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BIOL2609_L23_2007 - Molecular Ecology ECOL 2007 Lecture 23...

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Unformatted text preview: Molecular Ecology ECOL 2007 Lecture 23: Environmental Genomics The microbial ecology problem • It is estimated that only 1% of prokaryotes are culturable – Can be grown in the lab from environmental samples • They can be phenotypically very similar – Although large biochemical and genetic differences are found • Traditional methods of estimating microbial diversity therefore give a very biased view: – Underestimates from enrichment culture and subsequent characterization • Biochemical and/or DNA – Selection in favour of lab-friendly species • And against ‘rare’ species and those with unusual metabolism – No knowledge of the dominant species in nature • Even estimates of bacterial numbers directly from environmental samples are prone to bias due to growth medium • The invention of molecular techniques for estimating diversity directly from environmental samples, without the need for culture, has revolutionized our understanding of microbial diversity – Genetic stains – PCR of community DNA – Metagenomics Genetic stains • Genetic stains are flourescently labelled oligonucleotides that are complementary to a region of the genome – They are applied to intact cells, so the technique is called ‘flourescent in situ hybridization’ or FISH – Most are for rRNA genes so the resolution is one of bacteria v archaea v eukarya – Others do exist for certain functional genes – Can use multiple oligonucleotides at the same time (with different dyes) FISH analysis of sewage - Red is for ammonia oxidizers and green is for nitriet oxidizers. Suggesting cross-feeding of NO2- from the producers (ammonia oxidizers) to the consumers (nitriet oxidizers) FISH analysis of sewage - Red, green and blue probes indicate different functional groups of bacteria (the yellow colour is due to some bacteria hybridizing with more than one probe) PCR of community DNA • You have already done this yourselves using DGGE • An alternative technique is to generate clone libraries of the target gene You need to screen your clones before sequencing to identify which have different inserts, this is usually achieved by RFLP fingerprinting of colonies Metagenomics • This is more inclusive than looking at diversity in a single gene among the community • But the goal is not to generate a complete genome sequence, as done for some single species • In metagenomics the idea is to: – Detect as many genes as possible that encode recognizable proteins • From this you then work out a ‘phylogenetic scaffold’ to which they belong • This is done by sequencing overlaps to the genes that include phylogenetic markers (ie: rRNA) • In ecology, this has helped to identify metabolic function in phylogenetic groups – Eg: discovery of ammonia oxidizing archaea, proteorhodopsin in Sargasso Sea proteobacteria Metagenomics case study: acid mine drainage • Clone library from mixed environmental DNA • Shotgun sequencing of random clones – 76.2 million bp • Coverage up to 10x to ensure high quality assembly of genome sequence – Only two phylotypes present: • Leptospirillum sequences were essentially identical, indicating a single strain – Recent strong selection pressure? – Founder effect? • Ferroplasma sequences revealed mosaic genomes evolved from 1-3 ancestors – Homologous recombination? • Identification of putative genes allowed modelling of the biofilm metabolic pathways, eg: – Leptospirillum has Calvin cycle genes for CO2 fixation and so is capable of autotrophy – Also has nitrogenase genes for nitrogen fixation – Ferroplasma has large number of sugar and amino acid membrane transport genes so is probably a heterotroph • Acid mine drainage is a nasty extreme environment – Maintaining a neutral pH cytoplasm and resisting metal toxicity are problematic • Ferroplasma has genes for production of isoprenoid lipids (make membranes proton [H+] impermeable) and proton exporters • Leptospirillum has a large number of cell membrane production genes, suggesting a complex cell membrane Reconstructed environmental genomes allow putative metabolic functions of communities to be established Other techniques • Transcriptome – Use of microarrays or ‘gene chips’ to detect mRNA production • Proteome – 2D electrophoresis to detect translation of proteins ...
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