39548730
Beschreibung
Karteikarten von Jordan Ward, aktualisiert vor 6 Monate
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Erstellt von Jordan Ward
vor 6 Monate
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| Frage | Antworten |
| Microbial community | all microbes in a particular “sample”/environment |
| Microbiota | which means the living organisms of an ecosystem or a particular area |
| great plate count anomaly | – up to 10% of the total population can be cultured – the CFUs (on agar plates) are usually less than 10% of the total number of cells that we see under the microscope. |
| 16S rRNA gene is a good phylogenetic gene marker because? | -it is universal (=present in all Bacteria and Archaea) - encodes for an important cellular function (encodes for 16S ribosomal RNA) - Rare/limited horizontal transfer - sufficient length (to document evolutionary history) -- c. 1500 bp - with both highly conserved areas (= identical for all bacteria) and variable areas - Allows “broad-range/”universal” primers, and differentiation of taxa by sequence variability - Good available databases (curated) allow classification. |
| hypervariable regions in 16s? | V1-V9 |
| Primers used in microbial ecology studies? | In microbial ecology studies, universal primers that target 1 or 2 hypervariable regions are usually used. For example:– 533F and 904R = 370 bp (V4-5) |
| why cant 16s be used for fungi? and how are fungi sequenced? | because fungi do not have the 16S gene however they do have the 18S gene however its practically identical in all fungi. so Sequencing of Intergenic Transcribed Spacer (ITS) is used due to high variability due to no structural constraints. |
| why can 16s rRNA gene sequence identities be Microbial taxonomic definitions can be blurry/debated? | Historically = sequences of > 97% identity represent the same species. > 95% identity represent the same genus Current = sequences of > 99-100% identity represent the same species > 94.5% identity represent the same genus ➢ Some prokaryotes may have 100% identical 16S rRNA genes, but rest of genome clearly differs --> different species |
| Approach 1: DNA amplification, cloning and sequencing |
Image:
Screenshot (277) (Einbetten)
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| Approach 2: DNA “meta-barcoding” and high-throughput amplicon sequencing |
Image:
Screenshot (277) (Einbetten)
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| OTU VS ASV | cvcvcvcv |
| Microbial composition | Data = files (fasta) with sequence reads --> one read = one taxa ➢ Composition of taxa described as “relative abundance” (converted to a %) ➢ if 5000 of 10000 sequences belong to one species = 50% relative abundance ➢ Data is “compositional” -- if one taxa increases, something/others need to decrease ➢ DOES NOT equate to actual cell abundance... ➢ e.g., 50% relative abundance of 1 million cells, not same as 50% of 1 billion cells |
| Alpha vs Beta Diversity | Alpha diversity the diversity within a particular area or ecosystem; usually expressed by the number of species (i.e., species richness) in that ecosystem Beta diversity a comparison of of diversity between multiple microbial communities. |
| Correlating community compositions with environmental conditions |
16S rRNA gene sequencing of 3000 soil
samples from 606 sites in New Zealand
➢ Calculate correlations with soil variables
➢ Communities could differentiate sites grouped by key physico-chemical properties up to 83% accuracy
➢ i.e., if you gave them a sample
they could sequence/analyse
and predict the soil type
from composition of microbes
Remember correlation ≠ causation
Image:
Screenshot (277) (Einbetten)
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| Co-occurrence network analyses of taxa between each other |
Many samples from seagrasses
➢ Correlations of species abundances
represented/explored by networks
➢ Connected in network = more correlated
in co-occurring abundances
= more likely to be interacting
(again, just an indication!)
Image:
Screenshot (277) (Einbetten)
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| weaknesses | potential sampling bias (sample too big or small does not represent diversity). DNA extraction -- some cells (e.g., Gram-positives) hard to lyse. PCR biases:– Any primer mismatches will reduce amplification of that species– Formation of chimeras: strange formations of two different sequences– Can be recognized by bioinformatics tools and discarded.– rRNA copy numbers --> more copies = over-represented– Contamination from Classification of 16S sequences limited by the reference database used:– Errors in databases (misclassified sequences) affect results– Taxonomy often changing/evolving. Not possible to resolve species or strains etc with short sequences, and what is a “species”?– Taxa with identical 16S rRNA genes often have differing genes/genomes. 16S rRNA reveals the microorganisms that are present (dead or alive) and nothing about their functions/role in the environment. |
| Ribosomal gene operons | the production of rRNA is the rate-limiting step of ribosome synthesis [4], and fast-growing bacteria and archaea accelerate ribosome synthesis by encoding multiple rRNA operons [5]. Some bacteria and archaea have “unlinked” rRNA genes, where the 16S and 23S rRNA genes are separated by large swaths of genomic space (Fig. 1). This unlinked rRNA gene arrangement was first discovered in the thermophilic bacterium Thermus thermophilus [6]. Reports of unlinked rRNA genes soon followed in additional bacteria, including the planctomycete Pirellula marina [7], the aphid endosymbiont Buchnera aphidicola. Probably fast growing microbes need these to be transcribed together = more efficient, allows more protein production |
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