Living Reference Work Entry

Encyclopedia of Metagenomics

pp 1-11

Date: Latest Version

Diversity of Microbiomes in Beef Cattle

  • Lisa DursoAffiliated withAgroecosystem Management Research Unit, US Department of Agriculture, University Of Nebraska Email author 
  • , James E. WellsAffiliated withMeat Animal Research Center, USDA, Agricultural Research Service
  • , Min Seok KimAffiliated withMeat Safety & Quality Research, USDA Agricultural Research Service

Synonyms

Whole-genome sequencing and metagenomic sequencing

Definition

A microbiome refers to an assemblage of microorganisms associated with a specific habitat or niche.

Introduction

Microbes are minute single-cell life-forms common to most habitats on Earth. Animals harbor microbes on and within their body, and these microorganisms can influence health and well-being of the animal host. Microbes can reside on the skin, in the airways, in the reproductive tracts, and in the digestive tract of mammals. The hosts have developed symbiotic relationships with these microbes in the gastrointestinal tract that can influence nutrient availability to the host and are an important part of normal function. In particular, ruminant animals have evolved to exploit a symbiotic relationship with microbes that allows the digestion of complex fibrous biomass in their rumen, a pregastric chamber of their gastrointestinal tract.

Collectively, the microbes in an ecosystem consist of bacterial, archaeal, protozoal, and fungal communities called the microbiome. The bovine microbiomes serve as a foundation for animal health, a reservoir for human pathogens, and, in the case of the gastrointestinal microbiomes, a potential rich source of enzymes for industrial processes and biofuel production. The first step to understanding the role of the microbiomes in cattle is to determine which microbes are present and determine how and why they change over time. However, many of these microbes are difficult to culture and grow in the laboratory, so genomic techniques have provided analytical tools independent of difficult culture procedures. On a practical level, the initial cataloging of the microbiome members in beef cattle has focused almost exclusively on determining the diversity of bacteria from the rumen and feces – providing detailed lists of which bacteria are present in particular locations. Bacterial diversity includes looking at how many different kinds of bacteria are present (richness), as well the numerical distribution or proportion of bacteria within each group (evenness). Future work will likely expand to include information on which genes are expressed under particular circumstances. Genomic tools can also be used to investigate questions probing animal disease complexes such as mastitis and bovine respiratory disease or to elucidate ecological relationships such as the transmission of pathogenic or antibiotic-resistant bacteria from animals to humans.

Methods, Microbiomes, and Metagenomes

Approaches to genomic analysis of an ecosystem have been variable, and results have been difficult to relate from one study to another. Over a decade ago, randomly amplified polymorphic DNA (RAPD) allowed for rapid analysis and provided an ecosystem “fingerprint” of diversity but provided little information in regard to composition or abundance of bacteria or other microbes. Bacteria are the primary members of most ecosystems, and utilization of a conserved bacterial gene would allow for determination of composition. Nearly four decades ago, scientists reported on the conservation of the 16S ribosomal RNA (rRNA) gene and subsequently described a taxonomic system utilizing these genetic sequences. The 16S rRNA gene, or 16S rDNA, encodes part of the ribosome required for protein synthesis, and all bacteria have at least one copy of the gene. The 16S rDNA is composed of highly conserved DNA interrupted by nine separate variable regions (V1–V9) that can be used to identify specific bacterial groups and determine evolutionary relationships.

Utilizing the 16S rDNA, a variety of rapid molecular methods have been utilized to demonstrate changes in bacterial diversity, but these methods lack information on abundance. Early studies identified known community members and used tools such as hybridization probes to track designated bacterial groups in culture-independent systems. These investigations required scientists to know in advance what they were looking for, and only provided information on bacteria that were already known to be present. A second set of approaches was based on amplifying 16S rDNA from whole-community DNA samples (metagenomic samples) and then “fingerprinting” it by sorting the rDNA fragments by size or other parameters. One example of this type of fingerprinting is a method called denaturing gradient gel electrophoresis (DGGE). The amplified 16S fragments are sorted out by where they denature, and form a banding pattern in a gel. Regardless of how they are sorted, these fingerprints can be compared to examine the structure of bacterial communities between samples. Bands of interest can be cut out of the gel and sequenced to determine which bacteria are responsible for the differences. A second example of “fingerprinting” that has been applied in cattle systems is a technique called terminal restriction fragment length polymorphism (T-RFLP), where labeled PCR fragments are digested using a restriction enzyme and then sorted by size. While most microbiome analyses focus exclusively on the bacterial component of the community, T-RFLP has also been used to describe rumen protozoal communities.

Cloning and sequencing libraries of 16s rDNAs have provided useful information on diversity and abundance, but these studies are very expensive and labor intensive and typically have less than a few hundred 16S rDNA sequences. While these studies provided a glimpse into the structure of bacterial communities without the need to be able to culture bacteria in the laboratory, only the most simple microbiomes could be well characterized. However, next-generation sequencing technologies developed in recent years have allowed for high-throughput, low-cost DNA sequencing of thousands or even millions of DNA sequences, and this has allowed the statistical power needed to sequence 16s rDNAs and characterize complex communities, perform replications, follow changes in individual bacterial species composition over space and time, and catalog individual and group microbiome responses to stimuli. Sometimes called pyrosequencing, these high-throughput methods are based on sequencing relatively short fragments of DNA, with reads generally ranging around 100–200 bases. One limitation of 16S sequencing, be it classical library cloning or high-throughput sequencing, is the requirement for using PCR to amplify, or “photocopy,” the DNA before sequencing. The process of PCR requires primers to initiate the amplification process, and although a number of universal PCR primers that bind to conserved sequences have been widely adopted, they each have inherent biases that result in some bacterial groups being copied better than others. A further limitation for evaluating high-throughput 16S rDNA microbiome data is that the taxonomic assignments currently are based on only a small fragment of the entire 16S rRNA gene, typically only one or two of the nine variable regions. The compromise is that the great depth of sequencing that is possible with high-throughput metagenomic or pyrosequencing will compensate for the potential loss of resolution on any individual taxonomic assignment.

In regard to microbiome studies, the traditional bacterial taxonomic system is used to describe the results. Nonetheless, there is no consensus regarding which taxonomic level is most appropriate to describe a microbiota or which of the variable regions might provide the most useful information for communities as a whole or for specific functional groups of bacteria. Molecular ecologists use arbitrary DNA sequence similarity cutoffs to equate to species, genus, and class and thus make taxonomic assignments (Schloss and Handelsman 2004; Table 1). Recently, there has been a move away from the classic concept of “bacterial species” to the idea of functional groups or guilds of bacteria. The hypothesis is that a community setting harbors multiple bacteria that have similar functional roles and may be considered interchangeable in a particular microbiome. Nonetheless, a lack of understanding regarding the fundamental structure of bacterial communities – whether the unit of measurement should be taxonomic or guilds – contributes to the current lack of consensus on issues such as whether or not there are “core” microbiomes for cattle habitats.
Table 1

Relationship between taxonomic level and typical identity for 16s rDNA sequence for hierarchy of bacteria. Escherichia coli is presented as an example (Schloss and Handelsman 2004)

Taxonomic level

Sequence identity

Example

Species

97 %

Escherichia coli

Genus

95 %

Escherichia

Family

90 %

Enterobacteriaceae

Order

Not defined

Enterobacteriales

Class

85 %

Gammaproteobacteria

Phylum

80 %

Proteobacteria

Kingdom

Not defined

Eubacteria

Domain

Not defined

Bacteria

The term metagenome was first used by microbial community ecologists to describe all microbial genomic DNA in a particular environmental sample, collected and sequenced without the bias of culture-based techniques. The term described the starting sample – which consisted of all of the bacterial genomes and was thus considered “metagenomic.” Whole-community DNA sequencing allows researchers to evaluate all DNA in a microbiome without the biases of PCR. In this kind of sequencing approach, the DNA is sheared into fragments and sequenced directly. Since there was no amplification, the results can be quantified directly and compared across metagenomes. In addition to information on which bacteria are present, whole-community metagenomic sequencing provides information on not only for all inhabitants but also for what functional genes are present in a community. Classical library cloning and sequencing were not applicable to metagenomic studies, but next-generation high-throughput sequencing has made these studies possible.

Beef Cattle

Cattle have been domesticated for more than 10,000 years, with selection by man for meat, dairy, and/or work. The specific use of cattle often dictates the management strategy and diet. Beef cattle have been selected for meat production and meat quality, and, as such, management and diet of the animal promotes these qualities. However, diets for beef cattle can be highly variable through the beef production system. Cow-calf systems where cattle are born and weaned tend to be pasture based with animals consuming almost exclusively a forage diet, whereas in feedlots the diets tend to be rich in energy and highly digestible, which can influence the microbiomes in the rumen and feces differently. In addition, beef cattle may be fed coproducts generated from food and energy processing systems. Nonetheless, much of current microbial genomic studies in cattle has been done with production dairy animals fed rations intermediate in forage and grain compared to beef rations, and as a result information is included below.

The gastrointestinal tract is an open system responsible for nutrient digestion and absorption, and microbes are present throughout the system. The animal host has evolved not only to tolerate microbial presence but also to exploit microbial capabilities. Ruminant animals such as cattle have a four-compartment stomach that is specialized for pregastric digestion of plant materials. These four compartments are called the rumen, reticulum, omasum, and abomasum, of which the rumen is the largest and most studied. When calves are firstborn, the rumen is nonfunctional, but after about 3 weeks, the rumen begins to develop and is nearly fully functional by 6 months of age. In contrast, the lower gastrointestinal tract can develop a functional microbiome within a few weeks.

Rumen

The rumen works like a large fermentation vat, where bacteria, protozoa, and fungi break down the feed. The kinds of bacteria change over time as the rumen develops, and are influenced by the kind of food the animal is consuming. The microbes in the rumen can digest cellulosic materials such as grass and are a source of energy and protein for the host. The rumen contains eukaryotic microbes such as fungi and protozoa but is predominantly inhabited by bacteria. Although anaerobic techniques developed over the last 60 years have allowed the identification and study of many important microbes, these microbes are still fastidious and difficult to culture. A recent meta-analysis identified at least 88 different genera of bacteria cultured from various rumens (Kim et al. 2011).

Recent genomic studies consistently confirm the findings from earlier culture-based studies that the three main bacterial phyla found in the rumen are Firmicutes, Bacteroidetes, and Proteobacteria (Fig. 1). The Firmicutes are a group of thick-walled anaerobic bacteria and include bacteria from the classes Lactobacillales and Clostridia commonly associated with the rumen. The phyla Bacteroidetes and Proteobacteria are typically thin-walled bacteria, but only certain classes of the Proteobacteria can tolerate or even grow in the presence of oxygen. Together, these bacteria break down polysaccharides (such as cellulose, starch, pectin, and hemicellulose) and proteins and produce short-chain fatty acids that the animal absorbs from the rumen to use as a primary source for energy. In addition, microbial growth generates highly digestible microbial protein, which serves as a primary source for protein in the lower digestion tract. The rumen also contains another group of single-celled microbes called Archaea, a domain of ancient single-celled organisms responsible for methane production in the rumen. The diversity of the microbiome in the rumen has yet to be fully appreciated (Kim et al. 2011). Based on more than 13,000 full-length and partial 16S rDNA sequence reads, the rumen appears to harbor 19 different phyla representing 179 different genera of bacteria – although only 6,000 of the fragments could be assigned to a known bacterial genus. The archaea are represented by fewer sequences, but these could be assigned to 12 genus groups. Collectively, it is estimated that fewer than 71 % of the bacteria and 65 % of the archaea have been documented to date.
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Fig. 1

Relative abundance (phylum) of 16S rDNA sequences in rumen and feces (Source: Data acquired from RDP)

The rumen of a calf is sterile in the womb, and, like the rest of the gastrointestinal tract, it becomes inoculated first by bacteria present in the birth canal and environment. After birth, processing of anaerobic microbes is typically low based on classical culture methods. Subsequent establishment of anaerobic microbes comes from the mother and the environment. Young calves typically have different bacteria in the rumen than adult cattle for the first few weeks after birth, bacteria similar to adult cattle begin to be observed at 6 weeks of age, and after 9 weeks of age, the predominant bacteria are similar to adults (Dehority and Orpin 1988). Ruminal protozoa are unable to survive in the environment for long periods of time but do not appear at high levels until after 3 weeks of age, likely a result of contact from the mother.

Recent 16S rDNA pyrosequencing of rumen samples in three calves fed milk replacer not only confirms earlier culture work in young calves but provides a clearer picture of the developing bacterial microbiome (Li et al. 2012). Firmicutes and Bacteroidetes are the predominant phyla present in rumens of 2-week-old calves, with Proteobacteria accounting for nearly 20 % of the sequenced bacteria. The Proteobacteria change with age and are reduced to 10 % of the sequenced bacteria by 6 weeks and less than 2 % by 1 year of age on a forage diet. Less than 25 % of the bacterial genera identified were observed in all samples, and 8 % of the genera observed in the 2-week-old calf were never observed again, indicating that the development of the rumen bacterial microbiome was dynamic. Predominant genera in the 2-week-old calf rumen were Prevotella, Bacteroides, Oscillibacter, Paraprevotella, Butyricimonas, and Pelistega, whereas in the 6-week-old calf, the predominant genera were Bacteroides, Porphyromonas, Prevotella, Butyricimonas, and Coprococcus. Both microbiomes in rumens of these young calves were different than older animals.

In adult cattle, animals fed grain have more culturable bacteria per g of rumen sample compared to animals fed forage (Dehority and Orpin 1988). Variation in bacterial concentrations can be attributed to amount of grain in the diet, feeding frequency and level, sampling time, and animal-to-animal variation. When fed high-grain diets, culturable bacteria from genera Butyrivibrio, Selenomonas, Ruminobacter, Prevotella, Streptococcus, Lactobacillus, Peptostreptococcus, Propionibacterium, and Anaerovibrio have been observed. Grain diets are high in starch, and strains of Butyrivibrio, Ruminobacter, Lactobacillus, and Streptococcus can degrade starch, and strains of Selenomonas, Anaerovibrio, and Propionibacterium are able to utilize lactate that accumulates in the rumen when highly digestible grains are fed. When the rumen bacterial microbiome was analyzed for grain-fed animals using pyrosequencing (Callaway et al. 2010), Prevotella, Succinivibrio, Bacteroides, Megasphaera, Butyrivibrio, Ruminobacter, and Clostridium were observed at 3 % or greater, with an additional nine genera represented at 1–3 % of the sequenced bacteria. The addition of distillers grains with solubles, a coproduct from ethanol production from corn commonly fed to cattle, to the grain diets only resulted in changes for the genera Succinivibrio and Bacteroides. In 16 dairy cattle fed a low-forage diet, Prevotella, Butyrivibrio, and Shuttleworthia were predominant genera, but higher-order taxonomic groups Lachnospiraceae, Clostridiales, and Ruminococcaceae were also abundant that could not be genus classified (Jami and Mizrahi 2012). In this latter study, more than one-half of the bacteria appeared to be similar across animals indicating a conservation of bacterial types when fed a similar diet.

In forage-fed cattle, the rumen has been well characterized using classical culture techniques (Dehority and Orpin 1988). Butyrivibrio and Prevotella are two genera that predominate. Fiber digestion is important for proper rumen function, and cellulolytic species of Ruminococcus and Fibrobacter genera are common with forage diets. When the rumen bacterial microbiome was analyzed for Bermuda grass hay or wheatgrass-fed animals using pyrosequencing (Pitta et al. 2010), the genera Prevotella and Rikenella were predominant for both types of forage, with lower levels of 15 genera at nearly 1 % abundance or higher for either diet. The ruminal bacteria from animals fed Bermuda grass hay did have more genera and greater abundance for many of the lower level genera, but were collectively more similar than the animals grazing wheatgrass. In a separate study (de Menezes et al. 2011), T-RFLP was used to analyze the ruminal bacteria from cattle grazing pasture and observed similar high levels of Prevotella, but few Rikenella. Both studies observed a number of bacterial types not previously cultured or sequenced.

Prevotella is the major ruminal genus observed with high-throughput sequencing across most bovine diets, and three species of this genus were some of the first bacteria isolated from the rumen. These species have been well studied in the laboratory, and each has unique attributes for rumen function. In dairy cattle fed low-forage diets, real-time PCR has been used to quantify the major ruminal species based on known isolates (Stevenson and Weimer 2007). Real-time PCR, sometimes called quantitative PCR, uses fluorescence to measure the quantity of amplicions produced, either using a standard curve or using fluorescence-based probes. Prevotella accounted for as much as 60 % of the bacteria, but less than 4 % of the total bacteria appeared to be accounted for by the known Prevotella species. There is potential PCR bias with Prevotella primers and the ruminal Proteobacteria (Witzig et al. 2010), but the results suggest that the diversity of the dominant genera in the rumen is greater than expected and much more research needs to be done to characterize and understand these species role in rumen function.

The bovine rumen harbors a variety of bacteria, many of which have never been isolated and studied. The metagenomics approach to study the genomic composition of an ecosystem is a powerful approach with little bias due to culture or PCR procedures, and several recent studies have been reported for the bovine rumen. Deep sequence analysis of adherent bacteria to switchgrass incubated in the rumen sequenced nearly 270 gigabases of DNA and identified more than 27,000 potential genes with carbohydrate-degrading activity (Hess et al. 2011). In addition, this study was able to assemble 15 partially sequenced microbial genomes representing taxanomic orders Spirochaetales, Clostridiales, Bacteroidales, and Myxococcales, but no DNA assembly from the phyla Proteobacteria was reported. In contrast, a separate study (Berg Miller et al. 2012) analyzed total DNA from rumen fluid (non-adhered planktonic bacteria) and examined not only bacterial but also viral genomes. This latter study found DNA predominantly from the phyla Firmicutes and Proteobacteria and an abundance of bacterial prophage viruses that target these phyla members, suggesting a high degree of interaction between bacteria and bacterial viruses. Cloning of genes from bovine ruminal metagenomes has identified several novel proteins with cellulose degradation activities (Hess et al. 2011). Work continues to link enzyme production with individual microbial community members and to correlate the presence or absence of enzyme genes with other measurable rumen parameters.

The numerous metagenomic studies done on rumen samples show that rumen bacterial diversity is sensitive to many factors, including changes in diet, age, location, and season. As with other rumen microbial diversity studies to date, the small number of animals studied makes it difficult to discern if differences observed reflect universal patterns or stochastic variation; however, they provide a solid framework on which further investigations can be built. In addition, analyses and correlations of the rumen microbiome with production traits are just beginning.

Abomasum

The abomasum in the ruminant animal is the last compartment of the multichambered stomach and serves as the gastric stomach where acid is secreted and digestion begins. In addition, the gastric stomach is a barrier for bacterial transmission to the lower gastrointestinal tract. Nonetheless, the gastric stomach harbors an adapted microbiome, but little attempt has been made to isolate bacteria from the bovine abomasum. A recent microbiome study utilizing 16S rDNA pyrosequencing approaches observed a rich diversity of bacteria in the dairy calf abomasum spanning 15 phyla. As in the rumen, the Bacteroidetes were the most prevalent group, followed by Firmicutes and Proteobacteria (Li et al. 2011).

Feces

Early full-length 16S rDNA-based studies of cattle feces from individual dairy cattle (McGarvey et al. 2004) indicated that Firmicutes are the predominant bacteria phylum in feces. High-throughput 16S rDNA pyrosequencing of dairy feces from 20 animals confirmed that Firmicutes were the most numerous bacteria in the fecal samples, and showed a diverse microflora that included Clostridium, Porphyromonas, Bacteroides, Ruminococcus, Alistipes, Lachnospira, and Prevotella (Dowd et al. 2008). Full-length sequencing of beef cattle supported the work done in dairy and outlined the three top bacterial taxa in feces as Firmicutes, Bacteroides, and Proteobacteria (Fig. 1; Durso et al. 2010). Differences were noted between beef and dairy in the presence of bacteria from the phylum Spirochaetes, but it is hard to know if these trends would remain if larger numbers of animals were sampled. Work performed in monogastric systems, such as mice and humans, indicates that the ratio of Firmicutes to Bacteroides populations is linked to obesity; however, these trends have not been observed in cattle.

There has been much interest in the effect of diet on fecal microbial communities, and a number of studies have investigated various diet and management practices in beef or dairy cattle. One study examined a variety of diets in adult beef cattle, including high-forage diets (similar to grass-fed animals) and high-grain diets (similar to finishing diets in feedlots) (Shanks et al. 2011). Other studies have investigated the bacterial diversity of feces from animals fed various diet amendments, especially various forms of distillers’ grains (Callaway et al. 2010; Rice et al. 2012; Durso et al. 2012). In every instance examined to date, differences have been noted in community members between different diets, reinforcing the fact that diet is an important factor contributing to fecal microbial community structure. These studies have typically examined no more than five or six animals per diet and have not been repeated over time. However, a study investigating fecal bacteria in dairy cattle over 8 years revealed differences in community structure for animals on similar feed in different years (Rudi et al. 2012).

Metagenomic sequencing can be used to address questions associated with manure management, including the impact of veterinary antibiotic use on human health and the ability to trace, and eventually remediate, the source of specific fecal contamination in ground and surface waters. There is also interest, as in the rumen, in mining manure holding ponds and treatment facilities for novel enzymes that could have industrial uses. Whole-community metagenomic sequencing is being used to determine which antibiotic-resistance genes are in beef cattle feces, which bacteria are likely carrying those antibiotic-resistance genes, and how antibiotic resistance in cattle feces compares to antibiotic resistance in other agricultural and nonagricultural samples. Another potential application of metagenomic sequencing is to complement or validate bacterial source tracking. Much of the current bacterial source tracking work uses T-RFLP of E. coli isolates. Using metagenomic methods, whole-community 16S rDNA sequencing is used to determine where streams and waterways are being contaminated. The idea is that 16S rDNA profiles, or libraries, can be built to describe each of the potential contamination sources, and then the contaminated sample can be compared to the libraries to find the best match. These library-dependent community diversity methods are expensive, and many are being replaced by tests that target specific bacterial groups. However, the knowledge of the structure and diversity of fecal bacterial communities remains the foundation for bacterial source tracking methods.

Both 16S rDNA and whole-genome metagenomic sequencing methods provide information that can be used to begin comparing microbiomes in both the rumen and feces. While it is expected that the rumen and the lower gastrointestinal tract (GIT) will host distinctly different bacterial populations, it is still surprising how few species or genera are shared between the two compartments. Based on 16S rDNA analysis of rumen and fecal communities, 2.7 % of the bacterial genera were shared, and only 1.5 % of the bacterial species were shared (Fig. 2). Since these analyses are based on PCR amplification of the 16S rDNA gene from metagenomic samples, both living and dead bacteria are included. This means that in the transit from rumen to feces, the majority of the rumen bacteria not only die, but that their DNA is completely degraded.
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Fig. 2

Diversity of bacterial taxa in rumen and feces. Operational taxonomic units (OTUs) measured at 97 % (species level) and 95 % (genus level)

Other Microbiomes

The bovine GIT is host to many distinctive microbiomes. Although the rumen and lower large intestine (feces) have received the most attention, there are numerous other distinct GIT compartments, each with individual microbiomes. There are a variety of interactions between the animal host and the commensal microflora, and the microbial community is thought to play an important role in mucosal immunity and overall animal health. 16S rDNA sequencing, combined with traditional and metagenomic tools for microbial community analysis, is being used to elucidate cattle microbiomes in health, infection, and disease. It has been used to a limited extent to identify bacteria communities of healthy and diseased tissue, as well as bacterial communities associated with mastitis. High-throughput 16S rDNA pyrosequencing can also be applied to insect pests of cattle, in an effort to assess relative abundance of bacteria and begin to build the resources needed to identify new vector-borne bacteria that may be pathogenic to cattle.

Summary

Though great progress has been made in deeply characterizing the rumen and fecal bacterial communities of individual animals, or small groups of animals, even these microbiomes remain largely unexplored on a population level. The work performed to date, however, provides a foundation for large-scale projects looking at how the communities in these microbiomes change over time or in response to specific diet amendments. The concept of a “core” bacterial community that is essential for and defines a particular microbiome is widely accepted – although the specific definition of what constitutes a “core microbiome” is rarely defined. There are some differences between “core” community members defined using the traditional culture-based techniques and those that have been identified via metagenomic sequencing, especially in the rumen.

Cross-References

Animal Production, Applications of Metagenomics

Mammoth and Woolly Rhinoceros, Metagenomics of

Metagenome Plasticity of the Bovine Abomasal Microbiota

Terrestrial Vertebrate Animal Metagenomics, Domesticated Bovinae

Terrestrial Vertebrate Animal Metagenomics, Non-domesticated Bovinae, Buffalo

Terrestrial Vertebrate Animal Metagenomics, Non-domesticated Bovinae, Cattle

Terrestrial Vertebrate Animal Metagenomics, Non-domesticated Buffalo

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