Sequencing Introduced False Positive Rare Taxa Lead to Distorted Microbial Community Diversity, Assembly, and Interaction Interpretation in Amplicon Studies

BackgroundDue to the inherent scarcity of the microbial rare taxa, it is difficult to distinguish between bona fide rare taxa and potential false positives in metabarcoding amplicon sequencing studies. Although recently developed quality control and clustering or denoising algorithms could remove sequencing errors or non-biological artifact reads, no algorithm could remove high quality reads from sample-wise cross contaminations introduced by index misassignment. ResultsWe thoroughly evaluated the rate of index misassignment of the mostly used NovaSeq 6000 and DNBSEQ-G400 sequencing platforms using both commercial and customized mock communities, and observed significant higher (5.68% vs 0.08%) fraction of potential false positive reads for NovaSeq 6000 compared to DNBSEQ-G400 in. Significant batch effects could be caused by the randomly detected false positive or false negative rare taxa. These false detections introduced by index misassignment could also lead to inflated alpha diversity for relatively simple samples while underestimated alpha diversity for complex samples. Further test using a set of cow rumen samples reported differential rare taxa by different sequencing platforms. Correlation test of the rare taxa detected by each sequencing platform demonstrated that the Novaseq 6000 platform detected rare taxa had a much lower possibility to be correlated with the physiochemical properties of rumen fluid. Community assembly mechanism and microbial network association analysis indicated that false positive or negative rare taxa detection could lead to distorted community assembly process and identification of even fake keystone species of the community, one of which was confirmed negative by PCR cloning and following Sanger sequencing. ConclusionsMetabarcoding amplicon sequencing process may introduce scarce but not neglectable false positives. We highly suggest proper positive and negative controls and technical replicate settings, and proper sequencing platform selection in future amplicon studies, especially when the microbial rare biosphere should be focused.

NEW RECORDS AND RARE TAXA FOR THE FRESHWATER EPILITHIC DIATOMS OF COTE DIVOIRE

The aim of the present study was to contribute to knowledge of the freshwater epilithic diatoms flora of Cote dIvoire. Diatoms were sampled in February and July 2012 on glass slides previously immersed during a period of 30 days at ten stations.The species composition of new and rare taxa was compiled, accompanied by illustrations. Forty two taxa distributed among 16 genera, 8 families and 5 orders were recorded in the temporal survey.Based on species occurrence frequency, 32 rare, 2 occasional, and 8 common species were registered. According to geographic distribution, taxa recorded were mostly cosmopolitan (47.72%) and tropical (43.18%), while 9.09% were endemic.Taking into account their affinity towards pH, 3 classes of diatoms : acidophilic taxa (35.47%), indifferent taxa (59.52%) and alkaliphilic taxa (4.76%)were found in the Me River.

Assembly Processes and Co-occurrence Patterns of Abundant and Rare Bacterial Community in the Eastern Indian Ocean

Microbial communities are composed of many rare species and a few abundant species. Considering the disproportionate importance of rare species for ecosystem functioning, it is important to understand the mechanisms structuring the rare and abundant components of a diverse community in response to environmental changes. Here, we used a 16S ribosomal RNA gene sequencing approach to investigate the bacterial community diversity in the Eastern Indian Ocean (EIO) during the monsoon and intermonsoon. We employed a phylogenetic null model and network analysis to evaluate the assembly processes and co-occurrence pattern of the microbial community. We found that higher bacterial diversity was detected in the intermonsoon with high temperature and low Chlorophyll a concentrations and N/P ratios. The balance between ecological deterministic processes and stochastic processes varied with seasons in the EIO. Meanwhile, conditionally rare taxa (CRT) were more likely modulated by variable selection processes than always rare taxa (ART) and abundant taxa (AT) (CRT > ART > AT). By linking assembly process and species co-occurrence, we demonstrated that the microbial co-occurrence associations tended to be higher when deterministic processes (mainly variable selection) were weaker. This negative trend was observed in rare species rather than abundant species. The linkage could enhance our understanding of the underlying mechanisms underpinning the generation and maintenance of microbial community diversity.

The rich get richer and the poor get poorer: commonness and rarity of arctic tundra plants diverge under warming and herbivore exclusion

While most species are rare, our understanding of how rare species persist remains limited. Consequently, little is also known about how the commonness and rarity of co-occurring species might be differentially impacted by direct and indirect effects of climate change. We report results of a 15-year field experiment investigating effects on commonness and rarity of 14 arctic tundra plant taxa to warming and exclusion of large herbivores, factors demonstrated to have important effects on plant community composition in many biomes. Across all taxa, pooled commonness was reduced by experimental warming, and more strongly under herbivore exclusion than under herbivory. However, taxon-specific analyses revealed that although warming elicited variable effects on commonness, herbivore exclusion disproportionately reduced the commonness of rare taxa. Over the course of the experiment, we also observed trends in commonness and rarity under all treatments through time. Sitewide commonness increased for two common taxa, the deciduous shrubs Betula nana and Salix glauca, and declined in six other taxa, all of which were rare. Across experimental treatments, rates of increase and decline in commonness (i.e., temporal trends over the duration of the experiment) were strongly related to baseline commonness of taxa early in the experiment. Hence, commonness itself may be a strong predictor of plant species responses to climate change in the arctic tundra biome, but large herbivores may mediate such responses in rare taxa, perhaps facilitating their persistence.

Distinct Functions and Assembly Mechanisms of Soil Abundant and Rare Bacterial Taxa Under Increasing Pyrene Stresses

Elucidating the relative importance of species interactions and assembly mechanisms in regulating bacterial community structure and functions, especially the abundant and rare subcommunities, is crucial for understanding the influence of environmental disturbance in shaping ecological functions. However, little is known about how polycyclic aromatic hydrocarbon (PAH) stress alters the stability and functions of the abundant and rare taxa. Here, we performed soil microcosms with gradient pyrene stresses as a model ecosystem to explore the roles of community assembly in determining structures and functions of the abundant and rare subcommunities. The dose–effect of pyrene significantly altered compositions of abundant and rare subcommunities. With increasing pyrene stresses, diversity increased in abundant subcommunities, while it decreased in the rare. Importantly, the abundant taxa exhibited a much broader niche width and environmental adaptivity than the rare, contributing more to pyrene biodegradation, whereas rare taxa played a key role in improving subcommunity resistance to stress, potentially promoting community persistence and stability. Furthermore, subcommunity co-occurrence network analysis revealed that abundant taxa inclined to occupy the core and central position in adaptation to the pyrene stresses. Stochastic processes played key roles in the abundant subcommunity rather than the rare subcommunity. Overall, these findings extend our understanding of the ecological mechanisms and interactions of abundant and rare taxa in response to pollution stress, laying a leading theoretical basis that abundant taxa are core targets for biostimulation in soil remediation.

Methods to delineate membership in a ‘core’ community are inconsistent, rarely test the hypothesis of a ‘core’, and can mislead ecological analysis

Community ecology includes linking variation in system functions to the distribution and abundance of taxa. In inferring processes, functions, and causal taxa, it is common practice to assume a core community can be defined and that attributes of the core are representative of the entire dataset. Assuming categorical thresholds in abundance exist has the potential to be misleading, especially if rare taxa are contributing to ecological processes. Additionally, there are no standard criteria for core membership, complicating comparisons across studies. Rather, the existence of a core set of taxa can be treated as a hypothesis that may or may not be supported. We considered four methods commonly used for defining a core in studies of microbiomes and applied them to two published microbial data sets and simulations covering a range of plausible communities. We evaluated the ability of each method to correctly categorize taxa. Assignment of core taxa varied substantially among methods and datasets. Additionally, the ability of evaluated methods to capture the simulated core was contingent on the distribution of taxon abundances. While able to correctly identify core taxa in select cases, the methods disagreed more often than not. Given the lack of agreement among core assignment methods, categorization of taxa into sets corresponding to core and non-core is questionable and requires testing and validation before use in any particular context. Our results do not support applying methods of dimension reduction for core taxa classification, but instead provide additional rationale to favor analyses that use abundance data in their entirety.

Plankton Detection with Adversarial Learning and a Densely Connected Deep Learning Model for Class Imbalanced Distribution

Detecting and classifying the plankton in situ to analyze the population diversity and abundance is fundamental for the understanding of marine planktonic ecosystem. However, the features of plankton are subtle, and the distribution of different plankton taxa is extremely imbalanced in the real marine environment, both of which limit the detection and classification performance of them while implementing the advanced recognition models, especially for the rare taxa. In this paper, a novel plankton detection strategy is proposed combining with a cycle-consistent adversarial network and a densely connected YOLOV3 model, which not only solves the class imbalanced distribution problem of plankton by augmenting data volume for the rare taxa but also reduces the loss of the features in the plankton detection neural network. The mAP of the proposed plankton detection strategy achieved 97.21% and 97.14%, respectively, under two experimental datasets with a difference in the number of rare taxa, which demonstrated the superior performance of plankton detection comparing with other state-of-the-art models. Especially for the rare taxa, the detection accuracy for each rare taxa is improved by about 4.02% on average under the two experimental datasets. Furthermore, the proposed strategy may have the potential to be deployed into an autonomous underwater vehicle for mobile plankton ecosystem observation.

Revisiting the effect of PCR replication and sequencing depth on biodiversity metrics in environmental DNA metabarcoding

Environmental DNA (eDNA) metabarcoding is a common tool for measuring and cataloguing biodiversity, yet standard methodological approaches to generate metabarcoding data sets have yet to emerge, in part due to challenges understanding the biological and technical biases that affect eDNA profiles. Here, we explore how two experimental choices – depth of sequencing of PCR amplicon libraries and the number of PCR replicates – influence estimates of α and β diversity. We extracted DNA from six soil samples from three ecologically distinct locations, performed 24 PCR replicates from each using two common metabarcodes, and sequenced each to an average depth of 83,898 reads. We found PCR replicates are consistent in composition and relative abundance of abundant taxa, allowing differentiation of samples and sites. However, rare taxa were unique to one or a few replicates, suggesting that even large numbers of experimental replicates may be insufficient to catalogue biodiversity fully. We recommend that to differentiate sites, separately sequencing only a minimum of two PCR replicates to a depth that allows 1,000 reads identified to taxa, is sufficient to differentiate sites. We also conclude that metabarcoding is impractical for exhaustive taxonomic inventory and, because rare taxa are not amplified consistently, taxonomic tallies that rely on consensus among replicates artificially lower richness estimates. These findings provide new considerations for eDNA experimental design and data interpretation.