Microbial Signatures in Fertile Soils Under Long-Term N Management

Long-term reliance on inorganic N to maintain and increase crop yields in overly simplified cropping systems in the U.S. Midwest region has led to soil acidification, potentially damaging biological N2 fixation and accelerating potential nitrification activities. Building on this published work, rRNA gene-based analysis via Illumina technology with QIIME 2.0 processing was used to characterize the changes in microbial communities associated with such responses. Amplicon sequence variants (ASVs) for each archaeal, bacterial, and fungal taxa were classified using the Ribosomal Database Project (RDP). Our goal was to identify bioindicators from microbes responsive to crop rotation and N fertilization rates following 34–35 years since the initiation of experiments. Research plots were established in 1981 with treatments of rotation [continuous corn (Zea mays L.) (CCC) and both the corn (Cs) and soybean (Glycine max L. Merr.) (Sc) phases of a corn-soybean rotation], and of N fertilization rates (0, 202, and 269 kg N/ha) arranged as a split-plot in a randomized complete block design with three replications. We identified a set of three archaea, and six fungal genera responding mainly to rotation; a set of three bacteria genera whose abundances were linked to N rates; and a set with the highest number of indicator genera from both bacteria (22) and fungal (12) taxa responded to N fertilizer additions only within the CCC system. Indicators associated with the N cycle were identified from each archaeal, bacterial, and fungal taxon, with a dominance of denitrifier- over nitrifier- groups. These were represented by a nitrifier archaeon Nitrososphaera, and Woesearchaeota AR15, an anaerobic denitrifier. These archaea were identified as part of the signature for CCC environments, decreasing in abundance with rotated management. The opposite response was recorded for the fungus Plectosphaerella, a potential N2O producer, less abundant under continuous corn. N fertilization in CCC or CS systems decreased the abundance of the bacteria genera Variovorax and Steroidobacter, whereas Gp22 and Nitrosospira only showed this response under CCC. In this latter system, N fertilization resulted in increased abundances of the bacterial denitrifiers Gp1, Denitratisoma, Dokdonella, and Thermomonas, along with the fungus Hypocrea, a known N2O producer. The identified signatures could help future monitoring and comparison across cropping systems as we move toward more sustainable management practices. At the same time, this is needed primary information to understand the potential for managing the soil community composition to reduce nutrient losses to the environment.

Plant production-community composition relationship associated with fungal guilds depends on grassland disturbance in surface and subsurface soils

Purpose Soil fungal guilds have been proven to influence the plant community composition-production relationship, but not much is known about their effects on surface and subsurface soils under different disturbances. Methods Here, we assessed the functional characteristics of three fungal groups using the Ribosomal Database Project (RDP) classifier and data available in FUNGuild, and we characterized the community of saprotrophic, mycorrhizal, and potential plant pathogenic fungi in surface (0–10 cm) and subsurface soils (10–20 cm) of temperate grasslands under different management practices. Results We found that grassland disturbances decreased plant aboveground production and changed plant community composition. In surface soil, antagonistic interaction between potential plant pathogens and saprotrophic fungi drove the plant community composition-production relationship. In subsurface soil, this relationship was driven by antagonistic interaction between mycorrhizal fungi and potential plant pathogens. Conclusion These findings revealed that under grassland disturbances, the surface soil fungal communities were more strongly associated with plant community composition-production relationship than those from the subsurface soil were. Potential plant pathogens played an important role in plant community composition-production relationship. This knowledge is important for predicting the shifts in ecosystem functions as a consequence of changes in soil fungal groups during grassland management.

Influence of 16S rRNA Reference Databases in Amplicon-Based Environmental Microbiome Research

Purpose: The reference databases play a pivotal role in amplicon microbiome research but the sequence content and taxonomic information available in common reference databases differ. Studies on mock community and human health microbiome have revealed the problems associated with the choice of reference database on the outcome. Nonetheless, the influence of reference databases in environmental microbiome studies is not explicitly illustrated. Methods: This study analyzed the amplicon (V1V3, V3V4, V4V5 and V6V8) data of 128 soil samples and evaluated the impact of 16S rRNA databases, Genome Taxonomy Database (GTDB), Ribosomal Database Project (RDP), SILVA and Consensus Taxonomy (ConTax), on microbiome inference. Results: The analyses showed that the distribution of observed amplicon sequence variants was significantly different (P-value < 2.647e-12) across four datasets, generated based on different databases for each amplicon region. In addition, the beta diversity was also found to be altered by different databases. Further investigation revealed that the microbiome composition inferred by different databases vary significantly (P-value=0.001), irrespective of amplicon regions. Importantly, the study found that the core-microbiome structure in environmental studies could be altered by the reference databases. Conclusion: In summary, this present study illustrates that the choice of reference database could influence the outcome of environmental microbiome research.

Clinical Characteristics and Fecal Microbiome in Recurrent Versus Nonrecurrent Clostridioides difficile Infection

Background: Up to 30% of patients with Clostridioides difficile infection (CDI) develop recurrent infection, which is associated with a 33% increased risk of mortality at 180 days. The gut microbiome plays a key role in initial and recurrent episodes of CDI. We examined the clinical characteristics and gut microbial diversity in patients with recurrent (rCDI) versus nonrecurrent CDI at a tertiary-care academic medical center. Methods: Stool samples were collected from 113 patients diagnosed with CDI between 2018 and 2019. Clinical and demographic data were extracted from the electronic medical record (Table 1), and 16S rRNA sequencing of the v4 region was carried out on the Illumina MiSeq using 2×250 paired-end reads. Sequences were binned into operational taxonomic units (OTUs) using mothur and were classified to the genus level whenever possible using the ribosomal database project data set version 16. Alpha diversity was calculated using the Shannon diversity index. Β diversity was calculated using the Bray-Curtis dissimilarity matrix. Differential abundance testing was done using DESeq to assess taxonomic differences between groups. A P value of .05 was used to assess significance. Results: In total, 55 patients had rCDI (prior positive C. difficile polymerase chain reaction in last 7–365 days) and 58 had nonrecurrent CDI (Table 1). Patients with rCDI had a higher frequency of organ transplant and comorbidity. No differences in α not β diversity were observed between groups. Also, 4 OTUs were more abundant in those with rCDI: Ruminococcus (n = 2), Odoribacter, and Lactobacillus. Patients with rCDI had microbiomes with greater proportions of Bacteroidetes (27% of OTUs) compared to the nonrecurrent group (18%) as well as fewer OTUs belonging to the Firmicutes phyla compared to the nonrecurrent patients (56% vs 59%). Among the rCDI patients, those experiencing 2 or more recurrences had greater abundances of Bacteroides and Ruminococcus, while those experiencing only 1 recurrence had significantly greater abundances of Akkermensia, Ruminococcus, Streptococcus, Roseburia, Clostridium IV, and Collinsella compared to those with only 1 recurrence (Table 2). Conclusions: Patients with rCDI had a more impaired microbiome than those with initial CDI. Ruminococcus OTUs have been previously indicated as a risk factor for recurrence and treatment failure, and they were significantly more abundant in those with rCDI and among those with multiple recurrences. The greatest differences in the microbiome were observed between those with 1 recurrence compared to those with multiple recurrences. Interventions for gut microbiome restoration should focus particularly on those with recurrent CDI.Funding: NoDisclosures: None

Strength Lies in Diversity: How Community Diversity Limits Salmonella Abundance in the Chicken Intestine

The transfer of the intestinal microbiota from adult to juvenile animals reduces Salmonella prevalence and abundance. The mechanism behind this exclusion is unknown, however, certain member species may exclude or promote pathogen colonization and Salmonella abundance in chickens correlates with intestinal community composition. In this study, newly hatched chicks were colonized with Salmonella Typhimurium and 16S rRNA libraries were generated from the cecal bacterial community at 21, 28, 35, and 42 days of age. Salmonella was quantified by real-time PCR. Operational taxonomic units (OTUs) were assigned, and taxonomic assignments were made, using the Ribosomal Database Project. Bacterial diversity was inversely proportional to the Salmonella abundance in the chicken cecum (p &lt; 0.01). In addition, cecal communities with no detectable Salmonella (exclusive community) displayed an increase in the abundance of OTUs related to specific clostridial families (Ruminococcaceae, Eubacteriaceae, and Oscillospiraceae), genera (Faecalibacterium and Turicibacter) and member species (Ethanoligenens harbinense, Oscillibacter ruminantium, and Faecalibacterium prausnitzii). For cecal communities with high Salmonella abundance (permissive community), there was a positive correlation with the presence of unclassified Lachnospiraceae, clostridial genera Blautia and clostridial species Roseburia hominis, Eubacterium biforme, and Robinsoniella peoriensis. These findings strongly support the link between the intestinal bacterial species diversity and the presence of specific member species with Salmonella abundance in the chicken ceca. Exclusive bacterial species could prove effective as direct-fed microbials for reducing Salmonella in poultry while permissive species could be used to predict which birds will be super-shedders.

Microbial Genes Involved in the Aromatic Compound Degradation Deciphered Through Metagenomics Analysis of Industrial Wastewater.

Background: Understanding microbial and functional diversity from different stages of common effluent treatment plant (CETP) plays an important role to enhance the treatment performs of wastewater systems. However, unraveling microbial interactions as well as utilization of substrate involved in complex microbial communities is a challenging task. Hence, we demonstrate an integrated approach of shotgun metagenomics and whole genome sequencing to identify the microbial diversity and genes involved in degradation of benzoate, 1,2-dichloroethane and phenylalanine metabolism and degradation pathways from CETP microbiome.Results: The taxonomy profile was annotated using the Ribosomal Database Project (RDP) database in the MG-RAST server. The results showed that, bacteria accounted for 98.46% was the most abundant domain, followed by Eukaryota (0.10%) and Archea 0.02%. At Phylum level, Proteobacteria (28.8%) were dominant, followed by Bacteroidetes (16.1%), Firmicutes (11.7%) and Fusobacteria (6.9%). The most dominated species were Klebsiella pneumoniae, Wolinella succinogenes, Pseudomonas stutzeri, Desulfovibris vulgaris, Clostridium sticklandii, and Escherichia coli. The Clusters of Orthologous Groups (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, revealed the presence of the genes responsible for the metabolism and degradation of aromatic compounds. This information was validated with the whole genome analysis of the bacteria isolated from the CETP.Conclusion: The two type of integrated meta omics analyses revealed that the metabolic and degradation capability at both community wide and individual bacterial levels. In addition, we demonstrated that microbial diversity changes with the treatment process in which inlet of CETP effluent shows higher dominancy of Proteobacteria whereas in textile industry outlet the high abundance of Firmicutes was observed. We foresee this approach would contribute in designing the bioremediation strategies for the industrial treatment process.

The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community

There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comparisons analyzing the human oral microbiome. We compared the results of taxonomical classification by Greengenes, the Human Oral Microbiome Database (HOMD), National Center for Biotechnology Information (NCBI) 16S, SILVA, and the Ribosomal Database Project (RDP) using Quantitative Insights Into Microbial Ecology (QIIME) and the Divisive Amplicon Denoising Algorithm (DADA2). There were 15 phyla present in all of the analyses, four phyla exclusive to certain databases, and different numbers of genera were identified in each database. Common genera found in the oral microbiome, such as Veillonella, Rothia, and Prevotella, are annotated by all databases; however, less common genera, such as Bulleidia and Paludibacter, are only annotated by large databases, such as Greengenes. Our results indicate that using different reference databases in 16S rRNA amplicon data analysis could lead to different taxonomic compositions, especially at genus level. There are a variety of databases available, but there are no defined criteria for data curation and validation of annotations, which can affect the accuracy and reproducibility of results, making it difficult to compare data across studies.

DISCo-microbe: design of an identifiable synthetic community of microbes

Background Microbiomes are extremely important for their host organisms, providing many vital functions and extending their hosts’ phenotypes. Natural studies of host-associated microbiomes can be difficult to interpret due to the high complexity of microbial communities, which hinders our ability to track and identify individual members along with the many factors that structure or perturb those communities. For this reason, researchers have turned to synthetic or constructed communities in which the identities of all members are known. However, due to the lack of tracking methods and the difficulty of creating a more diverse and identifiable community that can be distinguished through next-generation sequencing, most such in vivo studies have used only a few strains. Results To address this issue, we developed DISCo-microbe, a program for the design of an identifiable synthetic community of microbes for use in in vivo experimentation. The program is composed of two modules; (1) create, which allows the user to generate a highly diverse community list from an input DNA sequence alignment using a custom nucleotide distance algorithm, and (2) subsample, which subsamples the community list to either represent a number of grouping variables, including taxonomic proportions, or to reach a user-specified maximum number of community members. As an example, we demonstrate the generation of a synthetic microbial community that can be distinguished through amplicon sequencing. The synthetic microbial community in this example consisted of 2,122 members from a starting DNA sequence alignment of 10,000 16S rRNA sequences from the Ribosomal Database Project. We generated simulated Illumina sequencing data from the constructed community and demonstrate that DISCo-microbe is capable of designing diverse communities with members distinguishable by amplicon sequencing. Using the simulated data we were able to recover sequences from between 97–100% of community members using two different post-processing workflows. Furthermore, 97–99% of sequences were assigned to a community member with zero sequences being misidentified. We then subsampled the community list using taxonomic proportions to mimic a natural plant host–associated microbiome, ultimately yielding a diverse community of 784 members. Conclusions DISCo-microbe can create a highly diverse community list of microbes that can be distinguished through 16S rRNA gene sequencing, and has the ability to subsample (i.e., design) the community for the desired number of members and taxonomic proportions. Although developed for bacteria, the program allows for any alignment input from any taxonomic group, making it broadly applicable. The software and data are freely available from GitHub (https://github.com/dlcarper/DISCo-microbe) and Python Package Index (PYPI).

171 Fecal microbiota transplant at weaning improves growth performance and alters fecal microbiome in pigs

To evaluate the effect of fecal microbiota transplant (FMT) on the growth performance and fecal microbiome, a total of 24 weaned pigs were stratified by weaning BW and sex, and assigned to one of two groups: a) Control (20% glycerol); b) FMT (from a healthy-grower-stage-no-antibiotics-treated pig). Microbiota mixture or placebo were drenched to pigs for two consecutive days after weaning (d-0 and -1). All pigs were fed antibiotics-free diets for an 8 feeding phase regimes: nursery phase 1, 2, and 3 (0–8, 8–21 and 21–40 d, respectively); finisher phase 1, 2, 3, 4, and 5 (40–63, 63–78, 78–117, 117–138, and 138–166 d, respectively). Individual pig BW was recorded at each phase change, and FOMeater data were collected at the end of trial. Growth and carcass data were analyzed by GLM procedure of SAS (Cary, NC) as CBD. Rectal swabs were collected prior to treatment, on d 1 & 2, and at each phase change. DNA was extracted from these swabs, amplified by primers targeting the V4 region of the 16S rDNA gene, and sequenced using an Illumina MiSeq sequencer. Sequences were classified against Ribosomal Database Project using Mothur (v.1.42) package. Pigs received FMT tended to have greater weight gain during finisher phase 1 (1.05 vs 0.91 kg/d, P = 0.07), and heavier HCW (105.5 vs 97.6 kg, P = 0.09) than control. PCoA plot based on the Jaccard distance shows that FMT pigs microbiota community was not different from control pigs until the end of nursery phase 2 (ANOSIM, R = 0.237, P &lt; 0.01) and 3 (R = 0.241, P = 0.01). Classification-based Random Forest revealed that OTU3 Streptococcus (d 3, 63, 117) and OTU95 Selenomonas (d 8, 21) were more abundant in the FMT pigs than in control pigs. Results suggests that FMT at weaning age from grower stage pig donor modulate microbiome and improve growth performance.

DISCo-microbe: Design of an identifiable synthetic community of microbes

Background Microbiomes are extremely important for their host organisms, providing many vital functions and extending their hosts’ phenotypes. Natural studies of host-associated microbiomes can be difficult to interpret due to the high complexity of microbial communities, which hinders our ability to track and identify individual members along with the many factors that structure or perturb those communities. For this reason, researchers have turned to synthetic or constructed communities in which the identities of all members are known. However, due to the lack of tracking methods and the difficulty of creating a more diverse and identifiable community that can be distinguished through next-generation sequencing, most such in vivo studies have used only a few strains. Results To address this issue, we developed DISCo-microbe, a program for the design of an identifiable synthetic community of microbes for use in in vivo experimentation. The program is composed of two modules; (1) create, which allows the user to generate a highly diverse community list from an input DNA sequence alignment using a custom nucleotide distance algorithm, and (2) subsample, which subsamples the community list to either represent a number of grouping variables, including taxonomic proportions, or to reach a user-specified maximum number of community members. As an example, we demonstrate the generation of a synthetic microbial community that can be distinguished through amplicon sequencing. The synthetic microbial community in this example consisted of 2340 members from a starting DNA sequence alignment of 10,000 16S rRNA sequences from the Ribosomal Database Project. We then subsampled the community list using taxonomic proportions to mimic a natural plant host–associated microbiome, ultimately yielding a diverse community of 853 members. Conclusions DISCo-microbe can create a highly diverse community list of microbes that can be distinguished through 16S rRNA gene sequencing, and has the ability to subsample (i.e., design) the community for the desired number of members and taxonomic proportions. Although developed for bacteria, the program allows for any alignment input from any taxonomic group, making it broadly applicable. The software and data are freely available from GitHub (https://github.com/dlcarper/DISCo-microbe) and Python Package Index (PYPI).