [Clostridium] 37 ns ns -0.43 ns 1.05 0.27 0.50 1.59 0 5.33 OTU43 Eubacterium 37 ns -0.33 ns ns 0.80 0.23 0.33 1.28 0.02 3.05 OTU49 [Clostridium] 37 ns ns ns 0.35 0.95 0.23 0.47 1.42 0 4.53 OTU61 Unclassified Clostridiaceae 37 ns ns ns -0.37 0.39 0.14 0.11 0.67 0 3.42 OTU62 Streptococcus 37 ns ns ns -0.38 0.04 0.01 0.02 0.06 0 0.18 OTU84 Eubacterium 37 0.37 0.46 ns ns 0.25 0.07 0.11 0.39 0.01 0.96 OTU87 [Clostridium] 37 ns ns ns -0.42 0.29 0.07 0.16 0.43 0 1.28 OTU91 [Heliorestis] 37 ns ns ns 0.36 0.32 0.12 0.08 0.56 0 1.44 OTU94 Clostridium 37 ns ns ns -0.35 0.23 0.05 0.13 0.33 0 1.01 OTU99 [Clostridium] 37 ns ns 0.45 ns 0.23 0.06 0.12 0.34 0 0.94 OTU108 [Clostridium] 37 ns ns 0.37 ns 0.19 0.03 0.14 0.25 0.01 0.51 OTU128 [Clostridium] 37 ns ns 0.34 ns 0.15 0.04 0.07 0.22 0 0.78 OTU141 Clostridium 37 ns ns -0.38 ns 0.11 0.02 0.07 0.16 0.01 0.38 OTU152 [Clostridium] 37 ns ns ns 0.44 0.15 0.04 0.07 0.22 0 0.93 OTU157 Oscillospira[Oscillibacter] 37 ns ns ns -0.34 0.10 0.03 0.04 0.15 0 0.32 OTU161 Unclassified Clostridiaceae 37 ns ns -0.37 ns 0.16 0.05 0.07 0.25 0 0.78 OTU167 [Dehalobacterium] 37 ns ns 0.34 ns 0.08 0.01 0.06 0.11 0 0.23 OTU188 [Clostridium] 37 ns ns -0.35 ns 0.08 0.02 0.05 0.11 0 0.32 OTU205 CoprococcusHespellia 37 ns ns 0.33 -0.46 0.03 0.01 0.02 0.04 0 0.10 OTU210 [Acetanaerobacterium] 37 ns ns ns -0.40 0.06 0.01 0.03 0.08 0 0.24 OTU237 Anaerotruncus 37 ns ns 0.39 -0.34 0.06 0.01 0.03 0.09 0 0.27 OTU238 Eubacterium 37 ns -0.37 ns ns 0.04 0.01 0.02 0.07 0 0.24 OTU252 [Eubacterium] 37 ns -0.33 -0.45 ns 0.04 0.01 0.02 0.06 0 0.11 OTU274 [Ruminococcus] 37 ns ns 0.44 -0.40 0.04 0.01 0.02 0.07 0 0.21 OTU281 RuminococcusClostridium 37 0.41 ns ns ns 0.01 0.002 0.01 0.02 0 0.05 OTU285 [Clostridium] 37 ns ns 0.33 -0.42 0.04 0.01 0.02 0.06 0 0.17 OTU289 [Clostridium] 37 0.38 ns 0.43 ns 0.03 0.01 0.02 0.04 0 0.10 OTU292 Unclassified Clostridiaceae 37 ns ns 0.33 ns 0.04 0.01 0.02 0.06 0 0.18 OTU308 [Clostridium] 37 ns ns ns -0.34 0.03 0.01 0.02 0.05 0 0.12 OTU343 Anaerotruncus 37 ns ns 0.34 -0.36 0.03 0.01 0.01 0.04 0 0.15 OTU346 [Anaerotruncus] 37 ns ns 0.38 ns 0.03 0.01 0.02 0.05 0 0.15 OTU362 [Clostridium] 37 ns ns ns -0.37 0.02 0.005 0.01 0.03 0 0.07 OTU368 Ruminococcus 37 ns ns ns -0.34 0.02 0.004 0.01 0.02 0 0.07 OTU388 [Clostridium] 37 ns ns 0.37 ns 0.02 0.004 0.01 0.03 0 0.10 OTU392 [Clostridium] 37 ns -0.33 ns ns 0.02 0.003 0.01 0.03 0 0.06 OTU470 [Clostridium] 37 ns ns -0.38 ns 0.02 0.002 0.01 0.02 0 0.04 OTU482 [Clostridium]Ruminococcus 37 ns ns -0.45 ns 0.02 0.004 0.01 0.02 0 0.08 OTU507 [Clostridium] 37 ns ns 0.38 ns 0.01 0.003 0.01 0.02 0 0.06 OTU515 [Clostridium] 37 0.33 ns ns ns 0.02 0.003 0.01 0.02 0 0.05 OTU574 Eubacterium 37 0.59* 0.41 ns ns 0.01 0.002 0.01 0.02 0 0.03 OTU654 [Ruminococcus] 37 ns -0.34 ns ns 0.01 0.002 0.01 0.01 0 0.04
Feces OTU5 [Clostridium] 37 ns ns ns -0.40 2.22 0.77 0.66 3.79 0.003 15.19 OTU12 [Clostridium] 37 -0.34 ns ns ns 0.96 0.25 0.45 1.47 0.004 4.67 OTU22 [Clostridium] 37 ns ns ns -0.37 0.41 0.16 0.08 0.74 0 3.77 OTU31 [Spiroplasma] 37 -0.35 ns ns ns 0.23 0.06 0.11 0.36 0 0.91 OTU32 [Clostridium] 37 ns ns -0.33 ns 0.74 0.37 -0.01 1.49 0 8.35 OTU33 [Ethanologenbacterium] 37 ns ns ns -0.34 0.10 0.03 0.03 0.17 0 0.65 OTU40 Turicibacter 37 ns ns ns -0.37 0.11 0.06 -0.01 0.23 0 1.52 OTU55 [Clostridium] 37 -0.36 ns ns ns 0.16 0.05 0.05 0.27 0 0.97 OTU77 Clostridium 37 ns ns ns -0.39 0.04 0.01 0.02 0.06 0 0.25 OTU94 Clostridium 37 ns ns ns -0.43 0.05 0.02 0.02 0.09 0 0.38 OTU103 ClostridiumRuminococcus 37 ns ns ns -0.37 0.06 0.02 0.03 0.10 0 0.38 OTU104 [Clostridium] 37 -0.37 ns ns ns 0.07 0.02 0.03 0.11 0 0.39 OTU125 Enterococcus 37 ns ns -0.37 ns 0.15 0.10 -0.06 0.35 0 0.88 OTU126 Eubacterium 37 ns ns ns -0.33 0.05 0.02 0.01 0.10 0 0.38 OTU143 [Clostridium] 37 -0.34 ns ns ns 0.02 0.01 0.002 0.03 0 0.17 OTU145 OscillospiraOscillibacter 37 ns ns ns -0.37 0.03 0.01 0.02 0.05 0 0.15 OTU151 Ruminococcus[Clostridium] 37 ns ns ns -0.35 0.04 0.01 0.02 0.06 0 0.21 OTU167 [Dehalobacterium] 37 ns ns ns -0.35 0.01 0.003 0.005 0.02 0 0.05 OTU203 CoprococcusAnaerostipes 37 ns ns ns 0.38 0.04 0.03 -0.02 0.10 0 0.25 OTU205 CoprococcusHespellia 37 ns ns ns -0.33 0.03 0.01 0.01 0.05 0 0.26 OTU207 CoprococcusHespellia 37 ns ns ns -0.34 0.03 0.01 0.01 0.04 0 0.17 OTU215 DoreaClostridium 37 -0.42 ns ns ns 0.01 0.004 0.01 0.02 0 0.05 OTU224 [Clostridium] 37 -0.34 ns ns ns 0.02 0.004 0.01 0.02 0 0.06 OTU259 [Escherichia/Hafnia/Shigella] 37 -0.33 ns ns ns 0.02 0.005 0.01 0.03 0 0.08 OTU288 Turicibacter 37 -0.34 ns ns ns 0.01 0.004 0.01 0.02 0 0.08 a Statistical comparisons were made for those OTUs that showed a relative abundance > 0.01% per intestinal site. Commented [s1]: noch extra erwähnen, dass nur die OTUs der meist abundanten OTUs, die in mehr b Only significant (P ≤ 0.05) correlations are presented. * P ≤ 0.001. als der Hälfte der Tiere in beiden Locations per gut site vorkamen analysiert wurden? cns, not significant; RFI, residual feed intake; TFI, total feed intake; TBWG, total body weight gain; FCR, feed conversion ratio; SE, standard error; CI, confidence interval; Pctl, percentile. dTaxonomic classification based on the Greengenes 16S rRNA gene database (greengenes.lbl.gov/cgi-bin/nph-index.cgi). eSequences not distinguishable between Escherichia, Hafnia and Shigella.
Table S5. Selected KEGG pathways correlating to feed efficiency and performance traits in female chickens across two geographical locations and by intestinal site.
Lower Upper 95% 95% 5th 95th COG Pathwaya-c KEGG Pathway n RFI TFI TBWG FCR Mean SE CI CI Pctl Pctl Ileum Amino acid metabolism Amino acid metabolism 31 ns ns ns -0.48 0.26 0.01 0.23 0.28 0.16 0.39 Amino acid metabolism Cysteine and methionine metabolism 31 ns ns ns -0.45 0.96 0.02 0.91 1.00 0.70 1.10 Amino acid metabolism Glycine, serine and threonine metabolism 31 ns ns 0.36 ns 0.85 0.03 0.79 0.90 0.55 0.95 Amino acid metabolism Histidine metabolism 31 ns ns ns -0.44 0.47 0.03 0.40 0.54 0.21 0.87 Amino acid metabolism Tyrosine metabolism 31 ns -0.56 ns -0.49 0.43 0.01 0.41 0.45 0.36 0.56 Amino acid metabolism Valine, leucine and isoleucine biosynthesis 31 ns 0.39 0.46 ns 0.60 0.03 0.54 0.66 0.30 0.83 Biosynthesis of other secondary Novobiocin biosynthesis 31 ns ns 0.41 ns 0.12 0.01 0.11 0.14 0.02 0.17 metabolites Biosynthesis of other secondary Phenylpropanoid biosynthesis 31 ns -0.51 ns -0.46 0.08 0.01 0.06 0.10 0.01 0.22 metabolites Carbohydrate metabolism C5-Branched dibasic acid metabolism 31 ns ns 0.41 ns 0.26 0.02 0.23 0.30 0.05 0.35 Carbohydrate metabolism Carbohydrate metabolism 31 ns -0.56 ns ns 0.13 0.01 0.12 0.15 0.06 0.21 Carbohydrate metabolism Glycolysis / Gluconeogenesis 31 ns ns -0.39 ns 1.32 0.05 1.22 1.42 1.02 1.82 Carbohydrate metabolism Pentose and glucuronate interconversions 31 ns ns ns -0.37 0.44 0.03 0.38 0.49 0.24 0.72 Carbohydrate metabolism Pentose phosphate pathway 31 ns -0.40 ns ns 0.91 0.02 0.87 0.95 0.79 1.06 Carbohydrate metabolism Pyruvate metabolism 31 ns ns ns -0.57* 1.21 0.01 1.18 1.23 1.09 1.29 Carbohydrate metabolism Starch and sucrose metabolism 31 ns -0.48 -0.36 ns 0.88 0.04 0.80 0.96 0.48 1.22 Cell motility Bacterial chemotaxis 31 ns 0.43 ns ns 0.42 0.04 0.35 0.50 0.07 0.73 Cell motility Flagellar assembly 31 ns 0.47 0.40 ns 0.54 0.05 0.43 0.65 0.06 1.10 Digestive system Peptidases 31 ns ns -0.39 ns 1.95 0.05 1.84 2.05 1.66 2.52 Energy metabolism Oxidative phosphorylation 31 ns 0.49 ns 0.39 1.16 0.05 1.06 1.27 0.84 1.65 Energy metabolism Sulfur metabolism 31 ns ns 0.40 ns 0.29 0.01 0.27 0.32 0.20 0.38 Folding, sorting and degradation Chaperones and folding catalysts 31 ns 0.47 ns 0.44 1.11 0.02 1.08 1.15 0.95 1.26 Glycan biosynthesis and Glycosaminoglycan degradation 31 ns ns -0.38 ns 0.01 0.003 0.01 0.02 0.002 0.05 metabolism Glycan biosynthesis and Other glycan degradation 31 ns -0.50 ns -0.38 0.06 0.01 0.05 0.07 0.02 0.14 metabolism Infectious diseases: Bacterial Vibrio cholerae pathogenic cycle 31 ns ns 0.38 ns 0.11 0.01 0.10 0.13 0.05 0.18 Lipid metabolism Arachidonic acid metabolism 31 ns -0.45 ns -0.45 0.05 0.01 0.04 0.06 0.01 0.13 Lipid metabolism Fatty acid biosynthesis 31 ns ns 0.47 ns 0.48 0.01 0.45 0.51 0.34 0.61 Lipid metabolism Glycerolipid metabolism 31 ns -0.46 -0.36 ns 0.45 0.01 0.42 0.47 0.35 0.54 Lipid metabolism Linoleic acid metabolism 31 ns -0.37 ns ns 0.04 0.01 0.02 0.05 0.003 0.13 Lipid metabolism Lipid biosynthesis proteins 31 ns ns 0.39 ns 0.60 0.01 0.58 0.63 0.46 0.71 Lipid metabolism Lipid metabolism 31 ns -0.42 ns ns 0.16 0.01 0.15 0.17 0.09 0.21 Lipid metabolism Synthesis and degradation of ketone bodies 31 ns ns -0.41 ns 0.08 0.01 0.07 0.10 0.04 0.16 Membrane transport ABC transporters 31 ns -0.41 ns -0.42 4.39 0.10 4.20 4.59 3.73 5.41 Membrane transport Cell motility and secretion 31 ns ns ns 0.48 0.27 0.01 0.25 0.30 0.16 0.36 Membrane transport Secretion system 31 ns 0.36 ns ns 2.13 0.09 1.95 2.31 1.19 2.76 Membrane transport Transporters 31 ns -0.52 ns ns 8.28 0.17 7.93 8.63 6.51 9.54 Metabolism of cofactors and Biotin metabolism 31 ns ns 0.39 ns 0.13 0.01 0.11 0.15 0.02 0.22 vitamins Metabolism of cofactors and Folate biosynthesis 31 ns ns 0.40 ns 0.38 0.01 0.35 0.41 0.25 0.51 vitamins Metabolism of cofactors and Pantothenate and CoA biosynthesis 31 ns 0.48 0.42 ns 0.54 0.02 0.50 0.58 0.29 0.70 vitamins Metabolism of cofactors and Porphyrin and chlorophyll metabolism 31 ns ns 0.36 ns 0.71 0.05 0.60 0.81 0.25 1.20 vitamins Metabolism of cofactors and Retinol metabolism 31 ns -0.46 ns ns 0.05 0.004 0.04 0.06 0.01 0.09 vitamins Metabolism of cofactors and Vitamin B6 metabolism 31 ns ns 0.41 ns 0.19 0.01 0.17 0.21 0.08 0.26 vitamins Metabolism of other amino acids Cyanoamino acid metabolism 31 ns -0.55 ns -0.43 0.25 0.02 0.22 0.29 0.15 0.51 Metabolism of other amino acids Phosphonate and phosphinate metabolism 31 ns ns 0.38 ns 0.05 0.004 0.04 0.06 0.01 0.09 Metabolism of other amino acids Selenocompound metabolism 31 ns -0.36 ns -0.37 0.42 0.005 0.41 0.43 0.37 0.46 Metabolism of other amino acids Taurine and hypotaurine metabolism 31 ns -0.54 ns ns 0.15 0.01 0.13 0.17 0.11 0.29 Metabolism of terpenoids and Polyketide sugar unit biosynthesis 31 ns -0.41 ns ns 0.13 0.01 0.11 0.15 0.07 0.26 polyketides Replication and repair Replication, recombination and repair 31 ns 0.39 ns ns 0.98 0.02 0.93 1.03 0.73 1.14 proteins Signaling molecules and interaction Cellular antigens 31 ns - ns -0.36 0.05 0.01 0.04 0.06 0.01 0.14 0.59 * Translation RNA transport 31 ns -0.41 ns ns 0.18 0.01 0.16 0.20 0.11 0.31 Translation Ribosome biogenesis in eukaryotes 31 ns ns ns 0.48 0.06 0.001 0.06 0.06 0.05 0.07 Transport and catabolism Lysosome 31 ns ns -0.37 ns 0.02 0.003 0.01 0.02 0.002 0.05 Xenobiotics biodegradation and Chloroalkane and chloroalkene degradation 31 ns -0.47 ns ns 0.19 0.01 0.17 0.21 0.12 0.33 metabolism Xenobiotics biodegradation and Drug metabolism - other enzymes 31 ns -0.37 ns ns 0.34 0.01 0.31 0.36 0.26 0.47 metabolism Xenobiotics biodegradation and Ethylbenzene degradation 31 ns -0.42 ns -0.43 0.06 0.01 0.05 0.08 0.03 0.18 metabolism Xenobiotics biodegradation and Naphthalene degradation 31 ns -0.45 ns ns 0.17 0.01 0.15 0.20 0.11 0.33 metabolism Xenobiotics biodegradation and Nitrotoluene degradation 31 ns ns 0.38 ns 0.09 0.01 0.07 0.10 0.01 0.14 metabolism Xenobiotics biodegradation and Toluene degradation 31 ns 0.41 ns 0.36 0.18 0.01 0.15 0.21 0.03 0.27 metabolism
Ceca Amino acid metabolism Lysine biosynthesis 31 -0.46 ns ns -0.46 0.97 0.01 0.95 0.99 0.88 1.05 Amino acid metabolism Phenylalanine, tyrosine and tryptophan 31 -0.37 ns ns ns 0.85 0.01 0.84 0.87 0.79 0.94 biosynthesis Biosynthesis of other secondary Butirosin and neomycin biosynthesis 31 ns ns 0.37 ns 0.08 0.002 0.07 0.08 0.06 0.10 metabolites Carbohydrate metabolism C5-Branched dibasic acid metabolism 31 -0.40 ns ns ns 0.36 0.002 0.35 0.36 0.34 0.37 Cell motility Bacterial chemotaxis 31 ns ns ns -0.39 0.72 0.02 0.67 0.77 0.51 0.94 Energy metabolism Carbon fixation pathways in prokaryotes 31 ns -0.38 ns ns 1.14 0.01 1.12 1.15 1.05 1.19 Energy metabolism Methane metabolism 31 ns ns 0.42 -0.53 1.51 0.02 1.48 1.54 1.35 1.68 Folding, sorting and degradation Chaperones and folding catalysts 31 ns ns -0.38 0.38 1.01 0.01 0.99 1.03 0.92 1.10 Folding, sorting and degradation Protein folding and associated processing 31 ns ns ns 0.41 0.58 0.01 0.57 0.60 0.52 0.67 Lipid metabolism Glycerophospholipid metabolism 31 ns ns ns 0.52 0.60 0.01 0.58 0.62 0.52 0.69 Lipid metabolism Linoleic acid metabolism 31 ns ns 0.44 -0.39 0.08 0.004 0.07 0.09 0.05 0.14 Lipid metabolism Lipid biosynthesis proteins 31 -0.37 ns ns ns 0.67 0.004 0.66 0.68 0.64 0.72 Membrane transport ABC transporters 31 ns ns 0.40 -0.45 4.39 0.06 4.26 4.52 3.96 5.17 Metabolism of cofactors and Folate biosynthesis 31 ns ns ns 0.45 0.29 0.01 0.28 0.31 0.25 0.36 vitamins Metabolism of cofactors and Lipoic acid metabolism 31 0.37 ns ns 0.51 0.03 0.002 0.02 0.03 0.01 0.05 vitamins Metabolism of cofactors and Nicotinate and nicotinamide metabolism 31 ns ns ns 0.36 0.46 0.003 0.45 0.47 0.44 0.49 vitamins Metabolism of cofactors and Porphyrin and chlorophyll metabolism 31 ns ns 0.37 -0.40 1.07 0.02 1.04 1.11 0.92 1.26 vitamins Metabolism of cofactors and Riboflavin metabolism 31 ns ns -0.45 ns 0.24 0.01 0.23 0.25 0.18 0.28 vitamins Metabolism of other amino acids Glutathione metabolism 31 ns ns -0.37 0.40 0.18 0.01 0.16 0.19 0.12 0.28 Metabolism of other amino acids Taurine and hypotaurine metabolism 31 ns ns -0.47 0.40 0.11 0.001 0.11 0.12 0.10 0.13 Metabolism of other amino acids beta-Alanine metabolism 31 ns ns ns 0.49 0.14 0.01 0.13 0.15 0.10 0.21 Metabolism of terpenoids and Biosynthesis of ansamycins 31 ns ns 0.41 -0.43 0.16 0.01 0.15 0.17 0.11 0.23 polyketides Metabolism of terpenoids and Terpenoid backbone biosynthesis 31 ns -0.36 ns ns 0.66 0.01 0.65 0.68 0.57 0.71 polyketides Nucleotide metabolism Nucleotide metabolism 31 ns ns -0.37 ns 0.06 0.002 0.06 0.07 0.04 0.09 Replication and repair DNA repair and recombination proteins 31 ns ns -0.36 ns 3.27 0.03 3.22 3.32 3.04 3.53 Translation Ribosome Biogenesis 31 ns ns -0.39 ns 1.69 0.01 1.66 1.71 1.55 1.80 Translation Ribosome biogenesis in eukaryotes 31 ns ns -0.44 0.48 0.06 0.001 0.06 0.06 0.05 0.06 Xenobiotics biodegradation and Benzoate degradation 31 ns -0.37 ns ns 0.30 0.004 0.29 0.31 0.25 0.33 metabolism Xenobiotics biodegradation and Bisphenol degradation 31 ns ns 0.45 -0.38 0.09 0.004 0.08 0.10 0.06 0.15 metabolism Xenobiotics biodegradation and Chloroalkane and chloroalkene degradation 31 ns ns 0.45 -0.39 0.24 0.01 0.22 0.25 0.18 0.30 metabolism Xenobiotics biodegradation and Ethylbenzene degradation 31 ns ns ns -0.43 0.07 0.003 0.06 0.07 0.04 0.10 metabolism Xenobiotics biodegradation and Naphthalene degradation 31 ns ns 0.36 -0.38 0.17 0.003 0.17 0.18 0.15 0.20 metabolism Xenobiotics biodegradation and Nitrotoluene degradation 31 ns ns 0.40 -0.48 0.15 0.01 0.13 0.16 0.10 0.24 metabolism
Feces Amino acid metabolism Arginine and proline metabolism 32 ns ns 0.37 ns 1.11 0.03 1.05 1.16 0.89 1.41 Amino acid metabolism Phenylalanine, tyrosine and tryptophan 32 ns ns ns -0.44 0.72 0.01 0.70 0.75 0.57 0.84 biosynthesis Amino acid metabolism Valine, leucine and isoleucine biosynthesis 32 ns ns ns -0.36 0.70 0.01 0.67 0.73 0.56 0.87 Biosynthesis of other secondary Novobiocin biosynthesis 32 -0.35 ns ns ns 0.15 0.003 0.14 0.15 0.12 0.17 metabolites Biosynthesis of other secondary Tropane, piperidine and pyridine alkaloid 32 -0.38 ns ns ns 0.13 0.002 0.13 0.14 0.10 0.15 metabolites biosynthesis Carbohydrate metabolism C5-Branched dibasic acid metabolism 32 -0.41 ns 0.45 -0.59* 0.33 0.005 0.32 0.34 0.24 0.36 Carbohydrate metabolism Pyruvate metabolism 32 ns ns 0.37 ns 1.23 0.01 1.21 1.25 1.15 1.33 Energy metabolism Energy metabolism 32 ns ns ns -0.41 1.00 0.01 0.98 1.02 0.86 1.10 Lipid metabolism Lipid biosynthesis proteins 32 ns ns ns -0.37 0.63 0.01 0.62 0.65 0.57 0.70 Lipid metabolism Synthesis and degradation of ketone bodies 32 ns ns ns 0.41 0.05 0.003 0.05 0.06 0.03 0.09 Metabolism of cofactors and Vitamin B6 metabolism 32 ns ns ns -0.37 0.23 0.004 0.23 0.24 0.20 0.26 vitamins Metabolism of other amino acids D-Alanine metabolism 32 ns ns ns 0.53 0.12 0.003 0.11 0.12 0.08 0.16 Metabolism of other amino acids D-Glutamine and D-glutamate metabolism 32 ns ns ns 0.36 0.14 0.003 0.14 0.15 0.12 0.17 Metabolism of other amino acids Taurine and hypotaurine metabolism 32 ns ns ns 0.44 0.13 0.002 0.13 0.13 0.11 0.14 Metabolism of terpenoids and Prenyltransferases 32 ns ns ns 0.37 0.28 0.01 0.26 0.29 0.20 0.36 polyketides Signal transduction Signal transduction mechanisms 32 ns ns -0.37 0.37 0.65 0.01 0.63 0.67 0.58 0.72 Signaling molecules and interaction Ion channels 32 0.38 ns ns 0.40 0.03 0.002 0.03 0.04 0.01 0.05 Xenobiotics biodegradation and Ethylbenzene degradation 32 ns ns 0.40 ns 0.05 0.003 0.05 0.06 0.04 0.08 metabolism aStatistical comparisons were made for those pathways that showed a relative abundance > 0.01% per intestinal site. bOnly significant (P ≤ 0.05) correlations are presented. * P ≤ 0.001. cCOG, Clusters of Orthologous Groups of proteins; KEGG, Kyoto Encyclopedia of Genes and Genomes; ns, not significant; RFI, residual feed intake; TFI, total feed intake;
TBWG, total body weight gain; FCR, feed conversion ratio; SE, standard error; CI, confidence interval; Pctl, percentile.
Table S6. Selected KEGG pathways correlating to feed efficiency and performance traits in male chickens across two geographical locations and by intestinal site.
Lowe Upper TBW r 95% 95% 5th 95th COG Pathwaya-c KEGG Pathway n RFI TFI G FCR Mean SE CI CI Pctl Pctl Ileum Nucleotide metabolism Nucleotide metabolism 37 ns ns ns -0.34 0.12 0.01 0.11 0.14 0.05 0.18 Membrane transport Other ion-coupled transporters 37 ns -0.33 ns ns 1.69 0.03 1.63 1.76 1.37 2.00
Ceca Amino acid metabolism Amino acid metabolism 37 ns ns ns -0.44 0.20 0.01 0.19 0.22 0.15 0.27 Amino acid metabolism Amino acid related enzymes 37 ns ns ns 0.33 1.66 0.01 1.64 1.69 1.51 1.77 Amino acid metabolism Tyrosine metabolism 37 -0.37 ns ns -0.40 0.39 0.002 0.38 0.39 0.37 0.41 Amino acid metabolism Valine, leucine and isoleucine degradation 37 ns ns ns -0.41 0.22 0.01 0.20 0.23 0.13 0.29 Biosynthesis of other secondary Novobiocin biosynthesis 37 ns ns -0.33 ns 0.14 0.002 0.13 0.14 0.11 0.16 metabolites Biosynthesis of other secondary Phenylpropanoid biosynthesis 37 ns ns ns 0.34 0.12 0.005 0.11 0.13 0.06 0.17 metabolites Carbohydrate metabolism Ascorbate and aldarate metabolism 37 ns ns ns -0.39 0.10 0.005 0.09 0.11 0.06 0.15 Carbohydrate metabolism Butanoate metabolism 37 ns ns ns -0.43 0.82 0.01 0.80 0.85 0.72 0.96 Carbohydrate metabolism Citrate cycle (TCA cycle) 37 ns ns ns -0.33 0.64 0.01 0.62 0.66 0.56 0.75 Carbohydrate metabolism Glyoxylate and dicarboxylate metabolism 37 ns ns ns -0.40 0.56 0.01 0.54 0.58 0.44 0.67 Carbohydrate metabolism Inositol phosphate metabolism 37 ns ns 0.37 -0.36 0.10 0.005 0.09 0.11 0.07 0.17 Carbohydrate metabolism Pentose and glucuronate interconversions 37 ns ns ns -0.41 0.51 0.01 0.50 0.53 0.46 0.58 Carbohydrate metabolism Pyruvate metabolism 37 ns ns ns -0.39 1.22 0.01 1.21 1.24 1.17 1.32 Excretory system Proximal tubule bicarbonate reclamation 37 ns ns ns -0.36 0.02 0.001 0.02 0.02 0.01 0.03 Folding, sorting and degradation Chaperones and folding catalysts 37 ns ns ns 0.35 1.02 0.01 1.00 1.03 0.93 1.08 Folding, sorting and degradation Protein export 37 ns ns ns 0.39 0.68 0.005 0.67 0.69 0.63 0.73 Folding, sorting and degradation RNA degradation 37 ns ns ns 0.40 0.50 0.003 0.50 0.51 0.47 0.54 Folding, sorting and degradation Restriction enzyme 37 ns ns ns 0.34 0.22 0.005 0.21 0.23 0.18 0.29 Lipid metabolism Glycerophospholipid metabolism 37 ns ns -0.33 ns 0.59 0.01 0.58 0.61 0.51 0.65 Lipid metabolism Linoleic acid metabolism 37 ns ns 0.33 ns 0.08 0.005 0.07 0.09 0.06 0.15 Lipid metabolism Synthesis and degradation of ketone bodies 37 ns ns 0.34 -0.40 0.05 0.002 0.05 0.06 0.02 0.07 Membrane transport ABC transporters 37 ns ns 0.35 -0.33 4.40 0.06 4.27 4.52 4.01 5.26 Membrane transport Other ion-coupled transporters 37 ns ns ns -0.34 1.29 0.02 1.26 1.32 1.09 1.45 Metabolism of cofactors and vitamins One carbon pool by folate 37 ns ns ns 0.34 0.67 0.01 0.65 0.69 0.56 0.73 Metabolism of cofactors and vitamins Retinol metabolism 37 ns ns ns -0.36 0.02 0.001 0.02 0.02 0.01 0.04 Metabolism of other amino acids beta-Alanine metabolism 37 -0.34 ns ns ns 0.13 0.004 0.12 0.14 0.09 0.18 Metabolism of terpenoids and Limonene and pinene degradation 37 ns ns ns -0.33 0.10 0.004 0.09 0.11 0.07 0.15 polyketides Signal transduction Signal transduction mechanisms 37 ns ns ns -0.34 0.61 0.005 0.60 0.62 0.57 0.66 Signaling molecules and interaction Cellular antigens 37 -0.34 -0.37 ns ns 0.01 0.001 0.01 0.01 0.003 0.03 Translation Aminoacyl-tRNA biosynthesis 37 ns ns ns 0.34 1.45 0.02 1.41 1.48 1.27 1.61 Translation RNA transport 37 ns ns -0.37 ns 0.16 0.003 0.15 0.16 0.12 0.19 Xenobiotics biodegradation and Aminobenzoate degradation 37 ns ns 0.35 -0.39 0.11 0.004 0.10 0.12 0.08 0.16 metabolism Xenobiotics biodegradation and Benzoate degradation 37 ns ns ns -0.41 0.31 0.004 0.30 0.32 0.25 0.35 metabolism Xenobiotics biodegradation and Bisphenol degradation 37 ns ns 0.35 -0.34 0.09 0.005 0.08 0.10 0.06 0.15 metabolism Xenobiotics biodegradation and Ethylbenzene degradation 37 ns ns 0.33 -0.37 0.07 0.003 0.07 0.08 0.06 0.11 metabolism Xenobiotics biodegradation and Naphthalene degradation 37 ns ns ns -0.44 0.17 0.003 0.17 0.18 0.15 0.21 metabolism Xenobiotics biodegradation and Xylene degradation 37 ns ns -0.34 ns 0.08 0.003 0.07 0.08 0.04 0.10 metabolism
Feces Amino acid metabolism Arginine and proline metabolism 37 ns -0.40 ns ns 1.12 0.03 1.05 1.19 0.64 1.43 Amino acid metabolism Histidine metabolism 37 -0.33 -0.38 ns ns 0.49 0.02 0.45 0.54 0.18 0.72 Amino acid metabolism Phenylalanine, tyrosine and tryptophan 37 ns -0.39 ns ns 0.66 0.03 0.60 0.73 0.08 0.97 biosynthesis Amino acid metabolism Valine, leucine and isoleucine biosynthesis 37 -0.40 -0.44 ns ns 0.67 0.03 0.61 0.72 0.26 0.89 Carbohydrate metabolism C5-Branched dibasic acid metabolism 37 ns -0.39 ns ns 0.29 0.01 0.26 0.32 0.03 0.38 Carbohydrate metabolism Pyruvate metabolism 37 ns -0.39 ns ns 1.22 0.02 1.18 1.26 1.07 1.35 Drug resistance: Antimicrobial beta-Lactam resistance 37 ns 0.37 ns ns 0.03 0.003 0.03 0.04 0.001 0.09 Energy metabolism Carbon fixation pathways in prokaryotes 37 -0.36 -0.36 ns ns 1.07 0.01 1.04 1.10 0.89 1.21 Excretory system Proximal tubule bicarbonate reclamation 37 0.47 0.50 0.33 ns 0.04 0.003 0.03 0.04 0.01 0.06 Folding, sorting and degradation Chaperones and folding catalysts 37 ns 0.36 0.40 ns 1.10 0.01 1.08 1.13 0.97 1.22 Glycan biosynthesis and metabolism Glycosyltransferases 37 ns 0.37 ns ns 0.48 0.02 0.45 0.51 0.28 0.63 Lipid metabolism Fatty acid biosynthesis 37 -0.34 -0.46 ns ns 0.51 0.01 0.48 0.54 0.34 0.66 Membrane transport Cell motility and secretion 37 ns 0.48 0.33 ns 0.24 0.01 0.22 0.27 0.12 0.32 Membrane transport Phosphotransferase system (PTS) 37 ns 0.35 ns ns 1.09 0.07 0.95 1.24 0.27 2.06 Metabolism of cofactors and vitamins One carbon pool by folate 37 -0.33 ns ns ns 0.56 0.02 0.52 0.59 0.36 0.72 Metabolism of cofactors and vitamins Pantothenate and CoA biosynthesis 37 -0.35 -0.44 ns ns 0.60 0.01 0.57 0.63 0.45 0.79 Nucleotide metabolism Nucleotide metabolism 37 0.35 ns ns ns 0.12 0.01 0.10 0.13 0.05 0.20 Signaling molecules and interaction Cellular antigens 37 0.35 ns ns ns 0.04 0.004 0.03 0.04 0.01 0.08 Transcription Transcription related proteins 37 0.41 0.37 ns ns 0.03 0.003 0.02 0.03 0.001 0.06 Translation Translation proteins 37 -0.38 ns ns ns 1.04 0.02 1.00 1.08 0.80 1.20 Transport and catabolism Lysosome 37 ns ns -0.39 ns 0.01 0.002 0.01 0.01 0.001 0.03 Xenobiotics biodegradation and Drug metabolism - cytochrome P450 37 ns ns ns 0.03 0.08 0.01 0.07 0.10 0.01 0.17 metabolism Xenobiotics biodegradation and Fluorobenzoate degradation 37 0.35 ns ns ns 0.02 0.004 0.01 0.03 0.000 0.08 metabolism 2 aStatistical comparisons were made for those pathways that showed a relative abundance > 0.01% per intestinal site. bOnly significant (P ≤ 0.05) correlations are presented. cCOG, Clusters of Orthologous Groups of proteins; KEGG, Kyoto Encyclopedia of Genes and Genomes; ns, not significant; RFI, residual feed intake; TFI, total feed intake;
TBWG, total body weight gain; FCR, feed conversion ratio; SE, standard error; CI, confidence interval; Pctl, percentile. Table S7. BLAST search results for most abundant operational taxonomic units (OTU) correlated to feed efficiency and performance traits in intestinal digesta and feces of broiler chickens raised at two geographical locations.
Similarity OTU Best BLAST hita GenBank accession No. [%] OTU1 Escherichia coli GU968184.1 99.30 Shigella flexneri str. ATCC 29903 NR_026331.1 99.30 OTU2 Turicibacter sanguinis AF349724.1 99.29 OTU4 Lactobacillus crispatus str. 214-1 NZ_ADGR01000076.1 99.12 OTU5 Clostridium sp. str. FCB90-3 AJ229251.1 86.45 OTU6 Acetanaerobacterium elongatum str. Z7 AY487928.1 92.82 OTU7 Anaerotruncus colihominis str. 14565 AJ315980.1 99.26 OTU8 Lactobacillus crispatus str. 214-1 NZ_ADGR01000076.1 98.95 OTU11 Streptococcus subsp. gallolyticus str. UCN34 FN597254.1 99.12 OTU12 Clostridium sp. str. WXC-8 EU057612.1 87.41 OTU14 Clostridium sp. strain str. P6 AY949857.1 86.68 OTU15 Escherichia coli GU968184.1 99.30 Shigella flexneri str. ATCC 29903 NR_026331.1 99.30 OTU17 Clostridium colicanis str. DSM 13634 AJ420008.1 86.31 OTU18 Blautia sp. str. GAM6-1 HM626177.1 86.95 OTU19 Clostridium sp. str. FCB45 AJ229248.1 87.57 OTU22 Clostridium sp. str. FCB90-3 AJ229251.1 87.00 OTU23 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 87.23 OTU25 Clostridium sp. str. FCB45 AJ229248.1 87.20 OTU29 Clostridium sp. strain str. P6 AY949857.1 86.86 OTU31 Spiroplasma lampyridicola str. ATCC 43206; PUP-1 AY189134.1 82.56 OTU32 Clostridium sp. str. FCB45 AJ229248.1 88.30 OTU33 Ethanologenbacterium harbin str. MD-12 AY434718.1 92.31 OTU35 Turicibacter sanguinis AF349724.1 99.12 OTU38 Clostridium sp. str. FCB90-3 AJ229251.1 87.36 OTU40 Turicibacter sanguinis AF349724.1 99.12 OTU43 Eubacterium desmolans L34618.1 97.80 OTU46 Faecalibacterium prausnitzii str. M21/2 NZ_ABED02000013.1 96.51 OTU49 Clostridium sp. str. P4-6 FJ848364.1 88.12 OTU52 Clostridium sp. str. P4-6 FJ848364.1 87.75 OTU54 Enterobacter cloacae subsp. dissolvens str. M425 GU979185.1 99.12 OTU55 Clostridium sp. str. FCB90-3 AJ229251.1 87.18 OTU61 Clostridiaceae str. 80Wd AB078861.1 87.23 OTU62 Streptococcus subsp. gallolyticus str. UCN34 FN597254.1 99.47 OTU69 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 87.23 OTU73 Acetanaerobacterium elongatum str. Z7 AY487928.1 93.39 OTU75 Clostridium leptum str. DSM 753T AJ305238.1 94.30 OTU77 Clostridium sp. str. M62/1 ACFX02000046.1 96.88 OTU81 Enterobacter sp. str. Nj-68 AM491469.1 98.24 OTU84 Eubacterium desmolans L34618.1 97.44 OTU87 Clostridium sp. strain str. P6 AY949857.1 86.13 OTU91 Heliorestis sp. str. HR10B EU908049.1 87.43 OTU94 Clostridium sp. str. FCB90-3 AJ229251.1 97.00 OTU99 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 87.04 OTU103 Clostridium leptum str. DSM 753T AJ305238.1 95.22 OTU104 Clostridium sp. str. P4-6 FJ848364.1 87.75 OTU108 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 88.01 OTU117 Clostridium sp. str. M62/1 ACFX02000046.1 97.79 OTU125 Enterococcus faecalis str. KLDS6.0609 FJ607291.1 99.12 OTU126 Eubacterium desmolans L34618.1 98.17 OTU128 Clostridium sp. str. FCB90-3 AJ229251.1 85.71 OTU131 Oscillibacter valericigenes str. Sjm18-20 (= NBRC AB238598.1 94.32 101213) OTU138 Escherichia coli GU968184.1 98.59 Shigella flexneri str. ATCC 29903 NR_026331.1 98.59 OTU141 Clostridium sp. str. YIT 12070 AB491208.1 95.03 OTU142 Clostridium sp. str. FCB90-3 AJ229251.1 87.00 OTU143 Clostridium aldenense str. RMA 9741 DQ279736.1 94.14 OTU145 Clostridium orbiscindens str. AIP028.07 EU541437.1 95.25 OTU148 Escherichia coli GU968184.1 99.12 Shigella flexneri str. ATCC 29903 NR_026331.1 99.12 OTU150 Clostridium sp. str. M62/1 ACFX02000046.1 98.35 OTU151 Clostridium leptum str. DSM 753T AJ305238.1 94.12 OTU152 Clostridium sp. str. FCB90-3 AJ229251.1 87.04 OTU157 Oscillibacter valericigenes str. Sjm18-20 (= NBRC AB238598.1 94.14 101213) OTU161 Clostridiaceae str. 80Wd AB078861.1 86.50 OTU164 Clostridium asparagiforme str. DSM 15981 ACCJ01000522.1 95.59 OTU165 Spiroplasma lampyridicola str. ATCC 43206; PUP-1 AY189134.1 81.32 OTU166 Turicibacter sanguinis AF349724.1 97.15 OTU167 Dehalobacterium formicoaceticum str. DMC X86690.1 91.07 OTU173 Clostridium leptum str. DSM 753T AJ305238.1 92.65 OTU174 Turicibacter sanguinis AF349724.1 99.29 OTU179 Clostridium sp. str. FCB45 AJ229248.1 87.20 OTU182 Clostridium spiroforme str. DSM 1552 NZ_ABIK02000013.1 99.47 OTU188 Clostridium sp. str. FCB45 AJ229248.1 88.28 OTU190 Eubacterium desmolans L34618.1 96.17 OTU192 Clostridium sp. str. FCB90-3 AJ229251.1 87.36 OTU203 Anaerostipes sp. str. 35-7 FJ947528.1 97.61 OTU205 Hespellia porcina str. PPC80 AF445239.2 95.96 OTU207 Hespellia porcina str. PPC80 AF445239.2 95.59 OTU209 Turicibacter sanguinis AF349724.1 97.53 OTU210 Acetanaerobacterium elongatum str. Z7 AY487928.1 89.28 OTU212 Enterobacter cloacae Nr. 3 Y17665.1 99.12 OTU215 Clostridium hylemonae str. CT-35 AB117570.1 95.78 OTU217 Clostridium sp. str. FCB90-3 AJ229251.1 86.63 OTU220 Escherichia coli GU968184.1 96.66 Shigella flexneri str. ATCC 29903 NR_026331.1 96.66 OTU224 Clostridium sp. str. P4-6 FJ848364.1 87.02 OTU228 Spiroplasma lampyridicola str. ATCC 43206; PUP-1 AY189134.1 85.05 OTU233 Clostridium sp. str. P4-6 FJ848364.1 87.02 OTU237 Anaerotruncus colihominis str. WAL 14565; DSM 17241 NR_027558.1 95.21 OTU238 Eubacterium desmolans L34618.1 97.99 OTU252 Eubacterium coprostanoligenes str. HL HM037995.1 93.21 OTU253 Turicibacter sanguinis AF349724.1 97.33 OTU259 Shigella sonnei str. 136 GQ259886.1 94.38 OTU274 Ruminococcus flavefaciens str. JF1 AY445601.1 88.44 OTU276 Turicibacter sanguinis AF349724.1 96.64 OTU281 Clostridium leptum str. DSM 753T AJ305238.1 95.4 OTU285 Clostridium sp. str. EBR-02E-0045 AB186359.1 87.18 OTU288 Turicibacter sanguinis AF349724.1 95.08 OTU289 Clostridium sp. FG4 AB207248.1 86.5 OTU292 Clostridiaceae str. 80Wd AB078861.1 87.04 OTU294 Shigella sp. str. 4104 FJ405328.1 94.20 OTU295 Clostridium propionicum str. DSM 1682 X77841.1 94.85 OTU298 Escherichia coli GU968184.1 99.12 Shigella flexneri str. ATCC 29903 NR_026331.1 99.12 OTU308 Clostridium sp. str. 6-29 FJ808604.1 84.49 OTU323 Turicibacter sanguinis AF349724.1 96.47 OTU325 Clostridium sp. str. 6-29 FJ808604.1 85.77 OTU329 Clostridium sp. str. M62/1 ACFX02000046.1 99.08 OTU341 Clostridium sp. str. M62/1 ACFX02000046.1 96.69 OTU343 Anaerotruncus colihominis str. WAL 14565; DSM 17241 NR_027558.1 98.53 OTU346 Anaerotruncus colihominis str. WAL 14565; DSM 17241 NR_027558.1 94.11 OTU348 Ruminococcus sp. str. 14531 AJ315979.1 98.35 OTU349 Sporobacter termitidis str. SYR Z49863.1 93.60 OTU352 Turicibacter sanguinis AF349724.1 96.47 OTU362 Clostridium sp. FG4 AB207248.1 85.40 OTU368 Ruminococcus sp. str. MLG080-3 AY653234.1 95.23 OTU388 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 87.41 OTU392 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 87.41 OTU415 Clostridium sp. str. YIT 12070 AB491208.1 93.92 OTU437 Clostridium sp. str. 6-29 FJ808604.1 86.50 OTU456 Photorhabdus luminescens PDBC EPN6.71 AY597525.2 90.86 OTU459 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 87.41 OTU466 Clostridium sp. str. SDG-Mt85-3Db DQ100445.1 89.77 OTU469 Clostridium sp. str. FCB90-3 AJ229251.1 86.24 OTU470 Clostridium sp. str. P4-6 FJ848364.1 87.75 OTU482 Clostridium sp. str. P4-6 FJ848364.1 87.00 OTU500 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 88.32 OTU504 Clostridium hylemonae str. CT-35 AB117570.1 95.59 OTU507 Clostridium cellulolyticum H10 str. H10; ATCC 35319 NC_011898.1 86.86 OTU515 Clostridium sp. FG4 AB207248.1 86.68 OTU519 Ruminococcus lactaris str. ATCC 29176 ABOU02000049.1 95.59 OTU520 Clostridium sp. str. FCB45 AJ229248.1 87.75 OTU553 Clostridium sp. strain str. P6 AY949857.1 85.04 OTU574 Eubacterium sp. str. WAL 17363 GQ461729.1 97.32 OTU610 Clostridium leptum str. DSM 753T AJ305238.1 93.57 OTU619 Pseudidiomarina sp. str. 908087 EU600203.2 99.12 OTU634 Clostridium sp. str. 6-29 FJ808604.1 86.50 OTU654 Ruminococcus sp. str. CCUG 37327 AJ318864.1 86.11 OTU725 Clostridium hylemonae str. CT-35 AB117570.1 95.78 aGreengenes database (greengenes.lbl.gov/cgi-bin/nph-index.cgi); last accessed 4/21/2017.
Table S8. Pearson’s correlations between selected bacterial genera and KEGG pathways in cecal digesta associated with the residual feed intake in male and female chickens across two geographical locations.
KEGG KEGG pathways pathways
Phenylalanine, tyrosine and Cellular Tyrosine beta-Alanine Lysine tryptophan Genusa,b antigens metabolism metabolism Genus biosynthesis biosynthesis Males Females Unclassified Clostridiales 1 ns ns ns Unclassified RF39 ns ns Lactobacillus ns ns ns Unclassified Ruminococcaceae ns ns ns Ruminococcus ns ns 0.35 Coprococcus ns ns ns a Statistical comparisons were made for bacterial genera and KEGG pathways that were associated with chicken’s residual feed intake. b Only significant (P ≤ 0.05) correlations are presented. Commented [Sina1]: auch nicht sign Korrelationen in Tabelle dargestellt c KEGG, Kyoto Encyclopedia of Genes and Genomes; ns, not significant. Table S9. Pearson’s correlations between selected bacterial genera and KEGG pathways in feces associated with the residual feed intake in male chickens across two geographical locations.
Carbon fixation Proximal Valine, pathways Fluoro- Pantothena tubule leucine and in Fatty acid benzoate One carbon te and CoA bicarbonate Transcripti isoleucine prokaryote Cellular biosynthesi degradatio Histidine Nucleotide pool by biosynthesi reclamatio on related Translation biosynthesi Genus s antigens s n metabolism metabolism folate s n proteins proteins s Lactobacillus -0.53 0.64 -0.54 ns -0.64 ns ns -0.58 0.58 ns ns -0.76 Unclassified ns -0.34 ns ns 0.44 -0.42 0.42 ns -0.40 -0.44 0.42 0.39 RF39 Unclassified ns ns ns ns ns ns ns ns ns ns ns ns Clostridiales 2 Unclassified 0.44 -0.52 0.48 -0.37 0.63 -0.57 0.54 0.52 -0.52 -0.61 0.53 0.57 Lachnospiraceae 1 Acinetobacter ns 0.42 ns 0.68 ns ns ns -0.35 0.45 ns -0.43 ns Diaphorobacter ns ns ns 0.61 ns ns -0.33 ns ns ns -0.40 ns Comamonas ns ns ns 0.60 ns ns -0.37 ns ns ns -0.44 ns Commented [Sina1]: siehe Kommentar Tabelle 7 Pseudomonas ns ns ns 0.55 ns ns ns ns ns ns ns ns Diaphorobacter und Comamonas waren bei AFBI nur in 3 von 19 Dorea 0.36 -0.37 0.40 -0.34 0.54 -0.54 0.51 0.44 -0.45 -0.55 0.46 0.49 Tieren vorhanden mit rel. Häufigkeit < 0.01 a Statistical comparisons were made for bacterial genera and KEGG pathways that were associated with chicken’s residual feed intake. b Only significant (P ≤ 0.05) correlations are presented. Commented [Sina2]: auch nicht signifikante Korrelationen in Tabelle c KEGG, Kyoto Encyclopedia of Genes and Genomes; ns, not significant. Table S10. Pearson’s correlations between selected bacterial genera and KEGG pathways in feces associated with the residual feed intake in female chickens across two geographical locations.
Tropane, Phenylalanine piperidine and C5-Branched Lipid , tyrosine and pyridine dibasic acid biosynthesis Lipoic acid Lysine Novobiocin tryptophan alkaloid Females metabolism Ion channels proteins metabolism biosynthesis biosynthesis biosynthesis biosynthesis Lactobacillus -0.67 ns ns ns ns -0.45 -0.52 -0.45 Unclassified Clostridiales 2 ns ns ns ns ns ns ns ns Acinetobacter ns ns ns ns ns ns ns ns Unclassified Lachnospiraceae 2 ns -0.53 0.49 -0.40 0.50 ns 0.46 ns Pseudomonas ns ns ns ns ns ns ns ns Methylobacterium ns ns ns ns ns ns ns 0.36 Commented [Sina1]: s. Kommentar Tab 7 a Statistical comparisons were made for bacterial genera and KEGG pathways that were associated with chicken’s residual feed intake.
bei Vetmed in weniger als der Hälfte der Tiere vorhanden b Only significant (P ≤ 0.05) correlations are presented. Commented [Sina2]: auch nicht sign Korrelationen in Tabelle c KEGG, Kyoto Encyclopedia of Genes and Genomes; ns, not significant. dargestellt