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Nearing, Jacob T., Gavin M. Douglas, André M. Comeau, and Morgan G. I. Langille. "Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches." PeerJ 6 (August 8, 2018): e5364. http://dx.doi.org/10.7717/peerj.5364.
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High-depth sequencing of universal marker genes such as the 16S rRNA gene is a common strategy to profile microbial communities. Traditionally, sequence reads are clustered into operational taxonomic units (OTUs) at a defined identity threshold to avoid sequencing errors generating spurious taxonomic units. However, there have been numerous bioinformatic packages recently released that attempt to correct sequencing errors to determine real biological sequences at single nucleotide resolution by generating amplicon sequence variants (ASVs). As more researchers begin to use high resolution ASVs, there is a need for an in-depth and unbiased comparison of these novel “denoising” pipelines. In this study, we conduct a thorough comparison of three of the most widely-used denoising packages (DADA2, UNOISE3, and Deblur) as well as an open-reference 97% OTU clustering pipeline on mock, soil, and host-associated communities. We found from the mock community analyses that although they produced similar microbial compositions based on relative abundance, the approaches identified vastly different numbers of ASVs that significantly impact alpha diversity metrics. Our analysis on real datasets using recommended settings for each denoising pipeline also showed that the three packages were consistent in their per-sample compositions, resulting in only minor differences based on weighted UniFrac and Bray–Curtis dissimilarity. DADA2 tended to find more ASVs than the other two denoising pipelines when analyzing both the real soil data and two other host-associated datasets, suggesting that it could be better at finding rare organisms, but at the expense of possible false positives. The open-reference OTU clustering approach identified considerably more OTUs in comparison to the number of ASVs from the denoising pipelines in all datasets tested. The three denoising approaches were significantly different in their run times, with UNOISE3 running greater than 1,200 and 15 times faster than DADA2 and Deblur, respectively. Our findings indicate that, although all pipelines result in similar general community structure, the number of ASVs/OTUs and resulting alpha-diversity metrics varies considerably and should be considered when attempting to identify rare organisms from possible background noise.
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Jeske, Jan Torsten, and Claudia Gallert. "Microbiome Analysis via OTU and ASV-Based Pipelines—A Comparative Interpretation of Ecological Data in WWTP Systems." Bioengineering 9, no. 4 (March 29, 2022): 146. http://dx.doi.org/10.3390/bioengineering9040146.
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Linking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service.
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Bergsten, Emma, Denis Mestivier, and Iradj Sobhani. "The Limits and Avoidance of Biases in Metagenomic Analyses of Human Fecal Microbiota." Microorganisms 8, no. 12 (December 9, 2020): 1954. http://dx.doi.org/10.3390/microorganisms8121954.
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An increasing body of evidence highlights the role of fecal microbiota in various human diseases. However, more than two-thirds of fecal bacteria cannot be cultivated by routine laboratory techniques. Thus, physicians and scientists use DNA sequencing and statistical tools to identify associations between bacterial subgroup abundances and disease. However, discrepancies between studies weaken these results. In the present study, we focus on biases that might account for these discrepancies. First, three different DNA extraction methods (G’NOME, QIAGEN, and PROMEGA) were compared with regard to their efficiency, i.e., the quality and quantity of DNA recovered from feces of 10 healthy volunteers. Then, the impact of the DNA extraction method on the bacteria identification and quantification was evaluated using our published cohort of sample subjected to both 16S rRNA sequencing and whole metagenome sequencing (WMS). WMS taxonomical assignation employed the universal marker genes profiler mOTU-v2, which is considered the gold standard. The three standard pipelines for 16S RNA analysis (MALT and MEGAN6, QIIME1, and DADA2) were applied for comparison. Taken together, our results indicate that the G’NOME-based method was optimal in terms of quantity and quality of DNA extracts. 16S rRNA sequence-based identification of abundant bacteria genera showed acceptable congruence with WMS sequencing, with the DADA2 pipeline yielding the highest congruent levels. However, for low abundance genera (<0.5% of the total abundance) two pipelines and/or validation by quantitative polymerase chain reaction (qPCR) or WMS are required. Hence, 16S rRNA sequencing for bacteria identification and quantification in clinical and translational studies should be limited to diagnostic purposes in well-characterized and abundant genera. Additional techniques are warranted for low abundant genera, such as WMS, qPCR, or the use of two bio-informatics pipelines.
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Thi Nhung, Doan, and Bui Van Ngoc. "Bioinformatic approaches for analysis of coral-associated bacteria using R programming language." Vietnam Journal of Biotechnology 18, no. 4 (May 24, 2021): 733–43. http://dx.doi.org/10.15625/1811-4989/18/4/15320.
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Recent advances in metagenomics and bioinformatics allow the robust analysis of the composition and abundance of microbial communities, functional genes, and their metabolic pathways. So far, there has been a variety of computational/statistical tools or software for analyzing microbiome, the common problems that occurred in its implementation are, however, the lack of synchronization and compatibility of output/input data formats between such software. To overcome these challenges, in this study context, we aim to apply the DADA2 pipeline (written in R programming language) instead of using a set of different bioinformatics tools to create our own workflow for microbial community analysis in a continuous and synchronous manner. For the first effort, we tried to investigate the composition and abundance of coral-associated bacteria using their 16S rRNA gene amplicon sequences. The workflow or framework includes the following steps: data processing, sequence clustering, taxonomic assignment, and data visualization. Moreover, we also like to catch readers’ attention to the information about bacterial communities living in the ocean as most marine microorganisms are unculturable, especially residing in coral reefs, namely, bacteria are associated with the coral Acropora tenuis in this case. The outcomes obtained in this study suggest that the DADA2 pipeline written in R programming language is one of the potential bioinformatics approaches in the context of microbiome analysis other than using various software. Besides, our modifications for the workflow execution help researchers to illustrate metagenomic data more easily and systematically, elucidate the composition, abundance, diversity, and relationship between microorganism communities as well as to develop other bioinformatic tools more effectively.
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Chiarello, Marlène, Mark McCauley, Sébastien Villéger, and Colin R. Jackson. "Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold." PLOS ONE 17, no. 2 (February 24, 2022): e0264443. http://dx.doi.org/10.1371/journal.pone.0264443.
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Advances in the analysis of amplicon sequence datasets have introduced a methodological shift in how research teams investigate microbial biodiversity, away from sequence identity-based clustering (producing Operational Taxonomic Units, OTUs) to denoising methods (producing amplicon sequence variants, ASVs). While denoising methods have several inherent properties that make them desirable compared to clustering-based methods, questions remain as to the influence that these pipelines have on the ecological patterns being assessed, especially when compared to other methodological choices made when processing data (e.g. rarefaction) and computing diversity indices. We compared the respective influences of two widely used methods, namely DADA2 (a denoising method) vs. Mothur (a clustering method) on 16S rRNA gene amplicon datasets (hypervariable region v4), and compared such effects to the rarefaction of the community table and OTU identity threshold (97% vs. 99%) on the ecological signals detected. We used a dataset comprising freshwater invertebrate (three Unionidae species) gut and environmental (sediment, seston) communities sampled in six rivers in the southeastern USA. We ranked the respective effects of each methodological choice on alpha and beta diversity, and taxonomic composition. The choice of the pipeline significantly influenced alpha and beta diversities and changed the ecological signal detected, especially on presence/absence indices such as the richness index and unweighted Unifrac. Interestingly, the discrepancy between OTU and ASV-based diversity metrics could be attenuated by the use of rarefaction. The identification of major classes and genera also revealed significant discrepancies across pipelines. Compared to the pipeline’s effect, OTU threshold and rarefaction had a minimal impact on all measurements.
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Ansorge, Rebecca, Giovanni Birolo, Stephen A. James, and Andrea Telatin. "Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments." International Journal of Molecular Sciences 22, no. 10 (May 18, 2021): 5309. http://dx.doi.org/10.3390/ijms22105309.
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The taxonomic composition of microbial communities can be assessed using universal marker amplicon sequencing. The most common taxonomic markers are the 16S rDNA for bacterial communities and the internal transcribed spacer (ITS) region for fungal communities, but various other markers are used for barcoding eukaryotes. A crucial step in the bioinformatic analysis of amplicon sequences is the identification of representative sequences. This can be achieved using a clustering approach or by denoising raw sequencing reads. DADA2 is a widely adopted algorithm, released as an R library, that denoises marker-specific amplicons from next-generation sequencing and produces a set of representative sequences referred to as ‘Amplicon Sequence Variants’ (ASV). Here, we present Dadaist2, a modular pipeline, providing a complete suite for the analysis that ranges from raw sequencing reads to the statistics of numerical ecology. Dadaist2 implements a new approach that is specifically optimised for amplicons with variable lengths, such as the fungal ITS. The pipeline focuses on streamlining the data flow from the command line to R, with multiple options for statistical analysis and plotting, both interactive and automatic.
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Hupfauf, Sebastian, Mohammad Etemadi, Marina Fernández-Delgado Juárez, María Gómez-Brandón, Heribert Insam, and Sabine Marie Podmirseg. "CoMA – an intuitive and user-friendly pipeline for amplicon-sequencing data analysis." PLOS ONE 15, no. 12 (December 2, 2020): e0243241. http://dx.doi.org/10.1371/journal.pone.0243241.
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In recent years, there has been a veritable boost in next-generation sequencing (NGS) of gene amplicons in biological and medical studies. Huge amounts of data are produced and need to be analyzed adequately. Various online and offline analysis tools are available; however, most of them require extensive expertise in computer science or bioinformatics, and often a Linux-based operating system. Here, we introduce “CoMA–Comparative Microbiome Analysis” as a free and intuitive analysis pipeline for amplicon-sequencing data, compatible with any common operating system. Moreover, the tool offers various useful services including data pre-processing, quality checking, clustering to operational taxonomic units (OTUs), taxonomic assignment, data post-processing, data visualization, and statistical appraisal. The workflow results in highly esthetic and publication-ready graphics, as well as output files in standardized formats (e.g. tab-delimited OTU-table, BIOM, NEWICK tree) that can be used for more sophisticated analyses. The CoMA output was validated by a benchmark test, using three mock communities with different sample characteristics (primer set, amplicon length, diversity). The performance was compared with that of Mothur, QIIME and QIIME2-DADA2, popular packages for NGS data analysis. Furthermore, the functionality of CoMA is demonstrated on a practical example, investigating microbial communities from three different soils (grassland, forest, swamp). All tools performed well in the benchmark test and were able to reveal the majority of all genera in the mock communities. Also for the soil samples, the results of CoMA were congruent to those of the other pipelines, in particular when looking at the key microbial players.
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Lim, Kahui, Matthew Rolston, Samantha Barnum, Cara Wademan, and Harold Leverenz. "A biogeographic 16S rRNA survey of bacterial communities of ureolytic biomineralization from California public restrooms." PLOS ONE 17, no. 1 (January 14, 2022): e0262425. http://dx.doi.org/10.1371/journal.pone.0262425.
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In this study, we examined the total bacterial community associated with ureolytic biomineralization from urine drainage systems. Biomineral samples were obtained from 11 California Department of Transportation public restrooms fitted with waterless, low-flow, or conventional urinals in 2019. Following high throughput 16S rRNA Illumina sequences processed using the DADA2 pipeline, the microbial diversity assessment of 169 biomineral and urine samples resulted in 3,869 reference sequences aggregated as 598 operational taxonomic units (OTUs). Using PERMANOVA testing, we found strong, significant differences between biomineral samples grouped by intrasystem sampling location and urinal type. Biomineral microbial community profiles and alpha diversities differed significantly when controlling for sampling season. Observational statistics revealed that biomineral samples obtained from waterless urinals contained the largest ureC/16S gene copy ratios and were the least diverse urinal type in terms of Shannon indices. Waterless urinal biomineral samples were largely dominated by the Bacilli class (86.1%) compared to low-flow (41.3%) and conventional samples (20.5%), and had the fewest genera that account for less than 2.5% relative abundance per OTU. Our findings are useful for future microbial ecology studies of urine source-separation technologies, as we have established a comparative basis using a large sample size and study area.
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Yen, Sandi, Jethro Johnson, and Nicholas E. Ilott. "Streamlined processing and analysis of 16S rRNA amplicon sequencing data with OCMS_16S and OCMSlooksy." Wellcome Open Research 7 (February 23, 2022): 68. http://dx.doi.org/10.12688/wellcomeopenres.17632.1.
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16S rRNA gene sequencing is a cost-effective method for profiling the bacterial component of a microbiome. Nevertheless, processing and analysis of the resulting sequencing data is often constrained by the availability of dedicated bioinformaticians - creating a bottleneck for biological interpretation. Multiple visualisation and analysis tools now exist for downstream analysis of 16S rRNA data. These tools are designed with biological scientists in mind and therefore consist of a graphical user interface that interacts with taxonomic counts tables to perform tasks such as alpha- and beta-diversity analysis and differential abundance. However, generating the input to these applications still relies on bioinformatics experience, creating a disconnect between data processing and data analysis. We aimed to bridge the gap between data processing and data analysis. To do this we have created two tools - OCMS_16S and OCMSlooksy - that perform data processing and data visualisation/analysis, respectively. OCMS_16S is a cgat-core based pipeline that wraps DADA2 functionality in order to facilitate processing of raw sequence reads into tables of amplicon sequence variant (ASV) counts using a simple command line interface. OCMSlooksy is an RShiny application that takes an OCMS_16S-generated SQLite database as input to facilitate data exploration and analysis. Combining these tools provides a simple, user-friendly workflow to facilitate 16S rRNA gene amplicon sequencing data analysis from raw reads to results.
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Miaow, Katie, Donnabella Lacap-Bugler, and Hannah L. Buckley. "Identifying optimal bioinformatics protocols for aerosol microbial community data." PeerJ 9 (September 30, 2021): e12065. http://dx.doi.org/10.7717/peerj.12065.
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Microbes are fundamental to Earth’s ecosystems, thus understanding ecosystem connectivity through microbial dispersal is key to predicting future ecosystem changes in a warming world. However, aerial microbial dispersal remains poorly understood. Few studies have been performed on bioaerosols (microorganisms and biological fragments suspended in the atmosphere), despite them harboring pathogens and allergens. Most environmental microbes grow poorly in culture, therefore molecular approaches are required to characterize aerial diversity. Bioinformatic tools are needed for processing the next generation sequencing (NGS) data generated from these molecular approaches; however, there are numerous options and choices in the process. These choices can markedly affect key aspects of the data output including relative abundances, diversity, and taxonomy. Bioaerosol samples have relatively little DNA, and often contain novel and proportionally high levels of contaminant organisms, that are difficult to identify. Therefore, bioinformatics choices are of crucial importance. A bioaerosol dataset for bacteria and fungi based on the 16S rRNA gene (16S) and internal transcribed spacer (ITS) DNA sequencing from parks in the metropolitan area of Auckland, Aotearoa New Zealand was used to develop a process for determining the bioinformatics pipeline that would maximize the data amount and quality generated. Two popular tools (Dada2 and USEARCH) were compared for amplicon sequence variant (ASV) inference and generation of an ASV table. A scorecard was created and used to assess multiple outputs and make systematic choices about the most suitable option. The read number and ASVs were assessed, alpha diversity was calculated (Hill numbers), beta diversity (Bray–Curtis distances), differential abundance by site and consistency of ASVs were considered. USEARCH was selected, due to higher consistency in ASVs identified and greater read counts. Taxonomic assignment is highly dependent on the taxonomic database used. Two popular taxonomy databases were compared in terms of number and confidence of assignments, and a combined approach developed that uses information in both databases to maximize the number and confidence of taxonomic assignments. This approach increased the assignment rate by 12–15%, depending on amplicon and the overall assignment was 77% for bacteria and 47% for fungi. Assessment of decontamination using “decontam” and “microDecon” was performed, based on review of ASVs identified as contaminants by each and consideration of the probability of them being legitimate members of the bioaerosol community. For this example, “microDecon’s” subtraction approach for removing background contamination was selected. This study demonstrates a systematic approach to determining the optimal bioinformatics pipeline using a multi-criteria scorecard for microbial bioaerosol data. Example code in the R environment for this data processing pipeline is provided.
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Costantini, Maria S., Matthew C. I. Medeiros, Lisa H. Crampton, and Floyd A. Reed. "Wild gut microbiomes reveal individuals, species, and location as drivers of variation in two critically endangered Hawaiian honeycreepers." PeerJ 9 (October 28, 2021): e12291. http://dx.doi.org/10.7717/peerj.12291.
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Background The gut microbiome of animals is an important component that has strong influence on the health, fitness, and behavior of its host. Most research in the microbiome field has focused on human populations and commercially important species. However, researchers are now considering the link between endangered species conservation and the microbiome. In Hawaiʻi, several threats (e.g., avian malaria and habitat loss) have caused widespread population declines of Hawaiian honeycreepers (subfamily: Carduelinae). These threats can have a significant effect on the avian gut microbiome and may even lead to disruption of microbial function. However, the gut microbiome of honeycreeper in the wild has yet to be explored. Methods We collected 13 and 42 fecal samples, respectively, from two critically endangered honeycreeper species, the ʻakikiki (Oreomystis bairdi) and the ʻakekeʻe (Loxops caeruleirostris). The 16S rRNA gene was sequenced and processed though a MOTHUR-based bioinformatics pipeline. Bacterial ASVs were identified using the DADA2 program and bacterial community analyses, including alpha and beta diversity measures, were conducted using R packages Phyloseq and vegan. Results A total of 8,958 bacterial ASVs were identified from the fecal samples. Intraspecific differences in the gut microbiome among individual birds explained most of the variation present in the dataset, however differences between species did exist. Both species had distinct microbiomes with minimal overlap in beta diversity. ‘Akikiki had a more diverse microbiome compared to ‘akekeʻe. Additionally, small but stastically significant differences in beta diversity also exist between sampling location and sexes in ʻakikiki. Conclusion ʻAkikiki and ʻakekeʻe are currently the focus of captive breeding efforts and plans to translocate the two species to other islands are underway. This baseline knowledge will help inform management decisions for these honeycreeper species in their native habitats, on other islands, and in captivity.
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Biehl, Lena M., Fedja Farowski, Catharina Hilpert, Angela Nowag, Anne Kretzschmar, Nathalie Jazmati, Anastasia Tsakmaklis, et al. "Longitudinal variability in the urinary microbiota of healthy premenopausal women and the relation to neighboring microbial communities: A pilot study." PLOS ONE 17, no. 1 (January 14, 2022): e0262095. http://dx.doi.org/10.1371/journal.pone.0262095.
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Background The understanding of longitudinal changes in the urinary microbiota of healthy women and its relation to intestinal microbiota is limited. Methods From a cohort of 15 premenopausal women without known urogenital disease or current symptoms, we collected catheter urine (CU), vaginal and periurethral swabs, and fecal samples on four visits over six months. Additionally, ten participants provided CU and midstream urine (MU) to assess comparability. Urine was subjected to expanded culture. 16S rRNA gene sequencing was performed on all urine, fecal, and selected vaginal and periurethral samples. Sequence reads were processed (DADA2 pipeline) and analyzed using QIIME 2 and R. Results Relative abundances of urinary microbiota were variable over 6–18 months. The degree of intraindividual variability of urinary microbiota was higher than that found in fecal samples. Still, nearly half of the observed beta diversity of all urine samples could be attributed to differences between volunteers (R2 = 0.48, p = 0.001). After stratification by volunteer, time since last sexual intercourse was shown to be a factor significantly contributing to beta diversity (R2 = 0.14, p = 0.001). We observed a close relatedness of urogenital microbial habitats and a clear distinction from intestinal microbiota in the overall betadiversity analysis. Microbiota compositions derived from MU differed only slightly from CU compositions. Within this analysis of low-biomass samples, we identified contaminating sequences potentially stemming from sequencing reagents. Conclusions Results from our longitudinal cohort study confirmed the presence of a rather variable individual urinary microbiota in premenopausal women. These findings from catheter urine complement previous observations on temporal dynamics in voided urine. The higher intraindividual variability of urinary microbiota as compared to fecal microbiota will be a challenge for future studies investigating associations with urogenital diseases and aiming at identifying pathogenic microbiota signatures.
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Virginio Junior, Gercino Ferreira, Maria Eduarda Reis, Ana Paula da Silva, Ariany Faria de Toledo, Amanda Moelemberg Cezar, Lucas William Mendes, Leandro Greco, Horácio Montenegro, Luiz Lehmann Coutinho, and Carla Maris Machado Bittar. "Does algae β-glucan affect the fecal bacteriome in dairy calves?" PLOS ONE 16, no. 9 (September 30, 2021): e0258069. http://dx.doi.org/10.1371/journal.pone.0258069.
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β-glucans has been reported to be associated with many health-promoting and improvements in animal performance, however, information about their effects on the bacterial community remains unknown. This study aimed to investigate how the addition of β-glucans can affect the fecal bacterial community with possible consequences on animal growth and health. For this, newborn Holstein calves (n = 14) were individually housed in tropical shelters and blocked according to sex, date, and weight at birth and randomly assigned to one of the following treatments: (1) Control: milk replacer (14% solids, 24% CP, 18.5% fat); (2) β-glucans: milk replacer supplemented with β-glucans (2 g/d). All calves were bucket fed 6 L/d of milk replacer and received water and starter concentrate ad libitum starting on d 2. To evaluate the bacteriome, fecal samples were collected at weeks 1, 2, 4, and 8. The bacterial community was assessed through sequencing of the V3-V4 region of the 16S rRNA gene on the Illumina MiSeq platform and analyzed using the DADA2 pipeline. No differences for Shannon and Chao1 indexes were observed for treatments, but both indexes increased with age (P < 0.001). There were dissimilarities in the structure of the bacterial community during the pre-weaning period (P = 0.01). In a deeper taxonomic level, Collinsella (Actinobacteriota), Prevotella (Bacteroidota), and Lactobacillus (Firmicutes) were the most abundant genera (9.84, 9.54, and 8.82% of the sequences, respectively). β-glucans promoted a higher abundance of Alloprevotella and Holdemanella, which may indicate a beneficial effect of supplementation on dairy calves. The bacterial community was highly correlated with the fecal score at weeks 1 and 2 and with starter concentrate intake at week 8. In conclusion, algae β-glucan supplementation could be beneficial to fecal bacteriome and consequently to the health and performance of dairy calves.
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Bartenslager, Alison, Nirosh Aluthge, John Loy, Matthew Spangler, and Samodha Fernando. "40 Resilience of the ocular microbiome in beef calves." Journal of Animal Science 98, Supplement_3 (November 2, 2020): 43. http://dx.doi.org/10.1093/jas/skaa054.077.
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Abstract Infectious Bovine Keratoconjuctivitis (IBK), or more commonly known as pinkeye, impacts the beef cattle industry with expenses reaching close to 150 million dollars annually. Thus far, successful prevention of infectious outbreaks of IBK have been limited. Partly, this may be due to our limited understanding of the establishment and composition of the ocular microbiome. However, understanding of the establishment and composition of the ocular microbiome, may provide indicators species for early detection of IBK and to identify a window of opportunity to treat IBK before outbreaks occur. As an attempt to characterize the establishment and colonization patterns of the ocular microbiome in beef calves, we conducted a longitudinal study utilizing 239 calves. The calves were placed on three different preventative treatments which included an initial vaccination followed by a booster 3 weeks later (Autogenous, Commercial, and Placebo). Ocular swabs were collected at four different time points during summer and fall months. The V4 region of the 16S rDNA gene was sequenced from the 889 samples collected using the Illumina Miseq™ platform. The resulting sequences were analyzed using the Dada2 pipeline. The analysis demonstrated a significant difference in community composition (p< 0.001) across time periods sampled, where the microbiome reverted back to the original composition within three months of ocular microbiome perturbation and vaccination, demonstrating the resilience of the ocular microbiome to perturbation. This suggests the ocular microbiome is stable at 30 days of age. We also identified Mycoplasma sp. and Moraxella sp. which are candidate organisms known to predispose animals to IBK. Moraxella was prevalent during initial sampling, while Mycoplasma demonstrated greater abundance at all time points. This study demonstrates the diversity and the resilience of the ocular microbiome in calves and the potential to develop probiotic interventions to reduce IBK outbreaks.
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Knoell, Allison, Nirosh Aluthge, Waseem Abbas, Alison Bartenslager, Jared Judy, Dennis Morris, Hannah C. Wilson, Kevin Herrick, Paul J. Kononoff, and Samodha Fernando. "247 The effect of diet on the microbial community structure and composition in lactating Jersey cows consuming a mixture of straw and dry distillers grains plus solubles in replacement of alfalfa hay." Journal of Animal Science 98, Supplement_3 (November 2, 2020): 138–39. http://dx.doi.org/10.1093/jas/skaa054.241.
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Abstract The rumen microbial community is responsible for producing a majority of the energetic needs for the animal, yet our understanding of the rumen microbiome is in its infancy. To better understand the effect of corn-ethanol coproducts on rumen microbial communities, a replicated 4 × 4 Latin square design study utilizing 12 cows in three squares was conducted to evaluate the replacement of alfalfa hay with a mixture (CoP) containing straw and dried distillers grains plus solubles (DDGS) in lactating Jersey cows. The experimental treatments were (proportions on a dry matter basis): a control diet (CON) containing 18.2% of alfalfa hay with no straw or DDGS. A low coproduct diet (LCoP) containing 12.1% alfalfa, 2.1% straw, and 6.0% DDGS. A medium coproduct diet (MCoP) containing 6.1% alfalfa, 4.2% straw, and 12.1% DDGS. A high coproduct diet (HCoP) containing 6.2% straw, 18.1% DDGS with no alfalfa. Rumen digesta samples were collected via an esophageal tube. No differences were observed for milk production and dry matter intake (P ≥ 0.307) (mean ± SEM) 19.5 kg ± 0.60, 29.6 kg ± 0.91, across treatments, while a decrease in methane was observed (P < 0.01) for the HCoP treatment. The bacterial community was assessed by sequencing the V4 region of the 16S rRNA gene. Additionally, the archaeal community was assessed by sequencing the V4-V5 region of the 16S rRNA gene on the Illumina MiSeq platform. Amplicon Sequence Variants were identified using the DADA2 pipeline. No significant differences were observed for the bacterial (P = 0.334) and archaeal (P = 0.593) communities. Although global effects in microbial community dynamics were not observed, differential taxa were observed with Lachnospiraceae being the major differentially abundant Family. The archaeal community composition demonstrated that Methanobacteriales to be the differentially abundant Order across treatments, and may contribute to methane production.
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Cohen, Adar, Liat Poupko, Hillary A. Craddock, Yair Motro, Boris Khalfin, Amit Zelinger, Sharon Tirosh-Levy, Shlomo E. Blum, Amir Steinman, and Jacob Moran-Gilad. "Fecal Microbiome Features Associated with Extended-Spectrum β-Lactamase-Producing Enterobacterales Carriage in Dairy Heifers." Animals 12, no. 14 (July 6, 2022): 1738. http://dx.doi.org/10.3390/ani12141738.
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Extended-spectrum β-lactamases (ESBLs) are a growing public health threat, and one key human exposure point is through livestock and the food supply. Understanding microbiome factors associated with fecal ESBL carriage can help detect and ideally assist with controlling and preventing ESBL dissemination among livestock. The objective of this study was to investigate the diversity and composition of the heifer fecal microbiota in ESBL-producing Enterobacterales (ESBL-PE) carriers and noncarriers. A total of 59 fecal samples were collected from replacement heifers between 12 and 18 months old from eight dairy farms in central Israel. Genomic DNA was extracted, and 16S rRNA amplicon sequencing was performed (Illumina short reads), focusing on a comparison between 33 ESBL-PE carriers (55.9%) and 26 (44.1%) noncarriers. Samples were analyzed and compared using QIIME2 (DADA2 pipeline and taxonomic assignment with SILVA database) and associated R packages for alpha and beta diversity and taxonomic abundances. Alpha diversity (Shannon diversity) and beta diversity (unweighted UniFrac) showed no significant difference between ESBL-PE carriers and noncarriers. Heifers from farms feeding calves with pooled colostrum had higher ESBL-PE carriage rates than heifers from farms feeding with individual mother colostrum (p < 0.001). Taxonomical abundance analysis revealed that the most common bacterial phyla were Bacteroidetes (44%) and Firmicutes (38%). There was no significant difference in taxonomic composition between ESBL-PE carriers and noncarriers at the phylum and genus levels. However, LEfSe biomarker discovery analysis identified several genera which were significantly different between carriers and noncarriers. For example, Prevotellacaea, Bacteroides, Rikenellaceae, and uncultured Bacteroidales were more abundant in ESBL carriers than noncarriers. Some aspects of microbiota composition differ between ESBL carriers and noncarriers in dairy heifers, specifically the abundance of certain genera. Feeding with pooled colostrum may play a role in that assembly. These could potentially serve as markers of ESBL-PE carriage. However, further research is needed to determine whether these observed differences have a significant impact on colonization with ESBL-PE.
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Kinstler, Sydney, Yanshao Li, Phillip Miller, Thomas E. Burkey, Melanie Trenhaile-Gannemann, Samodha C. Fernando, Allison Knoell, and Wesley A. Tom. "151 Effects of carbohydrate source on performance and gastrointestinal microbiota in nursery pigs." Journal of Animal Science 97, Supplement_2 (July 2019): 86. http://dx.doi.org/10.1093/jas/skz122.156.
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Abstract An experiment was conducted to determine the effects of carbohydrate source on growth performance and gastrointestinal microbiota in nursery pigs. Ninety-six pigs weaned at 21 d were randomly allotted to 16 pens (6 pigs/pen; 4 pens/treatment) with sex being represented evenly in each pen. Pigs had ad libitum access to feed and water for the 2-phase nursery period (28 d). Dietary treatments included: 1) NutrisureTM(a food-grade cooked cereal grain product), 2) oatmeal (food-grade oatmeal grain), 3) steam-rolled oats (SRO), or 4) dried-distillers grains as a negative control (DDGS). Ileal and colonic digesta and mucosa samples were collected on d 0, 14, and 28 (n = 6, 32, and 32, respectively) for analysis of microbial species using IlluminaTMnext generation sequencing. The DNA sequences were filtered through the DADA2 pipeline, Mothur, and QIIME. Pig body weights and feeder weights were also measured on d 0, 7, 14, 21, and 28. Pigs fed DDGS had lower average daily feed intake (ADFI) compared to other treatments during phase 1 (P < 0.05), but there were no differences in average daily gain (ADG) or gain:feed (G:F) among treatment. There were no differences among treatments for ADFI, ADG, or G:F for phase 2 or the overall experimental period. Microbial composition differed significantly among location in the gastrointestinal tract (P < 0.01) and among the digesta and mucosa samples extracted from the ileum and colon. There were no significant changes in the microbiota among diets (P > 0.1). Over time, there was a trend (P = 0.111) for the microbiota to vary; however, there was no interaction between the diet and sampling timepoint. In conclusion, carbohydrate sources did not affect gastrointestinal microbiota composition, ADFI, ADG, or G:F overall in this experiment. However, feed intake during phase 1 differed between DDGS and oat-based carbohydrate sources and microbial species were different between digesta and mucosa in the ileum and colon.
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Glenny, Elaine, Jintong Liu, Zorka Djukic, Michael Pellizzon, and Ian Carroll. "The Effect of Dietary Fiber Modifications in Purified Diets Relative to Grain-Based Diets on Gastrointestinal Anatomy and Intestinal Microbial Communities in Mice." Current Developments in Nutrition 4, Supplement_2 (May 29, 2020): 685. http://dx.doi.org/10.1093/cdn/nzaa050_008.
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Abstract Objectives The use of compositionally defined purified diets (PDs)—diets with known sources and quantities of all nutrients—permits investigators to control this major environmental factor in rodent studies. However, mice fed a standard PD exhibit abnormal gastrointestinal (GI) anatomy compared to mice fed Purina 5001, a grain-based diet (GBD). Interestingly, the addition a soluble fiber (inulin) to PDs (typically only containing cellulose, an insoluble fiber) ameliorates these adverse effects. The impact of PDs on the intestinal microbiota has not yet been investigated. We therefore sought to identify PD-supplemented fiber(s) that best recapitulate the GI health and intestinal microbiota of mice fed a GBD, while also including an additional reference GBD (Teklad 2020SX). Methods 7-week-old C57BL/6J male mice were individually housed and randomly assigned to a diet (two GBDs and four PDs with varying fiber composition) for 28 days. To assess changes in GI anatomy, small intestinal and colon lengths and colon and cecal weights were recorded at tissue harvest. Cecal contents, colon contents, and fecal pellets were collected for 16S rRNA gene sequencing to compare microbial profiles across different GI niches and between diets using the Divisive Amplicon Denoising Algorithm (DADA2) pipeline. Results Consistent with published data, GI anatomy was altered in mice consuming PDs compared to the Purina GBD. However, there were no significant anatomical differences between mice consuming PDs and the Teklad GBD. Characterization of microbial communities revealed that the GI niche (cecum, colon, or feces) dictated microbial composition (P < 0.001, ANOSIM). Microbiotas from mice fed any PD significantly differed from mice consuming either GBD (P < 0.05, ANOSIM). Microbiotas were also distinct between mice fed either Purina 5001 or Teklad 2020SX (P < 0.01, ANOSIM). Conclusions These data suggest that Purina 5001 does not represent all GBDs and that PDs may not significantly alter rodent GI anatomy compared to GBDs. As each diet tested significantly altered the microbial community, future work will seek to determine whether a specific PD-associated gut microbiota is beneficial to GI health. Funding Sources The NIH, the Honors Carolina Sarah Steele Danhoff Undergraduate Research Fund, and Research Diets, Inc.
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Ventin-Holmberg, R., M. Höyhtyä, S. Saqib, K. Korpela, A. Nikkonen, A. Salonen, W. M. de Vos, and K. L. Kolho. "DOP71 Fungal and bacterial gut microbiota in paediatric onset Inflammatory Bowel Disease introduced to infliximab." Journal of Crohn's and Colitis 15, Supplement_1 (May 1, 2021): S105. http://dx.doi.org/10.1093/ecco-jcc/jjab073.110.
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Abstract Background Paediatric Inflammatory Bowel Disease (PIBD), including Crohn’s Disease (CD), Ulcerative Colitis (UC) and IBD undefined (IBDU) is increasing worldwide and is characterized by an onset inflammation in the gastrointestinal tract. The patients may present severe symptoms such as abdominal pain, diarrhoea and bloody stool. No defined pathogenesis has been established for PIBD, but an imbalanced intestinal microbiota is strongly associated to the disease. Anti-tumour necrosis factor alpha (TNF-α) is an effective drug to treat inflammation in IBD, but up to half of the patients do not have a long-term response to the drug. Presently, there are no methods available to predict the TNF-α response. Here we have investigated the biomarkers of the gut fungal and bacterial microbiota, which are largely unexplored in paediatric patients, particularly for the fungal microbiota, with the aim to find possible predictors of drug response. Methods The gut microbiota composition of 30 PIBD (25 CD, 2 UC and 3 IBDU) patients at the Children′s Hospital, University of Helsinki receiving the anti-TNF-α drug infliximab (IFX) was studied by MiSeq sequencing targeting the bacterial 16S rRNA gene and fungal ITS region separately from faecal samples collected before the start of treatment and two and six weeks after treatment initiation. The response to IFX was evaluated by a faecal calprotectin value below 100 µg/g at week six after treatment initiation. The fungal MiSeq sequencing data was processed by using the DADA2 pipeline, annotated to the BLAST database and analysed using the package mare. The bacterial MiSeq sequencing data was analysed using mare and annotated to the SILVA database. Results Both the fungal and bacterial microbiota differed significantly between responders compared to non-responders to IFX, further validated by high predictive power (area under curve > 0.8) for therapy response. This difference was characterized by an increase in short-chain fatty acid producing bacteria, such as bacteria in the class Clostridia in the responders at baseline. This was observed as elevated Faecalibacterium and Subdoligranulum genera in particular of responders at baseline. Additionally, Candida was increased while Saccharomyces was decreased in non-responders at the end of the study. Finally, we observed that the interkingdom correlations differed between response groups to IFX. Conclusion Our results strengthen the proposal that the gut microbiota composition of PIBD patients could predict the response to anti-TNF-α treatment in the future.
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Egge, Elianne, Stephanie Elferink, Daniel Vaulot, Uwe John, Gunnar Bratbak, Aud Larsen, and Bente Edvardsen. "An 18S V4 rRNA metabarcoding dataset of protist diversity in the Atlantic inflow to the Arctic Ocean, through the year and down to 1000 m depth." Earth System Science Data 13, no. 10 (October 26, 2021): 4913–28. http://dx.doi.org/10.5194/essd-13-4913-2021.
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Abstract. Arctic marine protist communities have been understudied due to challenging sampling conditions, in particular during winter and in deep waters. The aim of this study was to improve our knowledge on Arctic protist diversity through the year, in both the epipelagic (< 200 m depth) and mesopelagic zones (200–1000 m depth). Sampling campaigns were performed in 2014, during five different months, to capture the various phases of the Arctic primary production: January (winter), March (pre-bloom), May (spring bloom), August (post-bloom), and November (early winter). The cruises were undertaken west and north of the Svalbard archipelago, where warmer Atlantic waters from the West Spitsbergen Current meet cold Arctic waters from the Arctic Ocean. From each cruise, station, and depth, 50 L of seawater was collected, and the plankton was size-fractionated by serial filtration into four size fractions between 0.45–200 µm, representing picoplankton (0.45–3 µm), small and large nanoplankton (3–10 and 10–50 µm, respectively), and microplankton (50–200 µm). In addition, vertical net hauls were taken from 50 m depth to the surface at selected stations. The net hauls were fractionated into the large nanoplankton (10–50 µm) and microplankton (50–200 µm) fractions. From the plankton samples DNA was extracted, the V4 region of the 18S rRNA-gene was amplified by polymerase chain reaction (PCR) with universal eukaryote primers, and the amplicons were sequenced by Illumina high-throughput sequencing. Sequences were clustered into amplicon sequence variants (ASVs), representing protist genotypes, with the dada2 pipeline. Taxonomic classification was made against the curated Protist Ribosomal Reference database (PR2). Altogether, 6536 protist ASVs were obtained (including 54 fungal ASVs). Both ASV richness and taxonomic composition varied between size fractions, seasons, and depths. ASV richness was generally higher in the smaller fractions and higher in winter and the mesopelagic samples than in samples from the well-lit epipelagic zone during summer. During spring and summer, the phytoplankton groups diatoms, chlorophytes, and haptophytes dominated in terms of relative read abundance in the epipelagic zone. Parasitic and heterotrophic groups such as Syndiniales and certain dinoflagellates dominated in the mesopelagic zone all year, as well as in the epipelagic zone during the winter. The dataset is available at https://doi.org/10.17882/79823 (Egge et al., 2014).
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Arévalo-Cortés, Andrea, Ashish Damania, Yurany Granada, Sara Zuluaga, Rojelio Mejia, and Omar Triana-Chavez. "Association of Midgut Bacteria and Their Metabolic Pathways with Zika Infection and Insecticide Resistance in Colombian Aedes aegypti Populations." Viruses 14, no. 10 (October 6, 2022): 2197. http://dx.doi.org/10.3390/v14102197.
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Introduction: Aedes aegypti is the vector of several arboviruses such as dengue, Zika, and chikungunya. In 2015–16, Zika virus (ZIKV) had an outbreak in South America associated with prenatal microcephaly and Guillain-Barré syndrome. This mosquito's viral transmission is influenced by microbiota abundance and diversity and its interactions with the vector. The conditions of cocirculation of these three arboviruses, failure in vector control due to insecticide resistance, limitations in dengue management during the COVID-19 pandemic, and lack of effective treatment or vaccines make it necessary to identify changes in mosquito midgut bacterial composition and predict its functions through the infection. Its study is fundamental because it generates knowledge for surveillance of transmission and the risk of outbreaks of these diseases at the local level. Methods: Midgut bacterial compositions of females of Colombian Ae. aegypti populations were analyzed using DADA2 Pipeline, and their functions were predicted with PICRUSt2 analysis. These analyses were done under the condition of natural ZIKV infection and resistance to lambda–cyhalothrin, alone and in combination. One-step RT-PCR determined the percentage of ZIKV-infected females. We also measured the susceptibility to the pyrethroid lambda–cyhalothrin and evaluated the presence of the V1016I mutation in the sodium channel gene. Results: We found high ZIKV infection rates in Ae. aegypti females from Colombian rural municipalities with deficient water supply, such as Honda with 63.6%. In the face of natural infection with an arbovirus such as Zika, the diversity between an infective and non-infective form was significantly different. Bacteria associated with a state of infection with ZIKV and lambda–cyhalothrin resistance were detected, such as the genus Bacteroides, which was related to functions of pathogenicity, antimicrobial resistance, and bioremediation of insecticides. We hypothesize that it is a vehicle for virus entry, as it is in human intestinal infections. On the other hand, Bello, the only mosquito population classified as susceptible to lambda–cyhalothrin, was associated with bacteria related to mucin degradation functions in the intestine, belonging to the Lachnospiraceae family, with the genus Dorea being increased in ZIKV-infected females. The Serratia genus presented significantly decreased functions related to phenazine production, potentially associated with infection control, and control mechanism functions for host defense and quorum sensing. Additionally, Pseudomonas was the genus principally associated with functions of the degradation of insecticides related to tryptophan metabolism, ABC transporters with a two-component system, efflux pumps, and alginate synthesis. Conclusions: Microbiota composition may be modulated by ZIKV infection and insecticide resistance in Ae. aegypti Colombian populations. The condition of resistance to lambda–cyhalothrin could be inducing a phenome of dysbiosis in field Ae. aegypti affecting the transmission of arboviruses.
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Chang, Jingjing, Wei Xiao, Yanlin Chen, Shenghua Qu, Yan Wang, and Xin Ma. "Analysis and optimization of idle noise caused by canister purge solenoid valve." E3S Web of Conferences 268 (2021): 01018. http://dx.doi.org/10.1051/e3sconf/202126801018.
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In the development process of a certain CHINA VI proprietary brand car model, there exists the problem of intermittent “dada” sound in the cockpit during idling. After investigation, it’s determined that the air pulse noise generated when the canister purge solenoid valve is working, it is transmitted to the car panels through the pipeline, and then to the cockpit, which would cause a “dada” sound. By adding expansion chamber in the desorption pipe and designing part of the pipeline which fixed in the clamp as rubber pipe, the intensity of air pulse can be effectively reduced and the transmission path of air pulse vibration can be blocked. Through objective testing and subjective evaluation, the scheme can greatly reduce the idle noise of the cockpit, thus improving the NVH performance of the vehicle and bringing comfortable riding environment to the passengers.
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Barnes, Christopher J., Linett Rasmussen, Maria Asplund, Steen Wilhelm Knudsen, Maja-Lisa Clausen, Tove Agner, and Anders J. Hansen. "Comparing DADA2 and OTU clustering approaches in studying the bacterial communities of atopic dermatitis." Journal of Medical Microbiology 69, no. 11 (November 1, 2020): 1293–302. http://dx.doi.org/10.1099/jmm.0.001256.
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Introduction. The pathogenesis of atopic dermatitis (AD) is not yet fully understood, but the bacterial composition of AD patients’ skin has been shown to have an increased abundance of Staphylococcus aureus . More recently, coagulase-negative Staphylococcus (CoNS) species were shown to be able to inhibit S. aureus , but further studies are required to determine the effects of Staphylococcus community variation in AD. Aim. Here we investigated whether analysing metabarcoding data with the more recently developed DADA2 approach improves metabarcoding analyses compared to the previously used operational taxonomic unit (OTU) clustering, and can be used to study Staphylococcus community dynamics. Methods. The bacterial 16S rRNA region from tape strip samples of the stratum corneum of AD patients (non-lesional skin) and non-AD controls was metabarcoded. We processed metabarcoding data with two different bioinformatic pipelines (an OTU clustering method and DADA2), which were analysed with and without technical replication (sampling strategy). Results. We found that OTU clustering and DADA2 performed well for community-level studies, as demonstrated by the identification of significant differences in the skin bacterial communities associated with AD. However, the OTU clustering approach inflated bacterial richness, which was worsened by not having technical replication. Data processed with DADA2 likely handled sequencing errors more effectively and thereby did not inflate molecular richness. Conclusion. We believe that DADA2 represents an improvement over an OTU clustering approach, and that biological replication rather than technical replication is a more effective use of resources. However, neither OTU clustering nor DADA2 gave insights into Staphylococcus community dynamics, and caution should remain in not overinterpreting the taxonomic assignments at lower taxonomic ranks.
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Blair, Lily, Jonathan U. Peled, Paul A. Giardina, John B. Slingerland, Ann E. Slingerland, Desiree Hollemon, Carine Ho, et al. "The Blood Microbiome Predicts Acute Graft-Versus-Host Disease after Stem Cell Transplantation." Blood 134, Supplement_1 (November 13, 2019): 4513. http://dx.doi.org/10.1182/blood-2019-129272.
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Introduction Translocation of intestinal bacteria across impaired mucosal barriers has long been believed to occur following exposure to chemotherapy. Consistent with this, we and others have previously reported that expansions of potentially pathogenic bacteria within the gastrointestinal microbiome precedes bloodstream infection. While the blood microbiome represents a rich area for investigation, detailed unbiased characterization of the blood microbiome has not previously been possible. Here, we sought to investigate the relationship between the blood and stool microbiome in patients undergoing allogeneic hematopoietic stem cell transplantation (HCT) who are at high risk for gut barrier dysfunction, severe infection, and the immunological complications of transplantation including graft-versus-host disease (GVHD). We show preliminary data suggesting that the blood microbiome may hold biomarkers for gut integrity. Subsequently, it may offer microbiological data supporting causative organisms in "culture-negative" fevers, or in itself, perform an immunomodulatory role acting as a damage/pathogen associated molecular pattern (DAMP/PAMP). Methods We sequenced serially-collected plasma and stool samples (n = 61 unique samples of each type) from a cohort of 19 patients who underwent allogeneic HCT at our center. Microbial cell-free DNA (mcfDNA) was extracted from plasma and sequenced using a next generation sequencing assay (Karius, Inc, Redwood City, CA). After sequences are processed, mcfDNA abundances are reported in molecules per microliter. Stool samples underwent were profiled using 16S-targeted sequencing (V4-V5 region) on the Illumina MISEQ platform and analyzed using the DADA2 pipeline. Association of blood microbial burden with clinical factors was assessed using a Wilcoxon rank sum test. Results We confirmed a high sequence homology between the DNA found in plasma and stool samples, thus demonstrating that circulating mcfDNA is gut-derived in these patients. By comparing microbial sequences from paired plasma and stool samples collected equivalent time points during the neutropenic nadir after HCT, we observed a correlation between the abundance of bacterial mcfDNA in plasma and DNA from the same microbes in stool. Of note, this occurred independently of conditioning regimen intensity, and was observed in patients who had received myeloablative, non-myeloablative and reduced intensity therapy. We assessed the association of bacterial mcfDNA burden (only considering sequences common to stool sequences) with various clinical factors. Translocation was significantly higher in patients who experienced pre-engraftment mucositis (any observed grade) compared with those who did not (p = 0.02, n = 5 in the mucositis group, any grade, and 12 in the mucositis-free group), but there was no relationship between the degree of translocation and HCT-CI, conditioning intensity, donor type, age or pre-engraftment fevers. We next asked whether translocation events were associated with acute GVHD (aGVHD) by assessing a subgroup of patients who received unmodified grafts (peripheral blood stem cell or bone marrow; n = 10) and tracked the degree of translocation from the gut to the blood stream pre-transplant, during the neutropenic nadir, and following engraftment. As shown in Figure 1, we observed low pre-transplant translocation (as quantified by the total bacterial DNA abundance in plasma where sequences were also shared in stool samples), and a marked increase during neutropenic nadir. Remarkably, even in this small cohort, we observe a higher burden of translocation in the post-engraftment period in patients who subsequently develop aGVHD, while it decreased to baseline levels in those who do not (n = 7 in the aGVHD group; n = 3 aGVHD-free; p = 0.05). Conclusions Here we demonstrate the first use of a culture-free molecular assay to track the blood microbiome and identify features of the circulating mcfDNA that correlate with the microbial DNA in stool samples. Despite the small sample size, these data suggest that the maintenance of a high mcfDNA-burden beyond the neutropenic nadir is associated with subsequent GVHD development, and provides some evidence for early gut barrier dysfunction that permits translocation in these patients. Disclosures Blair: Karius, Inc: Employment. Peled:Seres Therapeutics: Other: IP licensing fees, Research Funding. Giardina:Seres Therapeutics: Other: Salary funding. Slingerland:Seres Therapeutics: Other: Salary supported by Seres funding. Hollemon:Karius, Inc: Employment. Ho:Karius, Inc: Employment. Bercovici:Karius, Inc: Employment. Ahmed:Karius, Inc: Employment. Hong:Karius, Inc: Employment. Giralt:Celgene: Consultancy, Research Funding; Takeda: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Consultancy, Research Funding. van den Brink:Therakos: Consultancy, Honoraria; Merck & Co, Inc.: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Acute Leukemia Forum (ALF): Consultancy, Honoraria; Magenta and DKMS Medical Council: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria; Seres Therapeutics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Flagship Ventures: Consultancy, Honoraria; Juno Therapeutics: Other: Licensing; Evelo: Consultancy, Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria.
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An, Hojung, Mira A. Partha, Hojoon Lee, Billy Lau, Giwon Shin, Alison Figueroa Almeda, and Hanlee P. Ji. "Analysis of 16S rRNA sequencing in advanced colorectal cancer tissue samples." Journal of Clinical Oncology 40, no. 4_suppl (February 1, 2022): 163. http://dx.doi.org/10.1200/jco.2022.40.4_suppl.163.
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163 Background: Changes in the colon’s microbiota composition are contributors to the pathogenesis of colorectal cancer (CRC). Features of this microbiome may have prognostic significance. For this study, we analyzed 16S rRNA sequencing data from tumor tissue samples of advanced CRC patients and determined if there were potential correlations between microbiome composition and clinical outcomes. Methods: One hundred and thirty three advanced CRC patients in St. Vincent’s Hospital in Korea were enrolled. DNA was extracted from collected tissue samples, the V3-V4 regions were amplified, and a 16S rRNA gene amplicon library was prepared using an Illumina protocol. DNA was sequenced on an Illumina MiSeq instrument. We used three different bioinformatic packages to process the sequence data and evaluate the microbiome composition of each tumor. Results: The classification performances of three different analytic pipelines (Kraken2, QIIME2, and DADA2) were compared in a microbiome control sample. Among these, DADA2 and QIIME2 were chosen for use in subsequent analysis, due to their lower Chi-square (χ2) test statistic values on the control data. After excluding samples that retained less than 5% of total reads after merging, 120 samples were analyzed. The median age of the cohort was 63 years, 63.3% were male, and all were Korean. The distribution over primary sites was 27.5% from the right-side colon, 30.8% from the left-side colon, and 41.7% from the rectum. All subjects received the first line of systemic treatment. The median progression-free survival time was 8.9 months. Twenty-nine patients (24.2%) survived more than 24 months. When examining the results from the two bioinformatic packages, pairwise comparisons showed positive correlations in the relative abundances of the top 20 genera. Fusobacterium, a microbe known to relate to pathogenesis and prognosis of CRC, was not detected by QIIME2. Stratifying by primary site, rectal cancers showed higher alpha diversity than left- or right-side colon cancers. Separately, a higher serum CEA level (≥8) at diagnosis, and the presence of lung metastasis were both found to be related to higher alpha-diversity, a global indicator of microbiome composition. When excluding minimally abundant (< 1% per patient) genera, beta-diversity was found to be differentiable by T stage, the presence of lung metastasis, and the presence of liver metastasis. Most notably, beta-diversity differed between patients who survived more than two years and patients who died within 2 years. Using the DADA2 results, we confirmed that the presence of Fusobacterium nucleatum in CRC tissue was found to be a strong predictor of poor overall survival (OS), along with old age and liver metastasis. Conclusions: This study suggests potential associations between microbiome composition and clinical parameters of advanced CRC. Microbial biomarkers may be a valuable prognostic tool in this population.
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Mohd Salleh, Mohd Hairul, Yuzine Esa, Mohamad Syazwan Ngalimat, and Pelf Nyok Chen. "Faecal DNA metabarcoding reveals novel bacterial community patterns of critically endangered Southern River Terrapin, Batagur affinis." PeerJ 10 (March 29, 2022): e12970. http://dx.doi.org/10.7717/peerj.12970.
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Southern River Terrapin, Batagur affinis, is a freshwater turtle listed as critically endangered on the IUCN Red List since 2000. Many studies suggest that faecal DNA metabarcoding can shield light on the host-associated microbial communities that play important roles in host health. Thus, this study aimed to characterise and compare the faecal bacterial community between captive and wild B. affinis using metabarcoding approaches. A total of seven faeces samples were collected from captive (N = 5) and wild (N = 2) adult B. affinis aseptically, crossing the East and West coast of peninsular Malaysia. The DNA was extracted from the faeces samples, and the 16S rRNA gene (V3–V4 region) was amplified using polymerase chain reaction (PCR). The amplicon was further analysed using SILVA and DADA2 pipelines. In total, 297 bacterial communities taxonomic profile (phylum to genus) were determined. Three phyla were found in high abundance in all faeces samples, namely Firmicutes (38.69%), Bacteroidetes (24.52%), and Fusobacteria (6.95%). Proteobacteria were detected in all faeces samples (39.63%), except the wild sample, KBW3. Under genus level, Cetobacteriumwas found as the most abundant genus (67.79%), followed by Bacteroides (24.56%) and Parabacteroides (21.78%). The uncultured genus had the highest abundance (88.51%) even though not detected in the BK31 and KBW2 samples. The potential probiotic genera (75.00%) were discovered to be more dominant in B. affinis faeces samples. Results demonstrated that the captive B. affinis faeces samples have a greater bacterial variety and richness than wild B. affinis faeces samples. This study has established a starting point for future investigation of the gut microbiota of B. affinis.
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Dania, Margaret I., Bahram Faraji, and James Wachira. "Micronutrient Biosynthesis Potential of Spontaneous Grain Fermentation Microbiomes." International Journal of Environmental Research and Public Health 19, no. 24 (December 10, 2022): 16621. http://dx.doi.org/10.3390/ijerph192416621.
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Fermented foods play an important role in the human diet and particularly so in under-resourced environments where cold preservation is not attainable due to irregular supply of electricity. Fermented foods are reported to support gut health by contributing probiotics. The purpose of this study was to investigate the microbial diversity and metabolic potential of spontaneous millet fermentation. The literature in the field was reviewed and analyses were conducted on publicly available Sequence Read Archive (SRA) datasets. Quality analysis was performed with FastQC, and operational taxonomic units (OTUs) were generated using Quantitative Insights Into Microbial Ecology (QIIME2) and Divisive Amplicon Denoising Algorithm (DADA2) pipelines with Greengenes as the reference database. Metagenomics and pathways analysis were performed with Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2). Statistical analysis and visualization were accomplished with Statistical Analysis of Metagenomic Profiles (STAMP). At the family taxonomic level, there were differences in the relative abundances of the dominant taxa of bacteria that are involved in the spontaneous fermentation of millet namely Lactobacillaceae, Burkholderiaceae, Streptococcaceae, Leuconostocaceae, and Acetobacteraceae. Clostridiaceae was the dominant family in one dataset. The incidence of Lactobacillaceae and Bifidobacteriaceae suggest the probiotic characteristics of fermented millet. The datasets were collected with fermentations that were mediated by autochthonous microorganisms and the presence of some potential pathogens such as Enterobacteriaceae, Clostridiaceae, Aeromonadaceae, Microbacteiaceae, Pseudomonadaceae, and Neisseriaceae which suggest the need for standardization of fermentation approaches. The genomes show the potential to synthesize metabolites such as essential amino acids and vitamins, suggesting that the respective fermented foods can be further optimized to enhance nutritional benefits.
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Wade, W. G., and E. M. Prosdocimi. "Profiling of Oral Bacterial Communities." Journal of Dental Research 99, no. 6 (April 14, 2020): 621–29. http://dx.doi.org/10.1177/0022034520914594.
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The profiling of bacterial communities by the sequencing of housekeeping genes such as that encoding the small subunit ribosomal RNA has revealed the extensive diversity of bacterial life on earth. Standard protocols have been developed and are widely used for this application, but individual habitats may require modification of methods. This review discusses the sequencing and analysis methods most appropriate for the study of the bacterial component of the human oral microbiota. If possible, DNA should be extracted from samples soon after collection. If samples have to be stored for practical reasons, precautions to avoid DNA degradation on freezing should be taken. A critical aspect of profiling oral bacterial communities is the choice of region of the 16S rRNA gene for sequencing. The V1-V2 region provides the best discrimination between species of the genus Streptococcus, the most common genus in the mouth and important in health and disease. The MiSeq platform is most commonly used for sequencing, but long-read technologies are now becoming available that should improve the resolution of analyses. There are a variety of well-established data analysis pipelines available, including mothur and QIIME, which identify sequence reads as phylotypes by comparing them to reference data sets or grouping them into operational taxonomic units. DADA2 has improved sequence error correction capabilities and resolves reads to unique variants. Two curated oral 16S rRNA databases are available: HOMD and CORE. Expert interpretation of community profiles is required, both to detect the presence of contaminating DNA, which is commonly present in the reagents used in analysis, and to differentiate oral and nonoral bacteria and determine the significance of findings. Despite advances in shotgun whole-genome metagenomic methods, oral bacterial community profiling via 16S rRNA sequence analysis remains a valuable technique for the characterization of oral bacterial populations.
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Mohan, V., M. I. Pinto-Sanchez, A. Nardelli, R. Borojevic, G. De Palma, S. M. Collins, and P. Bercik. "A51 ROLE OF GUT MICROBIOTA IN THE EPISODIC NATURE OF SYMPTOMS IN IRRITABLE BOWEL SYNDROME." Journal of the Canadian Association of Gastroenterology 5, Supplement_1 (February 21, 2022): 58–60. http://dx.doi.org/10.1093/jcag/gwab049.050.
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Abstract Background Irritable bowel syndrome (IBS) is a complex functional gastrointestinal disorder with likely heterogenous pathophysiology, multiple symptoms, and comorbidities. Growing evidence shows that the gut microbiota composition and function are altered in IBS patients. However, identifying the critical drivers of clinical expression remains challenging due to the episodic occurrence of IBS symptoms, the inherent variability in composition of gut microbiota across individuals, and high sensitivity of gut microbiota to dietary and environmental cues. Aims To identify whether changes in gut microbiota composition accompany or, predict the occurrence of symptoms. Methods 28 IBS patients (IBS-D n=20, IBS-C n=8) and 10 healthy controls (HC) were followed longitudinally for 25 weeks, collecting stool samples, and recording their symptoms weekly. Stool microbiota profiles were assessed by 16S rRNA gene sequencing using Illumina platform. The sequences were preprocessed, filtered, and annotated using DADA2 and phyloseq pipelines; statistical analyses were performed using FactomineR and microbiomeanalyst packages in R. Statistical significance was set at p<0.05. Results Multifactorial analysis of clinical data classified 950 samples in 6 clusters. Distribution of samples among the clusters was based on Bristol stool scale defining symptomatic periods (scores <3 and >4 indicating abnormal stool) and asymptomatic periods (scores 3 or 4), with several gut and mood symptoms varying significantly between the two categories. IBS-D patients, but not IBS-C patients presented with changes in symptoms severity, such as pain, diarrhea, constipation, and anxiety during the symptomatic periods. Depression scores were, however, higher in IBS-C compared to IBS-D patients. In contrast, immune makers such as fecal b-defensin-2 and calprotectin were higher during asymptomatic periods in IBS-D, but not in IBS-C patients. Bacterial diversity profiles differed among IBS patients (IBS-D and IBS-C) and HC, namely Shannon index and Bray-Curtis distance, but they did not change significantly between the symptomatic and asymptomatic periods within each subtype. Despite this, several bacterial taxa unique to each cluster were identified using linear mixed models. Conclusions Our results demonstrate the need to study patterns of co-occurrence of IBS symptoms and their severity during symptomatic and asymptomatic periods to better understand the role of identified bacterial taxa in the symptom generation. Identifying their temporal changes and cross-feeding patterns in individual patients will shed light on the underlying mechanistic role of gut microbiota in IBS, which might be otherwise obscured by group generalizations. Funding Agencies CIHR
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Rabbia, V., G. De Palma, J. Lu, E. Verdu, S. M. Collins, R. Anglin, M. Surette, and P. Bercik. "A261 MICROBIOTA PROFILES OF PATIENTS WITH MENTAL DISODERS DIFFER FROM THOSE OF HEALTHY CONTROLS." Journal of the Canadian Association of Gastroenterology 3, Supplement_1 (February 2020): 138–39. http://dx.doi.org/10.1093/jcag/gwz047.260.
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Abstract Background Mental disorders are the leading cause of disabilities worldwide, with depression and anxiety among the most common ones, affecting up to 1/3 of the worldwide population at least once in their lifetime. In both preclinical models and clinical studies, gut microbiota has been associated with altered behavior and anxiety or depression, respectively. Aims To investigate 1) whether the microbial profiles of patients with generalized anxiety disorder (GAD) and major depression disorder (MDD) differ from those of healthy controls (HC), and 2) whether specific bacterial taxa associate with GAD or MDD. Methods 118 patients with primary GAD (n=82, 83.3 % female) or MDD (n=36, 62.9 % female) and 99 matched HC (66.6 % female) were recruited through the Anxiety Treatment and Research Centre. Anxiety, depression and stress levels were assessed by DASS-21 questionnaire. Stool samples were collected anaerobically and analysed for 16S rRNA gene sequencing through Illumina technique. The data was divided in 4 groups: 1) mental health disorder (MHD) combining GAD and MDD, 2) GAD, 3) MDD, and 4) HC. The data was analyzed following the pipelines of dada2 and QIIME2. RandomForest plugin for QIIME2 was used to investigate predictive characteristics of MHD, GAD or MDD microbiota. SPSS software v.23 was used to perform Spearman correlations and logistic regressions between microbial taxa and clinical scores. Results The mean anxiety score was 16.2 (severe anxiety) for GAD patients and 9.8 (moderate anxiety) for MDD patients; the mean depression score was 19.2 (moderate depression) for MDD patients and 16.0 (moderate depression) for GAD patients, while healthy controls averaged only 1.5 (normal anxiety) and 1.7 (normal depression) for anxiety and depression, respectively. The microbiota profile of the MHD group was predictive of the patients’ disease state with an 83.3% accuracy. In particular, increased relative abundance of Bacteroides ovatus and Bacteroides spp. and decreased relative abundance of Dialister spp. (Veilonellaceae), Haemophilus parainfluenzae and Bifidobacterium adolescentis, were predictive of MHD. Neither the GAD or MDD group microbiota profiles alone were accurate in the prediction of the patients’ disease state. There was a positive correlation between the relative abundance of Bacteroides spp. and a negative correlation between the relative abundance of Clostridium sensu stricto spp. and Sutterella, and the clinical scores of combined MDH and HC groups. Conclusions Our data suggest that patients with mental health disorders have different microbiota profiles compared to healthy controls. We have identified specific bacterial signatures that will inform mechanistic studies in gnotobiotic mouse models to investigate further the role of microbiome in mental disorders. Funding Agencies NIH
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Rabbia, V., G. De Palma, J. Lu, E. Verdu, H. Armstrong, S. M. Collins, R. Anglin, M. Surette, and P. Bercik. "A229 GUT MICROBIOTA PROFILES, DIET AND SHORT-CHAIN FATTY ACIDS AS PREDICTORS OF GENERALIZED ANXIETY DISORDER." Journal of the Canadian Association of Gastroenterology 5, Supplement_1 (February 21, 2022): 120–21. http://dx.doi.org/10.1093/jcag/gwab049.228.
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Abstract Background Generalized anxiety disorder (GAD) is a debilitating chronic condition with a lifetime prevalence of 4–7% worldwide. Both diet and gut microbiota have been previously associated with anxiety. Aims To investigate whether bacterial taxa and/or nutrients associate with GAD, and whether they differ from those of healthy controls (HC). Methods Patients with GAD (n=82) and matched HC (n=97) were assessed by validated questionnaires for anxiety (DASS-21), gastrointestinal (GI) symptoms (Rome III, Short-Form Leeds Dyspepsia), and dietary profiles by the Dietary Questionnaire for Epidemiological Studies. We quantified several blood and stool biomarkers, including inflammatory and neuroactive metabolites, as well as short-chain fatty acids. Stool microbiota profiles were assessed by16S rRNA gene sequencing through Illumina. The data was then analyzed following the pipelines of dada2 and by multiple factor analysis (MFA), mean comparisons, correlation, LEfSe and XGBoost using R software (v.1.2.1335). Multiple comparison results were corrected allowing 5% of FDR. Results Using MFA to analyze all variables, we identified 3 clusters: one mainly composed of HC (n=99, 91% HC, GI symptoms in 25% of subjects), a second mixed cluster (n=30, 80% GAD, GI symptoms in 80%) and a third cluster mainly composed of GAD patients (n=50, 98% GAD, GI symptoms in 86%). When focusing only on the HCs of cluster 1 (n=90) and GADs of cluster 3 (n=49), we found higher GI symptoms, body mass index, serum C-reactive protein and stool calprotectin levels (adj. p=1.3x10-9, 0.001, 0.017 and 0.017, respectively) and lower concentrations of propionate, butyrate and acetate in GAD compared to HC. GADs also reported overall lower caloric intake (kJ/day; adj. p=1.7x10-4) in the food frequency questionnaire. Fibre (g/day) was the macronutrient most negatively associated with anxiety scores (R=-0.44; adj. p=4.2x10-5). Bacteroides was the only bacterial taxon significantly associated with GAD, as well as with anxiety scores (R=0.31, adj. p=0.003). Interestingly, Bacteroides/fiber ratio was strongly correlated to anxiety scores (R=0.58, adj. p=2.7x10-09). Furthermore, demographic, biomarkers and bacterial taxa data were predictive of the patients’ disease state with 92.8% accuracy. The features that aid the model to predict disease state were Bacteroides/fiber ratio, GI symptoms and stool acetate levels. Conclusions Our results suggest that most GAD patients differ in dietary and microbiota profiles from HCs, and that the Bacteroides/fiber ratio, stool acetate and GI symptoms might be good predictors of disease state. Furthermore, these data strongly support the role of microbiota-gut-brain axis in genesis of psychiatric diseases, and they will inform mechanistic studies in gnotobiotic mouse models. Funding Agencies NIH
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Mlaga, Kodjovi D., Alban Mathieu, Charles Joly Beauparlant, Alban Ott, Ahmad Khodr, Olivier Perin, and Arnaud Droit. "HCK and ABAA: A Newly Designed Pipeline to Improve Fungi Metabarcoding Analysis." Frontiers in Microbiology 12 (May 5, 2021). http://dx.doi.org/10.3389/fmicb.2021.640693.
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IntroductionThe fungi ITS sequence length dissimilarity, non-specific amplicons, including chimaera formed during Polymerase Chain Reaction (PCR), added to sequencing errors, create bias during similarity clustering and abundance estimation in the downstream analysis. To overcome these challenges, we present a novel approach, Hierarchical Clustering with Kraken (HCK), to classify ITS1 amplicons and Abundance-Base Alternative Approach (ABAA) pipeline to detect and filter non-specific amplicons in fungi metabarcoding sequencing datasets.Materials and MethodsWe compared the performances of both pipelines against QIIME, KRAKEN, and DADA2 using publicly available fungi ITS mock community datasets and using BLASTn as a reference. We calculated the Precision, Recall, F-score using the True-Positive, False-positive, and False-negative estimation. Alpha diversity (Chao1 and Shannon metrics) was also used to evaluate the diversity estimation of our method.ResultsThe analysis shows that ABAA reduced the number of false-positive with all metabarcoding methods tested, and HCK increases precision and recall. HCK, coupled with ABAA, improves the F-score and bring alpha diversity metric value close to that of the BLASTn alpha diversity values when compared to QIIME, KRAKEN, and DADA2.ConclusionThe developed HCK-ABAA approach allows better identification of the fungi community structures while avoiding use of a reference database for non-specific amplicons filtration. It results in a more robust and stable methodology over time. The software can be downloaded on the following link: https://bitbucket.org/GottySG36/hck/src/master/.
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Meglécz, Emese, Vincent Dubut, Emmanuel Corse, and Aitor González. "VTAM: A robust pipeline for validating metabarcoding data using optimized parameters based on internal controls." ARPHA Conference Abstracts 4 (March 4, 2021). http://dx.doi.org/10.3897/aca.4.e64659.
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Metabarcoding has become a powerful approach to study biodiversity from environmental samples but it is still prone to some pitfalls. Several papers have called for good practice in study design, data production and analyses to ensure repeatability and comparability between studies. Notably, the importance of mock community samples, negative controls, and replicates is frequently highlighted (Alberdi et al. 2018, O'Rourke et al. 2020). However, their use in bioinformatics pipelines is often limited to post hoc verification of expectations by the user. Indeed, one of the biggest challenges in metabarcoding analyses is to take into account the trade-off between false positive (FP) and false negative (FN) occurrences. We thus developed the VTAM (Validation and Taxonomic Assignation of Metabarcoding data) pipeline, which is the first tool to use explicitly the negative control and mock samples to find optimal parameters to minimize false positive and negative occurrences. In addition, VTAM addresses all known technical error types including tag-jumps, repeatability among replicates, and also it is able to integrate more than one overlapping markers to further minimize false negative occurrences. In order to evaluate VTAM, we compared it with two other pipelines: a pipeline based on DADA2 (Callahan et al. 2016) and LULU (Frøslev et al. 2017), and a pipeline based on OBITools3 (Boyer et al. 2016) and metabaR (Zinger et al. 2020). Two datasets from fish and bat diet studies were analysed with the three different pipelines. Based on mock and negative samples, we demonstrate that VTAM showed the best precision for mock samples in both datasets, while specificity in negative controls were comparable among the three pipelines (Fig. 1). VTAM therefore constitutes a complete pipeline to filter and validate metabarcoding data, from raw FASTQ data to Amplicon Sequence Variant tables with taxonomic assignments. Our pipeline aggregates a series of features rarely grouped in a single pipeline and performs a non-arbitrary parameter optimization based on internal control samples to generate conservative but informative metabarcoding datasets. We believe VTAM provides a very valuable tool for the validation of metabarcoding data, which is essential for conducting robust analyses of biodiversity.
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Rolling, Thierry, Bing Zhai, John Frame, Tobias M. Hohl, and Ying Taur. "Customization of a DADA2-based pipeline for fungal internal transcribed spacer 1 (ITS1) amplicon data sets." JCI Insight 7, no. 1 (January 11, 2022). http://dx.doi.org/10.1172/jci.insight.151663.
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Weißbecker, Christina, Beatrix Schnabel, and Anna Heintz-Buschart. "Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology." GigaScience 9, no. 12 (November 30, 2020). http://dx.doi.org/10.1093/gigascience/giaa135.
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Abstract Background Amplicon sequencing of phylogenetic marker genes, e.g., 16S, 18S, or ITS ribosomal RNA sequences, is still the most commonly used method to determine the composition of microbial communities. Microbial ecologists often have expert knowledge on their biological question and data analysis in general, and most research institutes have computational infrastructures to use the bioinformatics command line tools and workflows for amplicon sequencing analysis, but requirements of bioinformatics skills often limit the efficient and up-to-date use of computational resources. Results We present dadasnake, a user-friendly, 1-command Snakemake pipeline that wraps the preprocessing of sequencing reads and the delineation of exact sequence variants by using the favorably benchmarked and widely used DADA2 algorithm with a taxonomic classification and the post-processing of the resultant tables, including hand-off in standard formats. The suitability of the provided default configurations is demonstrated using mock community data from bacteria and archaea, as well as fungi. Conclusions By use of Snakemake, dadasnake makes efficient use of high-performance computing infrastructures. Easy user configuration guarantees flexibility of all steps, including the processing of data from multiple sequencing platforms. It is easy to install dadasnake via conda environments. dadasnake is available at https://github.com/a-h-b/dadasnake.
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Kraemer, Julia G., Alban Ramette, Suzanne Aebi, Anne Oppliger, and Markus Hilty. "Influence of Pig Farming on the Human Nasal Microbiota: Key Role of Airborne Microbial Communities." Applied and Environmental Microbiology 84, no. 6 (January 12, 2018). http://dx.doi.org/10.1128/aem.02470-17.
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ABSTRACT It has been hypothesized that the environment can influence the composition of the nasal microbiota. However, the direct influence of pig farming on the anterior and posterior nasal microbiota is unknown. Using a cross-sectional design, pig farms ( n = 28) were visited in 2014 to 2015, and nasal swabs from 43 pig farmers and 56 pigs, as well as 27 air samples taken in the vicinity of the pig enclosures, were collected. As controls, nasal swabs from 17 cow farmers and 26 non-animal-exposed individuals were also included. Analyses of the microbiota were performed based on 16S rRNA amplicon sequencing and the DADA2 pipeline to define sequence variants (SVs). We found that pig farming is strongly associated with specific microbial signatures (including alpha- and beta-diversity), which are reflected in the microbiota of the human nose. Furthermore, the microbial communities were more similar within the same farm compared to between the different farms, indicating a specific microbiota pattern for each pig farm. In total, there were 82 SVs that occurred significantly more abundantly in samples from pig farms than from cow farmers and nonexposed individuals (i.e., the core pig farm microbiota). Of these, nine SVs were significantly associated with the posterior part of the human nose. The results strongly indicate that pig farming is associated with a distinct human nose microbiota. Finally, the community structures derived by the DADA2 pipeline showed an excellent agreement with the outputs of the mothur pipeline which was revealed by procrustes analyses. IMPORTANCE The knowledge about the influence of animal keeping on the human microbiome is important. Previous research has shown that pets significantly affect the microbial communities of humans. However, the effect of animal farming on the human microbiota is less clear, although it is known that the air at farms and, in particular, at pig farms is charged with large amounts of dust, bacteria, and fungi. In this study, we simultaneously investigated the nasal microbiota of pigs, humans, and the environment at pig farms. We reveal an enormous impact of pig farming on the human nasal microbiota which is far more pronounced compared to cow farming. In addition, we analyzed the airborne microbiota and found significant associations suggesting an animal-human transmission of the microbiota within pig farms. We also reveal that microbial patterns are farm specific, suggesting that the environment influences animals and humans in a similar manner.
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Scott-Baumann, James F., Jessica C. A. Friedersdorff, Bernardo Villarreal-Ramos, Jonathan King, Beverley Hopkins, Richard Pizzey, David Rooke, Glyn Hewinson, and Luis A. J. Mur. "The Faecal Microbiome of the Wild European Badger Meles meles: A Comparison Against Other Wild Omnivorous Mammals from Across the Globe." Current Microbiology 79, no. 12 (October 17, 2022). http://dx.doi.org/10.1007/s00284-022-03064-4.
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AbstractHere we investigate the faecal microbiome of wild European badgers Meles meles using samples collected at post-mortem as part of the All Wales Badger Found Dead study. This is the first published characterisation of the badger microbiome. We initially undertook a sex-matched age comparison between the adult and cub microbiomes, based on sequencing the V3–V4 region of the 16S rRNA gene. Analysis used the QIIME 2 pipeline utilising DADA2 and the Silva database for taxonomy assignment. Fusobacteria appeared to be more abundant in the microbiomes of the cubs than the adults although no significant difference was seen in alpha or beta diversity between the adult and cub badger microbiomes. Comparisons were also made against other wild, omnivorous, mammals’ faecal microbiomes using publicly available data. Significant differences were seen in both alpha and beta diversity between the microbiomes from different species. As a wildlife species of interest to the disease bovine tuberculosis, knowledge of the faecal microbiome could assist in identification of infected badgers. Our work here suggests that, if comparisons were made between the faeces of bTB infected and non-infected badgers, age may not have a significant impact on the microbiome.
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Oyewole, Oluwaseun Rume-Abiola, Philipp Latzin, Silvio D. Brugger, and Markus Hilty. "Strain-level resolution and pneumococcal carriage dynamics by single-molecule real-time (SMRT) sequencing of the plyNCR marker: a longitudinal study in Swiss infants." Microbiome 10, no. 1 (September 22, 2022). http://dx.doi.org/10.1186/s40168-022-01344-6.
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Abstract Background Pneumococcal carriage has often been studied from a serotype perspective; however, little is known about the strain-specific carriage and inter-strain interactions. Here, we examined the strain-level carriage and co-colonization dynamics of Streptococcus pneumoniae in a Swiss birth cohort by PacBio single-molecule real-time (SMRT) sequencing of the plyNCR marker. Methods A total of 872 nasal swab (NS) samples were included from 47 healthy infants during the first year of life. Pneumococcal carriage was determined based on the quantitative real-time polymerase chain reaction (qPCR) targeting the lytA gene. The plyNCR marker was amplified from 214 samples having lytA-based carriage for pneumococcal strain resolution. Amplicons were sequenced using SMRT technology, and sequences were analyzed with the DADA2 pipeline. In addition, pneumococcal serotypes were determined using conventional, multiplex PCR (cPCR). Results PCR-based plyNCR amplification demonstrated a 94.2% sensitivity and 100% specificity for Streptococcus pneumoniae if compared to lytA qPCR. The overall carriage prevalence was 63.8%, and pneumococcal co-colonization (≥ 2 plyNCR amplicon sequence variants (ASVs)) was detected in 38/213 (17.8%) sequenced samples with the relative proportion of the least abundant strain(s) ranging from 1.1 to 48.8% (median, 17.2%; IQR, 5.8–33.4%). The median age to first acquisition was 147 days, and having ≥ 2 siblings increased the risk of acquisition. Conclusion The plyNCR amplicon sequencing is species-specific and enables pneumococcal strain resolution. We therefore recommend its application for longitudinal strain-level carriage studies of Streptococcus pneumoniae.
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Bíró, Tibor, Mónika Duleba, Angéla Földi, Keve T. Kiss, Péter Orgoványi, Zsuzsa Trábert, Edit Vadkerti, Carlos E. Wetzel, and Éva Ács. "Metabarcoding as an effective complement of microscopic studies in revealing the composition of the diatom community – a case study of an oxbow lake of Tisza River (Hungary) with the description of a new Mayamaea species." Metabarcoding and Metagenomics 6 (October 7, 2022). http://dx.doi.org/10.3897/mbmg.6.87497.
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Diatoms are valuable bioindicators and their traditional classification and identification are mainly based on the morphological characteristics of their frustules. However, in recent years, DNA-based methods have been proposed and are rapidly growing in the scientific literature as a complementary tool to assess the ecological status of freshwaters. Diatom-based ecological status assessment uses indices calculated from sensitivity and tolerance values as well as relative abundance of species. Correct assessment requires an accurate identification of species. In the present study, diatom assemblages of an oxbow lake were investigated using light and scanning electron microscopy as well as metabarcoding using rbcL marker, and the identification results were compared, intending to match barcode sequences of species that are currently missing in the diatom reference database. The investigated oxbow is an important wetland for bird conservation, although it is impacted by land use. Taxon lists based on morphology and metabarcoding considerably differed when bioinformatics analysis involved DADA2 pipeline with Diat.barcode database. Previously unknown sequence variants of four pennate species were found with additional BLAST search. Using phylogeny and p-distance calculations sequences could be matched to three small-celled naviculoid species that were found under a microscope. One of them was found to be a new species of the genus Mayamaea and was described as a new species, Mayamaea ectorii. Additionally, spatial distribution maps for several small-celled naviculoid species are provided for the Hungarian territory.
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Kamberović, Jasmina, Marija Gligora Udovič, Maria Kahlert, Kálmán Tapolczai, Zorana Lukić, Adisa Ahmić, Anita Dedić, et al. "Composition of diatom communities on travertine barriers of the Una River (Bosnia and Herzegovina) obtained by DNA metabarcoding and morphological analysis." ARPHA Conference Abstracts 4 (March 4, 2021). http://dx.doi.org/10.3897/aca.4.e64954.
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The process of travertine formation and carbonate deposition in the rivers is unique, delicate, and depends on the activity of algae and mosses. Although diatoms have been used extensively in hydrobiological studies, the comparative analysis data on diatom communities of the travertine barriers in karstic rivers are still scarce. The study aimed to detect the diatom composition on travertine barriers in the Una River, the large karstic river in Bosnia and Herzegovina. An integrated classical morphological identification approach with metabarcoding was applied on eight samples across the river length profile. Morphological analyses were performed using both light and scanning electron microscopes. Subsequent DNA metabarcoding of the chloroplastic gene 312bp rbcL was done. The DADA2 pipeline was used for the bioinformatic treatment of the demultiplexed MiSeq reads to infer Amplicon Sequence Variants (ASVs). ASVs were taxonomically assigned using the Diat.barcode v7 reference database. A total of 126 species were identified using the morphological approach, while 133 ASVs were taxonomically assigned to 58 unique taxa with the molecular approach. Diatom community structures in terms of molecular and morphological approaches were congruent with 49 shared species. Species from genera Gomphonema, Navicula and Encyonema were less assigned in molecular analysis. The most abundant taxa in the Una River are alkaliphilous, belonging to the genera Gomphonema, Nitzshia and Navicula. Although specific for their extremely good chemical status, the travertine barriers of the Una River are largely inhabited with meso-eutraphentic taxa.
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Coelho, Marina Gavanski, Gercino Ferreira Virgínio Júnior, Cristiane Regina Tomaluski, Ariany Faria de Toledo, Maria Eduarda Reis, Sophia Cattleya Dondé, Lucas William Mendes, Luiz Lehmann Coutinho, and Carla Maris Machado Bittar. "Comparative study of different liquid diets for dairy calves and the impact on performance and the bacterial community during diarrhea." Scientific Reports 12, no. 1 (August 4, 2022). http://dx.doi.org/10.1038/s41598-022-17613-1.
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AbstractThe liquid diet composition can affect dairy calves' performance and diarrhea incidence. The effect of three liquid diets on performance, incidence of diarrhea, and microbial community during diarrhea occurrence in dairy calves were evaluated. At birth, 35 dairy calves (20 male and 15 female) were randomly assigned to one of three treatments—refrigerated whole milk (WM), acidified whole milk (AWM), and milk replacer (MR). Intake, fecal score, and rectal temperature were evaluated daily, and performance and blood parameters were evaluated weekly during the preweaning period. Fecal samples from diarrheic calves were collected, and one initial and one final sample for each episode were selected. The bacterial community was assessed by sequencing the V3-V4 region of the 16S rRNA gene on the Illumina MiSeq platform and analyzed using the DADA2 pipeline. Calves fed WM had higher body weight at weaning, average daily gain, body measurements, and concentration of blood metabolites. The AWM-fed calves had a lower rectal temperature and fever days. Moreover, the MR-fed calves had lower beta-hydroxybutyrate concentration and a higher incidence of diarrhea. The fecal bacterial community of diarrheic calves showed dissimilarity among the AWM and the other treatments. At the compositional level, we observed a higher abundance of Fusobacterium and Ruminococcus genera (AWM), Prevotella (WM), and Lactobacillus (MR). In the AWM and MR diarrheic calves' feces, we also observed some beneficial bacterial genera. The performance and incidence of diarrhea of dairy calves were influenced by the liquid diet consumed and the bacterial composition of diarrhea.
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Nielsen, Rune, Yaxin Xue, Inge Jonassen, Ingvild Haaland, Øyvind Kommedal, Harald G. Wiker, Christine Drengenes, Per S. Bakke, and Tomas M. L. Eagan. "Repeated bronchoscopy in health and obstructive lung disease: is the airway microbiome stable?" BMC Pulmonary Medicine 21, no. 1 (November 2, 2021). http://dx.doi.org/10.1186/s12890-021-01687-0.
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Abstract Objective Little is known concerning the stability of the lower airway microbiome. We have compared the microbiota identified by repeated bronchoscopy in healthy subjects and patients with ostructive lung diseaseases (OLD). Methods 21 healthy controls and 41 patients with OLD completed two bronchoscopies. In addition to negative controls (NCS) and oral wash (OW) samples, we gathered protected bronchoalveolar lavage in two fractions (PBAL1 and PBAL2) and protected specimen brushes (PSB). After DNA extraction, we amplified the V3V4 region of the 16S rRNA gene, and performed paired-end sequencing (Illumina MiSeq). Initial bioinformatic processing was carried out in the QIIME-2 pipeline, identifying amplicon sequence variants (ASVs) with the DADA2 algorithm. Potentially contaminating ASVs were identified and removed using the decontam package in R and the sequenced NCS. Results A final table of 551 ASVs consisted of 19 × 106 sequences. Alpha diversity was lower in the second exam for OW samples, and borderline lower for PBAL1, with larger differences in subjects not having received intercurrent antibiotics. Permutational tests of beta diversity indicated that within-individual changes were significantly lower than between-individual changes. A non-parametric trend test showed that differences in composition between the two exams (beta diversity) were largest in the PSBs, and that these differences followed a pattern of PSB > PBAL2 > PBAL1 > OW. Time between procedures was not associated with increased diversity. Conclusion The airways microbiota varied between examinations. However, there is compositional microbiota stability within a person, beyond that of chance, supporting the notion of a transient airways microbiota with a possibly more stable individual core microbiome.
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Rocha, Leonardo F., Jason P. Bond, and Ahmad M. Fakhoury. "Wheat Production Alters Soil Microbial Profiles and Enhances Beneficial Microbes in Double-Cropping Soybean." Frontiers in Agronomy 3 (January 10, 2022). http://dx.doi.org/10.3389/fagro.2021.807112.
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Plant-parasitic nematodes represent a substantial constraint on global food security by reducing the yield potential of all major crops. The soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is widely distributed across important soybean production areas of the U.S., being the major soybean yield-limiting factor, especially in the Midwestern U.S. Double cropped (DC) soybean is commonly planted following winter wheat. We previously reported double-cropping soybean fields with reduced SCN counts compared to fallow at both R1 growth stage (beginning of flowering) (−31.8%) and after soybean harvest (−32.7%). To test if higher counts of beneficial and SCN antagonistic microorganisms could be correlated with the suppression of SCN in fields previously planted with wheat, three field locations with noted SCN suppression were selected for a metagenomics study. Ten subplots were selected (5 wheat and 5 fallow pre-soybean) from each location. A total of 90 soil samples were selected: 3 fields ×2 treatments × 3 timepoints × 5 replications. Three DNA markers targeted distinct microbial groups: bacteria (16S V4-V5), fungi (ITS2), and Fusarium (tef1). Amplicons were sequenced using an Illumina MiSeq platform (300 bp paired-end). Sequencing datasets were processed in R using the DADA2 pipeline. Fungal populations were affected by location in all sampling periods and differed significantly between DC and fallow plots at soybean planting and after harvest (P < 0.001). Several enriched fungal and bacterial taxa in wheat plots, including Mortierella, Exophiala, Conocybe, Rhizobacter spp., and others, were previously reported to parasitize SCN and other plant-parasitic nematodes, suggesting a potential role of beneficial microbes in suppression of SCN in soybean fields double-cropped with wheat.
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Tzeng, Alice, Naseer Sangwan, Margaret Jia, Chin-Chih Liu, Karen S. Keslar, Erinn Downs-Kelly, Robert L. Fairchild, Zahraa Al-Hilli, Stephen R. Grobmyer, and Charis Eng. "Human breast microbiome correlates with prognostic features and immunological signatures in breast cancer." Genome Medicine 13, no. 1 (April 16, 2021). http://dx.doi.org/10.1186/s13073-021-00874-2.
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AbstractBackgroundCurrently, over half of breast cancer cases are unrelated to known risk factors, highlighting the importance of discovering other cancer-promoting factors. Since crosstalk between gut microbes and host immunity contributes to many diseases, we hypothesized that similar interactions could occur between the recently described breast microbiome and local immune responses to influence breast cancer pathogenesis.MethodsUsing 16S rRNA gene sequencing, we characterized the microbiome of human breast tissue in a total of 221 patients with breast cancer, 18 individuals predisposed to breast cancer, and 69 controls. We performed bioinformatic analyses using a DADA2-based pipeline and applied linear models with White’stor Kruskal–WallisH-tests with Benjamini–Hochberg multiple testing correction to identify taxonomic groups associated with prognostic clinicopathologic features. We then used network analysis based on Spearman coefficients to correlate specific bacterial taxa with immunological data from NanoString gene expression and 65-plex cytokine assays.ResultsMultiple bacterial genera exhibited significant differences in relative abundance when stratifying by breast tissue type (tumor, tumor adjacent normal, high-risk, healthy control), cancer stage, grade, histologic subtype, receptor status, lymphovascular invasion, or node-positive status, even after adjusting for confounding variables. Microbiome–immune networks within the breast tended to be bacteria-centric, with sparse structure in tumors and more interconnected structure in benign tissues. Notably,Anaerococcus,Caulobacter, andStreptococcus, which were major bacterial hubs in benign tissue networks, were absent from cancer-associated tissue networks. In addition,PropionibacteriumandStaphylococcus, which were depleted in tumors, showed negative associations with oncogenic immune features;StreptococcusandPropionibacteriumalso correlated positively with T-cell activation-related genes.ConclusionsThis study, the largest to date comparing healthy versus cancer-associated breast microbiomes using fresh-frozen surgical specimens and immune correlates, provides insight into microbial profiles that correspond with prognostic clinicopathologic features in breast cancer. It additionally presents evidence for local microbial–immune interplay in breast cancer that merits further investigation and has preventative, diagnostic, and therapeutic potential.
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Valeris-Chacin, Robert, Maria Pieters, Haejin Hwang, Timothy J. Johnson, and Randall S. Singer. "Association of Broiler Litter Microbiome Composition and Campylobacter Isolation." Frontiers in Veterinary Science 8 (May 24, 2021). http://dx.doi.org/10.3389/fvets.2021.654927.
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Infection with Campylobacter species is one of the leading causes of bacterial diarrhea in humans in the US. Chickens, which become colonized on the farm, are important reservoirs of this bacterium. Campylobacter can establish itself in the broiler house via a variety of sources, can survive in the litter of the house, and possibly persist over successive flock cycles. However, the role of the broiler litter microbiome on Campylobacter persistence is not clear. A matched case-control study was conducted to determine whether the broiler litter microbiome composition was associated with Campylobacter isolation within the broiler house. Flocks were classified as cases when either Campylobacter jejuni or Campylobacter coli was isolated in boot sock samples, or as controls otherwise. Case and control flocks were matched at the broiler house level. Composite broiler litter samples were collected and used for DNA extraction and 16S rRNA gene V4 region sequencing. Reads were processed using the DADA2 pipeline to obtain a table of amplicon sequence variants. Alpha diversity and differential bacterial relative abundance were used as predictors of Campylobacter isolation status in conditional logistic regression models adjusting for flock age and sampling season. Beta diversity distances were used as regressors in stratified PERMANOVA with Campylobacter isolation status as predictor, and broiler house as stratum. When Campylobacter was isolated in boot socks, broiler litter microbiome richness and evenness were lower and higher, respectively, without reaching statistical significance. Campylobacter isolation status significantly explained a small proportion of the beta diversity (genus-level Aitchison dissimilarity distance). Clostridium and Anaerostipes were positively associated with Campylobacter isolation status, whereas Bifidobacterium, Anaerosporobacter, and Stenotrophomonas were negatively associated. Our results suggest the presence of bacterial interactions between Campylobacter and the broiler litter microbiome. The negative association of Campylobacter with Bifidobacterium, Anaerosporobacter, and Stenotrophomonas in litter could be potentially exploited as a pre-harvest control strategy.
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Virgínio Júnior, Gercino Ferreira, Marina Gavanski Coelho, Ariany Faria de Toledo, Horácio Montenegro, Luiz Lehmann Coutinho, and Carla Maris Machado Bittar. "The Liquid Diet Composition Affects the Fecal Bacterial Community in Pre-weaning Dairy Calves." Frontiers in Animal Science 2 (April 29, 2021). http://dx.doi.org/10.3389/fanim.2021.649468.
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Feeding a liquid diet to the newborn calf has considerable implications for developing the intestinal microbiota, as its composition can shift the population to a highly adapted microbiota. The present work evaluated 15 Holstein calves individually housed and fed one of the three liquid diets: I – whole milk (n = 5), II – milk replacer (22.9% CP; 16.2% fat; diluted to 14% solids; n = 5) and III – acidified whole milk to pH 4.5 with formic acid (n = 5). All animals received 6 L of liquid diet, divided into two meals, being weaned at week 8 of life. Calves also had free access to water and starter concentrate. After weaning, all calves were grouped on pasture, fed with starter concentrate, and hay ad libitum. The fecal samples were collected at birth (0) and at weeks 1, 2, 4, 8, and 10 of life. The bacterial community was assessed the through sequencing of the V3-V4 region of the 16S rRNA gene on the Illumina MiSeq platform and analyzed using the DADA2 pipeline. Diversity indices were not affected by the liquid diets, but by age (P < 0.001) with weeks 1 and 2 presenting lower diversity, evenness, and richness values. The bacterial community structure was affected by diet, age, and the interaction of these factors (P < 0.01). Twenty-eight bacterial phyla were identified in the fecal samples, and the most predominant phyla were Firmicutes (42.35%), Bacteroidota (39.37%), and Proteobacteria (9.36%). The most prevalent genera were Bacteroides (10.71%), Lactobacillus (8.11%), Alloprevotella (6.20%). Over the weeks, different genera were predominant, with some showing significant differences among treatments. The different liquid diets altered the fecal bacterial community during the pre-weaning period. However, differences in the initial colonization due to different liquid diets are alleviated after weaning, when animals share a common environment and solid diet composition.
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Lettieri, Giulia Melo, Luander Medrado Santiago, Giancarlo Crosara Lettieri, Luiz Gustavo dos Anjos Borges, Letícia Marconatto, Laudimar Alves de Oliveira, Nailê Damé-Teixeira, and Loise Pedrosa Salles. "Oral Phenotype and Salivary Microbiome of Individuals With Papillon–Lefèvre Syndrome." Frontiers in Cellular and Infection Microbiology 11 (August 26, 2021). http://dx.doi.org/10.3389/fcimb.2021.720790.
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Papillon–Lefèvre syndrome (PLS) is an autosomal recessive rare disease, main characteristics of which include palmoplantar hyperkeratosis and premature edentulism due to advanced periodontitis (formerly aggressive periodontitis). This study aimed to characterize the oral phenotype, including salivary parameters, and the salivary microbiome of three PLS sisters, comparatively. Two sisters were toothless (PLSTL1 and PLSTL2), and one sister had most of the teeth in the oral cavity (PLST). Total DNA was extracted from the unstimulated saliva, and the amplicon sequencing of the 16S rRNA gene fragment was performed in an Ion PGM platform. The amplicon sequence variants (ASVs) were obtained using the DADA2 pipeline, and the taxonomy was assigned using the SILVA v.138. The main phenotypic characteristics of PLS were bone loss and premature loss of primary and permanent dentition. The PLST sister presented advanced periodontitis with gingival bleeding and suppuration, corresponding to the advanced periodontitis as a manifestation of systemic disease, stage IV, grade C. All three PLS sisters presented hyposalivation as a possible secondary outcome of the syndrome. Interestingly, PLST salivary microbiota was dominated by the uncultured bacteria Bacterioidales (F0058), Fusobacterium, Treponema, and Sulfophobococcus (Archaea domain). Streptococcus, Haemophilus, and Caldivirga (Archaea) dominated the microbiome of the PLSTL1 sister, while the PLSTL2 had higher abundances of Lactobacillus and Porphyromonas. This study was the first to show a high abundance of organisms belonging to the Archaea domain comprising a core microbiome in human saliva. In conclusion, a PLST individual does have a microbiota different from that of the periodontitis’ aggressiveness previously recognized. Due to an ineffective cathepsin C, the impairment of neutrophils probably provided a favorable environment for the PLS microbiome. The interactions of Bacteroidales F0058, Caldivirga, and Sulfophobococcus with the microbial consortium of PLS deserves future investigation. Traditional periodontal therapy is not efficient in PLS patients. Unraveling the PLS microbiome is essential in searching for appropriate treatment and avoiding early tooth loss.
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Prevel, Renaud, Raphaël Enaud, Arthur Orieux, Adrian Camino, Patrick Berger, Alexandre Boyer, Laurence Delhaes, and Didier Gruson. "Gut bacteriobiota and mycobiota are both associated with Day-28 mortality among critically ill patients." Critical Care 26, no. 1 (April 13, 2022). http://dx.doi.org/10.1186/s13054-022-03980-8.
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Abstract Introduction Gut microbiota is associated with host characteristics such as age, sex, immune condition or frailty and is thought to be a key player in numerous human diseases. Nevertheless, its association with outcome in critically ill patients has been poorly investigated. The aim of this study is to assess the association between gut microbiota composition and Day-28 mortality in critically ill patients. Methods Rectal swab at admission of every patient admitted to intensive care unit (ICU) between October and November 2019 was frozen at − 80 °C. DNA extraction was performed thanks to QIAamp® PowerFecal® Pro DNA kit (QIAgen®). V3–V4 regions of 16SRNA and ITS2 coding genes were amplified by PCR. Sequencing (2x250 bp paired-end) was performed on MiSeq sequencer (Illumina®). DADA2 pipeline on R software was used for bioinformatics analyses. Risk factors for Day-28 mortality were investigated by logistic regression. Results Fifty-seven patients were consecutively admitted to ICU of whom 13/57 (23%) deceased and 44/57 (77%) survived. Bacteriobiota α-diversity was lower among non-survivors than survivors (Shannon and Simpson index respectively, p < 0.001 and p = 0.001) as was mycobiota α-diversity (respectively p = 0.03 and p = 0.03). Both gut bacteriobiota and mycobiota Shannon index were independently associated with Day-28 mortality in multivariate analysis (respectively OR: 0.19, 97.5 CI [0.04–0.60], p < 0.01 and OR: 0.29, 97.5 CI [0.09–0.75], p = 0.02). Bacteriobiota β-diversity was significantly different between survivors and non-survivors (p = 0.05) but not mycobiota β-diversity (p = 0.57). Non-survivors had a higher abundance of Staphylococcus haemolyticus, Clostridiales sp., Campylobacter ureolyticus, Akkermansia sp., Malassezia sympodialis, Malassezia dermatis and Saccharomyces cerevisiae, whereas survivors had a higher abundance of Collinsella aerofaciens, Blautia sp., Streptococcus sp., Faecalibacterium prausnitzii and Bifidobacterium sp. Conclusion The gut bacteriobiota and mycobiota α diversities are independently associated with Day-28 mortality in critically ill patients. The causal nature of this interference and, if so, the underlying mechanisms should be further investigated to assess if gut microbiota modulation could be a future therapeutic approach.
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Teixeira, Daniel, Heron Hilário, Gustavo Rosa, Guilherme Santos, Gilmar Santos, and Daniel Carvalho. "Ichthyoplankton metabarcoding as a tool for studying fish reproductive dynamics." ARPHA Conference Abstracts 4 (March 4, 2021). http://dx.doi.org/10.3897/aca.4.e65404.
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The study of ichthyoplankton composition, abundance and distribution is paramount to understand the reproductive dynamics of local fish assemblages. The analysis of these parameters allows the identification of spawning sites, nursery areas and migration routes. However, due to the lack of characters in early life stages, the morphological identification of ichthyoplankton is often impractical and many studies identify only fish larvae. Additionally, its accuracy shows great variation between taxonomists and laboratories according to their experience and specialty. DNA barcoding emerged as an alternative to provide assertive identification of fish eggs and larvae, but it becomes too expensive and laborious when the study demands the processing of huge amounts of organisms. DNA metabarcoding can overcome these limitations as a rapid, cost-effective, broad and accurate taxonomy tool, allowing the identification of multiple individuals simultaneously. Here, we present the identification of a sample containing 68 fish eggs and another containing 293 fish larvae from a single site in the São Francisco River Basin, Eastern Brazil, through DNA metabarcoding. We used a low-cost saline DNA extraction followed by PCR amplification with three primer sets targeting the 12S rRNA gene: MiFish (~170bp), Teleo_1 (~60bp), and NeoFish (~190bp). The latter was recently developed by our research group specifically for the identification of Neotropical fishes. All the amplified samples were sequenced in a single multiplexed Illumina MiniSeq run. We performed the filtering steps and assigned Amplicon Sequence Variants (ASVs) using a DADA2/Phyloseq based pipeline and a custom 12S reference sequence database including 101 species and 70 genera from the Jequitinhonha and São Francisco basins. The species Cyphocharax gilbert, Leporinus taeniatus, Megaleporinus elongatus, Prochilodus argenteus, P. costatus and Psalidodon fasciatus were detected by all three primer sets in the larva pool, while Pterygoplichthys etentaculatus was detected solely by NeoFish (Fig. 1). Within the egg pool, all three markers detected the species Characidium zebra, Curimatella lepidura, M. elongatus, Pimelodus fur and P. costatus, but Brycon orthotaenia was detected only by NeoFish, P. maculatus only by Teleo, and P. pohli by MiFish and Teleo (Fig. 1). The consistency in species detection among all three markers underpins the credibility of this method to accurately describe the sample composition. Considering that most of species were exclusive to the larvae or egg pool, our experiment highlights the importance of including the identification of fish eggs in reproduction studies, as it can provide additional information about which species are spawning in an area. Furthermore, the application of DNA metabarcoding to the study of ichthyoplankton can help decision makers create more informed guidelines for conservation of economically and ecologically important fish species.
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Mendes, Izabela, Heron Hilário, Daniel Teixeira, and Daniel Cardoso de Carvalho. "Challenges in assessing the Neotropical fishes using DNA metabarcoding." ARPHA Conference Abstracts 4 (March 4, 2021). http://dx.doi.org/10.3897/aca.4.e65093.
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Species richness is a metric of biodiversity usually used in fish community assessment for monitoring programs. This metric is often obtained using traditional fisheries methods that rely on capture of target organisms, resulting in underestimation of fish species. DNA metabarcoding has been recognized as a powerful noninvasive alternative tool for fish biomonitoring and management. Despite the increasing popularity of this method for the assessment of aquatic megadiverse ecosystems, its implementation for studying the highly diverse Neotropical ichthyofauna still presents some challenges. One of them is to devise what primer set could reliably amplify the DNA of all fish species from a megadiverse river basin and have enough resolution to identify them. In order to identify and overcome these drawbacks, we have investigated the efficiency of the metabarcoding approach on Neotropical fishes using a mock sample containing genomic DNA of 18 fish species from the Jequitinhonha River basin, Eastern Brazil. We compared three primer sets targeting the 12S rRNA gene: two universal and widely used markers for fish metabarcoding [MiFish (~170bp) and Teleo_1 (~60bp)], and NeoFish (~190bp), recently developed by our research group specifically for the identification of Neotropical fishes (Milan et al., 2020). Two samples amplified using three primers were sequenced in a single multiplexed Illumina MiniSeq run, using normalized and non-normalized pools. Bioinformatic analyses were performed using a DADA2/Phyloseq based pipeline to perform filtering steps and to assign Amplicon Sequence Variants (ASVs). We used a custom 12S reference sequence database that included 190 specimens representing 101 species and 70 genera from the Jequitinhonha and São Francisco river basins. A total of 187 ASVs were recovered: 79, 66 and 42 for NeoFish, MiFish and Teleo_1, respectively. ASVs of unexpected species were identified for both pools (Fig. 1), though each of these ASVs had an abundance of less than 50 copies. In addition, species of the Hoplias and Prochilodus genera could not be identified at the species level, due to identical sequences within each genus, possibly because of the insufficient variation within the 12S region recovered by these primers’ amplicons. Unexpectedly, although a single individual of each species was placed in the pools, more than one ASV was identified for some species, likely caused by PCR biases. Overall, all primer sets displayed similar taxonomic resolution for the DNA pools and recovered all species, except for NeoFish, which could not detect Steindachneridion amblyurum due to an incompatibility in the 3’ of the NeoFish forward primer and Teleo_1, which could not identify Steindachnerina elegans. These results highlight the need of reliable databases in order to enable the full assignment of ASVs and OTUs to species level, and the importance of calibrating the DNA metabarcoding approach with mock samples to identify weaknesses and pivotal steps prior to the application on large scale DNA based biodiversity evaluation, that can help with the complex task of conserving the megadiverse Neotropical ichthyofauna.