1,721,008 research outputs found
Methodological considerations for the use of stable isotope probing in microbial ecology
No full textStable isotope probing (SIP) is a method used for labeling uncultivated microorganisms in environmental samples or directly in field studies using substrate enriched with stable isotope (e.g., 13C). After consumption of the substrate, the cells of microorganisms that consumed the substrate become enriched in the isotope. Labeled biomarkers, such as phospholipid-derived fatty acid (PLFA), ribosomal RNA, and DNA can be analyzed with a range of molecular and analytical techniques, and used to identify and characterize the organisms that incorporated the substrate. The advantages and disadvantages of PLFA-SIP, RNA-SIP, and DNA-SIP are presented. Using examples from our laboratory and from the literature, we discuss important methodological considerations for a successful SIP experiment
Enhancing functional metagenomics of complex microbial communities using stable isotopes
No full textExploring the function of genes encoded by uncultivated microorganisms is one of the major challenges facing microbiologists. Functions can be predicted by sequence comparisons to known genes and proteins, but proof of function requires the analysis of gene products by in vitro or in vivo expression, which is referred to as functional metagenomics. Using this approach, genetic material is retrieved from the environment, cloned, and expressed under laboratory conditions in order to screen for specific biochemical activities. Stable-isotope probing (SIP) is an approach for capturing genetic material of active microorganisms in environmental samples. This method facilitates functional metagenomics by directing the search towards microorganisms that are likely to possess genes of relevance to a specific research objective. In this chapter, we discuss how combined DNA-SIP and metagenomics research has been used for enhancing functional screening efforts. In addition, we highlight emerging methods, such as mRNA-SIP and Raman-microspectroscopy, that can help retrieve genetic material from targeted microbial groups for the discovery of novel functions
Phylogenetically Novel Uncultured Microbial Cells Dominate Earth Microbiomes
Full text linkTo describe a microbe's physiology, including its metabolism, environmental roles, and growth characteristics, it must be grown in a laboratory culture. Unfortunately, many phylogenetically novel groups have never been cultured, so their physiologies have only been inferred from genomics and environmental characteristics. Although the diversity, or number of different taxonomic groups, of uncultured clades has been studied well, their global abundances, or numbers of cells in any given environment, have not been assessed. We quantified the degree of similarity of 16S rRNA gene sequences from diverse environments in publicly available metagenome and metatranscriptome databases, which we show have far less of the culture bias present in primer-amplified 16S rRNA gene surveys, to those of their nearest cultured relatives. Whether normalized to scaffold read depths or not, the highest abundances of metagenomic 16S rRNA gene sequences belong to phylogenetically novel uncultured groups in seawater, freshwater, terrestrial subsurface, soil, hypersaline environments, marine sediment, hot springs, hydrothermal vents, nonhuman hosts, snow, and bioreactors (22% to 87% uncultured genera to classes and 0% to 64% uncultured phyla). The exceptions were human and human-associated environments, which were dominated by cultured genera (45% to 97%). We estimate that uncultured genera and phyla could comprise 7.3 × 1029 (81%) and 2.2 × 1029 (25%) of microbial cells, respectively. Uncultured phyla were overrepresented in metatranscriptomes relative to metagenomes (46% to 84% of sequences in a given environment), suggesting that they are viable. Therefore, uncultured microbes, often from deeply phylogenetically divergent groups, dominate nonhuman environments on Earth, and their undiscovered physiologies may matter for Earth systems. IMPORTANCE In the past few decades, it has become apparent that most of the microbial diversity on Earth has never been characterized in laboratory cultures. We show that these unknown microbes, sometimes called "microbial dark matter," are numerically dominant in all major environments on Earth, with the exception of the human body, where most of the microbes have been cultured. We also estimate that about one-quarter of the population of microbial cells on Earth belong to phyla with no cultured relatives, suggesting that these never-before-studied organisms may be important for ecosystem functions. Author Video: An author video summary of this article is available
Marine methylotrophs revealed by stable-isotope probing, multiple displacement amplification and metagenomics
No full textThe concentrations of one-carbon substrates that fuel methylotrophic microbial communities in the ocean are limited and the specialized guilds of bacteria that use these molecules may exist at low relative abundance. As a result, these organisms are difficult to identify and are often missed with existing cultivation and gene retrieval methods. Here, we demonstrate a novel proof of concept: using environmentally-relevant substrate concentrations in stable-isotope probing (SIP) incubations to yield sufficient DNA for large-insert metagenomic analysis through multiple displacement amplification (MDA). A marine surface-water sample was labelled sufficiently by incubation with near in situ concentrations of methanol. Picogram quantities of labelled C-13-DNA were purified from caesium chloride gradients, amplified with MDA to produce microgram amounts of high-molecular-weight DNA ( 10 000 clones. Denaturing gradient gel electrophoresis (DGGE) demonstrated minimal bias associated with the MDA step and implicated Methylophaga-like phylotypes with the marine metabolism of methanol. Polymerase chain reaction screening of 1500 clones revealed a methanol dehydrogenase (MDH) containing insert and shotgun sequencing of this insert resulted in the assembly of a 9-kb fragment of DNA encoding a cluster of enzymes involved in MDH biosynthesis, regulation and assembly. This novel combination of methodology enables future structure-function studies of microbial communities to achieve the long-desired goal of identifying active microbial populations using in situ conditions and performing a directed metagenomic analysis for these ecologically relevant microorganisms
mockrobiota: a public resource for microbiome bioinformatics benchmarking
Full text linkMock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at https://github.com/caporaso-lab/mockrobiota. The materials contained in mockrobiota include dataset and sample metadata, expected composition data, which are annotated based on one or more reference taxonomies, links to raw data (e.g., raw sequence data) for each mock community dataset, and optional reference sequences for mock community members. mockrobiota does not supply physical sample materials directly, but the dataset metadata included for each mock community indicate whether physical sample materials are available (and associated contact information). At the time of this writing, mockrobiota contains 11 mock community datasets with known species compositions (including bacterial, archaeal, and eukaryotic mock communities), analyzed by high-throughput marker-gene sequencing. The availability of standard, public mock community data will facilitate ongoing methods optimizations; comparisons across studies that share source data; greater transparency and access; and eliminate redundancy. This dynamic resource is intended to expand and evolve to meet the changing needs of the ‘omics community.</jats:p
A Novel Sparse Compositional Technique Reveals Microbial Perturbations
Full text linkThe central aims of many host or environmental microbiome studies are to elucidate factors associated with microbial community compositions and to relate microbial features to outcomes. However, these aims are often complicated by difficulties stemming from high-dimensionality, non-normality, sparsity, and the compositional nature of microbiome data sets. A key tool in microbiome analysis is beta diversity, defined by the distances between microbial samples. Many different distance metrics have been proposed, all with varying discriminatory power on data with differing characteristics. Here, we propose a compositional beta diversity metric rooted in a centered log-ratio transformation and matrix completion called robust Aitchison PCA. We demonstrate the benefits of compositional transformations upstream of beta diversity calculations through simulations. Additionally, we demonstrate improved effect size, classification accuracy, and robustness to sequencing depth over the current methods on several decreased sample subsets of real microbiome data sets. Finally, we highlight the ability of this new beta diversity metric to retain the feature loadings linked to sample ordinations revealing salient intercommunity niche feature importance
Discrete False-Discovery Rate Improves Identification of Differentially Abundant Microbes
Full text linkDS-FDR can achieve higher statistical power to detect significant findings in sparse and noisy microbiome data compared to the commonly used Benjamini-Hochberg procedure and other FDR-controlling procedures.</jats:p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
DNA-, RNA-, and protein-based stable-isotope probing for high-throughput biomarker analysis of active microorganisms
No full textStable-isotope probing (SIP) enables researchers to target active populations within complex microbial communities, which is achieved by providing growth substrates enriched in heavy isotopes, usually in the form of 13C, 18O, or 15N. After growth on the substrate and subsequent extraction of microbial biomarkers, typically nucleic acids or proteins, the SIP technique is used for the recovery and analysis of isotope-labelled biomarkers from active microbial populations. In the years following the initial development of DNA- and RNA-based SIP, it was common practice to characterize labelled populations by targeted gene analysis. Such approaches usually involved fingerprint-based analyses or sequencing clone libraries containing 16S rRNA genes or functional marker gene amplicons. Although molecular fingerprinting remains a valuable approach for rapid confirmation of isotope labelling, recent advances in sequencing technology mean that it is possible to obtain affordable and comprehensive amplicon profiles, or even metagenomes and metatranscriptomes from SIP experiments. Not only can the abundance of microbial groups be inferred from metagenomes, but researchers can bin, assemble, and explore individual genomes to build hypotheses about the metabolic capabilities of labelled microorganisms. Analysis of labelled mRNA is a more recent advance that can provide independent metatranscriptome-based analysis of active microorganisms. The power of metatranscriptomics is that mRNA abundance often correlates closely with the corresponding activity of encoded enzymes, thus providing insight into microbial metabolism at the time of sampling. Together, these advances have improved the sensitivity of SIP methods and allowed using labelled substrates at environmentally relevant concentrations. Particularly as methods improve and costs continue to drop, we expect that the integration of SIP with multiple omics-based methods will become prevalent components of microbial ecology studies, leading to further breakthroughs in our understanding of novel microbial populations and elucidation of the metabolic function of complex microbial communities. In this chapter, we provide protocols for obtaining labelled DNA, RNA, and proteins that can be used for downstream omics-based analyses
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