Microbial Tree Research Articles

Microbial Diversity and Open Questions about the Deep Tree of Life.

In this perspective, we explore the transformative impact and inherent limitations of metagenomics and single-cell genomics on our understanding of microbial diversity and their integration into the Tree of Life. We delve into the key challenges associated with incorporating new microbial lineages into the Tree of Life through advanced phylogenomic approaches. Additionally, we shed light on enduring debates surrounding various aspects of the microbial Tree of Life, focusing on recent advances in some of its deepest nodes, such as the roots of bacteria, archaea, and eukaryotes. We also bring forth current limitations in genome recovery and phylogenomic methodology, as well as new avenues of research to uncover additional key microbial lineages and resolve the shape of the Tree of Life.

Ecological niches and assembly dynamics of diverse microbial consortia in the gastrointestine of goat kids.

Goats are globally invaluable ruminants that balance food security and environmental impacts, and their commensal microbiome residing in the gastrointestinal tract (GIT) is associated with animal health and productivity. However, the reference genomes and functional repertoires of GIT microbes in goat kids have not been fully elucidated. Herein, we performed a comprehensive landscape survey of the GIT microbiome of goat kids using metagenomic sequencing and binning, spanning a dense sampling regime covering three gastrointestinal compartments spatially and five developmental ages temporally. We recovered 1002 high-quality metagenome-assembled genomes (termed the goat kid GIT microbial catalog [GKGMC]), 618 of which were novel. They encode more than 2.3 million nonredundant proteins, and represent a variety of carbohydrate-degrading enzymes and metabolic gene clusters. The GKGMC-enriched microbial taxa, particularly Sodaliphilus, expanded the microbial tree of life in goat kids. Using this GKGMC, we first deciphered the prevalence of fiber-degrading bacteria for carbohydrate decomposition in the rumen and colon, while the ileal microbiota specialized in the uptake and conversion of simple sugars. Moreover, GIT microorganisms were rapidly assembled after birth, and their carbohydrate metabolic adaptation occurred in three phases of progression. Finally, phytobiotics modified the metabolic cascades of the ileal microbiome, underpinned by the enrichment of Sharpea azabuensis and Olsenella spp. implicated in lactate formation and utilization. This GKGMC reference provides novel insights into the early-life microbial developmental dynamics in distinct compartments, and offers expanded resources for GIT microbiota-related research in goat kids.

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.

Long-read metagenomics paves the way toward a complete microbial tree of life.

Long-read metagenomics paves the way toward a complete microbial tree of life.

The electrochemical microbial tree: A new concept for wastewater treatment

Most wastewater treatment plants involve activated sludge units, in which the organic matter to be removed is oxidised by aerobic microorganisms. These units are highly energy intensive because of the power consumed to force oxygen transfer to the wastewater by aeration. An innovative device is presented here; it is called the “electrochemical microbial tree (EMT)” and is based on the opposite strategy: the organic matter is drawn up from the wastewater towards the air phase by capillary action along a porous structure, which hosts the microorganisms that oxidise the organic matter.The EMTs were made of carbon felt, with the bottom immersed in wastewater (14 cm), while the top emerged into the air at different heights (4, 8 or 12 cm). COD removal increased linearly with the height of the aerial section. The greatest height led to COD removal rates of 807 ± 62 mg O2/L/h, i.e. 2.6 times those of the control experiments. During COD removal, the pH decreased from 7.6 to 7.4 ± 0.2 with EMTs, while it increased to 7.9 ± 0.1 in the controls. The biofilm on the immersed section developed as the height of the aerial section increased. Many electroactive species were identified in the microbial populations, belonging to the Bacteroidia, Gammaproteobacteria and Clostridia classes. These observations revealed that electron transfer along the conductive felt contributed to organic matter oxidation, in parallel with mass transfer by capillarity. These pioneering results present the EMT as a promising new wastewater treatment disposal system that does not require any energy input.

Deep learning of a bacterial and archaeal universal language of life enables transfer learning and illuminates microbial dark matter

The majority of microbial genomes have yet to be cultured, and most proteins identified in microbial genomes or environmental sequences cannot be functionally annotated. As a result, current computational approaches to describe microbial systems rely on incomplete reference databases that cannot adequately capture the functional diversity of the microbial tree of life, limiting our ability to model high-level features of biological sequences. Here we present LookingGlass, a deep learning model encoding contextually-aware, functionally and evolutionarily relevant representations of short DNA reads, that distinguishes reads of disparate function, homology, and environmental origin. We demonstrate the ability of LookingGlass to be fine-tuned via transfer learning to perform a range of diverse tasks: to identify novel oxidoreductases, to predict enzyme optimal temperature, and to recognize the reading frames of DNA sequence fragments. LookingGlass enables functionally relevant representations of otherwise unknown and unannotated sequences, shedding light on the microbial dark matter that dominates life on Earth.

Drivers of soil microbial community assembly during recovery from selective logging and clear‐cutting

Abstract Despite important progress in understanding the impacts of forest clearing and logging on above‐ground communities, how these disturbances affect soil microbial β‐diversity and the ecological processes driving microbial assemblages are poorly understood. Furthermore, whether and how the microbial shifts affect vegetation composition and diversity during recovery of post‐logged forests remain elusive. Using a spatial grid experiment design in a primary tropical forest intermixed with post‐logged patches naturally recovered for half century in Hainan Island, China, we characterized and explained the distance–decay relationships of soil microbial similarities in primary, selectively logged and clear‐cut forests. Selectively logged sites showed a lower spatial turnover rate of bacterial assemblages based on phylogenetic and taxonomic β‐diversity, but a higher spatial turnover rate of fungal assemblages based on phylogenetic β‐diversity, suggesting a higher level of phylogenetic variability in fungal composition. Clear‐cut sites showed lower spatial turnover for both bacterial and fungal assemblages based on the two β‐diversity, indicating community homogenization. Main drivers of microbial assemblages shifted from soil properties in primary forest to tree composition in selectively logged sites, whereas microbial–tree associations declined in clear‐cut sites, leading to stochastically organized microbial assemblages. Synthesis and applications. The increased fungal phylogenetic turnover with tree turnover following selective logging promotes unassisted recovery of plant diversity. In contrast, the decoupling of tree and microbial turnover following clear‐cutting suggests restoration approaches based on tree planting, and tree species that have strong associations with bulk soil microbial community should be considered. Our findings advance the understanding of spatial patterns, processes and drivers of soil microbial assemblages in parallel with tree community recovery during regeneration of post‐logged tropical forests, and highlight the importance of coupling assemblage patterns between tree and soil fungal communities for conserving tropical forest biodiversity.

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.

Metagenomic discovery and functional validation of L-asparaginases with anti-leukemic effect from the Caspian Sea.

SummaryBy screening 27,000 publicly available prokaryotic genomes, we recovered ca. 6300 type I and ca. 5200 type II putative L-asparaginase highlighting the vast potential of prokaryotes. Caspian water with similar salt composition to the human serum was targeted for in silico L-asparaginase screening. We screened ca. three million predicted genes of its assembled metagenomes that resulted in annotation of 87 putative L-asparaginase genes. The L-asparagine hydrolysis was experimentally confirmed by synthesizing and cloning three selected genes in E. coli. Catalytic parameters of the purified enzymes were determined to be among the most desirable reported values. Two recombinant enzymes represented remarkable anti-proliferative activity (IC50 <1IU/ml) against leukemia cell line Jurkat while no cytotoxic effect on human erythrocytes or human umbilical vein endothelial cells was detected. Similar salinity and ionic concentration of the Caspian water to the human serum highlights the potential of secretory L-asparaginases recovered from these metagenomes as potential treatment agents.

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.

An assessment of genome annotation coverage across the bacterial tree of life.

Although gene-finding in bacterial genomes is relatively straightforward, the automated assignment of gene function is still challenging, resulting in a vast quantity of hypothetical sequences of unknown function. But how prevalent are hypothetical sequences across bacteria, what proportion of genes in different bacterial genomes remain unannotated, and what factors affect annotation completeness? To address these questions, we surveyed over 27 000 bacterial genomes from the Genome Taxonomy Database, and measured genome annotation completeness as a function of annotation method, taxonomy, genome size, 'research bias' and publication date. Our analysis revealed that 52 and 79 % of the average bacterial proteome could be functionally annotated based on protein and domain-based homology searches, respectively. Annotation coverage using protein homology search varied significantly from as low as 14 % in some species to as high as 98 % in others. We found that taxonomy is a major factor influencing annotation completeness, with distinct trends observed across the microbial tree (e.g. the lowest level of completeness was found in the Patescibacteria lineage). Most lineages showed a significant association between genome size and annotation incompleteness, likely reflecting a greater degree of uncharacterized sequences in 'accessory' proteomes than in 'core' proteomes. Finally, research bias, as measured by publication volume, was also an important factor influencing genome annotation completeness, with early model organisms showing high completeness levels relative to other genomes in their own taxonomic lineages. Our work highlights the disparity in annotation coverage across the bacterial tree of life and emphasizes a need for more experimental characterization of accessory proteomes as well as understudied lineages.

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.

Targeted isolation and cultivation of uncultivated bacteria by reverse genomics.

Most microorganisms from all taxonomic levels are uncultured. Single-cell genomes and metagenomes continue to increase the known diversity of Bacteria and Archaea, but while ‘omics can be used to infer physiological or ecological roles for species in a community, most of those hypothetical roles remain unvalidated. Here we report an approach to capture specific microorganisms from complex communities into pure cultures using genome-informed antibody engineering. We apply our reverse genomics approach to isolate and sequence single cells and to cultivate three different species-level lineages of human oral Saccharibacteria/TM7. Using our pure cultures we show that all three saccharibacteria species are epibionts of diverse Actinobacteria. We also isolate and cultivate human oral SR1 bacteria, which are members of a lineage of previously uncultured bacteria. Reverse-genomics-enabled cultivation of microorganisms can be applied to any species from any environment and has the potential to unlock the isolation, cultivation and characterization of species from as-yet-uncultured branches of the microbial tree of life.

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.

AnnoTree: visualization and exploration of a functionally annotated microbial tree of life.

Bacterial genomics has revolutionized our understanding of the microbial tree of life; however, mapping and visualizing the distribution of functional traits across bacteria remains a challenge. Here, we introduce AnnoTree—an interactive, functionally annotated bacterial tree of life that integrates taxonomic, phylogenetic and functional annotation data from over 27 000 bacterial and 1500 archaeal genomes. AnnoTree enables visualization of millions of precomputed genome annotations across the bacterial and archaeal phylogenies, thereby allowing users to explore gene distributions as well as patterns of gene gain and loss in prokaryotes. Using AnnoTree, we examined the phylogenomic distributions of 28 311 gene/protein families, and measured their phylogenetic conservation, patchiness, and lineage-specificity within bacteria. Our analyses revealed widespread phylogenetic patchiness among bacterial gene families, reflecting the dynamic evolution of prokaryotic genomes. Genes involved in phage infection/defense, mobile elements, and antibiotic resistance dominated the list of most patchy traits, as well as numerous intriguing metabolic enzymes that appear to have undergone frequent horizontal transfer. We anticipate that AnnoTree will be a valuable resource for exploring prokaryotic gene histories, and will act as a catalyst for biological and evolutionary hypothesis generation. AnnoTree is freely available at http://annotree.uwaterloo.ca

Uncovering the Uncultivated Majority in Antarctic Soils: Toward a Synergistic Approach.

Although Antarctica was once believed to be a sterile environment, it is now clear that the microbial communities inhabiting the Antarctic continent are surprisingly diverse. Until the beginning of the new millennium, little was known about the most abundant inhabitants of the continent: prokaryotes. From then on, however, the rising use of deep sequencing techniques has led to a better understanding of the Antarctic prokaryote diversity and provided insights in the composition of prokaryotic communities in different Antarctic environments. Although these cultivation-independent approaches can produce millions of sequences, linking these data to organisms is hindered by several problems. The largest difficulty is the lack of biological information on large parts of the microbial tree of life, arising from the fact that most microbial diversity on Earth has never been characterized in laboratory cultures. These unknown prokaryotes, also known as microbial dark matter, have been dominantly detected in all major environments on our planet. Laboratory cultures provide access to the complete genome and the means to experimentally verify genomic predictions and metabolic functions and to provide evidence of horizontal gene transfer. Without such well-documented reference data, microbial dark matter will remain a major blind spot in deep sequencing studies. Here, we review our current understanding of prokaryotic communities in Antarctic ice-free soils based on cultivation-dependent and cultivation-independent approaches. We discuss advantages and disadvantages of both approaches and how these strategies may be combined synergistically to strengthen each other and allow a more profound understanding of prokaryotic life on the frozen continent.

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.