Methods in Lung Microbiome Research.
Ontology highlight
ABSTRACT:
SUBMITTER: Carney SM
PROVIDER: S-EPMC7055701 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.
| S-EPMC5420141 | biostudies-literature
Project description:BackgroundMicrobiota profiles are strongly influenced by many technical aspects that impact the ability of researchers to compare results. To investigate and identify potential biases introduced by technical variations, we compared several approaches throughout the entire workflow of a microbiome study, from sample collection to sequencing, using commercially available mock communities (from bacterial strains as well as from DNA) and multiple human fecal samples, including a large set of positive controls created as a random mix of several participant samples.MethodsHuman fecal material was sampled, and aliquots were used to test two commercially available stabilization solutions (OMNIgene·GUT and Zymo Research) in comparison to samples frozen immediately upon collection. In addition, the methodology for DNA extraction, input of DNA, or the number of PCR cycles were analyzed. Furthermore, to investigate the potential batch effects in DNA extraction, sequencing, and barcoding, we included 139 positive controls.ResultsSamples preserved in both the stabilization buffers limited the overgrowth of Enterobacteriaceae when compared to unpreserved samples stored at room temperature (RT). These stabilized samples stored at RT were different from immediately frozen samples, where the relative abundance of Bacteroidota was higher and Actinobacteriota and Firmicutes were lower. As reported previously, the method used for cell disruption was a major contributor to variation in microbiota composition. In addition, a high number of cycles during PCR lead to an increase in contaminants detected in the negative controls. The DNA extraction had a significant impact on the microbial composition, also observed with the use of different Illumina barcodes during library preparation and sequencing, while no batch effect was observed in replicate runs.ConclusionOur study reaffirms the importance of the mechanical cell disruption method and immediate frozen storage as critical aspects in fecal microbiota studies. A comparison of storage conditions revealed that the bias was limited in RT samples preserved in stabilization systems, and these may be a suitable compromise when logistics are challenging due to the size or location of a study. Moreover, to reduce the effect of contaminants in fecal microbiota profiling studies, we suggest the use of ~125 pg input DNA and 25 PCR cycles as optimal parameters during library preparation.
| S-EPMC10101209 | biostudies-literature
Project description:BackgroundTargeted metagenomics and IS-Pro method are two of the many methods that have been used to study the microbiome. The two methods target different regions of the 16 S rRNA gene. The aim of this study was to compare targeted metagenomics and IS-Pro methods for the ability to discern the microbial composition of the lung microbiome of COPD patients.MethodsSpontaneously expectorated sputum specimens were collected from COPD patients. Bacterial DNA was extracted and used for targeted metagenomics and IS-Pro method. The analysis was performed using QIIME2 (targeted metagenomics) and IS-Pro software (IS-Pro method). Additionally, a laboratory cost per isolate and time analysis was performed for each method.ResultsStatistically significant differences were observed in alpha diversity when targeted metagenomics and IS-Pro methods' data were compared using the Shannon diversity measure (p-value = 0.0006) but not with the Simpson diversity measure (p-value = 0.84). Distinct clusters with no overlap between the two technologies were observed for beta diversity. Targeted metagenomics had a lower relative abundance of phyla, such as the Proteobacteria, and higher relative abundance of phyla, such as Firmicutes when compared to the IS-Pro method. Haemophilus, Prevotella and Streptococcus were most prevalent genera across both methods. Targeted metagenomics classified 23 % (144/631) of OTUs to a species level, whereas IS-Pro method classified 86 % (55/64) of OTUs to a species level. However, unclassified OTUs accounted for a higher relative abundance when using the IS-Pro method (35 %) compared to targeted metagenomics (5 %). The two methods performed comparably in terms of cost and time; however, the IS-Pro method was more user-friendly.ConclusionsIt is essential to understand the value of different methods for characterisation of the microbiome. Targeted metagenomics and IS-Pro methods showed differences in ability in identifying and characterising OTUs, diversity and microbial composition of the lung microbiome. The IS-Pro method might miss relevant species and could inflate the abundance of Proteobacteria. However, the IS-Pro kit identified most of the important lung pathogens, such as Burkholderia and Pseudomonas and may work in a more diagnostics-orientated setting. Both methods were comparable in terms of cost and time; however, the IS-Pro method was easier to use.
| S-EPMC8371770 | biostudies-literature
Project description:The investigation of wildlife gastrointestinal microbiomes by next-generation sequencing approaches is a growing field in microbial ecology and conservation. Such studies often face difficulties in sample preservation if neither freezing facilities nor liquid nitrogen (LQN) are readily available. Thus, in order to prevent microbial community changes because of bacterial growth after sampling, preservation buffers need to be applied to samples. However, the amount of microbial community variation attributable to the different preservation treatments and potentially affecting biological interpretation is hardly known. Here, we sampled feces of 11 sheep (Ovis aries sp.) by using swabs and analyzed the effect of air-drying, an inexpensive self-made nucleic acid preservation buffer (NAP), DNA/RNA Shield™, and RNAlater®, each together with freezing (for 10 days) or storing at room temperature (for 10 days) prior to 16S rRNA gene high-throughput sequencing to determine bacterial communities. Results revealed that the proportions of operational taxonomic units (OTUs) belonging to a bacterial phylum were affected by the preservation treatments, and that alpha diversities [observed OTUs, Shannon index, and phylogenetic diversity (PD)] were lower in all preservation treatments than in samples taken by forensic swabs and immediately frozen which is considered as the favored preservation treatment in the absence of any logistic constraints. Overall, NAP had better preservation qualities than RNAlater® and DNA/RNA Shield™ making this self-made buffer a valuable solution in wildlife microbiome studies.
| S-EPMC5281576 | biostudies-literature
Project description:IBD-RESPONSE samples - methodology substudy
| PRJEB74359 | ENA
Project description:Microbiome research has increased dramatically in recent years, driven by advances in technology and significant reductions in the cost of analysis. Such research has unlocked a wealth of data, which has yielded tremendous insight into the nature of the microbial communities, including their interactions and effects, both within a host and in an external environment as part of an ecological community. Understanding the role of microbiota, including their dynamic interactions with their hosts and other microbes, can enable the engineering of new diagnostic techniques and interventional strategies that can be used in a diverse spectrum of fields, spanning from ecology and agriculture to medicine and from forensics to exobiology. From June 19-23 in 2017, the NIH and NSF jointly held an Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome. This review is inspired by some of the topics that arose as priority areas from this unique, interactive workshop. The goal of this review is to summarize the Innovation Lab's findings by introducing the reader to emerging challenges, exciting potential, and current directions in microbiome research. The review is broken into five key topic areas: (1) interactions between microbes and the human body, (2) evolution and ecology of microbes, including the role played by the environment and microbe-microbe interactions, (3) analytical and mathematical methods currently used in microbiome research, (4) leveraging knowledge of microbial composition and interactions to develop engineering solutions, and (5) interventional approaches and engineered microbiota that may be enabled by selectively altering microbial composition. As such, this review seeks to arm the reader with a broad understanding of the priorities and challenges in microbiome research today and provide inspiration for future investigation and multi-disciplinary collaboration.
| S-EPMC7042322 | biostudies-literature
Project description:Lung Genomics Research Consortium
| PRJNA206539 | ENA
Project description:Metagenomic sequencing of human lung biospecimens
| PRJNA437169 | ENA
Project description:Microbiome research has recently gained centre-stage in both basic science and translational applications, yet researchers often feel that public communication about its potential overpromises. This manuscript aims to share a perspective on how scientists can engage in more open, ethical and transparent communication using an ongoing research project on food systems microbiomes as a case study. Concrete examples of strategically planned communication efforts are outlined, which aim to inspire and empower other researchers. Finally, we conclude with a discussion on the benefits of open and transparent communication from early-on in innovation pathways, mainly increasing trust in scientific processes and thus paving the way to achieving societal milestones such as the UN Sustainable Development Goals and the EU Green Deal.
| S-EPMC7763060 | biostudies-literature
Project description:Microbiome composition studies are increasingly shedding light on animal models of disease. This paper describes a protocol for analyzing the gut microbiome composition prior to and after the induction of mice to experimental autoimmune encephalomyelitis (EAE), the principal animal model of the human neuroinflammatory demyelinating disease multiple sclerosis (MS). We also address and provide data assessing the impact of mice reared in different animal facilities on EAE induction. Furthermore, we discuss potential regulators of the gut-microbiome-brain axis (GMBA) in relation to neuroinflammation and implications on demyelinating disease states. Our results suggest that mice reared in different animal facilities produce different levels of EAE induction. These results highlight the importance of accounting for consistent environmental conditions when inducing EAE and other animal models of disease. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Study of the composition of the gut microbiome in the neuroinflammatory model of experimental autoimmune encephalomyelitis Basic Protocol 2: Experimental procedures for DNA extraction and microbiome analysis.
| S-EPMC9540342 | biostudies-literature