The term microbiome, coined by Lederberg and McCray as "... the ecological community of
commensal, symbiotic and pathogenic microorganisms that literally share our body space ", brings together a considerable number of disciplines with the general aim of understanding and finally exploiting the functioning of microbial systems. The human microbiome continues to be intensively studied, but microbial samples have been collected from almost every conceivable habitat on Earth, from the upper atmosphere to the subsurface of the seabed, from hot springs to glacier ice, from caves to our Italian monuments, and from entrails of nematodes to whale carcasses.
Microbiome analysis makes use of a set of tools; A common workflow for microbiome analysis looks like this: sampling (e.g. soil, water, faeces), rRNA to DNA conversion or DNA extraction, DNA sequencing, and bioinformatics analysis to describe important properties of the microbiome . This pipeline is applied to a large number of samples from a wide range of environments. We distinguish a targeted sequencing approach using the polymerase chain reaction (PCR) of "marker genes", also known as amplicon squencing and a shotgun metagenomics approach .
Characterization of the prokaryotic microbiome using the 16S rRNA gene
The workhorse of the study of microbial diversity has so far been the 16S ribosomal RNA gene, which has been the subject of intense protocol development: see for example Earth Microbiome Project (EMP) and a detailed evaluation of 16S sequencing on Illumina Sequencing Platforms (MiSeq). However, while capturing the taxonomic composition of a microbial community, sequencing of maker genes is limited in its ability to reveal the diversity of functions present, which instead requires the application of alternative approaches.
Obtaining an accurate and relevant picture of the microbiome requires careful experimental design, sampling procedures free from unintended contamination can be extremely complex.
Other "meta-omics" methods that consider messenger RNA transcripts can reveal much more about microbial activities in a particular habitat. The combination of multiple strategies can be particularly powerful, metagenomic sequencing can involve building libraries from single gene markers (e.g. 16S rRNA genes), but also building libraries of entire microbial genomes, providing information on the functional potential of the microbiome under study.
Additionally, BioFab offers dedicated services to researchers wishing to sequence and analyze viral metagenomes (viromes) from environmental and clinical samples.
Caratterizzazione del microbioma eucariotico usando il gene rRNA 18S
The taxonomic profile of complex microbial communities through 16S rRNA marker genes has attracted widespread interest, uncovering a wide range of information on the bacterial composition of microbial communities, as well as their association with the state of health and disease. On the other hand, little is known about the eukaryotic components of microbiomes. Such components include single cell parasites and multicellular worms which are known to negatively impact the health of millions of people around the world. Current molecular methods for detecting the diversity of eukaryotic microbes in a sample rely on the sequencing of amplicons of hypervariable regions in the 18S rRNA eukaryotic gene.
As with the 16S rRNA gene used for the detection of bacterial taxa, the 18S rRNA gene is a suitable marker for eukaryotes, due to the presence of conserved genetic regions suitable for designing universal primers, separated by relatively short variable regions. which serve as barcodes to identify specific taxa. Additionally, the 18S gene has a large manually curated set of reference sequences available, essential for accurate taxonomic classification.
Current recommendations include the use of the variable region 18S 4 for broad taxonomic resolution, proposed by the Consortium for the Barcode of Life (CBOL | iBOL) , and the variable region 18S 9 proposed by Earth Microbiome Project (EMP) a > . However, adopting the 18S rRNA gene as a suitable marker faces a number of experimental and computational challenges. For example, differences in cell wall or membrane composition can affect extraction procedures, distorting the recovery of some taxa. The conserved DNA regions used for primer binding may not be 100% identical between taxa resulting in primer mismatch and consequent distortions in amplicon generation reactions.
In terms of taxonomic classification, the variability of the specific sequence of the evolutionary line can significantly affect the level at which different taxa can be resolved. While a specific variable region can be quite informative to differentiate genera or species in one evolutionary line, it can be relatively more conserved in another, allowing only a taxonomic assignment at a higher level (for example, order or family).
Therefore, additional genetic regions may be needed as markers to resolve genera or species into particular taxonomic groups.
Other genetic biomarkers in eukaryotes include the large ribosomal subunit and Internal Transcribed Spacers (ITS), mitochondrial cytochrome oxidase I, nuclear actin and alpha- / beta-tubulin proteins, myosin, Hsp70, and others. However, to date, systematic comparisons to evaluate these marker genes are dependent on the reference databases.
BioFab service specifications:
- Amplification of variable regions starting from DNA (extracted from soil, faeces or food)
- Barcoding with index Illumina
- Sequencing on Illumina platform with 2X300 paired-end running
- Depth & agrave; reading: 100,000 sequenced reads
- Delivery of sequencing data and" basic "or" advanced "bioinformatics analysis