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MICR3310 > 9 - Multi-omics Approaches for Microbial Communities > Flashcards

9 - Multi-omics Approaches for Microbial Communities Flashcards

1
Q

Why is AMR difficult to trace

A
  • It affects every environment on earth
  • It involves every kingdom of life
  • Not just one factor (multitude of different mechanism and any single microbe will have more than one mechanism of AMR)
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2
Q

Extracting nucleic acid from an environmental sample

A
  • Can capture DNA from non culturable organisms
  • Conclude which organisms are predominant by analyzing genomes
  • Can detect lateral gene transfer
  • Build phylogenies using DNA
  • Compare diversity
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3
Q

Three popular -omics methods

A
  • Targeted metagenomics
  • Metagenomics
  • Metatranscriptomics
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4
Q

Targeted metagenomics

A
  • 16S rRNA gene profiling
  • Quantitative method for determining population diversity and relative prevalence of members in a community
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5
Q

Metagenomics

A
  • Not quantitative
  • Used for functional genomics
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6
Q

Functional genomics

A
  • Metabolism
  • Antibiotic resistance markers
  • New synthetic pathways for novel compounds
  • Finding new microbes
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7
Q

Metatranscriptomics

A

Quantitative analysis of RNA to identify active metabolic pathways

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8
Q

Illumina sequencing steps

A
  1. Prepare genomic DNA sample
  2. Attach DNA to surface
  3. Bridge amplification
  4. Fragments become double stranded
  5. Denature the double stranded molecules
  6. Complete amplification
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9
Q

Building a sequence of an amplicon

A
  • Clusters are converted to single strands
  • DNA polymerase is used to synthesis a second strand using nucleotides each with a different coloured fluorophore
  • After each base is added the fluorescence is measured as the next base is added sequentially.
  • This generates the sequence
  • Allows 1000,000s of clusters to be sequenced in parallel
  • The adaptors contain unique barcodes that enable the
    distinction of each amplicon by computer algorithms
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10
Q

Steps of DNA sequence assembly

A
  • Base calling
  • Trimming
  • Assembly
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11
Q

Base calling

A
  • Conversion of the electronic signal to the reported base call
  • Quality control threshold and if this is not met the base will be termed unknown
  • Quality control removes noise from data leaving only high quality base calls
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12
Q

Trimming

A
  • Primer sequences are removed leaving the target sequences
  • This cleaned data goes into assembly pipelines
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13
Q

Assembly

A
  • Illumina generates “pair-end reads” ie. Each 330-440 bp fragment is sequenced from both ends sequentially
  • Computer Algorithms are used to identify the paired adaptors in each amplicon to
    generate a consensus sequence of both strands for each 440 bp fragment (called a
    kmer)
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14
Q

Kmer sequences

A
  • Can be aligned to create the genome sequence
  • Either de novo when the genome is unknown OR
  • Aligned or mapped to a reference genome
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15
Q

Metagenomics steps

A
  • Extract total DNA
  • DNA is fractionated (no amplification of a particular gene)
  • Sequence
  • Bioinformatics
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16
Q

Bioinformatics

A
  • Sequences are assembled into contigs
  • Binning separates contigs into genomes of known bacteria / archea / virus
  • Use a series of computational and statistical methods to assure sufficient coverage by assessing marker genes
  • Organise the genes into metabolic pathways (crosscheck for characteristics of known genera)
17
Q

Metatranscriptomics steps

A
  • Remove DNA
  • Purify the RNA
  • Convert RNA sequence to DNA sequence using a reverse transcriptase to create a library of copy DNA (cDNA)
  • Sequence
  • Bioinformatics analysis of sequence identity and the number of identical reads are counted
18
Q

High counts in metatranscriptomics

A

More transcription

19
Q

Low counts in metatranscriptomics

A

Less gene transcription

20
Q

Pros of metatranscriptomics

A

overview of the entire microbial population

21
Q

Cons of metatranscriptomics

A
  • Cannot tell what individual strains/species are carrying
  • e.g. g. Horizontal gene elements may appear multiple times but can’t tell if they are in the same strain or not
22
Q

Non culture dependent approaches for linking horizontal gene elements to a bacterial genome

A

Proximeta

23
Q

Proximeta

A
  • Type of proximity-ligation sequencing that permits reconstruction of high quality metagenomes of microbial communities, and also matches mobile genetic elements to their host genomes
  • Before DNA extraction, the bacterial cells are permabilised and the nucleic acid is cross-linked together (thus capturing the plasmids/phages etc)
  • After extraction the DNA is fragmented using endonucleases, then
    biotinylated and ligate cross-linked fragments so that chromosome and plasmid regions once linked by proximity are now joined on the same DNA strand for NGS.
  • The bioinformatics pipeline identifies the species and plots the elements against the
    phylogenetic tree.
24
Q

Pros of proximeta

A

Shows association of antibiotic resistance mobile elements to a particular family (eg. Neisseriaceae)

25
Q

Cons of proximeta

A
  • Not strain specific
  • Do not know if the genes are expressed unless transcriptomics is performed or the strains are cultured
26
Q

Actinobacteria enrichment

A

Enriched for phosphotransferases that modify aminoglycosides and beta-lactamases that degrade beta-lactams

27
Q

Firmicutes enrichment

A

Enriched for MFS pumps,
most antibiotic modifying enzymes and target protection mechanisms of resistance

28
Q

Proteobacteria enrichment

A

Enriched for RND and other efflux pumps in addition to genes modulating resistance.

29
Q

Human microbiome enrichment

A

enriched in most mechanisms
of resistance

30
Q

Resistomes governed by ecology

A

A few AR mechanisms were shared between the human microbiome and soil, but most diversity was dependent upon the phyla in each ecological niche

31
Q

Technological advances in computing and sequencing

A
  • New sequencing technologies (Illumina high through put sequencing)
  • Computing power (New computing algorithms to analyse huge datasets)

MICR3310 (28 decks)

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