Influence of qPCR workflow on target gene enumeration from environmental samples in the case of bioremediation potential estimation
Date
2012-10-22
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Abstract
Keskkonna reostumine erinevate saasteainetega (nt. naftasaadused, kloororgaanilised ühendid) on muutunud kriitiliseks probleemiks üle maailma kahjustades inimtervist, kahandades puhta joogivee varusid ning mõjutades terveid ökosüsteeme. Et klassikalised „pumpa-ja-töötle“ saastuse eemaldamise meetodid on töömahukad ja kallid, on viimastel kümnenditel hakatud aina enam otse reostuspaigas rakendama erinevaid bioloogilise tervenduse ehk bioremediatsiooni tehnoloogiaid, mis tuginevad suuresti saasteainete mikroobsele lagundamisele. Toimuvate protsesside käiku ja jätkusuutlikkust vastusena muutuvatele keskkonnatingimustele hinnatakse seejuures enamasti keemiliste ja mikrobioloogiliste parameetrite pikaajalise seire abil.
Kvantitatiivne polümeraasi ahelreaktsioon (qPCR) on aina sagedamini kasutust leidev metoodika saasteaineid lagundava mikroobikoosluse esinemise ja arvukuse hindamiseks bioremediatsiooni seirel. QPCR on kiire ja tundlik meetod, mis võimaldab nii taksonoomiliste kui funktsionaalsete märklaudgeenide arvukuse määramist hõimkonna tasemest liigi tasandini. Määratud arvukusi muude seireparameetritega (nt. saasteaine kontsentratsioon) kõrvutades on võimalik hinnata bioremediatsiooniprotsesside efektiivsust ja kulgemist uuritavas kohas. Et märklaudgeenide arvukuse määramise edukus keskkonnaproovidest sõltub mitmetest faktoritest, näiteks mikroobikoosluse DNA eraldamise meetodist ja kvaliteedist, inhibiitorite esinemisest eraldatud DNA-s, qPCR reaktsioonikeemia tüübist, märklaudjärjestuse amplifikatsiooni efektiivsusest ja tulemuste analüüsi kvaliteedist, hindasimegi erinevate qPCR reaktsiooni- ja analüüsiprotsessi modifikatsioonide mõju keskkonnaproovidest märklaudgeeni absoluutse ja suhtelise arvukuse määramisele. Leidsime, et varieeruvused qPCRi töövoos ja analüüsiprotsessis mõjutavad oluliselt märklaudgeeni absoluutse ja suhtelise arvukuse määramist keskkonnaproovidest ning seeläbi ka bioremediatsiooniga rakendamisega seotud otsuseid.
The increasingly industrialized global economy that has emerged over the last century has led to dramatically elevated releases of anthropogenic chemicals into the environment impacting whole ecosystems (i.e. the Gulf of Mexico oil spill), drinking water supplies or directly human health. Concurrently with increasing pollution levels, avid interest in developing strategies for remediation of environmental contaminants has emerged. As classic “suck and truck” strategies followed by off-site treatments are expensive, the in situ bioremediation processes like monitored natural attenuation (MNA), biostimulation, bioaugmentation and rhizoremediation have become an attractive way to rehabilitate contaminated sites. These bioremediation techniques rely extensively on the presence of an active microbial degrader population able to transform the bioavailable contaminants into harmless or less dangerous compounds. Bioremediation processes need to be continuously monitored to ensure their efficiency and sustainability. One of the increasingly used methods in bioremediation monitoring is quantitative polymerase chain reaction (qPCR) which enables quantification of the abundance of gene markers within the environment. The quantitative data generated can be used to relate variation in gene abundances with variation in abiotic and biotic factors and process rates. However, target gene quantification results from environmental samples depend on a number of factors such as the method and quality of DNA extraction, the subsequent presence of inhibitory substances in the extracted microbial community DNA, the qPCR chemistry used, the amplification efficiency achieved and the overall quality of the resultant datasets. We evaluated the scope of these aspects affecting gene enumerations by qPCR and found that modifications in qPCR workflow and analysis procedure steps can significantly influence the target gene quantification and normalization results from environmental samples and consequently also bioremediation related decision-making. For environmental monitoring purposes the most suitable method workflow relating to the characteristics of individual experiment conducted should be chosen to ensure the quality and truthfulness of obtained results.
The increasingly industrialized global economy that has emerged over the last century has led to dramatically elevated releases of anthropogenic chemicals into the environment impacting whole ecosystems (i.e. the Gulf of Mexico oil spill), drinking water supplies or directly human health. Concurrently with increasing pollution levels, avid interest in developing strategies for remediation of environmental contaminants has emerged. As classic “suck and truck” strategies followed by off-site treatments are expensive, the in situ bioremediation processes like monitored natural attenuation (MNA), biostimulation, bioaugmentation and rhizoremediation have become an attractive way to rehabilitate contaminated sites. These bioremediation techniques rely extensively on the presence of an active microbial degrader population able to transform the bioavailable contaminants into harmless or less dangerous compounds. Bioremediation processes need to be continuously monitored to ensure their efficiency and sustainability. One of the increasingly used methods in bioremediation monitoring is quantitative polymerase chain reaction (qPCR) which enables quantification of the abundance of gene markers within the environment. The quantitative data generated can be used to relate variation in gene abundances with variation in abiotic and biotic factors and process rates. However, target gene quantification results from environmental samples depend on a number of factors such as the method and quality of DNA extraction, the subsequent presence of inhibitory substances in the extracted microbial community DNA, the qPCR chemistry used, the amplification efficiency achieved and the overall quality of the resultant datasets. We evaluated the scope of these aspects affecting gene enumerations by qPCR and found that modifications in qPCR workflow and analysis procedure steps can significantly influence the target gene quantification and normalization results from environmental samples and consequently also bioremediation related decision-making. For environmental monitoring purposes the most suitable method workflow relating to the characteristics of individual experiment conducted should be chosen to ensure the quality and truthfulness of obtained results.
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Keywords
bioremedatsioon, polümeraasahelreaktsioon, saastained, efektiivsus, biomarkerid, bioremedation, polymerase chain reaction, pollutants, effectiveness, biochemical markers