Recapitulating phylogenies using k-mers: from trees to networks

Annotation-free prediction of microbial dioxygen utilization

Aerobes require dioxygen (O2) to grow; anaerobes do not. However, nearly all microbes-aerobes, anaerobes, and facultative organisms alike-express enzymes whose substrates include O2, if only for detoxification. This presents a challenge when trying to assess which organisms are aerobic from genomic data alone. This challenge can be overcome by noting that O2 utilization has wide-ranging effects on microbes: aerobes typically have larger genomes encoding distinctive O2-utilizing enzymes, for example. These effects permit high-quality prediction of O2 utilization from annotated genome sequences, with several models displaying ≈80% accuracy on a ternary classification task for which blind guessing is only 33% accurate. Since genome annotation is compute-intensive and relies on many assumptions, we asked if annotation-free methods also perform well. We discovered that simple and efficient models based entirely on genomic sequence content-e.g., triplets of amino acids-perform as well as intensive annotation-based classifiers, enabling rapid processing of genomes. We further show that amino acid trimers are useful because they encode information about protein composition and phylogeny. To showcase the utility of rapid prediction, we estimated the prevalence of aerobes and anaerobes in diverse natural environments cataloged in the Earth Microbiome Project. Focusing on a well-studied O2 gradient in the Black Sea, we found quantitative correspondence between local chemistry (O2:sulfide concentration ratio) and the composition of microbial communities. We, therefore, suggest that statistical methods like ours might be used to estimate, or "sense," pivotal features of the chemical environment using DNA sequencing data.IMPORTANCEWe now have access to sequence data from a wide variety of natural environments. These data document a bewildering diversity of microbes, many known only from their genomes. Physiology-an organism's capacity to engage metabolically with its environment-may provide a more useful lens than taxonomy for understanding microbial communities. As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. Annotation-free algorithms enable rapid characterization of natural samples, highlighting quantitative correspondence between sequences and local O2 levels in a data set from the Black Sea. This example suggests that DNA sequencing might be repurposed as a multi-pronged chemical sensor, estimating concentrations of O2 and other key facets of complex natural settings.

Alignment-Free Analysis of Whole-Genome Sequences From Symbiodiniaceae Reveals Different Phylogenetic Signals in Distinct Regions

Dinoflagellates of the family Symbiodiniaceae are predominantly essential symbionts of corals and other marine organisms. Recent research reveals extensive genome sequence divergence among Symbiodiniaceae taxa and high phylogenetic diversity hidden behind subtly different cell morphologies. Using an alignment-free phylogenetic approach based on sub-sequences of fixed length k (i.e. k-mers), we assessed the phylogenetic signal among whole-genome sequences from 16 Symbiodiniaceae taxa (including the genera of Symbiodinium, Breviolum, Cladocopium, Durusdinium and Fugacium) and two strains of Polarella glacialis as outgroup. Based on phylogenetic trees inferred from k-mers in distinct genomic regions (i.e. repeat-masked genome sequences, protein-coding sequences, introns and repeats) and in protein sequences, the phylogenetic signal associated with protein-coding DNA and the encoded amino acids is largely consistent with the Symbiodiniaceae phylogeny based on established markers, such as large subunit rRNA. The other genome sequences (introns and repeats) exhibit distinct phylogenetic signals, supporting the expected differential evolutionary pressure acting on these regions. Our analysis of conserved core k-mers revealed the prevalence of conserved k-mers (>95% core 23-mers among all 18 genomes) in annotated repeats and non-genic regions of the genomes. We observed 180 distinct repeat types that are significantly enriched in genomes of the symbiotic versus free-living Symbiodinium taxa, suggesting an enhanced activity of transposable elements linked to the symbiotic lifestyle. We provide evidence that representation of alignment-free phylogenies as dynamic networks enhances the ability to generate new hypotheses about genome evolution in Symbiodiniaceae. These results demonstrate the potential of alignment-free phylogenetic methods as a scalable approach for inferring comprehensive, unbiased whole-genome phylogenies of dinoflagellates and more broadly of microbial eukaryotes.

Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming

Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs) and spread to humans. Here, we performed a longitudinal study in a large-scale commercial poultry farm in China, collecting E. coli isolates from both farm and slaughterhouse; targeting animals, carcasses, workers and their households and environment. By using whole-genome phylogenetic analysis and network analysis based on single nucleotide polymorphisms (SNPs), we found highly interrelated non-pathogenic and pathogenic E. coli strains with phylogenetic intermixing, and a high prevalence of shared multidrug resistance profiles amongst livestock, human and environment. Through an original data processing pipeline which combines omics, machine learning, gene sharing network and mobile genetic elements analysis, we investigated the resistance to 26 different antimicrobials and identified 361 genes associated to antimicrobial resistance (AMR) phenotypes; 58 of these were known AMR-associated genes and 35 were associated to multidrug resistance. We uncovered an extensive network of genes, correlated to AMR phenotypes, shared among livestock, humans, farm and slaughterhouse environments. We also found several human, livestock and environmental isolates sharing closely related mobile genetic elements carrying ARGs across host species and environments. In a scenario where no consensus exists on how antibiotic use in the livestock may affect antibiotic resistance in the human population, our findings provide novel insights into the broader epidemiology of antimicrobial resistance in livestock farming. Moreover, our original data analysis method has the potential to uncover AMR transmission pathways when applied to the study of other pathogens active in other anthropogenic environments characterised by complex interconnections between host species.

Livestock have been suggested as an important source of antimicrobial-resistant (AMR) Escherichia coli, capable of infecting humans and carrying resistance to drugs used in human medicine. China has a large intensive livestock farming industry, poultry being the second most important source of meat in the country, and is the largest user of antibiotics for food production in the world. Here we studied antimicrobial resistance gene overlap between E. coli isolates collected from humans, livestock and their shared environments in a large-scale Chinese poultry farm and associated slaughterhouse. By using a computational approach that integrates machine learning, whole-genome sequencing, gene sharing network and mobile genetic elements analysis we characterized the E. coli community structure, antimicrobial resistance phenotypes and the genetic relatedness of non-pathogenic and pathogenic E. coli strains. We uncovered the network of genes, associated with AMR, shared across host species (animals and workers) and environments (farm and slaughterhouse). Our approach opens up new avenues for the development of a fast, affordable and effective computational solutions that provide novel insights into the broader epidemiology of antimicrobial resistance in livestock farming.

Large-scale k-mer-based analysis of the informational properties of genomes, comparative genomics and taxonomy

Information theoretic approaches are ubiquitous and effective in a wide variety of bioinformatics applications. In comparative genomics, alignment-free methods, based on short DNA words, or k-mers, are particularly powerful. We evaluated the utility of varying k-mer lengths for genome comparisons by analyzing their sequence space coverage of 5805 genomes in the KEGG GENOME database. In subsequent analyses on four k-mer lengths spanning the relevant range (11, 21, 31, 41), hierarchical clustering of 1634 genus-level representative genomes using pairwise 21- and 31-mer Jaccard similarities best recapitulated a phylogenetic/taxonomic tree of life with clear boundaries for superkingdom domains and high subtree similarity for named taxons at lower levels (family through phylum). By analyzing ~14.2M prokaryotic genome comparisons by their lowest-common-ancestor taxon levels, we detected many potential misclassification errors in a curated database, further demonstrating the need for wide-scale adoption of quantitative taxonomic classifications based on whole-genome similarity.

Comparison of 15 dinoflagellate genomes reveals extensive sequence and structural divergence in family Symbiodiniaceae and genus Symbiodinium

Background

Dinoflagellates in the family Symbiodiniaceae are important photosynthetic symbionts in cnidarians (such as corals) and other coral reef organisms. Breakdown of the coral-dinoflagellate symbiosis due to environmental stress (i.e. coral bleaching) can lead to coral death and the potential collapse of reef ecosystems. However, evolution of Symbiodiniaceae genomes, and its implications for the coral, is little understood. Genome sequences of Symbiodiniaceae remain scarce due in part to their large genome sizes (1–5 Gbp) and idiosyncratic genome features.

Results

Here, we present de novo genome assemblies of seven members of the genus Symbiodinium, of which two are free-living, one is an opportunistic symbiont, and the remainder are mutualistic symbionts. Integrating other available data, we compare 15 dinoflagellate genomes revealing high sequence and structural divergence. Divergence among some Symbiodinium isolates is comparable to that among distinct genera of Symbiodiniaceae. We also recovered hundreds of gene families specific to each lineage, many of which encode unknown functions. An in-depth comparison between the genomes of the symbiotic Symbiodinium tridacnidorum (isolated from a coral) and the free-living Symbiodinium natans reveals a greater prevalence of transposable elements, genetic duplication, structural rearrangements, and pseudogenisation in the symbiotic species.

Conclusions

Our results underscore the potential impact of lifestyle on lineage-specific gene-function innovation, genome divergence, and the diversification of Symbiodinium and Symbiodiniaceae. The divergent features we report, and their putative causes, may also apply to other microbial eukaryotes that have undergone symbiotic phases in their evolutionary history.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-00994-6.

The past, present and future of the tree of life

The advent of comparative genomics in the late 1990s led to the discovery of extensive lateral gene transfer in prokaryotes. The resulting debate over whether life as a whole is best represented as a tree or a network has since given way to a general consensus in which trees and networks co-exist rather than stand in opposition. Embracing this consensus allows us to move beyond the question of which is true or false. The future of the tree of life debate lies in asking what trees and networks can, and should, do for science.

Exploring short k-mer profiles in cells and mobile elements from Archaea highlights the major influence of both the ecological niche and evolutionary history

BACKGROUND

K-mer-based methods have greatly advanced in recent years, largely driven by the realization of their biological significance and by the advent of next-generation sequencing. Their speed and their independence from the annotation process are major advantages. Their utility in the study of the mobilome has recently emerged and they seem a priori adapted to the patchy gene distribution and the lack of universal marker genes of viruses and plasmids. To provide a framework for the interpretation of results from k-mer based methods applied to archaea or their mobilome, we analyzed the 5-mer DNA profiles of close to 600 archaeal cells, viruses and plasmids. Archaea is one of the three domains of life. Archaea seem enriched in extremophiles and are associated with a high diversity of viral and plasmid families, many of which are specific to this domain. We explored the dataset structure by multivariate and statistical analyses, seeking to identify the underlying factors.

RESULTS

For cells, the 5-mer profiles were inconsistent with the phylogeny of archaea. At a finer taxonomic level, the influence of the taxonomy and the environmental constraints on 5-mer profiles was very strong. These two factors were interdependent to a significant extent, and the respective weights of their contributions varied according to the clade. A convergent adaptation was observed for the class Halobacteria, for which a strong 5-mer signature was identified. For mobile elements, coevolution with the host had a clear influence on their 5-mer profile. This enabled us to identify one previously known and one new case of recent host transfer based on the atypical composition of the mobile elements involved. Beyond the effect of coevolution, extrachromosomal elements strikingly retain the specific imprint of their own viral or plasmid taxonomic family in their 5-mer profile.

CONCLUSION

This specific imprint confirms that the evolution of extrachromosomal elements is driven by multiple parameters and is not restricted to host adaptation. In addition, we detected only recent host transfer events, suggesting the fast evolution of short k-mer profiles. This calls for caution when using k-mers for host prediction, metagenomic binning or phylogenetic reconstruction.

Inferring Phylogenomic Relationship of Microbes Using Scalable Alignment-Free Methods

Inferring phylogenetic relationships among hundreds or thousands of microbial genomes is an increasingly common task. The conventional phylogenetic approach adopts multiple sequence alignment to compare gene-by-gene, concatenated multigene or whole-genome sequences, from which a phylogenetic tree would be inferred. These alignments follow the implicit assumption of full-length contiguity among homologous sequences. However, common events in microbial genome evolution (e.g., structural rearrangements and genetic recombination) violate this assumption. Moreover, aligning hundreds or thousands of sequences is computationally intensive and not scalable to the rate at which genome data are generated. Therefore, alignment-free methods present an attractive alternative strategy. Here we describe a scalable alignment-free strategy to infer phylogenetic relationships using complete genome sequences of bacteria and archaea, based on short, subsequences of length k (k-mers). We describe how this strategy can be extended to infer evolutionary relationships beyond a tree-like structure, to better capture both vertical and lateral signals of microbial evolution.

Mapping of cis-acting expression quantitative trait loci in human scalp hair follicles

BACKGROUND

The association of molecular phenotypes, such as gene transcript levels, with human common genetic variation can help to improve our understanding of interindividual variability of tissue-specific gene regulation and its implications for disease.

METHODS

With the aim to capture the spectrum of biological processes affected by regulatory common genetic variants (minor allele frequency ≥ 1%) in healthy hair follicles (HFs) from scalp tissue, we performed a genome-wide mapping of cis-acting expression quantitative trait loci (eQTLs) in plucked HFs, and applied these eQTLs to help further explain genomic findings for hair-related traits.

RESULTS

We report 374 high-confidence eQTLs found in occipital scalp tissue, whose associated genes (eGenes) showed enrichments for metabolic, mitotic and immune processes, as well as responses to steroid hormones. We were able to replicate 68 of these associations in a smaller, independent dataset, in either frontal and/or occipital scalp tissue. Furthermore, we found three genomic regions overlapping reported genetic loci for hair shape and hair color. We found evidence to confirm the contributions of PADI3 to human variation in hair traits and suggest a novel potential candidate gene within known loci for androgenetic alopecia.

CONCLUSIONS

Our study shows that an array of basic cellular functions relevant for hair growth are genetically regulated within the HF, and can be applied to aid the interpretation of interindividual variability on hair traits, as well as genetic findings for common hair disorders.

Alignment-free inference of hierarchical and reticulate phylogenomic relationships

We are amidst an ongoing flood of sequence data arising from the application of high-throughput technologies, and a concomitant fundamental revision in our understanding of how genomes evolve individually and within the biosphere. Workflows for phylogenomic inference must accommodate data that are not only much larger than before, but often more error prone and perhaps misassembled, or not assembled in the first place. Moreover, genomes of microbes, viruses and plasmids evolve not only by tree-like descent with modification but also by incorporating stretches of exogenous DNA. Thus, next-generation phylogenomics must address computational scalability while rethinking the nature of orthogroups, the alignment of multiple sequences and the inference and comparison of trees. New phylogenomic workflows have begun to take shape based on so-called alignment-free (AF) approaches. Here, we review the conceptual foundations of AF phylogenetics for the hierarchical (vertical) and reticulate (lateral) components of genome evolution, focusing on methods based on k-mers. We reflect on what seems to be successful, and on where further development is needed.

Benchmarking of alignment-free sequence comparison methods

BACKGROUND

Alignment-free (AF) sequence comparison is attracting persistent interest driven by data-intensive applications. Hence, many AF procedures have been proposed in recent years, but a lack of a clearly defined benchmarking consensus hampers their performance assessment.

RESULTS

Here, we present a community resource (http://afproject.org) to establish standards for comparing alignment-free approaches across different areas of sequence-based research. We characterize 74 AF methods available in 24 software tools for five research applications, namely, protein sequence classification, gene tree inference, regulatory element detection, genome-based phylogenetic inference, and reconstruction of species trees under horizontal gene transfer and recombination events.

CONCLUSION

The interactive web service allows researchers to explore the performance of alignment-free tools relevant to their data types and analytical goals. It also allows method developers to assess their own algorithms and compare them with current state-of-the-art tools, accelerating the development of new, more accurate AF solutions.

Laser-assisted Hair Regrowth: Fractional Laser Modalities for the Treatment of Androgenic Alopecia

Background:

A large proportion of the population is at sometime affected by androgenic alopecia. Current therapies consisting of minoxidil or finasteride are often the first choices for treatment. These regimens are limited by their efficacy, side-effect profiles, and often lengthy treatment courses. Low level laser/light has shown to be relatively effective and safe for the treatment of hair loss, and a number of products are currently available to consumers. Recently, fractional lasers have been examined as treatment options for androgenic alopecia. The mechanism of action of these minimally invasive resurfacing procedures is thought to be 2-fold. First, the microscopic injuries created by these treatments may induce a favorable wound healing environment that triggers hair growth. Alternatively, disruption of the stratum corneum allows for improved transdermal passage of well-established therapeutic drugs to the hair roots.

Methods:

A literature review was performed to evaluate the efficacy of these emerging treatments on hair regrowth.

Results:

Nine original studies examining the effect of fractional lasers on hair growth in androgenic alopecia have been reviewed.

Conclusions:

Preliminary evidence suggests that fractional laser therapies have a positive effect on hair regrowth; however, most of the literature is limited to case reports, and small prospective and retrospective series. Further studies, in the form of well-designed randomized controlled trials, are necessary to evaluate the efficacy, safety, and optimal treatment courses.

k-mer Similarity, Networks of Microbial Genomes, and Taxonomic Rank

Microbial genomes have been shaped by parent-to-offspring (vertical) descent and lateral genetic transfer. These processes can be distinguished by alignment-based inference and comparison of phylogenetic trees for individual gene families, but this approach is not scalable to whole-genome sequences, and a tree-like structure does not adequately capture how these processes impact microbial physiology. Here we adopted alignment-free approaches based on k-mer statistics to infer phylogenomic networks involving 2,783 completely sequenced bacterial and archaeal genomes and compared the contributions of rRNA, protein-coding, and plasmid sequences to these networks. Our results show that the phylogenomic signal arising from ribosomal RNAs is strong and extends broadly across all taxa, whereas that from plasmids is strong but restricted to closely related groups, particularly Proteobacteria. However, the signal from the other chromosomal regions is restricted in breadth. We show that mean k-mer similarity can correlate with taxonomic rank. We also link the implicated k-mers to genome annotation (thus, functions) and define core k-mers (thus, core functions) in specific phyletic groups. Highly conserved functions in most phyla include amino acid metabolism and transport as well as energy production and conversion. Intracellular trafficking and secretion are the most prominent core functions among Spirochaetes, whereas energy production and conversion are not highly conserved among the largely parasitic or commensal Tenericutes. These observations suggest that differential conservation of functions relates to niche specialization and evolutionary diversification of microbes. Our results demonstrate that k-mer approaches can be used to efficiently identify phylogenomic signals and conserved core functions at the multigenome scale. IMPORTANCE Genome evolution of microbes involves parent-to-offspring descent, and lateral genetic transfer that convolutes the phylogenomic signal. This study investigated phylogenomic signals among thousands of microbial genomes based on short subsequences without using multiple-sequence alignment. The signal from ribosomal RNAs is strong across all taxa, and the signal of plasmids is strong only in closely related groups, particularly Proteobacteria. However, the signal from other chromosomal regions (∼99% of the genomes) is remarkably restricted in breadth. The similarity of subsequences is found to correlate with taxonomic rank and informs on conserved and differential core functions relative to niche specialization and evolutionary diversification of microbes. These results provide a comprehensive, alignment-free view of microbial genome evolution as a network, beyond a tree-like structure.

Alignment-Free Sequence Analysis and Applications

Genome and metagenome comparisons based on large amounts of next generation sequencing (NGS) data pose significant challenges for alignment-based approaches due to the huge data size and the relatively short length of the reads. Alignment-free approaches based on the counts of word patterns in NGS data do not depend on the complete genome and are generally computationally efficient. Thus, they contribute significantly to genome and metagenome comparison. Recently, novel statistical approaches have been developed for the comparison of both long and shotgun sequences. These approaches have been applied to many problems including the comparison of gene regulatory regions, genome sequences, metagenomes, binning contigs in metagenomic data, identification of virus-host interactions, and detection of horizontal gene transfers. We provide an updated review of these applications and other related developments of word-count based approaches for alignment-free sequence analysis.

Alignment-free sequence comparison: benefits, applications, and tools

Alignment-free sequence analyses have been applied to problems ranging from whole-genome phylogeny to the classification of protein families, identification of horizontally transferred genes, and detection of recombined sequences. The strength of these methods makes them particularly useful for next-generation sequencing data processing and analysis. However, many researchers are unclear about how these methods work, how they compare to alignment-based methods, and what their potential is for use for their research. We address these questions and provide a guide to the currently available alignment-free sequence analysis tools.

Robust Inference of Genetic Exchange Communities from Microbial Genomes Using TF-IDF

Bacteria and archaea can exchange genetic material across lineages through processes of lateral genetic transfer (LGT). Collectively, these exchange relationships can be modeled as a network and analyzed using concepts from graph theory. In particular, densely connected regions within an LGT network have been defined as genetic exchange communities (GECs). However, it has been problematic to construct networks in which edges solely represent LGT. Here we apply term frequency-inverse document frequency (TF-IDF), an alignment-free method originating from document analysis, to infer regions of lateral origin in bacterial genomes. We examine four empirical datasets of different size (number of genomes) and phyletic breadth, varying a key parameter (word length k) within bounds established in previous work. We map the inferred lateral regions to genes in recipient genomes, and construct networks in which the nodes are groups of genomes, and the edges natively represent LGT. We then extract maximum and maximal cliques (i.e., GECs) from these graphs, and identify nodes that belong to GECs across a wide range of k. Most surviving lateral transfer has happened within these GECs. Using Gene Ontology enrichment tests we demonstrate that biological processes associated with metabolism, regulation and transport are often over-represented among the genes affected by LGT within these communities. These enrichments are largely robust to change of k.