A diverse microbial population colonizes the sterile mammalian gastrointestinal tract during and after birth. There is increasing evidence that this complex microbiome plays a crucial role in the development of the mucosal immune system and influences newborn health. Microbial colonization is a complex process influenced by a two-way interaction between host and microbes and a variety of external factors, including maternal microbiota, the birth process, diet, and antibiotics.
The objective of this study was to evaluate the composition of the total bacteria in the rumen and jejunum of newborn calves, and determine how the composition changes during normal development. Our results suggest that each sampled age group has its distinct microbiota, as reflected by the clustering of the samples by age group, with two different pipelines.
In this study, the α-diversity of the bacterial community was greatest at the middle-end of the trial, richness was following the adaptation period to the growing diet, and diversity was invariable throughout much of the trial. Bacterial community diversity was lower by the beginning of the trial, increasing in the next weeks following the adaptation period.
Oikonomou et al. (2014) and Klein- Jöbstl et al. (2014) in their studies have described an increase in species richness and diversity with the animals increasing age. Our data agree with Austin et al. (2018) in that the 28-day samples had increased richness compared with samples at weaning, suggesting a stabilization of the microbiome in more mature animals. In contrast, in the study by Klein et al. (2019), richness, diversity, and the number of observed OTUs, decreased significantly between 6 and 24 hours after birth. In the same way, a decrease in mean Chao estimate, Shannon and observed OTUs, during the first day after birth was seen in calves in the studies of Alipour et al. (2018) and Yeoman et al. (2018). Possible explanations given by these authors are selective effects from the environment, especially the diets given to the animals, and a higher diversity caused by prenatal colonization.
The ruminal ecosystem is a complex consortium of different bacterial species living in a symbiotic relationship with the host. Zhou et al. (2015) in their review on rumen bacteria found that in ruminal populations the most abundant phylum always falls on Firmicutes and Bacteroidetes. Similarly, Tapio et al. (2017), report that the main phylum is represented by Firmicutes (55.9–86.8%) followed by Bacteroidetes (8- 24.4%) and Proteobacteria (0.9–13.4%), with other phyla such as Actinobacteria, Cyanobacteria representing less than 0.5%.
Next-generation sequencing and bioinformatics tools have greatly advanced our knowledge about the phylogenetic diversity and ecological role of microbes inhabiting the mammalian gut. However, there is a lack of information on the evaluation of these computational tools in the context of the gastrointestinal ruminants microbiome as these programs have mostly been benchmarked on real or simulated datasets generated from human studies. In this study, we also compared the outcomes from two different methods, 1) KRAKEN2, and 2) a pipeline based in USEARCH, to assess the taxonomic profiles (bacteria) of rumen and jejunum microbial communities using DNA sequencing. Our study finds that these programs perform similarly and achieve the same conclusions.
Similarly, Neves et al. (2017), in their study, compared the outcomes of KRAKEN2 and a pipeline developed in-house based on MOTHUR (Schloss 2009; 2020), both approaches revealed a similar phylum distribution of the most abundant taxa, with Bacteroidetes, Firmicutes, and Proteobacteria accounting for approximately 80% of total bacterial abundance. Similar results were described in the study of Glendinning et al. (2020); they performed a metagenomic analysis of samples taken from the ruminal contents of cattle, sheep, reindeer, and red deer, with the taxonomies assigned with KRAKEN2; in all ruminant species, Bacteroidetes was the most abundant phylum, with Firmicutes being the second. Similarly, Palomba et al. (2017), using USEARCH with rumen and reticulum samples, detected high levels of phylum Planctomycetes; phylum Firmicutes; phylum Bacteroidetes; and phylum Synergistetes), plus several other families with a moderate relative abundance (> 3%), belonging to the usual components of the ruminal microbiota of sheep, cattle and dairy cows.
The main identified phylum's and their changes over time in this work were Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. These findings agree with the proportions reported by Jiao et al. (2015), and Malmuthuge et al. (2015), and Sbardellati et al. (2020), using 16S rRNA, observed dominance of Proteobacteria phylum during the first week, but after that were replaced by Firmicutes and Bacteroidetes phyla. Also, O´Hara et al. (2020) in their study using USEARCH commands, found that the proportion of bacteria were manly Firmicutes, Bacteroidetes, and Proteobacteria, also Actinobacteria, Fibrobacteres, Spirochaete, and Cyanobacteria, same as our finding with both programs USEARCH and KRAKEN2.
Gut microbial colonization during the preweaning period has primarily been studied using fecal samples because it is a non-invasive way to collect samples from the same individual over time (Klein et al. 2019; Alipour et al. 2018 and Yeoman et al. 2018). However, Malmuthuge et al. (2014) reported that bacterial composition could vary depending on the GIT region and sample type used (content versus mucosal tissue). Palomba et al. (2017), and Zeng et al. (2017) using USEARCH commands, found an important difference in the taxonomy across the GIT of the pre-weaned lambs' understudy, being Firmicutes and Bacteroidetes the most abundant phylum in all GIT, as in our data wherefrom 7-day the proportion of Firmicutes and Bacteroidetes increase in jejunum; also Taschuk and Griebel (2012) and Klein et al. (2019) reported Firmicutes and Bacteroidetes dominated the bacterial communities along with the GIT and the relative abundance of these 2 phyla varied greatly among local gut regions and between the tissue and content within each region (Malmuthuge and Guan, 2017).
In animals raised on calf starter, GIT microbial communities in those fed silage or mixed diets became more alike and more diverse with age. Animals had a succession of microorganisms representing similar taxa but different specific OTUs present at different ages. Therefore, age is one of the major driving forces in the establishment of microbial communities in developing calves (Jami et al. 2013; Dill-McFarland et al. 2017, 2019). Ma et al. (2020) detected changes in gut microbial diversity in healthy calves that were fed only milk replacer (same amount under the same age), and therefore, speculate that host (age and growth) was the main factor driving the development of microbial diversity in the early life of calves. Li et al. (2012), reported that calves fed with a milk substitute and subsequently with a starter feed showed a predominance of the phylum Bacteroidetes during the first 6 weeks of age; this is similar to the results obtained in this work (P ≤ 0.05, Fig. 3c).
As we can see throughout many studies, the microbial populations maintain some stability through time, and for that reason, many authors speak of a microbial core. A microbial core is defined as a set of microbial species present in individuals within a given species (Taschuk et al. 2012).
Henderson et al. (2015) carried out a study of the composition of the microbial community of the rumen in different species, including cows, goats, camels, buffaloes, sheep, and how this microbiome could vary by factors like diet and the host, however, thanks to the fact that a central microbiome (a core) is hypothesized to be present, variations are small even in a wide geographical range. They collected samples in 35 different countries, where the dominant bacterial phylum was mainly Firmicutes, Bacteroidetes, Proteobacteria, and Fibrobacter (representing about 90%). The seven most abundant bacterial groups comprised 67.1% of all bacterial sequence data, were detected in all samples, and can be considered the "dominant" ruminal bacteria. These were Prevotella, Butyrivibrio, and Ruminococcus, as well as Lachnospiraceae, Ruminococcaceae, Bacteroidales, and Clostridiales.
Xue et al. (2018), analyzed the microbiome of 334 dairy cows, finding that there was a bacterial core that represented 46% of all the bacteria found in the samples, these phyla were Firmicutes (21.67%), Bacteroidetes (20.68%), Proteobacteria (0.52%).
There is also an intestinal core; Fraune et al. (2007) studied this nucleus over three decades and he defined it as a stable population across samples that is relatively constant, with an endosymbiotic relationship between the host and its microbiota. Taschuk et al. (2012) mention that the central microbiome (core) must be redefined at a functional level, with greater emphasis on the processes carried out by the resident biota, and less emphasis on the absolute or relative abundance of individual organisms.
Therefore, maintaining the tolerance and stability of populations may require the presence and interaction of a relatively consistent and specific microbiota, for example, many diseases, such as inflammatory bowel disease, or ruminal acidosis have been associated with changes in the microbial population, so it is not uncommon to find a species-bacterial core that helps to maintain homeostasis (Fraune et al. 2007; Taschuk et al. 2012).
Research continues to show that small changes in ruminal microbial taxa or the abundance of specific microbes impact livestock productivity. Factors such as age, diet, feeding system, host species, and even geography, can alter the proportions of ruminal microorganisms. Several studies have analyzed different factors that affect the colonization of the digestive tract, such as age, diet, geographic location, feeding system, etc. Most studies concluded that the common factor that affects how populations of the digestive tract microbiota move are diet. We can observe this in works such as those of Malmuthuge et al. (2011), Petri et al. (2013), Iqbal et al. (2018), Clemmons et al. (2019), Guo et al. (2020), and many other authors that focus on the relationship between the type of diet or the diet changes and microbiome and how this impacts production.
The microbiota plays a fundamental role in the development of immunity and gastrointestinal metabolism, so knowing these populations allows not only to prevent diseases but also to improve productive parameters. This work used the USEARCH and KRAKEN2 programs, and demonstrated that they both are good tools in the analysis of the GIT microbiota in ruminants; an important point to mention is that we found USEARCH to be user-friendly because it has good technical support, its user manuals remain updated, and they were complete, with explanations of the function and use of each of its commands. Therefore, we recommend USEARCH for those who are beginning in microbiome analysis. Even so, we think that using two pipelines supported by a collection of tools could help control the sources of variation present in these kinds of analyses (e.g. analytical pipelines, related databases, and software parameters), which will lead to more reliable biological interpretations and improved taxonomic evaluation at the species level (minimizing unclassified sequences).
Our results showed the profile of microbial colonization of the gastrointestinal tract of 0 to 42-day-old calves from a tropical region of Mexico. However, it is necessary to analyze other aspects of this colonization and how it can influence factors such as the pattern of microbial succession along with the GIT in pre-ruminant and ruminant animals. This knowledge is essential since it influences the development and maturation of the host's GIT, as well as the development of the immune system and therefore, the health of the animals. In addition, information on the viability, genetic sequences (metagenomics), or even gene expression (metatranscriptomics and metaproteomics) of the described microbial core is required. Therefore, much remains to be understood regarding the underlying mechanisms of possible interactions between the ruminal and intestinal microbial communities and their host. In addition, more emphasis should be placed on dysbiosis caused by antimicrobials in feed and the possibility of using the gut microbiome as prebiotics and probiotics as antimicrobial substitutes. In the future, it will be possible with the collection of microbiota data to create bioinformatics tools, such as algorithms based on the establishment of digestive tract populations to predict patterns with which we can prevent diseases and help design preventive treatment strategies.