Microbial population identification involves high-throughput sequencing of bacterial 16S rRNA genes and fungal 18S rRNA genes, as well as ITS (Internal Transcribed Spacer) sequences. The goal is to characterize microbial populations by sequencing the specific genetic regions. The term "16S rRNA gene" (18S rRNA gene) refers to the corresponding DNA sequences encoding the ribosomal 16S rRNA (18S rRNA) in bacterial (fungal) genomes. These genes include nine hypervariable regions (V1-V9) and ten conserved regions. The ITS, consisting of ITS1 and ITS2, is situated between the 18S and 5.8S regions and the 5.8S and 28S regions, respectively, in the eukaryotic ribosomal rRNA gene sequence. Sequencing of these specific regions provides valuable information about microbial species and their abundance.
In theory, the absence of information about a particular species in the analyzed sample implies its non-existence in that sample. However, two practical scenarios could affect this determination. Firstly, the PCR primers used may exhibit bias, meaning that the species could be present in the sample (albeit at a low abundance), but PCR amplification fails, leading to its non-detection in subsequent sequencing. Secondly, the absence of relevant information about this species in the database may result in the inability to align the obtained sequences to information about the species during analysis, even if the species is present in the sequenced data.
The inclusion of biological replicates is a critical consideration in the design of diversity projects, particularly those focused on differential analysis. In studies involving differential analysis, both parametric and non-parametric tests, such as t-tests and rank-sum tests, are commonly employed. Regardless of the test method, calculations involving parameters like variance and mean are integral, and meaningful numerical values can only be derived when biological replicates are present. Thus, from the perspective of data analysis principles, biological replicates are indispensable. Additionally, the factors influencing environmental samples in diversity research are inherently complex. A singular sample representing a group is insufficient and yields unreliable results. The incorporation of biological replicates adds statistical significance to the study, enhancing its reliability in the face of the multifaceted influences on environmental samples in diversity research.
Beyond diversity studies, in conventional experimental designs, the distinctions among biological replicates, technical replicates, and pooled samples have always been pivotal considerations influencing experimental design. Let's delve into the definitions and significance of these three concepts. Biological replicates, in simple terms, refer to different samples subjected to the same treatment. The inclusion of biological replicates is aimed at validating general conclusions by summarizing the results of one set of samples and generalizing these characteristics to the entire category of samples. Technical replicates are repetitions of technical procedures introduced during experiments to account for potential errors or deviations. For instance, in sequencing, performing three sequencing runs on the same soil sample forms a set of technical replicates, demonstrating the stability of library preparation and sequencing results within a reasonable range. Pooled samples, as the name suggests, involve the thorough mixing of multiple samples (often in equal proportions). Pooling samples serves to homogenize differences among individual samples, providing a more representative blend that better encapsulates the features of this category of samples. These three sample design approaches can be employed in combination or individually, depending on the research objectives. For specific inquiries, feel free to consult our technical team.
Soil Sample Collection: Choose a representative soil area and employ sterile tools to collect a specified amount of soil at a depth of 5-10 cm. Remove any impurities, portion, label, and seal each sample bag containing approximately 5-10g of soil. Store the sealed samples immediately at low temperatures. Fecal Sample Collection: Use sterile fecal collection devices or other sterilized containers to collect fecal samples. Portion, label, and promptly store the samples at low temperatures (alternatively, label and store first before portioning). For each sample, distribute into several sterile centrifuge tubes, each containing approximately 0.2g. In cases where individual mouse feces are insufficient (<0.2g), biological replicates can be combined. Avoid prolonged exposure of fecal samples to air to prevent contamination and degradation. For valuable or challenging-to-collect samples, it is advisable to create backups.
Amplicon sequencing involves PCR amplification of specific genomic regions for a particular group of microorganisms. The DNA quality check is only a part of the quality assessment, and the decision to proceed with sequencing is contingent upon the PCR amplification quality control report. In cases where nucleic acid extraction yields limited material, but sufficient quality and quantity of PCR products can be obtained, sequencing can still be carried out.
Firstly, consider whether endophytic bacteria can be isolated. If isolation is not feasible, there is an inherent risk of plant and animal tissue contamination in the sample. The potential risk in amplicon sequencing lies in the amplification of plant chloroplasts and animal mitochondrial sequences. Metagenomic sequencing may result in substantial host contamination, particularly if the host lacks a reference genome. In such cases, amplicon sequencing should be considered as a preferable option.
For amplicon sequencing, it is advisable to conduct a literature review to select primers that effectively exclude chloroplast sequences, thereby assessing the feasibility of the study. For metagenomic sequencing, a preliminary test on a subset of samples is recommended. This allows an understanding of the proportion of host (plants and animals) and microbial components within the samples. It is essential to evaluate whether the microbial data is sufficient for subsequent analyses. If the microbial data is insufficient, additional sequencing may be considered to achieve an analyzable dataset.
For research purposes only, not intended for clinical diagnosis, treatment, or individual health assessments.