BackgroundIn many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs) present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base errors. We also introduce a novel chimera removal program, Perseus, that exploits the sequence abundances associated with pyrosequencing data. We use data sets where samples of known diversity have been amplified and sequenced to quantify the effect of each of the sources of error on OTU inflation and to validate these algorithms.ResultsAmpliconNoise outperforms alternative algorithms substantially reducing per base error rates for both the GS FLX and latest Titanium protocol. All three sources of error lead to inflation of diversity estimates. In particular, chimera formation has a hitherto unrealised importance which varies according to amplification protocol. We show that AmpliconNoise allows accurate estimates of OTU number. Just as importantly AmpliconNoise generates the right OTUs even at low sequence differences. We demonstrate that Perseus has very high sensitivity, able to find 99% of chimeras, which is critical when these are present at high frequencies.ConclusionsAmpliconNoise followed by Perseus is a very effective pipeline for the removal of noise. In addition the principles behind the algorithms, the inference of true sequences using Expectation-Maximization (EM), and the treatment of chimera detection as a classification or 'supervised learning' problem, will be equally applicable to new sequencing technologies as they appear.

We present an algorithm, PyroNoise, that clusters the flowgrams of 454 pyrosequencing reads using a distance measure that models sequencing noise. This infers the true sequences in a collection of amplicons. We pyrosequenced a known mixture of microbial 16S rDNA sequences extracted from a lake and found that without noise reduction the number of operational taxonomic units is overestimated but using PyroNoise it can be accurately calculated.

No abstract

The formation of viscous foams on aeration basins and secondary clarifiers of activated sludge plants is a common and widespread problem. Foam formation is often attributed to the presence of mycolic acidcontaining actinomycetes (mycolata). In order to examine the relationship between the number of mycolata and foam, we developed a group-specific probe targeting the 16S rRNA of the mycolata, a protocol to permeabilize mycolata, and a statistically robust quantification method. Statistical analyses showed that a lipase-based permeabilization method was quantitatively superior to previously described methods (P << 0.05). When mixed liquor and foam samples were examined, most of the mycolata present were rods or cocci, although filamentous mycolata were also observed. A nested analysis of variance showed that virtually all of the measured variance occurred between fields of view and not between samples. On this basis we determined that as few as five fields of view could be used to give a statistically meaningful sample. Quantitative fluorescent in situ hybridization (FISH) was used to examine the relationship between foaming and the concentration of mycolata in a 20-m 3 completely mixed activated sludge plant. Foaming occurred when the number of mycolata exceeded a certain threshold value. Baffling of the plant affected foaming without affecting the number of mycolata. We tentatively estimated that the threshold foaming concentration of mycolata was about 2 ؋ 10 6 cells ml ؊1 or 4 ؋ 10 12 cells m ؊2. We concluded that quantitative use of FISH is feasible and that quantification is a prerequisite for rational investigation of foaming in activated sludge.Microbe-based treatment problems occur in the plants of even the most sophisticated and experienced water utilities. One of the most intractable and widespread problems is the formation of viscous foams in activated sludge plants. Such foams appear as bacterial biomass floating on the surfaces of aeration basins and secondary sedimentation tanks. The presence of foam may lead to severe operational problems and may cause plants to fail effluent standards. The occurrence of foam is unpredictable, and there is uncertainty about the cause and mechanism of foaming; the control mechanisms used currently are empirical and frequently ineffective (45). It is thought that foams may form when gas bubbles are stabilized by the presence of hydrophobic particles and surfactants; the bubbles then rise to the surface and accumulate (45). The hydrophobic particles are assumed to be bacteria.Microscopic examination of foams usually reveals the presence of large numbers of one or two filamentous bacterial morphotypes. It is assumed that the morphotypes that are branched are mycolic acid-containing actinomycetes (mycolata) (13, 48) and that unbranched filaments are Microthrix parvicella (45). Putative mycolata morphotypes are the most widely reported morphotypes (39,43) and are often referred to as "nocardia." However, a wide range of mycolata are now associated with foaming. Plate cou...

Nucleic acid based techniques, such as quantitative PCR (qPCR) and next generation sequencing (NGS), provide new insights into microbial water quality, but considerable uncertainty remains around their correct interpretation. We demonstrate, for different water sources in informal settlements in the Kathmandu Valley, Nepal, significant Spearman rank correlations between conventional and molecular microbiology methods that indicate faecal contamination. At family and genera level, 16S rRNA amplicon sequencing results obtained with the low-cost, portable next generation sequencer MinION from Oxford Nanopore Technologies had significant Spearman rank correlations with Illumina MiSeq sequencing results. However, method validation by amplicon sequencing of a MOCK microbial community revealed the need to ascertain MinION sequencing results for putative pathogens at species level with complementary qPCR assays. Vibrio cholerae hazards were poorly associated with plate count faecal coliforms, but flagged up by the MinION screening method, and confirmed by a qPCR assay. Plate counting methods remain important to assess viability of faecal coliforms in disinfected water sources. We outline a systematic approach for data collection and interpretation of such complementary results. In the Kathmandu Valley, there is high variability of water quality from different sources, including for treated water samples, illustrating the importance of disinfection at the point of use.