METAGENOMICS AND ITS RELEVANCE TO ANIMAL DISEASES
During last century, several techniques were developed for studying microbes, including physiology, genetics and epidemiology. The identification of the bacterial pathogens in clinical settings is largely dependent on the techniques developed in late eighties. Veterinary diagnostic bacteriology is still practicing physical detection and characterization of causative bacteria under the microscope using techniques developed by Hans Christian Gram and isolation of the bacteria in colonies on petri plates that was initiated by Robert Koch. The microbes have different and specific need for growth on solid media which increases the workflow and skill requirements in the diagnostic microbiology laboratory. Sometimes, the carbon sources in the culture media are not exactly similar to the requirements of the bacterial growth reflecting into success in isolating only limited bacterial members of the community (Nocker et al., 2007). Pathogen identification based on the traditional approach using morphology, physiology, chemistry, and biochemical characterization generally requires 2 to 5 days. In addition, phenotypic methods fail to identify the microorganism up to the species or strain level (Bochner, 2009). In some situations, the pathogens are difficult to visualize under microscope or the organisms are refractory to known culturing methods. The indirect approaches were thus developed that are independent of the culturing techniques such as, identification of specific proteins and /or nucleic acids. Molecular biology techniquesbased assays reduced the pathogen identification time (Castro-Escarpulli et al., 2015). Although, these approaches target specific molecules for individual pathogens therefore, it is difficult to detect unsuspected pathogens in the samples and requires multiple assays. The first-generation sequencing technology, Sanger sequencing, along with PCR based tests facilitated molecular identification and characterization of the pathogens and greatly aided in understanding of molecular epidemiology and host pathogen interactions. However, these technologies require prior knowledge of the pathogens and genomic sequences for clonal amplification. Beginning of the 21st century has witnessed the strengths of nucleic acid-based tests to identify, characterize and strain type the microbes. Several PCR based tests were developed in past and have been successful in demonstrating the capabilities of identifying the microbial pathogens (Costa et al., 2014). In case of bacterial pathogens, the discrepancy between the cultured diversity and in situ existing diversity resulted in adoption of the culture independent techniques for study of the bacterial communities in different niches (Hugenholtz et al., 1998; Zoetendal et al., 2004). The next generation sequencing techniques have an advantage that they are capable of identifying large number of pathogens simultaneously. The advancements in the Sanger chemistry based nucleic acid sequencing technologies have brought the
sequencing-based tests in the diagnostic laboratories. The 16S rRNA gene was being used in identification of the microbes. The 16S rRNA based phylogeny approach was introduced by Carl Woese in 1987 with 12 bacterial phyla with a few culturable representatives in each. Despite the 16S rRNA based lineages not being officially recognized (due to the continuous discovery of sequence signatures belonging to undescribed phyla), presently, the ARB-Silva database lists 67 phyla, including 37 candidate phyla; the Ribosomal Database Project 10, lists 49 phyla, including 20 candidate phyla; and National Centre for Biotechnology Information (NCBI) lists 120 phyla, including 90 candidate phyla. The phyla other than the candidate phyla do not have cultured representatives.
Metagenomics
It was a common belief that the organisms easily cultured from an ecosystem are numerically and functionally significant ones. However, later it was proven that these organisms are rarely dominant (Hugenholtz, 2002). These organisms usually get isolated due to their ability to grow in nutrient rich media at moderate temperature and under routine laboratory conditions. The cultivable organism’s proportion constitutes less than 1- 10% of the total microbial diversity (Prakash et al., 2013). The fact was earlier known as “the great plate count anomaly” but the unculturability could not be proven till the advent of molecular biology tools. Sequencing of the phylogenic marker genes was introduced to identify uncultured microbes in the environment. This approach was used largely to reconstruct phylogenies, comparison of microbial distribution in samples employing sequencing or restriction fragnent lenth polymorphism (RFLP) and quantification of relative abundance of each taxonomic group using hybridization with group-specific probes and primers.
Metagenomics helps to identify the diversity, to study the population structure and to screen and isolate genes of our interest from the members which are yet to be cultured. The 16S rRNA based phylogeny has paved way for faster identification of the pathogens as well as differentiation among the closely associated species based on the full length 16S rRNA gene sequence. The technique was developed for identification of yet to be cultured microbes from the environmental niches. The word ‘metagenome’ was first used by Handelsman et al. (1998) and refers to sequence-based study of collection of all microbial genomes found in a sample. Later, the technique was used extensively for identifying unculturable microbes from different ecosystems as well as directly identification of the functional enzymes from the metagenomic samples. The 16S rRNA based phylogeny, in combination with metagenomics approach, has allowed unbiased comparisons of microbial community members across various biological niche areas. A similar marker gene, 18S rRNA can be used for identification of eukaryotic microbes like unicellular and multicellular parasites. Although, this approach has limitations in resolving the microbial diversity lower taxonomic ranks and the universal primers are not truly universal and does not guarantee the representation of all the microbes in the sample. This approach can identify the species of the microbe but fails to provide information on the subspecies or strain information that is vital for the diagnosis in terms of pathogenicity or antibiotic resistance. This shortcoming has limited the use 16S rRNA based metagenomics into the diagnosis of microbial diseases. A better resolution can be achieved using shotgun metagenomics approach. The term ‘shotgun metagenomics’ is used to define a methodology of direct sequencing of DNA extracted from a sample without culture or enrichment. This approach is used for clinical samples in the hope of detecting and characterizing pathogens.
Metagenomic approaches
Sequencing the samples for metagenomic diagnosis has two main approaches. The first approach uses amplification of the phylogenic marker genes (preferably the 16/18S rRNA gene) after PCR amplification. The universal presence of the selected phylogenic gene in the organisms facilitates simultaneous detection of several organisms in the sample. The approach is popularly known as amplicon sequencing and a typical workflow is given in Fig. 1. Amplicon sequencing can be used for the samples where the input sample contains tissue or sample matrix that can contribute to the metagenomic DNA. Sample multiplexing; running several samples in a single sequencing run on the next generation sequencer has further reduced the costs and affordability of the technology. The 16S rRNA gene contains 9 hypervariable regions spanned with constant regions. Parts of the 16S rRNA genes that are not under strong negative selection, the mutations tend to accumulate, and variable regions are formed within the gene. The variable/hypervariable regions are flanked by the conserved regions that constituted the basis of designing the universal primers for simultaneous amplification of variable regions for microbial phylogeny. The amplified 16S rRNA genes from the samples are sequenced using next generation sequencing technologies and the sequence data is used for identification of the microbial composition within the samples. Initially, the term ‘next-generation sequencing’ was used to describe the high-throughput sequencing chemistry from classical Sanger sequencing. Later, they were recognized as second generation sequencing technologies that were based on nano engineered platforms facilitating the simultaneous sequencing of millions of nucleic acid molecules in one setup and capable of generating several gigabases (Gb) of sequence data that could be used for genome sequencing, variant detections, gene activities and basic understanding of the host pathogen interactions. However, the approach could not generate the full length 16S rRNA gene. The secondgeneration technologies needed clonal amplification of the input DNA molecules to produce detectable signal for sequencing. The third-generation sequencing technologies rely on directly sequencing the nucleic acid molecules directly. The third-generation sequencing technology is still in infancy and suffers from the throughput requirements of open-ended diagnostic utility. Currently, NGS techniques are classified as second- and third- generation sequencing methods. The second-generation technologies have limitations to sequence the complete 16/18S rRNA genes, which is crucial for taxonomic identification of the microbes up to species and strain level. Further, this approach excludes the viral counterpart which is one of the most important pathogen classes from animal health as well as zoonotic point of view. Shotgun metagenomics was successfully used to identify all types of microbes from the sequence data (Pallen, 2014). The term shotgun metagenomics refers to sequencing of the total DNA isolated from the sample and is done by using k-mer based taxonomic classifier software.
Metagenomics in diagnosis
In situations, where the conventional and molecular tests-based diagnostics fail to identify the causative agents in the samples, the metagenomic approach that is basically culture free and faster, might provide an answer. Today, it is increasingly evident that the differences in host-associated microbial communities can influence the balance between health and disease in conditions not normally thought of as microbial or infectious in origin: for example, inflammatory bowel disease, cancer or obesity. Sometimes, it may not be sufficient to focus diagnostic efforts on single pathogen in clinical samples that is thought to cause disease. Instead, it is now recognized that interactions between organisms in a community can influence disease outcome and, in some cases, it might even be appropriate to treat a whole microbial community as a pathogenic entity. Given the difficulty of culturing most of the viruses, shotgun sequencing to identify and detect human-associated viruses has been tried. The genomes of DNA viruses can be recovered through shotgun sequencing of DNA directly extracted from a sample. To detect RNA viruses, RNA extracted from a sample has to be converted to cDNA (Batty et al., 2013). The first use of metagenomics for presumptive diagnosis was reported by Wilson et al. (2014) for diagnosis of leptospirosis in the cerebrospinal fluid (CSF) by amplicon sequencing that was not detected in a control sample. The diagnosis was further confirmed by specific molecular tools and serology. In a first study, fecal metagenomics was used to detect bacterial pathogens (Nakamura et al., 2008). 156 Campylobacter sequences were found in a sample taken during a bout of illness but were absent from a convalescent sample from the same individual. The potential of diagnostic metagenomics was demonstrated on stool samples collected during the outbreak of Shiga-toxigenic E. coli O104:H4 in Germany during May–June 2011 (Loman et al., 2013). The authors could get deep coverage of the outbreak strain genome from several stool metagenomes, Illumina MiSeq bench top sequencer and subsequently using higherthroughput instrument, HiSeq2500, also recovered genome-level coverage of other pathogens like Campylobacter jejuni, Clostridium difficile, Salmonella enterica, that had been detected by routine microbiological investigation in several STEC-negative samples. This study clearly established the proof-ofprinciple that metagenomics could be used not only to detect, but also to characterize bacterial pathogens within a sample. Next generation sequencing of the pig saliva samples revealed that Streptococcus was most abundant genera and S. suis was the most abundant species suggesting that the pig saliva is a potent source of S. suis infection to piglets and animal handlers (Murase et al., 2019). In another study metagenomics was used to identify S. suis, a zoonotic pathogen, in a patient whose blood bacterial cultures were negative to post antibiotic therapy (Dai et al., 2019). Culturenegative sample of necrotic hepatitis using whole-metagenome shotgun sequencing was used to detect B. melitensis (Lazarevic et al., 2018). As Chlamydiae require labour-intensive culturing, the metagenomic method was used for characterizing the chlamydial plasmids in samples and a novel species of chlamydia was also reported (Taylor-Brown et al., 2017). Pyrosequencing was used for identifying organisms associated with mastitis, a multi etiological syndrome. The mastitis milk samples were characterized by culture as Trueperella pyogenes and Streptococcus spp.
Compiled & Shared by- Team, LITD (Livestock Institute of Training & Development)
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