scholarly journals Longitudinal differential abundance analysis of microbial marker-gene surveys using smoothing splines

2017 ◽  
Author(s):  
Joseph N. Paulson ◽  
Hisham Talukder ◽  
Héctor Corrada Bravo
Keyword(s):  
Infectious Diseases ◽  
Community Dynamics ◽  
Marker Gene ◽  
Initial Step ◽  
Smoothing Splines ◽  
Taxonomic Composition ◽  
Sequencing Data ◽  
Differential Abundance ◽  
Time Periods ◽  
Complex Relationships

AbstractBackgroundHigh-throughput targeted sequencing of the 16S ribosomal RNA marker gene is often used to profile and characterize the taxonomic composition of microbial communities. This type of big high-through sequencing data is rapidly being applied to various infectious diseases like diarrhea. While many studies are limited to single “snapshots” of these communities, there is increasing recognition that longitudinal profiling of these communities are required to understand community dynamics and the complex relationships between dynamics and phenotypes of interest. Statistical methods that determine microbial features that are differentially expressed are required as an initial step to characterizing phenotypic associations with community dynamics in big data and infectious diseases.ResultsWe present a novel method for longitudinal marker-gene surveys based on smoothing splines that allows discovery and inference of time periods where specific microbial features are differentially abundant. We applied our method to three 16S marker-gene surveys, including, groups of gnotobiotic mice on two diets, patients challenged with ETEC (H10407), and a vaginal microbiome of healthy women. Employing our methodology we recover known bacterial differences and highlight a few extra species providing insight into when specific changes occurred. Additionally, in the cohort challenged with ETEC we recover proposed probiotic bacteriaBacteroides xylanisolvens, Collinsella aerofaciens, andFaecalibacterium prausnitziiassociatons with healthy individuals.ConclusionsThe method presented is, to our knowledge, the first flexible method of its kind implemented as a software capable of detecting time periods of differential abundance for microbial features species between two or more sample groups of interest. Our method is available within themetagenomeSeqopen-source software for analysis of metagenomic package available through the Bioconductor project and is termed metaSplines.

scholarly journals Assessing 16S marker gene survey data analysis methods using mixtures of human stool sample DNA extracts

2018 ◽  
Author(s):  
Nathan D Olson ◽  
M. Senthil Kumar ◽  
Shan Li ◽  
Stephanie Hao ◽  
Winston Timp ◽  
...  
Keyword(s):  
16S Rrna ◽  
De Novo ◽  
Marker Gene ◽  
Real Data ◽  
Qualitative Assessment ◽  
Data Sets ◽  
Sequencing Data ◽  
Differential Abundance ◽  
Analysis Methods ◽  
Downstream Analysis

AbstractBackgroundAnalysis of 16S rRNA marker-gene surveys, used to characterize prokaryotic microbial communities, may be performed by numerous bioinformatic pipelines and downstream analysis methods. However, there is limited guidance on how to decide between methods, appropriate data sets and statistics for assessing these methods are needed. We developed a mixture dataset with real data complexity and an expected value for assessing 16S rRNA bioinformatic pipelines and downstream analysis methods. We generate an assessment dataset using a two-sample titration mixture design. The sequencing data were processed using multiple bioinformatic pipelines, i) DADA2 a sequence inference method, ii) Mothur a de novo clustering method, and iii) QIIME with open-reference clustering. The mixture dataset was used to qualitatively and quantitatively assess count tables generated using the pipelines.ResultsThe qualitative assessment was used to evalute features only present in unmixed samples and titrations. The abundance of Mothur and QIIME features specific to unmixed samples and titrations were explained by sampling alone. However, for DADA2 over a third of the unmixed sample and titration specific feature abundance could not be explained by sampling alone. The quantitative assessment evaluated pipeline performance by comparing observed to expected relative and differential abundance values. Overall the observed relative abundance and differential abundance values were consistent with the expected values. Though outlier features were observed across all pipelines.ConclusionsUsing a novel mixture dataset and assessment methods we quantitatively and qualitatively evaluated count tables generated using three bioinformatic pipelines. The dataset and methods developed for this study will serve as a valuable community resource for assessing 16S rRNA marker-gene survey bioinformatic methods.

scholarly journals Longitudinal assessment of the bovine ocular bacterial community dynamics in calves

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Alison C. Bartenslager ◽  
Nirosh D. Althuge ◽  
John Dustin Loy ◽  
Matthew M. Hille ◽  
Matthew L. Spangler ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Community Dynamics ◽  
Bacterial Community Composition ◽  
Clinical Signs ◽  
Sampling Time ◽  
Experimental Population ◽  
Opportunistic Pathogens ◽  
Time Periods ◽  
Over Time

Abstract Background Infectious Bovine Keratoconjunctivitis (IBK), commonly known as pinkeye, is one of the most significant diseases of beef cattle. As such, IBK costs the US beef industry at least 150 million annually. However, strategies to prevent IBK are limited, with most cases resulting in treatment with antibiotics once the disease has developed. Longitudinal studies evaluating establishment of the ocular microbiota may identify critical risk periods for IBK outbreaks or changes in the microbiota that may predispose animals to IBK. Results In an attempt to characterize the establishment and colonization patterns of the bovine ocular microbiota, we conducted a longitudinal study consisting of 227 calves and evaluated the microbiota composition over time using amplicon sequence variants (ASVs) based on 16S rRNA sequencing data and culture-based approaches. Beef calves on trial consisted of both male (intact) and females. Breeds were composed of purebred Angus and composites with varying percentages of Simmental, Angus, and Red Angus breeds. Average age at the start of the trial was 65 days ±15.02 and all calves remained nursing on their dam until weaning (day 139 of the study). The trial consisted of 139 days with four sampling time points on day 0, 21, 41, and 139. The experimental population received three different vaccination treatments (autogenous, commercial (both inactivated bacteria), and adjuvant placebo), to assess the effectiveness of different vaccines for IBK prevention. A significant change in bacterial community composition was observed across time periods sampled compared to the baseline (p < 0.001). However, no treatment effect of vaccine was detected within the ocular bacterial community. The bacterial community composition with the greatest time span between sampling time periods (98d span) was most similar to the baseline sample collected, suggesting re-establishment of the ocular microbiota to baseline levels over time after perturbation. The effect of IgA levels on the microbial community was investigated in a subset of cattle within the study. However, no significant effect of IgA was observed. Significant changes in the ocular microbiota were identified when comparing communities pre- and post-clinical signs of IBK. Additionally, dynamic changes in opportunistic pathogens Moraxella spp. were observed and confirmed using culture based methods. Conclusions Our results indicate that the bovine ocular microbiota is well represented by opportunistic pathogens such as Moraxella and Mycoplasma. Furthermore, this study characterizes the diversity of the ocular microbiota in calves and demonstrates the plasticity of the ocular microbiota to change. Additionally, we demonstrate the ocular microbiome in calves is similar between the eyes and the perturbation of one eye results in similar changes in the other eye. We also demonstrate the bovine ocular microbiota is slow to recover post perturbation and as a result provide opportunistic pathogens a chance to establish within the eye leading to IBK and other diseases. Characterizing the dynamic nature of the ocular microbiota provides novel opportunities to develop potential probiotic intervention to reduce IBK outbreaks in cattle.

scholarly journals Bovine tuberculosis disturbs parasite functional trait composition in African buffalo

2019 ◽  
Vol 116 (29) ◽  
pp. 14645-14650 ◽  
Author(s):  
Brianna R. Beechler ◽  
Kate S. Boersma ◽  
Peter E. Buss ◽  
Courtney A. C. Coon ◽  
Erin E. Gorsich ◽  
...  
Keyword(s):  
Community Composition ◽  
Bovine Tuberculosis ◽  
Community Dynamics ◽  
Parasite Community ◽  
Functional Trait ◽  
Taxonomic Composition ◽  
African Buffalo ◽  
Emerging Infections ◽  
Parasite Communities ◽  
Parasite Richness

Novel parasites can have wide-ranging impacts, not only on host populations, but also on the resident parasite community. Historically, impacts of novel parasites have been assessed by examining pairwise interactions between parasite species. However, parasite communities are complex networks of interacting species. Here we used multivariate taxonomic and trait-based approaches to determine how parasite community composition changed when African buffalo (Syncerus caffer) acquired an emerging disease, bovine tuberculosis (BTB). Both taxonomic and functional parasite richness increased significantly in animals that acquired BTB than in those that did not. Thus, the presence of BTB seems to catalyze extraordinary shifts in community composition. There were no differences in overall parasite taxonomic composition between infected and uninfected individuals, however. The trait-based analysis revealed an increase in direct-transmitted, quickly replicating parasites following BTB infection. This study demonstrates that trait-based approaches provide insight into parasite community dynamics in the context of emerging infections.

scholarly journals An emergent clade of SARS-CoV-2 linked to returned travellers from Iran

2020 ◽  
Author(s):  
John-Sebastian Eden ◽  
Rebecca Rockett ◽  
Ian Carter ◽  
Hossinur Rahman ◽  
Joep de Ligt ◽  
...  
Keyword(s):  
New Zealand ◽  
Infectious Diseases ◽  
Genome Sequencing ◽  
Phylogenetic Analyses ◽  
Emerging Infectious Diseases ◽  
Whole Genome Sequencing Data ◽  
Viral Diversity ◽  
Whole Genome ◽  
Sequencing Data ◽  
Public Data

AbstractThe SARS-CoV-2 epidemic has rapidly spread outside China with major outbreaks occurring in Italy, South Korea and Iran. Phylogenetic analyses of whole genome sequencing data identified a distinct SARS-CoV-2 clade linked to travellers returning from Iran to Australia and New Zealand. This study highlights potential viral diversity driving the epidemic in Iran, and underscores the power of rapid genome sequencing and public data sharing to improve the detection and management of emerging infectious diseases.

scholarly journals Reducing bias in risk indices for COVID-19

2022 ◽  
Vol 17 (s1) ◽  
Author(s):  
Michał Paweł Michalak ◽  
Jack Cordes ◽  
Agnieszka Kulawik ◽  
Sławomir Sitek ◽  
Sławomir Pytel ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Spatial Heterogeneity ◽  
Disease Burden ◽  
Risk Indices ◽  
Study Evaluation ◽  
Dynamical Properties ◽  
Time Periods ◽  
Regional Disease ◽  
Over Time

Spatiotemporal modelling of infectious diseases such as coronavirus disease 2019 (COVID-19) involves using a variety of epidemiological metrics such as regional proportion of cases and/or regional positivity rates. Although observing changes of these indices over time is critical to estimate the regional disease burden, the dynamical properties of these measures, as well as crossrelationships, are usually not systematically given or explained. Here we provide a spatiotemporal framework composed of six commonly used and newly constructed epidemiological metrics and conduct a case study evaluation. We introduce a refined risk estimate that is biased neither by variation in population size nor by the spatial heterogeneity of testing. In particular, the proposed methodology would be useful for unbiased identification of time periods with elevated COVID-19 risk without sensitivity to spatial heterogeneity of neither population nor testing coverage.We offer a case study in Poland that shows improvement over the bias of currently used methods. Our results also provide insights regarding regional prioritisation of testing and the consequences of potential synchronisation of epidemics between regions. The approach should apply to other infectious diseases and other geographical areas.

scholarly journals Early onset preeclampsia in a model for human placental trophoblast

2019 ◽  
Vol 116 (10) ◽  
pp. 4336-4345 ◽  
Author(s):  
Megan A. Sheridan ◽  
Ying Yang ◽  
Ashish Jain ◽  
Alex S. Lyons ◽  
Penghua Yang ◽  
...  
Keyword(s):  
Early Onset ◽  
Marker Gene ◽  
Disease Onset ◽  
Initial Step ◽  
Sequencing Analysis ◽  
Cell Adhesion And Migration ◽  
Early Onset Preeclampsia ◽  
And Migration ◽  
Induced Pluripotent ◽  
Pregnancy Marker

We describe a model for early onset preeclampsia (EOPE) that uses induced pluripotent stem cells (iPSCs) generated from umbilical cords of EOPE and control (CTL) pregnancies. These iPSCs were then converted to placental trophoblast (TB) representative of early pregnancy. Marker gene analysis indicated that both sets of cells differentiated at comparable rates. The cells were tested for parameters disturbed in EOPE, including invasive potential. Under 5% O2, CTL TB and EOPE TB lines did not differ, but, under hyperoxia (20% O2), invasiveness of EOPE TB was reduced. RNA sequencing analysis disclosed no consistent differences in expression of individual genes between EOPE TB and CTL TB under 20% O2, but, a weighted correlation network analysis revealed two gene modules (CTL4 and CTL9) that, in CTL TB, were significantly linked to extent of TB invasion. CTL9, which was positively correlated with 20% O2(P= 0.02) and negatively correlated with invasion (P= 0.03), was enriched for gene ontology terms relating to cell adhesion and migration, angiogenesis, preeclampsia, and stress. Two EOPE TB modules, EOPE1 and EOPE2, also correlated positively and negatively, respectively, with 20% O2conditions, but only weakly with invasion; they largely contained the same sets of genes present in modules CTL4 and CTL9. Our experiments suggest that, in EOPE, the initial step precipitating disease is a reduced capacity of placental TB to invade caused by a dysregulation of O2response mechanisms and that EOPE is a syndrome, in which unbalanced expression of various combinations of genes affecting TB invasion provoke disease onset.

scholarly journals Ecological and Technical Mechanisms for Cross-Reaction of Human Fecal Indicators with Animal Hosts

2019 ◽  
Vol 86 (5) ◽  
Author(s):  
Shuchen Feng ◽  
Warish Ahmed ◽  
Sandra L. McLellan
Keyword(s):  
False Positive ◽  
Marker Gene ◽  
Fecal Pollution ◽  
Marker Genes ◽  
Indicator Organisms ◽  
Sequencing Data ◽  
Content Type ◽  
E Coli ◽  
Cross Reactions ◽  
Nonspecific Amplification

ABSTRACT Quantitative PCR (qPCR) assays for human/sewage marker genes have demonstrated sporadic positive results in animal feces despite their high specificities to sewage and human feces. It is unclear whether these positive reactions are caused by true occurrences of microorganisms containing the marker gene (i.e., indicator organisms) or nonspecific amplification (false positive). The distribution patterns of human/sewage indicator organisms in animals have not been explored in depth, which is crucial for evaluating a marker gene’s true- or false-positive reactions. Here, we analyzed V6 region 16S rRNA gene sequences from 257 animal fecal samples and tested a subset of 184 using qPCR for human/sewage marker genes. Overall, specificities of human/sewage marker genes within sequencing data were 99.6% (BacV6-21), 96.9% (Lachno3), and 96.1% (HF183, indexed by its inferred V6 sequence). Occurrence of some true cross-reactions was associated with atypical compositions of organisms within the genera Blautia or Bacteroides. For human/sewage marker qPCR assays, specificities were 96.7% (HF183/Bac287R), 96.2% (BacV6-21), 95.6% (human Bacteroides [HB]), and 94.0% (Lachno3). Select assays duplexed with either Escherichia coli or Enterococcus spp. were also validated. Most of the positive qPCR results in animals were low level and, on average, 2 orders of magnitude lower than the copy numbers of E. coli and Enterococcus spp. The lower specificity in qPCR assays compared to sequencing data was mainly caused by amplification of sequences highly similar to the marker gene and not the occurrence of the exact marker sequence in animal fecal samples. IMPORTANCE Identifying human sources of fecal pollution is critical to remediate sanitation concerns. Large financial investments are required to address these concerns; therefore, a high level of confidence in testing results is needed. Human fecal marker genes validated in this study showed high specificity in both sequencing data and qPCR results. Human marker sequences were rarely found in individual animals, and in most cases, the animals had atypical microbial communities. Sequencing also revealed the presence of closely related organisms that could account for nonspecific amplification in certain assays. Both the true cross-reactions and the nonspecific amplification had low signals well below E. coli or Enterococcus levels and likely would not impact the assay’s ability to reliably detect human fecal pollution. No animal source had multiple human/sewage marker genes present; therefore, using a combination of marker genes would increase the confidence of human fecal pollution detection.

scholarly journals Below-ground plant–fungus network topology is not congruent with above-ground plant–animal network topology

2015 ◽  
Vol 1 (9) ◽  
pp. e1500291 ◽  
Author(s):  
Hirokazu Toju ◽  
Paulo R. Guimarães ◽  
Jens M. Olesen ◽  
John N. Thompson
Keyword(s):  
Network Topology ◽  
Network Architecture ◽  
Community Dynamics ◽  
Species Coexistence ◽  
Interspecific Interactions ◽  
Fungal Species ◽  
Sequencing Data ◽  
Phylogenetic Groups ◽  
Form Complex ◽  
Below Ground

In nature, plants and their pollinating and/or seed-dispersing animals form complex interaction networks. The commonly observed pattern of links between specialists and generalists in these networks has been predicted to promote species coexistence. Plants also build highly species-rich mutualistic networks below ground with root-associated fungi, and the structure of these plant–fungus networks may also affect terrestrial community processes. By compiling high-throughput DNA sequencing data sets of the symbiosis of plants and their root-associated fungi from three localities along a latitudinal gradient, we uncovered the entire network architecture of these interactions under contrasting environmental conditions. Each network included more than 30 plant species and hundreds of mycorrhizal and endophytic fungi belonging to diverse phylogenetic groups. The results were consistent with the notion that processes shaping host-plant specialization of fungal species generate a unique linkage pattern that strongly contrasts with the pattern of above-ground plant–partner networks. Specifically, plant–fungus networks lacked a “nested” architecture, which has been considered to promote species coexistence in plant–partner networks. Rather, the below-ground networks had a conspicuous “antinested” topology. Our findings lead to the working hypothesis that terrestrial plant community dynamics are likely determined by the balance between above-ground and below-ground webs of interspecific interactions.

scholarly journals Differential abundance analysis for microbial marker-gene surveys

2013 ◽  
Vol 10 (12) ◽  
pp. 1200-1202 ◽  
Author(s):  
Joseph N Paulson ◽  
O Colin Stine ◽  
Héctor Corrada Bravo ◽  
Mihai Pop
Keyword(s):  
Marker Gene ◽  
Differential Abundance ◽  
Differential Abundance Analysis

scholarly journals System Biology Modeling with Compositional Microbiome Data Reveals Personalized Gut Microbial Dynamics and Keystone Species

2018 ◽  
Author(s):  
Chenhao Li ◽  
Lisa Tucker-Kellogg ◽  
Niranjan Nagarajan
Keyword(s):  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Community Dynamics ◽  
Keystone Species ◽  
Microbial Interactions ◽  
Natural Environments ◽  
Sequencing Data ◽  
Predator Prey ◽  
Public Datasets ◽  
Microbiome Data

AbstractA growing body of literature points to the important roles that different microbial communities play in diverse natural environments and the human body. The dynamics of these communities is driven by a range of microbial interactions from symbiosis to predator-prey relationships, the majority of which are poorly understood, making it hard to predict the response of the community to different perturbations. With the increasing availability of high-throughput sequencing based community composition data, it is now conceivable to directly learn models that explicitly define microbial interactions and explain community dynamics. The applicability of these approaches is however affected by several experimental limitations, particularly the compositional nature of sequencing data. We present a new computational approach (BEEM) that addresses this key limitation in the inference of generalised Lotka-Volterra models (gLVMs) by coupling biomass estimation and model inference in an expectation maximization like algorithm (BEEM). Surprisingly, BEEM outperforms state-of-the-art methods for inferring gLVMs, while simultaneously eliminating the need for additional experimental biomass data as input. BEEM’s application to previously inaccessible public datasets (due to the lack of biomass data) allowed us for the first time to analyse microbial communities in the human gut on a per individual basis, revealing personalised dynamics and keystone species.

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