scholarly journals Microbiome meets classical microbiology: quantifying sample CFU using 16S rRNA gene sequencing data

2020 ◽  
Author(s):  
Giuliano Netto Flores Cruz ◽  
Ana Paula Christoff ◽  
Luiz Felipe Valter de Oliveira
Keyword(s):  
High Throughput ◽  
Cross Validation ◽  
Microbial Load ◽  
Cumulative Probability ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Probability Models ◽  
Microbial Composition ◽  
Wide Range ◽  
Ngs Data

Abstract Background Next-generation sequencing (NGS) has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample microbial composition. However, most studies are limited to sample information regarding relative bacterial abundances (sample proportions), ignoring scenarios in which sample microbe biomass can vary widely. Here, we develop an equivolumetric protocol for amplicon library preparation capable of generating NGS data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances within each sample. Within a determined range, we show that the estimation of sample colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues.Results Observed read counts were consistently proportional to input DNA, total microbial load, and bacterium-specific sample abundances, although a saturation tendency was observed as abundances increased. Using Bayesian cumulative probability models, predictive errors in sample CFU estimation varied constantly below one order of magnitude - as measured by the mean absolute log10-ratio (MALR). For total microbial load, observed MALR was no greater than 0.2 during both cross-validation and validation on a test dataset. For observed bacteria, estimation of taxon-specific CFU showed MALR values of at most 0.5. We also performed leave-one-group-out cross-validation to assess predictive performance for previously unseen bacteria. While most bacteria showed MALR no greater than 1, such a threshold was exceeded only by Bacillus cereus.Conclusions Being able to estimate sample CFU in a high-throughput fashion has a wide range of applications, from the study of built environments to public health surveillance. This study shows that equivolumetric protocols along with cumulative probability models allow sample CFU estimation from microbiome datasets. Further, our approach has the potential to generalize to previously unmodeled bacteria, an important feature in high-throughput settings. Lastly, it remains clear that NGS data are not inherently restricted to sample proportions only, and microbiome science can finally meet the working scales of classical microbiology.

scholarly journals Equivolumetric Protocol Generates Library Sizes Proportional to Total Microbial Load in 16S Amplicon Sequencing

2021 ◽  
Vol 12 ◽  
Author(s):  
Giuliano Netto Flores Cruz ◽  
Ana Paula Christoff ◽  
Luiz Felipe Valter de Oliveira
Keyword(s):  
16S Rrna ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Predictive Performance ◽  
Amplicon Sequencing ◽  
Microbial Load ◽  
Cumulative Probability ◽  
Sequencing Data ◽  
Probability Models ◽  
Order Of Magnitude

High-throughput sequencing of 16S rRNA amplicon has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample bacterial composition directly from samples. However, most studies are limited to information regarding relative bacterial abundances (sample proportions), ignoring scenarios in which sample microbe biomass can vary widely. Here, we use an equivolumetric protocol for 16S rRNA amplicon library preparation capable of generating Illumina sequencing data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances within each sample. Under specified conditions, we show that the estimation of colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues. Our results indicate that predictive errors vary consistently below one order of magnitude for total microbial load and abundance of observed bacteria. We also demonstrate our approach has the potential to generalize to previously unseen bacteria, but predictive performance is hampered by specific taxa of uncommon profile. Finally, it remains clear that high-throughput sequencing data are not inherently restricted to sample proportions only, and such technologies bear the potential to meet the working scales of traditional microbiology.

scholarly journals Equivolumetric protocol generates library sizes proportional to total microbial load in next-generation sequencing

2020 ◽  
Author(s):  
Giuliano Netto Flores Cruz ◽  
Ana Paula Christoff ◽  
Luiz Felipe Valter de Oliveira
Keyword(s):  
Next Generation Sequencing ◽  
Predictive Performance ◽  
Cumulative Probability ◽  
Next Generation ◽  
Probability Models ◽  
Microbial Composition ◽  
Order Of Magnitude ◽  
High Level ◽  
Ngs Data ◽  
Generation Sequencing

AbstractNext-generation sequencing (NGS) has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample microbial composition. However, most studies are limited to information regarding relative bacterial abundances, ignoring scenarios in which sample microbe biomass can vary widely. Here, we develop an equivolumetric protocol for amplicon library preparation capable of generating NGS data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances. Under specified conditions, we argue that the estimation of colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues. Our results indicate that predictive errors vary consistently below one order of magnitude for observed bacteria. We also demonstrate our approach has the potential to generalize to previously unseen bacteria, but predictive performance is hampered by specific taxa of uncommon profile. Finally, it remains clear that NGS data are not inherently restricted to relative information only, and microbiome science can indeed meet the working scales of traditional microbiology.

scholarly journals Allometry and Ecology of the Bilaterian Gut Microbiome

mBio ◽  
2018 ◽  
Vol 9 (2) ◽  
pp. e00319-18 ◽  
Author(s):  
Scott Sherrill-Mix ◽  
Kevin McCormick ◽  
Abigail Lauder ◽  
Aubrey Bailey ◽  
Laurie Zimmerman ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Island Biogeography ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Data Set ◽  
Community Construction ◽  
Wide Range ◽  
Niche Diversification ◽  
Bacterial Lineages

ABSTRACT Classical ecology provides principles for construction and function of biological communities, but to what extent these apply to the animal-associated microbiota is just beginning to be assessed. Here, we investigated the influence of several well-known ecological principles on animal-associated microbiota by characterizing gut microbial specimens from bilaterally symmetrical animals (Bilateria) ranging from flies to whales. A rigorously vetted sample set containing 265 specimens from 64 species was assembled. Bacterial lineages were characterized by 16S rRNA gene sequencing. Previously published samples were also compared, allowing analysis of over 1,098 samples in total. A restricted number of bacterial phyla was found to account for the great majority of gut colonists. Gut microbial composition was associated with host phylogeny and diet. We identified numerous gut bacterial 16S rRNA gene sequences that diverged deeply from previously studied taxa, identifying opportunities to discover new bacterial types. The number of bacterial lineages per gut sample was positively associated with animal mass, paralleling known species-area relationships from island biogeography and implicating body size as a determinant of community stability and niche complexity. Samples from larger animals harbored greater numbers of anaerobic communities, specifying a mechanism for generating more-complex microbial environments. Predictions for species/abundance relationships from models of neutral colonization did not match the data set, pointing to alternative mechanisms such as selection of specific colonists by environmental niche. Taken together, the data suggest that niche complexity increases with gut size and that niche selection forces dominate gut community construction. IMPORTANCE The intestinal microbiome of animals is essential for health, contributing to digestion of foods, proper immune development, inhibition of pathogen colonization, and catabolism of xenobiotic compounds. How these communities assemble and persist is just beginning to be investigated. Here we interrogated a set of gut samples from a wide range of animals to investigate the roles of selection and random processes in microbial community construction. We show that the numbers of bacterial species increased with the weight of host organisms, paralleling findings from studies of island biogeography. Communities in larger organisms tended to be more anaerobic, suggesting one mechanism for niche diversification. Nonselective processes enable specific predictions for community structure, but our samples did not match the predictions of the neutral model. Thus, these findings highlight the importance of niche selection in community construction and suggest mechanisms of niche diversification.

scholarly journals Microbial Composition of Human Appendices from Patients following Appendectomy

mBio ◽  
2013 ◽  
Vol 4 (1) ◽  
Author(s):  
Caitriona M. Guinane ◽  
Amany Tadrous ◽  
Fiona Fouhy ◽  
C. Anthony Ryan ◽  
Eugene M. Dempsey ◽  
...  
Keyword(s):  
Human Health ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Evolutionary Development ◽  
Rrna Gene ◽  
Limited Data ◽  
Microbial Composition ◽  
Content Type ◽  
Study Results ◽  
Human Appendix

ABSTRACT The human appendix has historically been considered a vestige of evolutionary development with an unknown function. While limited data are available on the microbial composition of the appendix, it has been postulated that this organ could serve as a microbial reservoir for repopulating the gastrointestinal tract in times of necessity. We aimed to explore the microbial composition of the human appendix, using high-throughput sequencing of the 16S rRNA gene V4 region. Seven patients, 5 to 25 years of age, presenting with symptoms of acute appendicitis were included in this study. Results showed considerable diversity and interindividual variability among the microbial composition of the appendix samples. In general, however, Firmicutes was the dominant phylum, with the majority of additional sequences being assigned at various levels to Proteobacteria, Bacteroidetes, Actinobacteria, and Fusobacteria. Despite the large diversity in the microbiota found within the appendix, however, a few major families and genera were found to comprise the majority of the sequences present. Interestingly, also, certain taxa not generally associated with the human intestine, including the oral pathogens Gemella, Parvimonas, and Fusobacterium, were identified among the appendix samples. The prevalence of genera such as Fusobacterium could also be linked to the severity of inflammation of the organ. We conclude that the human appendix contains a robust and varied microbiota distinct from the microbiotas in other niches within the human microbiome. The microbial composition of the human appendix is subject to extreme variability and comprises a diversity of biota that may play an important, as-yet-unknown role in human health. IMPORTANCE There are currently limited data available on the microbial composition of the human appendix. It has been suggested, however, that it may serve as a “safe house” for commensal bacteria that can reinoculate the gut at need. The present study is the first comprehensive view of the microbial composition of the appendix as determined by high-throughput sequencing. We have determined that the human appendix contains a wealth of microbes, including members of 15 phyla. Important information regarding the associated bacterial diversity of the appendix which will help determine the role, if any, the appendix microbiota has in human health is presented.

scholarly journals Learning Sparse Log-Ratios for High-Throughput Sequencing Data

2021 ◽  
Author(s):  
Elliott Gordon-Rodriguez ◽  
Thomas P. Quinn ◽  
John P. Cunningham
Keyword(s):  
High Throughput ◽  
Latent Variables ◽  
High Throughput Sequencing ◽  
Compositional Data ◽  
Predictive Accuracy ◽  
Learning Algorithm ◽  
Sequencing Data ◽  
Genetic Sequencing ◽  
Wide Range ◽  
Benchmark Datasets

AbstractThe automatic discovery of interpretable features that are associated to an outcome of interest is a central goal of bioinformatics. In the context of high-throughput genetic sequencing data, and Compositional Data more generally, an important class of features are the log-ratios between subsets of the input variables. However, the space of these log-ratios grows combinatorially with the dimension of the input, and as a result, existing learning algorithms do not scale to increasingly common high-dimensional datasets. Building on recent literature on continuous relaxations of discrete latent variables, we design a novel learning algorithm that identifies sparse log-ratios several orders of magnitude faster than competing methods. As well as dramatically reducing runtime, our method outperforms its competitors in terms of sparsity and predictive accuracy, as measured across a wide range of benchmark datasets.

scholarly journals Isolation of SAR11 Marine Bacteria from Cryopreserved Seawater

mSystems ◽  
2020 ◽  
Vol 5 (6) ◽  
pp. e00954-20
Author(s):  
Elizabeth A. Monaghan ◽  
Kelle C. Freel ◽  
Michael S. Rappé
Keyword(s):  
High Throughput ◽  
Marine Bacteria ◽  
Mixed Cultures ◽  
Rrna Gene ◽  
Marine Microorganisms ◽  
Culture Collections ◽  
Natural Systems ◽  
Wide Range ◽  
Long Time ◽  
Cultivation Experiment

ABSTRACTWhile marine microorganisms are frequently studied in their natural environment, isolated strains are invaluable resources that can be used in controlled experiments to expand upon direct observations from natural systems. Here, we sought a means to enhance culture collections of SAR11 marine bacteria by testing the use of seawater cryopreserved with glycerol as an inoculum. Using a raw seawater sample collected from the tropical Pacific Ocean, a subsample was diluted in seawater growth medium to create 576 2-ml dilution cultures containing 5 cells each and incubated for a high-throughput culturing (HTC) experiment, while another portion was cryopreserved in 10% glycerol. After 10 months, a cryopreserved aliquot was thawed and used to create a second cultivation experiment of 480 2-ml cultures containing 5 cells each and 470 cultures containing 105 cells each. The raw seawater cultivation experiment resulted in the successful isolation of 54 monocultures and 29 mixed cultures, while cryopreserved seawater resulted in 59 monocultures and 29 mixed cultures. Combined, the cultures included 51 SAR11 isolates spanning 11 unique 16S rRNA gene amplicon sequence variants (ASVs) from the raw seawater inoculum and 74 SAR11 isolates spanning 13 unique ASVs from cryopreserved seawater. A vast majority (92%) of SAR11 isolates from the two HTC experiments were members of SAR11 subclade Ia, though subclades IIIa and Va were also recovered from cryopreserved seawater and subclade Ib was recovered from both. The four most abundant SAR11 subclade Ia ASVs found in the initial seawater environmental sample were isolated by both approaches.IMPORTANCE High-throughput dilution culture has proved to be a successful approach to bring some difficult-to-isolate planktonic microorganisms into culture, including the highly abundant SAR11 lineage of marine bacteria. While the long-term preservation of bacterial isolates by freezing them in the presence of cryoprotectants, such as glycerol, has been shown to be an effective method of storing viable cells over long time periods (i.e., years), to our knowledge it had not previously been tested for its efficacy in preserving raw seawater for later use as an inoculum for high-throughput cultivation experiments. We found that SAR11 and other abundant marine bacteria could be isolated from seawater that was previously cryopreserved for nearly 10 months at a rate of culturability similar to that of the same seawater used fresh, immediately after collection. Our findings (i) expand the potential of high-throughput cultivation experiments to include testing when immediate isolation experiments are impractical, (ii) allow for targeted isolation experiments from specific samples based on analyses such as microbial community structure, and (iii) enable cultivation experiments across a wide range of other conditions that would benefit from having source inocula available over extended periods of time.

scholarly journals High throughput sequencing unravels tomato-pathogen interactions towards a sustainable plant breeding

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Maria Doroteia Campos ◽  
Maria do Rosário Félix ◽  
Mariana Patanita ◽  
Patrick Materatski ◽  
Carla Varanda
Keyword(s):  
Plant Breeding ◽  
High Throughput ◽  
Plant Pathogen ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Molecular Networks ◽  
Sequencing Data ◽  
Sources Of Resistance ◽  
Tomato Plants ◽  
Wide Range

AbstractTomato (Solanum lycopersicum) is one of the most economically important vegetables throughout the world. It is one of the best studied cultivated dicotyledonous plants, often used as a model system for plant research into classical genetics, cytogenetics, molecular genetics, and molecular biology. Tomato plants are affected by different pathogens such as viruses, viroids, fungi, oomycetes, bacteria, and nematodes, that reduce yield and affect product quality. The study of tomato as a plant-pathogen system helps to accelerate the discovery and understanding of the molecular mechanisms underlying disease resistance and offers the opportunity of improving the yield and quality of their edible products. The use of functional genomics has contributed to this purpose through both traditional and recently developed techniques, that allow the identification of plant key functional genes in susceptible and resistant responses, and the understanding of the molecular basis of compatible interactions during pathogen attack. Next-generation sequencing technologies (NGS), which produce massive quantities of sequencing data, have greatly accelerated research in biological sciences and offer great opportunities to better understand the molecular networks of plant–pathogen interactions. In this review, we summarize important research that used high-throughput RNA-seq technology to obtain transcriptome changes in tomato plants in response to a wide range of pathogens such as viruses, fungi, bacteria, oomycetes, and nematodes. These findings will facilitate genetic engineering efforts to incorporate new sources of resistance in tomato for protection against pathogens and are of major importance for sustainable plant-disease management, namely the ones relying on the plant’s innate immune mechanisms in view of plant breeding.

scholarly journals Analysis of Hindgut Microbiome of Sheep and Effect of Different Husbandry Conditions

Animals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 4
Author(s):  
Giulietta Minozzi ◽  
Filippo Biscarini ◽  
Emanuela Dalla Costa ◽  
Matteo Chincarini ◽  
Nicola Ferri ◽  
...  
Keyword(s):  
Animal Health ◽  
Control Group ◽  
P Value ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Core Microbiome ◽  
Fecal Microbiome ◽  
Microbiome Composition ◽  
The Core ◽  
Wide Range

The microbiome is now seen as an important resource to understand animal health and welfare in many species. However, there are few studies aiming at identifying the association between fecal microbiome composition and husbandry conditions in sheep. A wide range of stressors associated with management and housing of animals increases the hypothalamic–pituitary axis activity, with growing evidence that the microbiome composition can be modified. Therefore, the purpose of the present study was to describe the core microbiome in sheep, characterized using 16S rRNA gene sequencing, and to explore whether exposure to stressful husbandry conditions changed sheep hindgut microbiome composition. Sheep (n = 10) were divided in two groups: isolated group (individually separated for 3 h/day) and control group (housed in the home pen for the entire trial period). Sheep core microbiome was dominated by Firmicutes (43.6%), Bacteroidetes (30.38%), Proteobacteria (10.14%), and Verrucomicrobia (7.55%). Comparative results revealed few operational taxonomic units (OTUs) with significantly different relative abundance between groups. Chao1, abundance-based coverage estimator (ACE), and Fisher’s alpha indices did not show differences between groups. OTU-based Bray–Curtis distances between groups were not significant (p-value = 0.07). In conclusion, these results describing the core microbiome of sheep do not suggest a strong effect of stressful husbandry conditions on microbial composition.

scholarly journals Comparative analysis of amplicon and metagenomic sequencing methods reveals key features in the evolution of animal metaorganisms

2019 ◽  
Author(s):  
Philipp Rausch ◽  
Malte Rühlemann ◽  
Britt Hermes ◽  
Shauni Doms ◽  
Tal Dagan ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Microbial Composition ◽  
Evolutionary Patterns ◽  
Wide Range ◽  
Taxonomic Groups ◽  
And Function

AbstractBackgroundThe interplay between hosts and their associated microbiome is now recognized as a fundamental basis of the ecology, evolution and development of both players. These interdependencies inspired a new view of multicellular organisms as “metaorganisms”. The goal of the Collaborative Research Center “Origin and Function of Metaorganisms” is to understand why and how microbial communities form long-term associations with hosts from diverse taxonomic groups, ranging from sponges to humans in addition to plants.MethodsIn order to optimize the choice of analysis procedures, which may differ according to the host organism and question at hand, we systematically compared the two main technical approaches for profiling microbial communities, 16S rRNA gene amplicon- and metagenomic shotgun sequencing across our panel of ten host taxa. This includes two commonly used 16S rRNA gene regions and two amplification procedures, thus totaling five different microbial profiles per host sample.ConclusionWhile 16S rRNA gene-based analyses are subject to much skepticism, we demonstrate that many aspects of bacterial community characterization are consistent across methods and that metagenomic shotgun results are largely dependent on the employed pipeline. The resulting insight facilitates the selection of appropriate methods across a wide range of host taxa. Finally, by contrasting taxonomic and functional profiles and performing phylogenetic analysis, we provide important and novel insight into broad evolutionary patterns among metaorganisms, whereby the transition of animals from an aquatic to a terrestrial habitat marks a major event in the evolution of host-associated microbial composition.

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