Daring to be differential: metabarcoding analysis of soil and plant-related microbial communities using amplicon sequence variants and operational taxonomical units

- Third, differences in the method used affected sample diversity and number of detected differentially abundant families upon treatment.
- With the advent of these technologies, the newest research challenges are in the area of data analysis and interpretation..
- We based our analysis on two of the most prominent methods in the field: an OTU- clustering method using the USEARCH-UPARSE work- flow and an error-model based ASV method by the DADA2 workflow [14, 21].
- Community richness (defined by the number of ASVs) and diversity (measured by the Shannon diversity index) were both slightly lower in the OTU method than in the ASV method for all sequencing depths in the simulated datasets (Fig.
- 50,000 sequences), the ASV method outperformed the OTU method in the samples with higher community richness.
- Similarly, se- quencing depth and sample richness were highly corre- lated in the ASV method, leading to an underestimation of the community richness at lower sequencing depths in diverse bacterial communities (Fig.
- Additionally, a plateau in the richness curves was noticed for both the ASV and OTU methods..
- b Selected families of the bacterial soil dataset with their respective relative abundance per treatment for the ASV and OTU methods.
- 6.1%) in the low-level taxonomy than the number of unclassified OTUs (9.1.
- This is likely due to sequences of different strains that are clus- tered together as one OTU in the culture-based mock..
- In addition, the taxonomy assignment of the culture-based mock communities (V3-V4 region) was compared with the taxonomy determined on the complete 16S rRNA gene of the isolated strains in the bacterial collection.
- in the number of ASVs detected for both the ASV and usASV methods.
- 0.001), indicating less strict mer- ging and filtering of the OTU method.
- detected ASVs was correlated with the sequencing depth, i.e., the number of ASVs increased with enhanced sequencing depth as observed in the simulated data.
- this hints at the influ- ence of the ASV read partitioning (Fig.
- 3 Representation of the species richness, diversity, and coverage for the simulated bacterial dataset either analyzed by the ASV method (red) or OTU method (blue).
- Between the ASV and OTU method, 143 families overlapped, but 40 families were found exclusively in the OTU method..
- Two of the unique OTU families were also detected using the usASV method.
- mean relative abundance (RA) in the bacterial commu- nity.
- Originally, most of these families occurred in the ASV dataset but had been removed by abundance filter- ing.
- The larger proportion of significant fam- ilies in the OTU method was mainly due to low abun- dant families (RA <.
- Of the 77 fam- ilies with sole significance in the OTU method, 24 over- lapped in the usASV method, illustrating that preprocessing (filtering and merging of USEARCH) was responsible for approximately 30% of the uniquely sig- nificant families present in the OTU method.
- Of all sig- nificant families in the OTU dataset, three families were completely absent in the ASV dataset..
- 4 Shannon diversity and richness versus sequencing depth of ASV, OTU, and usASV methods in the bacterial soil dataset.
- Differences in the biological inference of the treatment effect were observed between the ASV and OTU methods.
- 5 Differences between the ASV, OTU, and usASV methods in bacterial communities in the soil dataset.
- Both Shannon diversity and richness were signifi- cantly lower in the ASV method than in the OTU and usASV methods, in accordance with the soil dataset but in contrast to the simulated and mock datasets (P <.
- In most samples, the richness of the ASV and the usASV methods seemed to be correlated with the sequencing depth, but was less than for the bacterial soil dataset (Fig.
- The Shannon diversity and community richness was sig- nificantly higher in the rhizosphere compared to the endosphere for all methods (P <.
- Only one bacterial family, the Rhodobia- ceae, was absent in the OTU method.
- The RA of this fam- ily, although still low, was remarkably higher in the usASV samples (0.11.
- 0.02 for the endosphere) than in the ASV samples (0.041.
- All remaining ASV families were detected in the other two methods as well..
- Similar to the soil dataset, the 22 unique OTU families ab- sent in the ASV and the usASV methods were low abun- dant, with an RA below 0.5%.
- In total, 145 families were detected in the usASV and OTU methods, whereas only 85 of these occurred in the ASV method.
- 6 Shannon diversity and richness verus sequencing depth of ASV, OTU, and usASV methods in the bacterial plant dataset.
- After identifying the families in the bacterial com- munities, differential abundances between rhizo- and endosphere samples were compared.
- The ASV method resulted in 32 families that were significantly enriched or depleted in the endosphere, in contrast to 151 and 83 differential families for the OTU and usASV methods, respectively (FDR <.
- 0.05) in the ASV method for all four families, significant for only MND8 in the usASV method, with no significant de- pletion found at family level when analyzed using the OTU method (Table S4).
- Three families that were significantly differential in the usASV method were completely absent in the OTU method.
- Furthermore, 17 other families were detected as significantly differential in the usASV method, but not in the OTU method.
- Except for three families, namely 0319_6G20, Archangiaceae, and MND8, all the signifi- cant families detected with the ASV method were also significant in the usASV method..
- The ASV method resulted in fewer than 50% of the families in comparison to the OTU table (86 vs.
- 186 families), while after the 0.5% fil- tering, 70% of the families counted in the OTU method were found in the ASV method (29 vs.
- Using the ASV method, the simulated fungal data had a higher diversity and richness than in the OTU method, which was again highly correlated with the sequencing depth (Fig.
- However, in the fungal culture-based mock community, richness was overstated in the OTU method compared to richness in the ASV (15 ± 2) and usASV while at the same time the diversity of the OTU method was lower than the other two methods (Fig.
- Similar to the bacterial dataset, coverage for the simulated fungal dataset and culture-based mock was similar among all three methods, although with a slightly enhanced performance for the ASV method at the level of order and family in the simulated dataset (Fig.
- The number of false positives was lower in the ASV method (five genera) than those in the OTU method (28 genera) and usASV (23 genera), which probably resulted in an overestimation of richness (Table S1)..
- In the soil-related dataset, the unfiltered ASV method provided half as many ASVs/OTUs as the OTU method did (2253 vs.
- Results for the fungal alpha diversity were comparable with those in the bacterial communities for the three methods, with a significantly lower Shannon diversity and richness for the ASV method than for the OTU and usASV methods (P <.
- A similar plateau was observed in the OTU method, with only a slight increase observed as sequencing depth in- creased.
- The usASV results were comparable to those of the ASV method..
- In the OTU method, 50 additional fungal families were identified, most of which were absent in the ASV method due to the abundance filtering.
- Fourteen families were missing in the ASV dataset, but they were low- abundant in the OTU dataset (RA <.
- Analysis of the effect of tillage on the fungal family level (Fig.
- S5 C) revealed that in the ASV method, con- ventional tillage significantly changed the abundance of.
- The same three families were also signifi- cantly affected in the OTU and usASV methods.
- Three additional significant families were found in the OTU method and seven extra families were found in the usASV method (FDR <.
- In conclusion, the ASV method outperformed the OTU method when estimating the correct number of fungal species when the sample richness was low or when sufficient sequencing depth was present, possibly due to an increased number of false positives in the OTU method.
- Differences between the two methods were found for low-abundant fungal families in the biological dataset, although this was less pronounced in compari- son to the bacterial community..
- Additionally, even though the data- bases are extensive, they most probably do not contain all sequences present in the culture-based mock..
- In contrast to the community composition of the culture-based mock that was comparable when analyzed with ASV, OTU, or usASV methods, we detected unique families for each method in the soil- and plant-related datasets.
- of higher diversity in the sample, community richness and diversity are underestimated by the ASV and OTU methods, but the ASV method outperforms the OTU method when sequencing depth is high enough.
- The ASV richness seems to correlate with the sequen- cing depth, as the richness curve from the ASV method reaches a plateau, whereas this correlation was not de- tected in the OTU method.
- In our datasets, differences in diversities between rhizosphere and endosphere in the plant dataset could, for example, be detected in all methods.
- Major differences were found between used methods in the significantly differential families upon treatment in the soil dataset and compartment in the plant dataset, most distinctly for low-abundant bacterial families.
- For example, in the plant dataset, the Xanthomonadaceae and Sphin- gomonadaceae are significantly depleted in the endo- sphere when analyzed with the ASV or the usASV methods, but these high abundant families (>.
- 4% in the rhizosphere and >.
- 1.5% in the endosphere) are not detected as significant in the OTU methods..
- The number of ASVs show a correlation with diversity and, when the community is diverse enough, the richness is better estimated in the ASV method than in the OTU method.
- In contrast, the OTU method overestimated the richness in the fungal culture-based mock due to a higher number of false pos- itives that were not observed in the bacterial culture- based mock.
- In the field trial, soil was exposed to three treatments: (i) farm compost application (0 vs.
- All plants used in the experiments were grown in pots filled with Belgian field soil.
- For both bacterial and fungal datasets, reads were removed with more than three errors in the forward and five errors in the reverse reads.
- Statistical analysis of the simulated and culture-based mock communities.
- taxa present in the mock community and correctly identified), false positives (FPs.
- taxa not originally present in the mock community, but identified in the analysis), and false negatives (FNs.
- taxa originally present in the mock community, but not identified in the ana- lysis) were calculated.
- Statistical analysis of the biological datasets.
- Dif- ferential abundance in the soil microbiome was assessed for the effect of non-inversion tillage vs.
- Shannon di- versity of the bacterial culture-based mock community for each method..
- For each method, richness of the bacterial culture-based mock community with increasing sequencing depth (until 80,000 sequences).
- Shannon diversity of the fungal culture-based mock community for each method.
- For each method, richness of the fungal culture-based mock community with increasing sequencing depth (until 100,000 sequences).
- Differential abundances for non- inverted tillage versus conventional tillage in the soil dataset for bacterial families in all methods.
- The light and dark blue colors indicates decrease and increase in the relative abundance, respectively..
- Representation of the species richness, diversity, and coverage for the simulated fungal dataset analyzed either using the ASV method (red) or OTU method (blue).
- Shannon diversity and richness versus sequencing depth of ASV, OTU and usASV method in the fungal soil dataset (A and B) and differential abundances for non-inverted tillage versus plowing in the soil dataset for fungal families in all methods (C)..
- The light and dark blue colors indicate decrease and increase in the relative abundance, respectively.
- Six technical replicates were analyzed, each resulting in the same values for coverage, FPs, and FNs.
- Relative abundances of five families in the OTU, ASV, and usASV methods.
- 16S rRNA sequences of the bacterial strains of the mock community.
- Composition of the fungal mock community using the different DNA extraction methods..
- was involved in the design and supervision of the soil experiment, S..
- The funding agen- cies had no role in the design of the study, collection, analysis, or interpret- ation of data, or in writing the manuscript..
- The raw demultiplexed sequence data are available in the NCBI Sequence Read Archive under accession numbers PRJNA602824 (field soil dataset), PRJNA524079 (plant-related experiment) and PRJNA601852 (bacterial and fungal mock) and PRJNA601863 (simulated bacterial and fungal mock)..
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