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A unique signal distorts the perception of species richness and composition in high-throughput sequencing surveys of microbial communities: a case study of fungi in indoor dust.

Adams RI, Amend AS, Taylor JW, Bruns TD - Microb. Ecol. (2013)

Bottom Line: Sequence-based surveys of microorganisms in varied environments have found extremely diverse assemblages.Next, we used in silico manipulations of the observed data to confirm that a unique signature can be identified with HTS approaches when the source is abundant, whether or not the taxon identity is distinct.Lastly, aerobiology of indoor fungi is discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant & Microbial Biology, University of California, Berkeley, CA, 94720, USA, adamsri@berkeley.edu.

ABSTRACT
Sequence-based surveys of microorganisms in varied environments have found extremely diverse assemblages. A standard practice in current high-throughput sequence (HTS) approaches in microbial ecology is to sequence the composition of many environmental samples at once by pooling amplicon libraries at a common concentration before processing on one run of a sequencing platform. Biomass of the target taxa, however, is not typically determined prior to HTS, and here, we show that when abundances of the samples differ to a large degree, this standard practice can lead to a perceived bias in community richness and composition. Fungal signal in settled dust of five university teaching laboratory classrooms, one of which was used for a mycology course, was surveyed. The fungal richness and composition in the dust of the nonmycology classrooms were remarkably similar to each other, while the mycology classroom was dominated by abundantly sporulating specimen fungi, particularly puffballs, and appeared to have a lower overall richness based on rarefaction curves and richness estimators. The fungal biomass was three to five times higher in the mycology classroom than the other classrooms, indicating that fungi added to the mycology classroom swamped the background fungi present in indoor air. Thus, the high abundance of a few taxa can skew the perception of richness and composition when samples are sequenced to an even depth. Next, we used in silico manipulations of the observed data to confirm that a unique signature can be identified with HTS approaches when the source is abundant, whether or not the taxon identity is distinct. Lastly, aerobiology of indoor fungi is discussed.

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Observed richness of fungal OTUs in each of the five classrooms sampled. (I) Observed fungal OTUs are lower in classroom E where mycology class was conducted than in the other classrooms. Shading around the lines represents the standard deviation. (II) Fungal biomass in each of the sampled rooms. Fungal biomass is significantly higher in classroom E than in the other classrooms. Box and whisker plot showing the median (thick black line), the quartiles (boxed), and the extreme values (as whiskers). Outliers are shown as circles. Biomass is represented as P. purpurogenum spore equivalents as measured by qPCR of SSU rRNA gene. (III) Proportion of sequence reads for each of the 20 most abundant taxa in each of the classrooms, where each shade represents a different OTU. Note that classrooms A–D have a similar composition, while classroom E is distinct. Puffball taxa are indicated with an asterisk. The taxa are the same as those listed in Table 1
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Fig1: Observed richness of fungal OTUs in each of the five classrooms sampled. (I) Observed fungal OTUs are lower in classroom E where mycology class was conducted than in the other classrooms. Shading around the lines represents the standard deviation. (II) Fungal biomass in each of the sampled rooms. Fungal biomass is significantly higher in classroom E than in the other classrooms. Box and whisker plot showing the median (thick black line), the quartiles (boxed), and the extreme values (as whiskers). Outliers are shown as circles. Biomass is represented as P. purpurogenum spore equivalents as measured by qPCR of SSU rRNA gene. (III) Proportion of sequence reads for each of the 20 most abundant taxa in each of the classrooms, where each shade represents a different OTU. Note that classrooms A–D have a similar composition, while classroom E is distinct. Puffball taxa are indicated with an asterisk. The taxa are the same as those listed in Table 1

Mentions: Taxa appear in the same abundance order (1–20) that they appear in Fig. 1(III). All significant indicator taxa were either positively associated with classroom E (the puffballs) or negatively with classroom E (common fungi in low abundance)


A unique signal distorts the perception of species richness and composition in high-throughput sequencing surveys of microbial communities: a case study of fungi in indoor dust.

Adams RI, Amend AS, Taylor JW, Bruns TD - Microb. Ecol. (2013)

Observed richness of fungal OTUs in each of the five classrooms sampled. (I) Observed fungal OTUs are lower in classroom E where mycology class was conducted than in the other classrooms. Shading around the lines represents the standard deviation. (II) Fungal biomass in each of the sampled rooms. Fungal biomass is significantly higher in classroom E than in the other classrooms. Box and whisker plot showing the median (thick black line), the quartiles (boxed), and the extreme values (as whiskers). Outliers are shown as circles. Biomass is represented as P. purpurogenum spore equivalents as measured by qPCR of SSU rRNA gene. (III) Proportion of sequence reads for each of the 20 most abundant taxa in each of the classrooms, where each shade represents a different OTU. Note that classrooms A–D have a similar composition, while classroom E is distinct. Puffball taxa are indicated with an asterisk. The taxa are the same as those listed in Table 1
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3824195&req=5

Fig1: Observed richness of fungal OTUs in each of the five classrooms sampled. (I) Observed fungal OTUs are lower in classroom E where mycology class was conducted than in the other classrooms. Shading around the lines represents the standard deviation. (II) Fungal biomass in each of the sampled rooms. Fungal biomass is significantly higher in classroom E than in the other classrooms. Box and whisker plot showing the median (thick black line), the quartiles (boxed), and the extreme values (as whiskers). Outliers are shown as circles. Biomass is represented as P. purpurogenum spore equivalents as measured by qPCR of SSU rRNA gene. (III) Proportion of sequence reads for each of the 20 most abundant taxa in each of the classrooms, where each shade represents a different OTU. Note that classrooms A–D have a similar composition, while classroom E is distinct. Puffball taxa are indicated with an asterisk. The taxa are the same as those listed in Table 1
Mentions: Taxa appear in the same abundance order (1–20) that they appear in Fig. 1(III). All significant indicator taxa were either positively associated with classroom E (the puffballs) or negatively with classroom E (common fungi in low abundance)

Bottom Line: Sequence-based surveys of microorganisms in varied environments have found extremely diverse assemblages.Next, we used in silico manipulations of the observed data to confirm that a unique signature can be identified with HTS approaches when the source is abundant, whether or not the taxon identity is distinct.Lastly, aerobiology of indoor fungi is discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant & Microbial Biology, University of California, Berkeley, CA, 94720, USA, adamsri@berkeley.edu.

ABSTRACT
Sequence-based surveys of microorganisms in varied environments have found extremely diverse assemblages. A standard practice in current high-throughput sequence (HTS) approaches in microbial ecology is to sequence the composition of many environmental samples at once by pooling amplicon libraries at a common concentration before processing on one run of a sequencing platform. Biomass of the target taxa, however, is not typically determined prior to HTS, and here, we show that when abundances of the samples differ to a large degree, this standard practice can lead to a perceived bias in community richness and composition. Fungal signal in settled dust of five university teaching laboratory classrooms, one of which was used for a mycology course, was surveyed. The fungal richness and composition in the dust of the nonmycology classrooms were remarkably similar to each other, while the mycology classroom was dominated by abundantly sporulating specimen fungi, particularly puffballs, and appeared to have a lower overall richness based on rarefaction curves and richness estimators. The fungal biomass was three to five times higher in the mycology classroom than the other classrooms, indicating that fungi added to the mycology classroom swamped the background fungi present in indoor air. Thus, the high abundance of a few taxa can skew the perception of richness and composition when samples are sequenced to an even depth. Next, we used in silico manipulations of the observed data to confirm that a unique signature can be identified with HTS approaches when the source is abundant, whether or not the taxon identity is distinct. Lastly, aerobiology of indoor fungi is discussed.

Show MeSH