Bacterial Diversity Associated with Feeding Boschveld Indigenous Chickens with Sorghum-Based Diets

doi:10.21203/rs.3.rs-3996941/v1

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Bacterial Diversity Associated with Feeding Boschveld Indigenous Chickens with Sorghum-Based Diets

https://doi.org/10.21203/rs.3.rs-3996941/v1

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The metagenomics technique was applied to assess the effects of sorghum-based diets on the gut microbes of Boschveld indigenous chickens. A total of 420 unsexed, day-old Boschveld indigenous chickens, in a completely randomized design, were assigned to a three sorghum varieties (red, brown, and white) x 5 inclusion levels (0, 25, 50, 75, and 100%) x 4 replicate with 7 chicks per replicate for 90 days. The bacterial communities at alpha diversity indices at observed; Shannon and Simpson indexes were more abundant at day 90 of sample collection than on day 60. The group of chickens offered diets with 50% (level 3) inclusion of sorghum varieties had more bacteria than other inclusion levels. The dominant bacteria communities at the phylum level were Firmicutes, Proteobacteria, and Bacteroidia, while Lactobacillus - Aviarius, Comamoducuae, and Methylobacterium were dominant at the genus level. Boschveld chickens fed diets with the white sorghum variety were the only group with 1% of Campybacterales present in their guts compared to groups fed red and brown sorghum varieties at the phylum level. The same group of chickens fed diets, including the white sorghum variety, showed Streptococcus at 6%, which was unique to the guts of this group compared to their counterparts at the genus level. This study provided information about how feeding different diets influences bacterial diversity and dominance in chickens' gut microbiomes.

Biological sciences/Biological techniques

Biological sciences/Molecular biology

16S Sequencing

indigenous chickens

microbiota

poultry production

sorghum

The gut microbiota of chickens plays an important role in nutrition absorption, immunity development, and disease resistance, based on the production of vitamins, short-chain fatty, organic acids, and antimicrobial compounds (Feng et al., 2022). It has also been stated that the poultry microbiome has an essential impact on chicken growth performance and feed conversion.

The composition and diversity of chicken intestinal microbiomes are strongly influenced by varying factors such as diet and age of the bird. Wilson et al. (2005) also suggested that the age of birds and diets may significantly influence the presence of gut microbiome diversity. Poultry diet has been reported as one of the most important factors having a direct or indirect relationship with and influence on the microbiota balance and chicken gut health (Wickramasuriya et al., 2022), while Haberecht et al. (2020) further stated that the microbial community contained in poultry feed might play an essential role in the colonization of poultry gut microbiota. According to Aruwa et al. (2021), the composition of the gut microbiome always differs between younger and older chicks. However, environmental factors have also been noted as an aspect that affects the gut microbial community in chickens (Shang et al., 2018). Although diet is mainly recognized as one of the leading factors that shape the gut microbiota (Lugvigsen et al., 2016), there is increasing evidence from genome-wide association studies (GWSA) that reveals the important effect of the host’s genetic factors on their gut microbiota (Feng et al., 2022). Pan and Yu (2014) stated that the genetic changes related to weight gain and feed efficiency may also change poultry's gut physiology and microbial community composition.

The importance of intestinal microbial community profiles in poultry is currently an issue because any factor that affects intestinal health can alter nutrient uptake, feed intake, feed conversion, immune status, and pathogen resistance (Hubert et al., 2019; Thomas et al., 2019). Therefore, it will be beneficial to the poultry sector to evaluate the influence of the gut microbial community on the host’s nutrient and energy use. Evaluating bacterial communities and intestine developments of different genetic lines of chickens has become a recent point of interest. However, there is very little literature on how the composition of the microbiome differs amongst varying chicken breeds, especially local, indigenous chickens (Al-Marzooqi et al., 2020). Hence, this study aimed to evaluate the effect of feeding diets formulated with a sorghum variety grown in South Africa on the gut microbes of Boschveld indigenous chickens.

The Alpha diversity indices of the Boschveld indigenous chickens’ microbial communities at days 60 and 90 of collection, according to the three different sorghum varieties fed.

In the current study, the differences between the species communities were presented according to the Observed, Shannon, and Simpson indexes at days 60 and 90 of sample collections, as reflected in Fig. 1 (A). The Observed and Shannon diversity indexes, known to demonstrate the abundance of bacterial species present, revealed all three sorghum varieties to have more bacteria varieties on day 90 than on day 60. Regardless of the sorghum variety offered to chickens, the two measures gradually increased from days 60 to 90, suggesting that the diversity of bacteria in each sample grows as the chickens get older. However, the summary of the Simpson diversity index, which measures the species diversity considering the number of species present, showed more bacterial species on day 90 than 60. This pattern was noted in chickens fed any of the three sorghum varieties.

Alpha diversity was also calculated at different inclusion levels of the sorghum varieties (presented in Fig. 1 (B)), where bacteria were in abundance in the group of chickens offered feed with a 50% (level 3) inclusion of red and white sorghum varieties at observed, Shannon and Simpson diversity indexes. The group of chickens that was offered 25% (level 2) of the red and white sorghum varieties inclusion had the lowest bacterial counts at observed and Shannon indexes. However, the bacteria abundance and diversity of the chickens fed brown sorghum variety was highest in chickens offered feed with a 25% (level 2) inclusion across all diversity indexes. At 25% (level 2) of red and white sorghum inclusion, the lowest level of bacterial abundance and diversity on the was recorded while in brown sorghum had their lowest diversity at 50% (level 3) inclusion.

Microbial community diversity amongst Boschveld indigenous chickens fed different sorghum-based diets at different inclusion levels, including three sorghum varieties.

Figure 2 shows the microbial profiles of Boschveld chickens on the days of collection. Sorghum varieties with five inclusion levels were used when formulating the trial diets, and these are represented using the Principal Coordinates Analysis (PCoA). The PCoA plots clustered the bacterial diversity according to the sorghum varieties offered during the trials of the current study. Also, they illustrated the microbial succession when chickens were 60 and 90 days old. The microbial profiles from Boschveld chicken guts had a statistical difference (P < 0.05) in the species diversity at days 60 and 90 of the collection, shown in Fig. 2 (A). The bacteria in the chicken’s gut at days 60 and 90 clustered far from each other, although there were very few bacteria that clustered together during these collection periods.

The bacterial diversity from the guts of the chickens, when divided according to the three sorghum varieties (red, brown, and white) and as presented in Fig. 2 (B), were significantly different (P < 0.05). Microbial communities found in the gut of Boschveld chickens offered the control diet, red and white sorghum varieties clustered closely together. The group that was fed the brown sorghum variety had few bacteria clustering close to the other varieties. Still, it also had some bacteria that were unique and clustered separately. The inclusion level's effect on the chickens’ guts – regardless of the sorghum varieties included, as shown in Figure S2 were not significantly different (P > 0.05). However, the bacterial diversity at different inclusion levels was similar at all levels, although there were outliers noted from levels 1,2,3 and 5, which clustered closely together.

The phylogenetic analysis results, which present the bacterial similarities between the chickens’ guts from all studied treatments as of the days of sample collection, are shown in Fig. 3. The phylogenetic results corroborated the PCoA results, which indicated the significant difference in the diversity of the bacterial communities found in the guts of chickens at days 60 and 90. However, amazingly, the microbiome community of chickens offered feed formulated with the sorghum brown variety at inclusion of 100% (level 5) at collection day 60 was similar to the group of chickens fed the diet with the inclusion of the sorghum white variety at 75% (level 4) at day 90 (Fig. 3).

The gut microbial diversities and community composition among Boschveld indigenous chickens fed different sorghum-based diets at the Phylum level.

The phylum ranks below the kingdom and above the class in taxonomy, and scientists generally use the term phylum for bacteria and animals. The results found in the current study at the phylum level (Fig. 4) showed Firmicutes dominating the bacterial communities in the chicken's gut from all groups followed by Proteobacteria, Bacteroidota, and Actinobacteria at day 60. The groups of chickens fed diets with the brown sorghum variety included during formulation, regardless of the inclusion level, had bacterial community patterns similar to those of chickens offered diets with the white variety infused. However, when fed the brown variety, chickens had an abundance of Firmicutes in their guts, followed by Proteobacteria.

Furthermore, chickens offered the control diet, which included 0% sorghum, had more Firmicutes at day 60 and more Proteobacteria at day 90. However, findings from chickens fed diets formulated with the inclusion of the red sorghum varieties had an overall abundance of Firmicutes, followed by Proteobacteria, Actinobacteria, and Bacteroidota (Fig. 5).The influence of the inclusion levels on the bacterial diversity of Boschveld chickens is presented in Fig. 6. The group of chickens offered diets formulated with the inclusion of 25% (level 2) of the sorghum red variety had more Firmicutes present, followed by the group that provided the red sorghum variety with a 75% (level 4) inclusion level. At day 90 of sample collection, however, Proteobacteria were abundant compared to other bacterial compositions. These bacteria were noted mainly in the gut of chickens fed diets formulated with sorghum white included at 25% (level 2), followed by the group offered sorghum brown included at 50% (level 3). Overall, the bacterial community found in abundance were Firmicutes at all levels (0, 25, 50, 75, and 100%), followed by Proteobacteria, Desulfobacterota, Bacteroidota, and Actinobacteria.

The microbiome composition of Boschveld chicken gut at the genus level. The Krona plot in Fig. 7 showed the presence of bacteria at the age of collection (60 and 90 days). At day 60 (A), Lactobacillus aviarius was the most dominant group at 18%, followed by the Comamoduceae at 12% and uncultured bacterium at 7%. On day 90 (B), Comamonadaceae was the most dominant (23%), followed by Methylobacterium – Methylorubrum (8%) and Escherichia – Shingella (6%).

The effect of sorghum varieties at the genus level is presented in the Krona plot in Fig. 8. The brown sorghum variety (A) inclusion revealed the Comamonadoceae (11%) followed by Uncultured bacterium (10%) and Methylobacterium – Methylorubrum (7%), although the group offered a diet with the red sorghum variety (B) was dominated by Lactobacillus – Aviarius (35%), Comamozadaceae (7%) and Escherichia – Shigella (4%). The inclusion of the white sorghum variety (C) impacted the gut of Boschveld chickens and was dominated by Comomadaceae (24%), Methylobacterium – Methylorubum (9%) and Lactobacillus – Aviarius (6%). Furthermore, chickens fed diets with the white variety included had 6% Streptococcus, which was present only in the guts of this group and not in those of their counterparts.

Microbial taxa associated with different sorghum-based diets in Boschveld indigenous chickens.

The core taxa Venn diagram (Fig. 9 (A)) demonstrates the bacterial similarities found in the Boschveld chicken's gut-fed diets formulated with the three sorghum varieties (brown, red, and white) at days 60 and 90. A total of 902 bacterial communities were noted during the whole trial. However, from the recorded bacterial communities, about 187 species were reported only on day 60 and about 274 on day 90. Meanwhile, 441 common bacterial species were observed on both day 60 and day 90 of the collection.

The core taxa Venn diagram (Fig. 9 (B)) illustrates the bacterial similarities found in the Boschveld gut-fed chicken formulated with the three sorghum varieties. The bacterial varieties found between chickens fed the control diets, and those fed the brown variety had 15 common bacterial species. However, the group of Boschveld chickens offered the control diet, and those fed with the inclusion of the white variety had 18 common bacterial communities across the entire trial. In contrast, control x red had 18 common bacteria. The brown and red groups had only 36 bacteria in common. The white x red had 97 common bacterial communities. Furthermore, brown x white had 197 common bacteria across the entire study, which was the most when compared to the groups fed other varieties.

The microbial community in chicken guts may affect their gut health and overall performance either negatively or positively. Hence, having chickens with a healthy gut is essential for efficient digestion, nutrient absorption, a strong immune system, and optimal performance (Choct, 2009; Ciurescu et al., 2023). Young chicks have been reported to have fewer bacterial species in their intestinal tracts than growing adult chickens, making their gut microflora more accepting of pathogens than older chicks (Choct, 2009; Aruwa et al., 2021).

Bird age has been identified as an important factor influencing the gut's bacterial composition (Shang et al., 2018). A report by Bae et al. (2017) supported the pattern noted in the current study, where the bacterial abundance increased as chickens grow at the Shannon level, and also, in support of these findings, Haberecht et al. (2020) state that, while the microbial communities in chickens are considered fully formed within the first weeks of life, they continue to mature as the chicken grows while responding to stresses and the environmental challenges they are exposed to. The current study noted a difference in bacterial communities at days 60 and 90 of sample collection. The change in the environmental conditions might have influenced the species diversity because this study was conducted during the transition from winter to spring. Rama et al. (2023) reported the seasonality analysis results, which showed that ceca samples from broilers sampled in the summer harbored a richer microbial community; these results resonated with the long transit time of the digest, which benefits the extensive fermentation activities.

The differences in the bacterial profiles influenced by sorghum varieties were noted in this study. In support of these results, Bailey (2010) reveals that the environmental aspects may influence the diversity in the presence of microbiome profiles. In addition, sex, genetics, age, feed particle size and feed sources have also been identified as factors that may affect chicken's gut health (Wickramasuriya et al., 2022). In the present study, the bacterial pattern varied amongst the groups of chickens fed different sorghum varieties and at different ages. These findings are supported by Jurburg et al. (2019), who also noted an age-dependent microbiota pattern in their study. In addition, feeding chickens pelleted diets increases their overall growth rate through the increased feed intake, while their gizzards weigh less than chickens fed mash diets (Engberg et al., 2002). Therefore, particle size (fine or coarse) and the feed form (mash or pelleted) have a significant influence during the development of a chicken’s digestive tract (Amerah et al., 2007). Hence, it is likely that feed form may affect the gut microbiome in chickens because of its effect on the dynamics of gut digestion and development. The diversity in the microbial community noted in this study may be due to the particle size and feed form because the studied chickens were offered pellet feed.

Diet aspects like composition, processing methods, digestibility, and feeding methods may also all negatively influence the balanced/healthy chicken gut ecosystem, especially in young chicks (Apajalahti et al., 2002; Choch, 2009).

The streptococcus bacterium, which was noted in the present study, is a good and safer bacterium that fights infection and helps the body to stay healthy (Cui et al., 2016). The study by Torok et al. (2006) also presented data from two sets of broiler chickens fed different diets, resulting in two distinct gut microbial communities, thus supporting the findings of the present research. However, recent reports are revealing that chickens consume a considerable volume of their bedding materials such as straw and sawdust, which are composed mostly of hard fibre. While this might influence the microbial communities in chickens’ guts, the lack of literature means that it is too early to conclude a definitive link between chickens’ bedding materials and bad microflora.

Haberecht et al. (2020) reported that every batch of feed ingredient varies in its microbiota community composition, and this could be the reason behind the diverse bacterial communities observed in the gut of Boschveld chickens fed feed formulated with the inclusion of brown, red, and white sorghum at five inclusion levels. However, the composition of gut microbiota in chickens has also been reported to be influenced mostly by the type of samples collected such as the small intestine, the mucosa layer of the gut wall, and caeca contents, which may be the reason behind varying bacterial patterns in poultry studies (Sun et al., 2013; Kang et al., 2021).

The study conducted by Xu et al. (2016) recorded a low proportion of Bacteroidetes in caged chickens when compared to groups reared under free-range systems. These findings suggest that the conditions in poultry housing structures are also an influential factor in the microbiota diversity of chickens (Kers et al., 2018; Hubert et al., 2019).

In conclusion, the results found in this present that more bacterial presence was observed in older chickens at day 90 than when they were younger. It was noted that Firmicutes was the most abundant bacterium in most chicken groups. Bacteria observed in this study are known to be healthy and common in poultry gut microbes. Therefore, sorghum-based diets may be fed to Boschveld indigenous chickens without causing an adverse effect on their gut health. However, future works are still needed to determine the influence of diet composition and feed forms on the microbial diversity in different chicken breeds.

Ethical approval. Ethical clearance was obtained from theCollege of Agriculture and Environmental Science, University of South Africa (Unisa) Animal Research Ethics Committee (approval number 2020/CAES_AREC/003). All ethics and animal welfare guidelines were followed during the conduction of the experiment.

Study area. The study trials were conducted for 90 days from August until November 2021 at Dreamland AH, Plot 60, Evaton Road in Sebokeng, Gauteng province, South Africa. The coordinates of the study area are 26.6071° S and 27.8473°. The ambient temperature in the study area ranges from 14 to 29°C in summer and 1 to 23°C in winter.

Sourcing of Sorghum varieties and formulation of the experimental diets. The three sorghum varieties (Brown, White, and Red) assessed in this study were sourced from the Agricultural Research Council-Grain Crops Institute, Potchefstroom, North-West Province, South Africa, the coordinates of which are 26°43'43.16"S - 27°04'47.71"E. The mean temperature around the area in summer is above 22°C and, in winter, is below 20°C. These sorghum varieties were planted in fields under the same environmental conditions during summer. Plant collection and use was in accordance with all the relevant guidelines. Diets (Table 1) were formulated with brown, red, and white sorghum varieties to meet the requirements, as recommended in the specifications indicated in Aviagen (2014). Feed ingredients were mechanically ground and then mixed in a mixing machine before they could be transferred into a pellet-making machine and were steamed to a temperature of 80⁰ C. All chickens received starter diets (crumbled pellet) from day one until day 14 before being introduced to the main pelleted diet (2mm in size) for the remaining days of the trial. Chickens were offered feed and water ad libitum.

Sample collection. The study was conducted over 90 days using 420-day-old, unsexed Boschveld indigenous chickens purchased from Boschveld Ranching (Pty) Ltd in Bela-Bela, in the Limpopo province of South Africa. On days 60 and 90, two chickens per replicate were slaughtered using the cervical dislocation method. The birds were immersed in hot water and de-feathered, then cleaned and dissected to harvest the internal organs. The study is reported in accordance with arrive guidelines. The caeca (the two blind pouches located in the joint where the small and large intestines are joined) were cut off and immediately stored in tubes filled with 70% ethanol. These were kept on ice and later stored in a freezer at - 20⁰ C for further processing.

Microbial DNA isolation and Amplicon library preparations. A Zymo Research Corporation Quick-DNA Fungal/Bacterial extraction kit was used to isolate the DNA from the collected caeca samples. After that, the genomic DNA samples were PCR amplified using a universal primer pair 341F and 805R, targeting the V3 and V4 regions of the bacterial 16S targeted rRNA gene sequencing technology. The resulting amplicons were purified, end-repaired, and illumina-specific adapter sequences were ligated to each amplicon (NEBNext Ultra II DNA library prep kit). The amplicons were then sequenced on Illumina’s MiSeq platform.

Sequencing. The amplicons were sequenced on Illumina’s MiSeq platform using a MiSeq v3 (600 cycles) kit. About 20Mb of data (2x300bp long paired-end reads) were produced for each sample. The demultiplexed paired-end reads, and the associated metadata file was imported into the Quantitative Insights into Microbial Ecology 2 (QIIME2, version 2-2022.2.0) pipeline for sequence filtering, quality control, and analysis. The Divisive Amplicon Denoising Algorithm 2 (DADA2) was used to filter and analyze the joined sequences to obtain the operational taxonomic units (OTUs) based on a 97% identity threshold.

Data analysis. The OTUs were categorized into distinct taxonomic levels by the SILVA 138 database classifier. The clustered OTUs were then rarefied to even sampling depths, and both alpha and beta diversities were calculated. Alpha diversity was calculated using the Shannon index, Simpson index, and Observed OTUs index using the phyloseq package (R version 3.5.0 2018-04-23). To compute the microbial beta diversity, dissimilarity analyses were performed, and sample Bray-Curtis distances were visualized on PCoA plots. Multivariate beta diversity analysis was verified by using non-parametric PERMANOVA and the Adonis function in R with 999 permutations (p < 0.05).

Data availability.

Data is provided within the manuscript and supplementary information file.

Acknowledgments

The authors would like to acknowledge the Agricultural Research Council – Grain Crops Institute, Potchefstroom, South Africa, for the supply of sorghum varieties. We also thank the National Research Foundation (grant number 123307) and the University of South Africa for their financial support.

Author contributions

Conceptualization, N.N., T.M., M.M; supervision; M.M; writing original draft, N.N.; methodology; T.M., N.N.; manuscript review and editing, M.M., T.M., C.A.M., A.N.S.; funding acquisition, N.N., M.M; bioinformatics and statistical analysis, T.M.; All authors have read and agreed to the published version of the manuscript.

Competing interests

The authors declare no competing interests.

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Table 1

Composition analysis of the experimental diets.
DIET (%)
Ingredients	0%	25%	50%	75%	100%
Yellow maize	51.33	38.49	25.66	12.83	-
Sorghum	-	12.83	25.66	38.49	51.33
Soya bean	33.03	20.01	25.91	25.22	25.23
Soya oil cake	-	19.12	13.52	10.62	7.8
Limestone powder	12.30	7.80	7.10	9.70	12.3
Potassium carbonate	1.20	0.50	0.90	1.00	1.2
Mono calcium phosphate	0.98	0.10	0.10	0.99	0.98
Salt	0.30	0.30	0.30	0.30	0.3
Premix	0.40	0.40	0.40	0.40	0.4
Lysine	0.18	0.17	0.17	0.17	0.17
Methionine	0.28	0.28	0.28	0.28	0.28
Total	100	100	100	100	100
Level 1 = 0; Level 2 = 25%; Level 3 = 50%; Level 4 = 75%; Level 5 = 100%.

No competing interests reported.

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Bacterial Diversity Associated with Feeding Boschveld Indigenous Chickens with Sorghum-Based Diets

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