Microbial Tree Of Life Research Articles

Sparsification of large ultrametric matrices: insights into the microbial Tree of Life

Ultrametric matrices appear in many domains of mathematics and science; nevertheless, they can be large and dense, making them difficult to store and manipulate, unlike large but sparse matrices. In this manuscript, we exploit that ultrametric matrices can be represented as binary trees to sparsify them via an orthonormal base change based on Haar-like wavelets. We show that, with overwhelmingly high probability, only an asymptotically negligible fraction of the off-diagonal entries in random but large ultrametric matrices remain non-zero after the base change; and develop an algorithm to sparsify such matrices directly from their tree representation. We also identify the subclass of matrices diagonalized by the Haar-like wavelets and supply a sufficient condition to approximate the spectrum of ultrametric matrices outside this subclass. Our methods give computational access to a covariance matrix model of the microbiologists’ Tree of Life, which was previously inaccessible due to its size, and motivate introducing a new wavelet-based (beta-diversity) metric to compare microbial environments. Unlike the established metrics, the new metric may be used to identify internal nodes (i.e. splits) in the Tree that link microbial composition and environmental factors in a statistically significant manner.

Machine learning improves genome quality prediction across the microbial tree of life.

Machine learning improves genome quality prediction across the microbial tree of life.

Sequence-structure-function relationships in the microbial protein universe

For the past half-century, structural biologists relied on the notion that similar protein sequences give rise to similar structures and functions. While this assumption has driven research to explore certain parts of the protein universe, it disregards spaces that don’t rely on this assumption. Here we explore areas of the protein universe where similar protein functions can be achieved by different sequences and different structures. We predict ~200,000 structures for diverse protein sequences from 1,003 representative genomes across the microbial tree of life and annotate them functionally on a per-residue basis. Structure prediction is accomplished using the World Community Grid, a large-scale citizen science initiative. The resulting database of structural models is complementary to the AlphaFold database, with regards to domains of life as well as sequence diversity and sequence length. We identify 148 novel folds and describe examples where we map specific functions to structural motifs. We also show that the structural space is continuous and largely saturated, highlighting the need for a shift in focus across all branches of biology, from obtaining structures to putting them into context and from sequence-based to sequence-structure-function based meta-omics analyses.

Molecular Evolutionary Dynamics of Energy Limited Microorganisms.

Microorganisms have the unique ability to survive extended periods of time in environments with extremely low levels of exploitable energy. To determine the extent that energy limitation affects microbial evolution, we examined the molecular evolutionary dynamics of a phylogenetically diverse set of taxa over the course of 1,000 days. We found that periodic exposure to energy limitation affected the rate of molecular evolution, the accumulation of genetic diversity, and the rate of extinction. We then determined the degree that energy limitation affected the spectrum of mutations as well as the direction of evolution at the gene level. Our results suggest that the initial depletion of energy altered the direction and rate of molecular evolution within each taxon, though after the initial depletion the rate and direction did not substantially change. However, this consistent pattern became diminished when comparisons were performed across phylogenetically distant taxa, suggesting that although the dynamics of molecular evolution under energy limitation are highly generalizable across the microbial tree of life, the targets of adaptation are specific to a given taxon.

Characterization of Metagenome-Assembled Genomes and Carbohydrate-Degrading Genes in the Gut Microbiota of Tibetan Pig.

Tibetan pig is an important domestic mammal, providing products of high nutritional value for millions of people living in the Qinghai-Tibet Plateau. The genomes of mammalian gut microbiota encode a large number of carbohydrate-active enzymes, which are essential for the digestion of complex polysaccharides through fermentation. However, the current understanding of microbial degradation of dietary carbohydrates in the Tibetan pig gut is limited. In this study, we produced approximately 145 gigabases of metagenomic sequence data for the fecal samples from 11 Tibetan pigs. De novo assembly and binning recovered 322 metagenome-assembled genomes taxonomically assigned to 11 bacterial phyla and two archaeal phyla. Of these genomes, 191 represented the uncultivated microbes derived from novel prokaryotic taxa. Twenty-three genomes were identified as metagenomic biomarkers that were significantly abundant in the gut ecosystem of Tibetan pigs compared to the other low-altitude relatives. Further, over 13,000 carbohydrate-degrading genes were identified, and these genes were more abundant in some of the genomes within the five principal phyla: Firmicutes, Bacteroidetes, Spirochaetota, Verrucomicrobiota, and Fibrobacterota. Particularly, three genomes representing the uncultivated Verrucomicrobiota encode the most abundant degradative enzymes in the fecal microbiota of Tibetan pigs. These findings should substantially increase the phylogenetic diversity of specific taxonomic clades in the microbial tree of life and provide an expanded repertoire of biomass-degrading genes for future application to microbial production of industrial enzymes.

Standardized phylogenetic and molecular evolutionary analysis applied to species across the microbial tree of life

There is growing interest in reconstructing phylogenies from the copious amounts of genome sequencing projects that target related viral, bacterial or eukaryotic organisms. To facilitate the construction of standardized and robust phylogenies for disparate types of projects, we have developed a complete bioinformatic workflow, with a web-based component to perform phylogenetic and molecular evolutionary (PhaME) analysis from sequencing reads, draft assemblies or completed genomes of closely related organisms. Furthermore, the ability to incorporate raw data, including some metagenomic samples containing a target organism (e.g. from clinical samples with suspected infectious agents), shows promise for the rapid phylogenetic characterization of organisms within complex samples without the need for prior assembly.

Erratum for Royalty and Steen, "Quantitatively Partitioning Microbial Genomic Traits among Taxonomic Ranks across the Microbial Tree of Life".

Volume 4, no. 4, e00446-19, 2019, [https://doi.org/10.1128/mSphere.00446-19][1]. The original Table S2 file in the supplemental material contained unstandardized data and has now been replaced with a version that contains standardized data, as described in Materials and Methods. [1]: /lookup/doi/

Quantitatively Partitioning Microbial Genomic Traits among Taxonomic Ranks across the Microbial Tree of Life.

Widely used microbial taxonomies, such as the NCBI taxonomy, are based on a combination of sequence homology among conserved genes and historically accepted taxonomies, which were developed based on observable traits such as morphology and physiology. A recently proposed alternative taxonomy database, the Genome Taxonomy Database (GTDB), incorporates only sequence homology of conserved genes and attempts to partition taxonomic ranks such that each rank implies the same amount of evolutionary distance, regardless of its position on the phylogenetic tree. This provides the first opportunity to completely separate taxonomy from traits and therefore to quantify how taxonomic rank corresponds to traits across the microbial tree of life. We quantified the relative abundances of clusters of orthologous group functional categories (COG-FCs) as a proxy for traits within the lineages of 13,735 cultured and uncultured microbial lineages from a custom-curated genome database. On average, 41.4% of the variation in COG-FC relative abundance is explained by taxonomic rank, with domain, phylum, class, order, family, and genus explaining, on average, 3.2%, 14.6%, 4.1%, 9.2%, 4.8%, and 5.5% of the variance, respectively (P < 0.001 for all). To our knowledge, this is the first work to quantify the variance in metabolic potential contributed by individual taxonomic ranks. A qualitative comparison between the COG-FC relative abundances and genus-level phylogenies, generated from published concatenated protein sequence alignments, further supports the idea that metabolic potential is taxonomically coherent at higher taxonomic ranks. The quantitative analyses presented here characterize the integral relationship between diversification of microbial lineages and the metabolisms which they host.IMPORTANCE Recently, there has been great progress in defining a complete taxonomy of bacteria and archaea, which has been enabled by improvements in DNA sequencing technology and new bioinformatic techniques. A new, algorithmically defined microbial tree of life describes those linkages, relying solely on genetic data, which raises the issue of how microbial traits relate to taxonomy. Here, we adopted cluster of orthologous group functional categories as a scheme to describe the genomic contents of microbes, a method that can be applied to any microbial lineage for which genomes are available. This simple approach allows quantitative comparisons between microbial genomes with different gene compositions from across the microbial tree of life. Our observations demonstrate statistically significant patterns in cluster of orthologous group functional categories at taxonomic levels that span the range from domain to genus.

Genomic and metagenomic insights into the microbial community of a thermal spring

BackgroundWater springs provide important ecosystem services including drinking water supply, recreation, and balneotherapy, but their microbial communities remain largely unknown. In this study, we characterized the spring water microbiome of Comano Terme (Italy) at four sampling points of the thermal spa, including natural (spring and well) and human-built (storage tank, bathtubs) environments. We integrated large-scale culturing and metagenomic approaches, with the aim of comprehensively determining the spring water taxonomic composition and functional potential.ResultsThe groundwater feeding the spring hosted the most atypical microbiome, including many taxa known to be recalcitrant to cultivation. The core microbiome included the orders Sphingomonadales, Rhizobiales, and Caulobacterales, and the families Bradyrhizobiaceae and Moraxellaceae. A comparative genomic analysis of 72 isolates and 30 metagenome-assembled genomes (MAGs) revealed that most isolates and MAGs belonged to new species or higher taxonomic ranks widely distributed in the microbial tree of life. Average nucleotide identity (ANI) values calculated for each isolated or assembled genome showed that 10 genomes belonged to known bacterial species (> 95% ANI), 36 genomes (including 1 MAG) had ANI values ranging 85–92.5% and could be assigned as undescribed species belonging to known genera, while the remaining 55 genomes had lower ANI values (< 85%). A number of functional features were significantly over- or underrepresented in genomes derived from the four sampling sites. Functional specialization was found between sites, with for example methanogenesis being unique to groundwater whereas methanotrophy was found in all samples.ConclusionsCurrent knowledge on aquatic microbiomes is essentially based on surface or human-associated environments. We started uncovering the spring water microbiome, highlighting an unexpected diversity that should be further investigated. This study confirms that groundwater environments host highly adapted, stable microbial communities composed of many unknown taxa, even among the culturable fraction.

Modeling central metabolism and energy biosynthesis across microbial life

BackgroundAutomatically generated bacterial metabolic models, and even some curated models, lack accuracy in predicting energy yields due to poor representation of key pathways in energy biosynthesis and the electron transport chain (ETC). Further compounding the problem, complex interlinking pathways in genome-scale metabolic models, and the need for extensive gapfilling to support complex biomass reactions, often results in predicting unrealistic yields or unrealistic physiological flux profiles.ResultsTo overcome this challenge, we developed methods and tools (http://coremodels.mcs.anl.gov) to build high quality core metabolic models (CMM) representing accurate energy biosynthesis based on a well studied, phylogenetically diverse set of model organisms. We compare these models to explore the variability of core pathways across all microbial life, and by analyzing the ability of our core models to synthesize ATP and essential biomass precursors, we evaluate the extent to which the core metabolic pathways and functional ETCs are known for all microbes. 6,600 (80 %) of our models were found to have some type of aerobic ETC, whereas 5,100 (62 %) have an anaerobic ETC, and 1,279 (15 %) do not have any ETC. Using our manually curated ETC and energy biosynthesis pathways with no gapfilling at all, we predict accurate ATP yields for nearly 5586 (70 %) of the models under aerobic and anaerobic growth conditions. This study revealed gaps in our knowledge of the central pathways that result in 2,495 (30 %) CMMs being unable to produce ATP under any of the tested conditions. We then established a methodology for the systematic identification and correction of inconsistent annotations using core metabolic models coupled with phylogenetic analysis.ConclusionsWe predict accurate energy yields based on our improved annotations in energy biosynthesis pathways and the implementation of diverse ETC reactions across the microbial tree of life. We highlighted missing annotations that were essential to energy biosynthesis in our models. We examine the diversity of these pathways across all microbial life and enable the scientific community to explore the analyses generated from this large-scale analysis of over 8000 microbial genomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2887-8) contains supplementary material, which is available to authorized users.

Comparative transcriptomics across the prokaryotic tree of life

Whole-transcriptome sequencing studies from recent years revealed an unexpected complexity in transcriptomes of bacteria and archaea, including abundant non-coding RNAs, cis-antisense transcription and regulatory untranslated regions (UTRs). Understanding the functional relevance of the plethora of non-coding RNAs in a given organism is challenging, especially since some of these RNAs were attributed to ‘transcriptional noise’. To allow the search for conserved transcriptomic elements we produced comparative transcriptome maps for multiple species across the microbial tree of life. These transcriptome maps are detailed in annotations, comparable by gene families, and BLAST-searchable by user provided sequences. Our transcriptome collection includes 18 model organisms spanning 10 phyla/subphyla of bacteria and archaea that were sequenced using standardized RNA-seq methods. The utility of the comparative approach, as implemented in our web server, is demonstrated by highlighting genes with exceptionally long 5′UTRs across species, which correspond to many known riboswitches and further suggest novel putative regulatory elements. Our study provides a standardized reference transcriptome to major clinically and environmentally important microbial phyla. The viewer is available at http://exploration.weizmann.ac.il/TCOL, setting a framework for comparative studies of the microbial non-coding genome.

Microbiomes in light of traits: A phylogenetic perspective

A focus on the phenotypic characteristics of microorganisms-their traits-offers a path for interpreting the growing amount of microbiome data. We review key aspects of microbial traits, as well as approaches used to assay their phylogenetic distribution. Recent studies reveal that microbial traits are differentially conserved across the tree of life and appear to be conserved in a hierarchical fashion, possibly linked to their biochemical complexity. These results suggest a predictive framework whereby the genetic (or taxonomic) resolution of microbiome variation among samples provides information about the traits under selection. The organizational parallels seen among human and free-living microbiomes seem to support this idea. Developments in this framework may offer predictions not only for how microbial composition responds to changing environmental conditions, but also for how these changes may alter the health or functioning in human, engineered, and environmental systems.

Function in the tree of life

Microbiome How does the composition of microbial communities integrate functionally with the wider environment? Martiny et al. review how patterns of microbial species abundances in different environments and disease states can have strong evolutionary signals. Some environmental changes select the survival of organisms with conserved metabolisms requiring complex configurations of proteins and cofactors that have long evolutionary histories, such as methane producers. In contrast, surviving antibiotic exposure may only require a single gene that can be traded promiscuously among many unrelated organisms. So, depending on the key ingredient (whether it is temperature, light, nutrient, or a dose of antibiotic) and the evolutionary history of its complementary metabolism, shifting environmental conditions will have predictable effects at different levels within the microbial tree of life. Science , this issue p. [10.1126/science.aac9323][1] [1]: /lookup/doi/10.1126/science.aac9323

A comparison of the sorption reactivity of bacteriogenic and mycogenic Mn oxide nanoparticles.

Biogenic MnO2 minerals affect metal fate and transport in natural and engineered systems by strongly sorbing metals ions. The ability to produce MnO2 is widely dispersed in the microbial tree of life, leading to potential differences in the minerals produced by different organisms. In this study, we compare the structure and reactivity of biogenic Mn oxides produced by the biofilm-forming bacterium Pseudomonas putida GB-1 and the white-rot fungus Coprinellus sp. The rate of Mn(II) oxidation, and thus biomineral production, was 45 times lower for Coprinellus sp. (5.1 × 10(-2) mM d(-1)) than for P. putida (2.32 mM d(-1)). Both organisms produced predominantly Mn(IV) oxides with hexagonal-sheet symmetry, low sheet stacking, small particle size, and Mn(II/III) in the interlayer. However, we found that mycogenic MnO2 could support a significantly lower quantity of Ni sorbed via inner-sphere coordination at vacancy sites than the bacteriogenic MnO2: 0.09 versus 0.14 mol Ni mol(-1) Mn. In addition, 50-100% of the adsorbed Ni partitioned to the MnO2, which accounts for less than 20% of the sorbent on a mass basis. The vacancy content, which appears to increase with the kinetics of MnO2 precipitation, exerts significant control on biomineral reactivity.

RrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development.

Microbiologists utilize ribosomal RNA genes as molecular markers of taxonomy in surveys of microbial communities. rRNA genes are often co-located as part of an rrn operon, and multiple copies of this operon are present in genomes across the microbial tree of life. rrn copy number variability provides valuable insight into microbial life history, but introduces systematic bias when measuring community composition in molecular surveys. Here we present an update to the ribosomal RNA operon copy number database (rrnDB), a publicly available, curated resource for copy number information for bacteria and archaea. The redesigned rrnDB (http://rrndb.umms.med.umich.edu/) brings a substantial increase in the number of genomes described, improved curation, mapping of genomes to both NCBI and RDP taxonomies, and refined tools for querying and analyzing these data. With these changes, the rrnDB is better positioned to remain a comprehensive resource under the torrent of microbial genome sequencing. The enhanced rrnDB will contribute to the analysis of molecular surveys and to research linking genomic characteristics to life history.