Beta Diversity Estimates Research Articles

Establishment of methanogen bacterial interactions during the preweaning period of dairy cattle

Ruminant livestock are major contributors to anthropogenic methane emissions in the United States and worldwide. Enteric methane is generated by methanogenic archaea residing in ruminant digestive tracts. Information on when methanogens colonize the gut and when they begin to interact with bacteria during the early phases of the ruminant life cycle is less explored. The objectives of this study were (i) to investigate the composition of the methanogenic archaeal community at birth and through the weaning transition and (ii) to determine if and when the methanogenic archaea begin to interact with bacteria in the lower gut of neonatal dairy calves. Ten female Holstein calves (approximately 45kg birth weight) were enrolled in the study. Fecal samples were collected every two weeks (Wk 2, 4, 6, 8, 10, and 12) between birth and weaning and analyzed for methanogenic archaeal diversity via 16S rRNA amplicon sequencing and quantitative real-time PCR (RT-qPCR). Estimates of alpha diversity (Observed species, and Shannon diversity index) and beta diversity (weighted and unweighted UniFrac distances) showed significant differences (P < 0.05) between archaeal communities across timepoints. Both 16S rRNA amplicon sequencing and RT-qPCR analyses revealed Methanobrevibacter was the most prevalent genus at Wk2, Wk4, and Wk6, whereas Methanosphaera gradually increased with time and was most abundant at Wk10 and Wk12. Correlation analysis revealed that Methanobrevibacter and Methanosphaera were inversely correlated with each other and formed distinct cohorts with specific bacterial lineages similar to those reported in the mature rumen, thus revealing that these associations are established during the preweaning period. Therefore, the preweaning period presents a window of opportunity to interfere with early-life methanogenic colonization with the ultimate goal of reducing enteric methane emissions without perturbing ruminal function later in the life of dairy cattle.

Enhancing environmental DNA metabarcoding from marine ecosystems: Impact of filter type, storage method, and storage time on the assessment of fish alpha and beta diversity

AbstractThe collection of environmental DNA (eDNA) and subsequent metabarcoding are useful tools for assessing marine fish biodiversity noninvasively. It is of particular importance to evaluate biodiversity in regions that are hard to access and thus less well studied. Sampling and preservation methods tailored to the specific circumstances are required. Aquatic eDNA is often captured on filters made of different materials and pore sizes, and subsequently stored under divergent conditions for varying periods of time. Previous studies on multispecies detection in marine systems have primarily focused on capture and extraction effects. Our study, in contrast, examined the effects of filter type, storage method, and storage time on DNA yield, alpha (i.e., ZOTU richness) and beta diversity (i.e., ZOTU composition) recovered from a marine ecosystem in Shark Bay, Western Australia. We compared two different filter types (cellulose‐nitrate filters with pore sizes of 0.45 μm; glass‐fiber filters with pore sizes of 0.1 μm), two storage methods (preservation in Longmire's solution and drying, respectively), various storage times (30–68 days) on two metabarcoding assays using different fish‐specific primers. Our results showed that storage time decreased DNA yield and affected alpha and beta diversity estimates. Cellulose‐nitrate filters stored in Longmire's solution proved to be the best combination with the smallest decrease in DNA yield, no effect on alpha diversity and consistent community compositions. Storing glass‐fiber filters in Longmire's solution led to a decrease in eDNA yield and alpha diversity estimates with increasing storage time. Furthermore, the largest change in beta diversity for each metabarcode was found for glass‐fiber filters regardless of storage method. Our results highlight the importance of considering storage time and interactions between storage method and filter when analyzing eDNA results, especially when storing samples for an extended time period or comparison of samples stored for different durations.

Comparison of DNA extraction methods on different sample matrices within the same terrestrial ecosystem

Metataxonomic studies of ecosystem microbiotas require the simultaneous processing of samples with contrasting physical and biochemical traits. However, there are no published studies of comparisons of different DNA extraction kits to characterize the microbiotas of the main components of terrestrial ecosystems. Here, and to our knowledge for the first time, five DNA extraction kits were used to investigate the composition and diversity of the microbiota of a subset of samples typically studied in terrestrial ecosystems such as bulk soil, rhizosphere soil, invertebrate taxa and mammalian feces. DNA extraction kit was associated with changes in the relative abundance of hundreds of ASVs, in the same samples, resulting in significant differences in alpha and beta diversity estimates of their microbiotas. Importantly, the impact of DNA extraction kit on sample diversity varies according to sample type, with mammalian feces and soil samples showing the most and least consistent diversity estimates across DNA extraction kits, respectively. We show that the MACHEREY–NAGEL NucleoSpin® Soil kit was associated with the highest alpha diversity estimates, providing the highest contribution to the overall sample diversity, as indicated by comparisons with computationally assembled reference communities, and is recommended to be used for any large-scale microbiota study of terrestrial ecosystems.

Gut microbiota variations in wild yellow baboons (Papio cynocephalus) are associated with sex and habitat disturbance

Although male and female mammals differ in biological traits and functional needs, the contribution of this sexual dimorphism to variations in gut bacteria and fungi (gut microbiota) in relation to habitat type has not been fully examined. To understand whether the combination of sex and habitat affects gut microbiota variation, we analyzed 40 fecal samples of wild yellow baboons (Papio cynocephalus) living in contrasting habitat types (intact, well-protected vs. fragmented, less protected forests) in the Udzungwa Mountains of Tanzania. Sex determination was performed using the marker genes SRY (Sex-determining Region Y) and DDX3X-DDX3Y (DEAD-Box Helicase 3). Samples were attributed to 34 individuals (19 females and 15 males) belonging to five social groups. Combining the results of sex determination with two amplicon sequencing datasets on bacterial (V1–V3 region of the 16S rRNA gene) and fungal (ITS2) gut communities, we found that overall, baboon females had a significantly higher gut bacterial richness compared to males. Beta diversity estimates indicated that bacterial composition was significantly different between males and females, and this was true for individuals from both well- and less protected forests. Our results highlight the combined role of sex and habitat type in shaping variation in gut microbial communities in wild non-human primates.

Effects of environmental translocation and host characteristics on skin microbiomes of sun-basking fish.

Variation in the composition of skin-associated microbiomes has been attributed to host species, geographical location and habitat, but the role of intraspecific phenotypic variation among host individuals remains elusive. We explored if and how host environment and different phenotypic traits were associated with microbiome composition. We conducted repeated sampling of dorsal and ventral skin microbiomes of carp individuals (Cyprinus carpio) before and after translocation from laboratory conditions to a semi-natural environment. Both alpha and beta diversity of skin-associated microbiomes increased substantially within and among individuals following translocation, particularly on dorsal body sites. The variation in microbiome composition among hosts was significantly associated with body site, sun-basking, habitat switch and growth, but not temperature gain while basking, sex, personality nor colour morph. We suggest that the overall increase in the alpha and beta diversity estimates among hosts were induced by individuals expressing greater variation in behaviours and thus exposure to potential colonizers in the pond environment compared with the laboratory. Our results exemplify how biological diversity at one level of organization (phenotypic variation among and within fish host individuals) together with the external environment impacts biological diversity at a higher hierarchical level of organization (richness and composition of fish-associated microbial communities).

A gut microbiome signature for HIV and metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD), has emerged as an increasingly recognized problem among people living with HIV (PLWH). The gut-liver axis is considered to be strongly implicated in the pathogenesis of MASLD. We aimed to characterize the gut microbiota composition in PLWH and MASLD and compare it with that of two control groups: PLWH without MASLD and individuals with MASLD without HIV infection. We collected clinical data and stool samples from participants. Bacterial 16S rRNA genes were amplified, sequenced, and clustered into operational taxonomic unit. Alpha diversity was studied by Shannon and Simpson indexes. To study how different the gut microbiota composition is between the different groups, beta diversity estimation was evaluated by principal coordinate analysis (PCoA) using Bray-Curtis dissimilarity. To further analyze differences in microbiome composition we performed a linear discriminant analysis (LDA) effect size (LEfSe). We included 30 HIV+MASLD+, 30 HIV+MASLD- and 20 HIV-MASLD+ participants. Major butyrate producers, including Faecalibacterium, Ruminococcus, and Lachnospira dominated the microbiota in all three groups. Shannon's and Simpson's diversity metrics were higher among MASLD+ individuals (Kruskal-Wallis p = 0.047). Beta diversity analysis showed distinct clustering in MASLD-, with MASLD+ participants overlapping regardless of HIV status (ADONIS significance <0.001). MASLD was associated with increased homogeneity across individuals, in contrast to that observed in the HIV+NAFDL- group, in which the dispersion was higher (Permanova test, p value <0.001; ANOSIM, p value <0.001). MASLD but not HIV determined a different microbiota structure (HIV+MASLD- vs. HIV+MASLD+, q-value = 0.002; HIV-MASLD+ vs. HIV+MASLD+, q-value = 0.930; and HIV-MASLD+ vs. HIV+MASLD-, q-value < 0.001). The most abundant genera in MASLD- were Prevotella, Bacteroides, Dialister, Acidaminococcos, Alloprevotella, and Catenibacterium. In contrast, the most enriched genera in MASLD+ were Ruminococcus, Streptococcus, Holdemanella, Blautia, and Lactobacillus. We found a microbiome signature linked to MASLD, which had a greater influence on the overall structure of the gut microbiota than HIV status alone.

Comparison of iSeq and MiSeq as the two platforms for 16S rRNA sequencing in the study of the gut of rat microbiome

Amplicon-based next-generation sequencing (NGS) of the 16S ribosomal RNA (16S) regions is a culture-free method used to identify and analyze Procaryota occurring within a given sample. The prokaryotic 16S rRNA gene contains conserved regions and nine variable regions (V1-V9) frequently used for phylogenetic classification of genus or species in diverse microbial populations. This work compares the accuracy and efficacy of two platforms, iSeq and MiSeq from Illumina, used in sequencing 16S rRNA. The most important similarities and differences of 16S microbiome sequencing in 20 fecal rat samples were described. Genetic libraries were prepared according to 16S Metagenomic Sequencing Library Preparation (Illumina) for the V3 and V4 regions of the 16S. The species richness obtained using iSeq technology was lower compared to MiSeq. At the second taxonomy level (L2), the abundance of taxa was comparable for both platforms. At the L7, the taxa abundance was significantly different, and the number of taxa was higher for the MiSeq. The alpha diversity was lower for iSeq than for MiSeq, starting from the order to the species level. The beta diversity estimation revealed statistically significant differences in microbiota diversity starting from the class level to the species level in samples sequenced on two investigated platforms. This work disclosed that the iSeq platform could be used to evaluate the bacterial profile of the samples to characterize the overall profile. The MiSeq System seems to be better for a detailed analysis of the differences in the microbiota composition.Key points• iSeq platform allows to shorten the sequencing time three times compared to the MiSeq.• iSeq can only be used for an initial and quick microbiome assessment.• MiSeq is better for a detailed analysis of the differences in the microbiota composition.

Meta-analysis of community composition patterns of halophyte and xerophyte rhizosphere associated bacteria

In plant roots, prokaryote-plant interactions have been extensively studied worldwide, demonstrating their importance for plant survival and growth, through the exploitation of microbial metabolic processes, such as nitrogen fixation and Extracellular Polymeric Substances (EPS). Climatic and edaphological forces structure the soil bacterial pool from which plants acquire a large share of their rhizosphere microbiome. As halophyte and xerophyte plants are subject to extreme environmental conditions, prokaryote-root interactions could be pivotal for plant establishment and survival, even more under the imminent scenario of climate change and increased water scarcity; yet, we have a limited understanding on large-scale geographical patterns of root-microbe communities in arid environments. Here, we used a meta-analysis approach to compare prokaryotic community composition associated to the rhizospheres of halophytes and xerophytes from ‘arid’ environments, representing 13 angiosperm plant species from five countries (Mexico, Namibia, Pakistan, Tunisia and USA), using a Qiime2 pipeline. In taxonomic terms, rhizosphere prokaryotic communities are diverse and include cosmopolitan classes like Alphaproteobacteria, Bacilli, and Gammaproteobacteria, as well as some site-specific groups like haline-thriving Haloarchaea, and PAUC43f which was found only in Pakistan samples. Alpha (ACE, Faith PD y Shannon) and beta (Jaccard) diversity estimates suggested that the main factors modeling microbial communities are host plant family, plant ecological strategy and the abiotic environment (bioclimatic variables, soil pH and total exchangeable bases). Furthermore, life history strategy (deciduous vs. perennial) is not significant for these communities' structure. Thus, this work presents an early sketch on the macro-geographical patterns driving rhizosphere microbiomes in arid environments.

FISH, cephalopods and associated habitats of the Discovery rise seamounts, Southeast Atlantic

In February 2019, seamounts of the Discovery Rise, SE Atlantic (41–45°S, 3°W - 3°E), were explored in support of the application of the Ecosystem Approach to Fisheries Management in the Southeast Atlantic Fisheries Organization (SEAFO) Convention Area. Video records of the seafloor were produced by the Video-Assisted Multisampler System (VAMS) along 15 valid transects conducted in plateau and flank areas of Shannon, Tablemount, Discovery and Heardman seamounts at depths ranging from 394 to 1839 m. Nine benthic seascapes were classified and described based on substrate hardness, texture, slope, physical and biological modifiers as observed in the video images. Predominant water masses were estimated from temperature, salinity and dissolved oxygen vertical profiles obtained by CTD casts in the vicinity of each transect. A total of 366 fishes were seen (total observation time = 25.0 h) and classified in 32 morphotypes, included in 9 orders and 12 families. Most fish morphotypes (14) were included in the Macrouridae family. Family Moridae, on the other hand, included 65.3% of all fish records (239), with two particularly abundant morphotypes: Laemonema sp. (116) and Guttigadus sp. (92). Thirteen cephalopods were observed and classified in five morphotypes; the oegopsid squid Moroteuthopsis ingens was the most abundant of them (6). Despite the taxonomic uncertainties associated with video identifications, the explored region was found to contain a mixture of tropical – subtropical and subantarctic faunas of the Atlantic. Similarities of fauna composition and non-directional beta diversity estimates revealed some degree of seamount identity, but 57.5–61.9% of morphotypes were shared among seamounts (Jaccard = 0.425, Sørensen = 0.381). Fishes and cephalopods were more frequently observed on the shallower plateau areas under the influence of warmer and more oxygenated Antarctic Intermediate Waters. Depth and related factors did not influence richness, but dissimilarities in fauna composition between video transects increased with increasing depth intervals. Spatial habitat heterogeneity may have accounted for the increased beta diversity within seamounts. The most widely explored Tablemount seamount contained the most diverse observed sites, but also a considerable spatial variability likely associated with seascape heterogeneity. In two sites (transects 11 and 14), there were exceptionally high aggregations of the morid cods Laemonema sp., at the shallowest ‘gravely’ site explored (397 m), and Guttigadus sp., at a site of intermediate depth (1020 m) covered mostly by soft sediments. Neither of these species (or congenerics) have been previously classified as ‘seamount-aggregating” species. On the other hand, the Patagonian toothfish (Dissostichus eleginoides) and other commercial species known to aggregate in these seamounts were not found in the explored areas.

Plume Layer Influences the Amazon Reef Sponge Microbiome Primary Producers

Symbiont relationships between corals and photosynthetic microorganisms sustain coral reef existence. However, the Great Amazon Reef System (GARS) stays under a plume layer that attenuates the entry of light, and instead of corals, sponges are the major reef epifauna, for which little is known about the function of the associated microbiome. Here, we used genome-resolved metagenomics to investigate how the sponge microbiome supports its host and overcomes the reduced light availability, recovering 205 MAGs from Agelas and Geodia sponges with completeness &amp;gt;70% and contamination &amp;lt;10%. Beta diversity estimates based on the 16S rRNA genes indicated the microbiomes of Amazon and Caribbean sponges to be distinct (P&amp;lt;0.01), with heterotrophic lifestyles being prevalent in Amazon sponge microbiomes (P&amp;lt;0.05). Nevertheless, genes indicating the carbon fixation pathways 3-Hydroxypropionate/4-Hydroxybutyrate cycle, 3-Hydroxypropionate bicycle, Reductive Tricarboxylic Acid Cycle, and Calvin-Benson-Bassham cycle could be recovered in low abundance. The presence of Cyanobacteria, represented by both 16S rRNA analyses and low-quality MAGs indicated light incidence on the reef. The metabolic profile shows that the GARS sponge microbiome had genes for sulfate reduction, sulfur oxidation, nitric oxide reduction, ammonia oxidation, nitrate reduction, nitrite ammonification, nitrite oxidation, and nitrite reduction, indicating that the microbiome might play a role in detoxification of the holobiont. We conclude, that neither the plume-limited photosynthesis of the sponge microbiome nor the primary producers sustain the organic carbon input for the sponges, which likely live off plume-associated organic carbon and their heterotrophic microbiota.

How do distribution mapping methods perform in estimating beta diversity at macroecological scales? A case study with Neotropical anurans.

Species distribution mapping methods have their advantages and limitations concerning their use on theoretical and/or applied macroecological approaches. However, it remains underexplored how the estimates of community ecology metrics vary across the distributions generated by different mapping methods. Here, we mapped the distribution patterns of the anuran beta diversity in the Atlantic Forest and Cerrado hotspots generated by three mapping methods: point-to-grid (PTG), extent-of-occurrence (EOO), and ecological niche modelling (ENM) maps, so we were able to compare the congruence of the local contribution to beta diversity index (LCBD) among them, as well as their turnover and nestedness components. PTGs generated the most divergent LCBD values probably due to the more resolved spatial scale in which species' presence are considered, so EEO and ENM generated similar beta diversity estimates for both hotspots. High LCBD values in the Cerrado were recorded in ecotone regions, whereas in the Atlantic Forest the highest beta diversity values were found along the Atlantic coast. The structure of beta diversity of PTG showed way too high values of importance for the turnover component compared to the EEO and ENM maps, which also recorded higher importance for the turnover than for the nestedness component.

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

Environmental DNA (eDNA) metabarcoding is an increasingly popular tool for measuring and cataloguing biodiversity. Because the environments and substrates in which DNA is preserved differ considerably, eDNA research often requires bespoke approaches to generating eDNA data. Here, we explore how two experimental choices in eDNA study design—the number of PCR replicates and the depth of sequencing of PCR replicates—influence the composition and consistency of taxa recovered from eDNA extracts. We perform 24 PCR replicates from each of six soil samples using two of the most common metabarcodes for Fungi and Viridiplantae (ITS1 and ITS2), and sequence each replicate to an average depth of ~84,000 reads. We find that PCR replicates are broadly consistent in composition and relative abundance of dominant taxa, but that low abundance taxa are often unique to one or a few PCR replicates. Taxa observed in one out of 24 PCR replicates make up 21–29% of the total taxa detected. We also observe that sequencing depth or rarefaction influences alpha diversity and beta diversity estimates. Read sampling depth influences local contribution to beta diversity, placement in ordinations, and beta dispersion in ordinations. Our results suggest that, because common taxa drive some alpha diversity estimates, few PCR replicates and low read sampling depths may be sufficient for many biological applications of eDNA metabarcoding. However, because rare taxa are recovered stochastically, eDNA metabarcoding may never fully recover the true amplifiable alpha diversity in an eDNA extract. Rare taxa drive PCR replicate outliers of alpha and beta diversity and lead to dispersion differences at different read sampling depths. We conclude that researchers should consider the complexity and unevenness of a community when choosing analytical approaches, read sampling depths, and filtering thresholds to arrive at stable estimates.

Species-rich bark and ambrosia beetle fauna (Coleoptera, Curculionidae, Scolytinae) of the Ecuadorian Amazonian Forest Canopy.

Canopy fogging was used to sample the diversity of bark and ambrosia beetles (Coleoptera, Curculionidae, Scolytinae) at two western Amazonian rainforest sites in Ecuador. Sampling was conducted by Dr Terry Erwin and assistants from 1994–2006 and yielded 1158 samples containing 2500 scolytine specimens representing more than 400 morphospecies. Here, we analyze a subset of these data representing two ecological groups: true bark beetles (52 morphospecies) and ambrosia beetles (69 morphospecies). A high percentage of these taxa occurred as singletons and doubletons and their species accumulation curves did not reach an asymptote. Diversity estimates placed the total scolytine species richness for this taxon subset present at the two sites between 260 and 323 species. The α-diversity was remarkably high at each site, while the apparently high β-diversity was an artifact of undersampling, as shown by a Monte Carlo resampling analysis. This study demonstrates the utility of canopy fogging for the discovery of new scolytine taxa and for approximate diversity assessment, but a substantially greater sampling effort would be needed for conclusive alpha as well as beta diversity estimates.

TaxonTableTools: A comprehensive, platform-independent graphical user interface software to explore and visualise DNA metabarcoding data.

DNA metabarcoding is increasingly used as a tool to assess biodiversity in research and environmental management. Powerful analysis software exists to process raw data. However, the translation of sequence read data into biological information and downstream analyses may be difficult for end users with limited expertise in bioinformatics. Thus, there is a growing need for easy-to-use, graphical user interface (GUI) software to analyse and visualise DNA metabarcoding data. Here, we present TaxonTableTools (TTT), a new platform-independent GUI that aims to fill this gap by providing simple, reproducible analysis and visualisation workflows. At its base, TTT uses a "TaXon table", which is a data format that can be generated easily within TTT from two input files: a read table and a taxonomy table obtained using various published metabarcoding pipelines. TTT analysis and visualisation modules include Venn diagrams to compare taxon overlap among replicates, samples, or analysis methods. TTT analyses and visualises basic statistics, such as read proportion per taxon, as well as more sophisticated visualisations, such as interactive Krona charts for taxonomic data exploration. Various ecological analyses can be produced directly, including alpha or beta diversity estimates, and rarefaction analysis ordination plots. Metabarcoding data can be converted into formats required for traditional, taxonomy-based analyses performed by regulatory bioassessment programs. In addition, TTT is able to produce html-based interactive graphics that can be analysed in any web browser. The software comes with a manual and tutorial, is free and publicly available through GitHub (https://github.com/TillMacher/TaxonTableTools) or the Python package index (https://pypi.org/project/taxontabletools/).

TaxonTableTools - A comprehensive, platform-independent graphical user interface software to explore and visualise DNA metabarcoding data

DNA-based identification methods, such as DNA metabarcoding, are increasingly used as biodiversity assessment tools in research and environmental management. Although powerful analysis software exists to process raw data, the translation of sequence read data into biological information and downstream analyses may be difficult for end users with limited expertise in bioinformatics. Thus, the need for easy-to-use, graphical user interface (GUI) software to analyze and visualize DNA metabarcoding data is growing. Here we present TaxonTableTools (TTT), a new platform-independent GUI that aims to fill this gap by providing simple, reproducible analysis and visualization workflows. The input format of TTT is a so-called "TaXon table". This data format can easily be generated within TTT from two common file formats that can be obtained using various published DNA metabarcoding pipelines: a read table and a taxonomy table. TTT offers a wide range of processing, filtering and analysis modules. The user can analyze and visualize basic statistics, such as read proportion per taxon, as well as more sophisticated visualizations such as interactive Krona charts for taxonomic data exploration, or complex parallel category diagrams to assess species distribution patterns. Venn diagrams can be calculated to compare taxon overlap among replicates, samples, or analysis methods. Various ecological analyses can be produced directly, including alpha or beta diversity estimates, rarefaction analyses, and principal coordinate or non-metric multidimensional scaling plots. The taxonomy of a data set can be validated via the Global Biodiversity Information Facility (GBIF) API to check for synonyms and spelling mistakes. Furthermore, geographical distribution data can be automatically downloaded from GBIF. Additionally, TTT offers a conversion tool for DNA metabarcoding data into formats required for traditional, taxonomy-based analyses performed by regulatory bioassessment programs. Beyond that, TTT is able to produce fully interactive html-based graphics that can be analyzed in any web browser. The software comes with a manual and tutorial, is free and publicly available through GitHub (https://github.com/TillMacher/TaxonTableTools) or the Python package index (https://pypi.org/project/taxontabletools/).

Effects of Rare Microbiome Taxa Filtering on Statistical Analysis

Background: The accuracy of microbial community detection in 16S rRNA marker-gene and metagenomic studies suffers from contamination and sequencing errors that lead to either falsely identifying microbial taxa that were not in the sample or misclassifying the taxa of DNA fragment reads. Removing contaminants and filtering rare features are two common approaches to deal with this problem. While contaminant detection methods use auxiliary sequencing process information to identify known contaminants, filtering methods remove taxa that are present in a small number of samples and have small counts in the samples where they are observed. The latter approach reduces the extreme sparsity of microbiome data and has been shown to correctly remove contaminant taxa in cultured “mock” datasets, where the true taxa compositions are known. Although filtering is frequently used, careful evaluation of its effect on the data analysis and scientific conclusions remains unreported. Here, we assess the effect of filtering on the alpha and beta diversity estimation as well as its impact on identifying taxa that discriminate between disease states.Results: The effect of filtering on microbiome data analysis is illustrated on four datasets: two mock quality control datasets where the same cultured samples with known microbial composition are processed at different labs and two disease study datasets. Results show that in microbiome quality control datasets, filtering reduces the magnitude of differences in alpha diversity and alleviates technical variability between labs while preserving the between samples similarity (beta diversity). In the disease study datasets, DESeq2 and linear discriminant analysis Effect Size (LEfSe) methods were used to identify taxa that are differentially abundant across groups of samples, and random forest models were used to rank features with the largest contribution toward disease classification. Results reveal that filtering retains significant taxa and preserves the model classification ability measured by the area under the receiver operating characteristic curve (AUC). The comparison between the filtering and the contaminant removal method shows that they have complementary effects and are advised to be used in conjunction.Conclusions: Filtering reduces the complexity of microbiome data while preserving their integrity in downstream analysis. This leads to mitigation of the classification methods' sensitivity and reduction of technical variability, allowing researchers to generate more reproducible and comparable results in microbiome data analysis.

Abstract 4638: Associations of fecal microbial profiles with non-malignant breast disease and breast cancer in the Ghana Breast Health Study

Abstract Background and objective: Breast cancer burden is rising in Africa; however, breast cancer risk factors remain largely understudied in this population. The gut microbiome may play a role in the etiology of breast cancer through the regulation of estrogen homeostasis and other metabolic or immunologic pathways. We investigated the association of fecal bacteria with breast neoplasms in a case-control study conducted in Accra and Kumasi, Ghana, comprising 102 non-malignant breast disease cases, 379 invasive breast cancer cases, and 414 population-based controls nested within the Ghana Breast Health Study. Methods: We used the MO-BIO PowerMag kit for DNA extraction and sequenced the V4 region of 16S rRNA gene to characterize bacteria in fecal samples. We used DADA2 to process sequencing data. We calculated estimates of alpha diversity (observed sequence variants, Shannon index, and Faith's phylogenetic diversity), beta diversity (Bray Curtis and unweighted/weighted UniFrac), and presence/absence and relative abundance of select taxa. We then estimated the associations of the microbial metrics with non-malignant breast disease and malignant breast cancer using multivariable unconditional logistic regression. Results: Odds of malignant breast cancer were statistically significantly lower with increasing alpha diversity (all Ptrends &amp;lt;0.0001). For example, comparing those in the highest vs. lowest tertile of observed sequence variants, the odds ratio and 95% confidence interval was 0.22 (0.13-0.36). Alpha diversity estimates were also lower for non-malignant breast disease cases compared to controls but were similar to malignant cases. Likewise, based on the multivariable MiRKAT test, which compares kernel similarity matrices based on beta diversity metrics, overall microbiota composition was similar between non-malignant and malignant cases (all p's &amp;gt; 0.1) but was statistically significantly different for both case groups compared controls (all p's &amp;lt;0.001). After correction for multiple testing, 49 taxa were significantly differentially prevalent among non-malignant and malignant cases compared to controls. Cases tended to have a lower prevalence of the Families Lachnospiraceae, Ruminococcaceae, and Prevotellaceae, and the genera Bifidobacterium, Collinsella, Coprococcus, and Mitsuokella. Notably, previous evidence suggests that some of these differentially prevalent taxa encode the enzymes ß-glucuronidase and/or ß-galactosidase, which are involved in estrogen metabolism. Conclusions: Our findings suggest lower fecal alpha diversity, differences in overall microbial composition, and prevalence of certain taxa involved in estrogen metabolism may be associated with both non-malignant breast disease and invasive breast cancer. Given that the gut bacteria are potentially modifiable and targetable, our findings warrant further investigation into the role of the gut microbiota in hormone regulation and etiology of breast cancer in integrative, prospective studies. Citation Format: Doratha Byrd, Emily Vogtmann, Zeni Wu, Autumn Hullings, Xing Hua, Thomas Ahearn, James J. Goedert, Jianxin Shi, Jonine Figueroa, Louise Brinton, Montserrat Garcia-Closas, Rashmi Sinha. Associations of fecal microbial profiles with non-malignant breast disease and breast cancer in the Ghana Breast Health Study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4638.

An Assessment of Environmental Metabarcoding Protocols Aiming at Favoring Contemporary Biodiversity in Inventories of Deep-Sea Communities

The abyssal seafloor covers more than 50% of planet Earth and is a large reservoir of still mostly undescribed biodiversity. It is increasingly targeted by resource-extraction industries and yet is drastically understudied. In such remote and hard-to-access ecosystems, environmental DNA (eDNA) metabarcoding is a useful and efficient tool for studying biodiversity and implementing environmental impact assessments. Yet, eDNA analysis outcomes may be biased toward describing past rather than present communities as sediments contain both contemporary and ancient DNA. Using commercially available kits, we investigated the impacts of five molecular processing methods on eDNA metabarcoding biodiversity inventories targeting prokaryotes (16S), unicellular eukaryotes (18S-V4), and metazoans (18S-V1, COI). As the size distribution of ancient DNA is skewed toward small fragments, we evaluated the effect of removingshort DNA fragments via size selection and ethanol reconcentration using eDNA extracted from 10 g of sediment at five deep-sea sites. We also compare communities revealed by eDNA and environmental RNA (eRNA) co-extracted from ∼2 g of sedimen at the same sites. Results show that removing short DNA fragments does not affect alpha and beta diversity estimates in any of the biological compartments investigated. Results also confirm doubts regarding the possibility to better describe live communities using eRNA. With ribosomal loci, eRNA, while resolving similar spatial patterns than co-extracted eDNA, resulted in significantly higher richness estimates, supporting hypotheses of increased persistence of ribosomal RNA (rRNA) in the environment and unmeasured bias due to overabundance of rRNA and RNA release. With the mitochondrial locus, eRNA detected lower metazoan richness and resolved fewer spatial patterns than co-extracted eDNA, reflecting high messenger RNA lability. Results also highlight the importance of using large amounts of sediment (≥10 g) for accurately surveying eukaryotic diversity. We conclude that eDNA should be favored over eRNA for logistically realistic, repeatable, and reliable surveys and confirm that large sediment samples (≥10 g) deliver more complete and accurate assessments of benthic eukaryotic biodiversity and that increasing the number of biological rather than technical replicates is important to infer robust ecological patterns.

Lactobacillus pentosus KCA1 Decreases Vaginal and Gut Microbiota Associated with Bacterial Vaginosis

Introduction: Bacterial vaginosis (BV) which affects 14%–50% of reproductive-aged women in Nigeria is misdiagnosed and underreported. Treatment option is antibiotics, which leads to recurrent infections. The objectives of this study are three folds: first, to determine effects of oral feeding of Lactobacillus pentosus KCA1 on the vaginal and gut microbiota of women diagnosed with BV; second, to measure the level of two pro-inflammatory cytokines interleukin-1 (IL-1)-beta and IL-6 before and after KCA1 consumption; and third, to determine the relative abundance of bacterial metabolic genes. Materials and Methods: Seven women diagnosed with BV by Nugent score (7–10) were recruited to provide vaginal and gut sample before and after 14-day oral intake of 3 g of L. pentosus KCA1. The DNA from the swabs was processed for 16S rRNA metagenomics using Illumina MiSeq platform. The paired-end sequence FASTQ reads were imported into Illumina Basespace pipeline for quality check. In addition, EzBioCloud pipeline was used for alpha- and beta-diversity estimation using PKSSU4.0 version and open reference UCLUST_MC2 for operational taxonomic units picking at 97% cutoff. Blood samples were analyzed using ELISA technique. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States was used to predict the metabolic functions from the 16S rRNA gene dataset. Results: On average, there was no significant difference at P = 0.05 in the alpha-indices typified by Shannon index. The beta-diversity showed different clustering positions with principal coordinate analysis. However, at individual taxonomic categories, there was a significant decrease in the relative abundance of some genera associated with BV after KCA1 feeding with a corresponding increase of Lactobacillus genus. Bacterial genes related to defense systems were upregulated in the vagina. There was a two-fold downregulation of IL-1-beta after consumption of KCA1. Conclusion: Our findings suggest that L. pentosus KCA1 taken orally lowers pro-inflammatory cytokine and IL-1-beta and decreases the relative abundance of BV-associated bacteria.

A novel bioaugmentation technique effectively increases the skin-associated microbial diversity of captive eastern hellbenders.

Captive environments are maintained in hygienic ways that lack free-flowing microbes found in animals’ natural environments. As a result, captive animals often have depauperate host-associated microbial communities compared to conspecifics in the wild and may have increased disease susceptibility and reduced immune function. Eastern hellbenders (Cryptobranchus alleganiensis alleganiensis) have suffered precipitous population declines over the past few decades. To bolster populations, eastern hellbenders are reared in captivity before being translocated to the wild. However, the absence of natural microbial reservoirs within the captive environment diminishes the diversity of skin-associated bacteria on hellbender skin and may negatively influence their ability to defend against pathogenic species once they are released into the wild. To prepare hellbenders for natural bacteria found in riverine environments, we devised a novel bioaugmentation method to increase the diversity of skin microbial communities within a captive setting. We exposed juvenile hellbenders to increasing amounts of river water over 5 weeks before translocating them to the river. We genetically identified and phylogenetically compared bacteria collected from skin swabs and river water for alpha (community richness) and beta (community composition) diversity estimates. We found that hellbenders exposed to undiluted river water in captivity had higher alpha diversity and distinct differentiation in the community composition on their skin, compared to hellbenders only exposed to well water. We also found strong evidence that hellbender skin microbiota is host-specific rather than environmentally driven and is colonized by rare environmental operational taxonomic units in river water. This technique may increase hellbender translocation success as increasing microbial diversity is often correlated with elevated disease resistance. Future work is necessary to refine our methods, investigate the relationship between microbial diversity and hellbender health and understand how this bioaugmentation technique influences hellbenders’ survival following translocation from captivity into the wild.