orthofisher: a broadly applicable tool for automated gene identification and retrieval

Inferences on the evolution of the ascorbic acid synthesis pathway in insects using Phylogenetic Tree Collapser (PTC), a tool for the automated collapsing of phylogenetic trees using taxonomic information

When inferring the evolution of a gene/gene family, it is advisable to use all available coding sequences (CDS) from as many species genomes as possible in order to infer and date all gene duplications and losses. Nowadays, this means using hundreds or even thousands of CDSs, which makes the inferred phylogenetic trees difficult to visualize and interpret. Therefore, it is useful to have an automated way of collapsing large phylogenetic trees according to a taxonomic term decided by the user (family, class, or order, for instance), in order to highlight the minimal set of sequences that should be used to recapitulate the full history of the gene/gene family being studied at that taxonomic level, that can be refined using additional software. Here we present the Phylogenetic Tree Collapser (PTC) program (https://github.com/pegi3s/phylogenetic-tree-collapser), a flexible tool for automated tree collapsing using taxonomic information, that can be easily used by researchers without a background in informatics, since it only requires the installation of Docker, Podman or Singularity. The utility of PTC is demonstrated by addressing the evolution of the ascorbic acid synthesis pathway in insects. A Docker image is available at Docker Hub (https://hub.docker.com/r/pegi3s/phylogenetic-tree-collapser) with PTC installed and ready-to-run.

Convergent reductive evolution in bee-associated lactic acid bacteria

Distantly related organisms may evolve similar traits when exposed to similar environments or engaging in certain lifestyles. Several members of the Lactobacillaceae (LAB) family are frequently isolated from the floral niche, mostly from bees and flowers. In some floral LAB species (henceforth referred to as bee-associated), distinctive genomic (e.g., genome reduction) and phenotypic (e.g., preference for fructose over glucose or fructophily) features were recently documented. These features are found across distantly related species, raising the hypothesis that specific genomic and phenotypic traits evolved convergently during adaptation to the floral environment. To test this hypothesis, we examined representative genomes of 369 species of bee-associated and non-bee-associated LAB. Phylogenomic analysis unveiled seven independent ecological shifts towards the floral niche in LAB. In these bee-associated LAB, we observed pervasive, significant reductions of genome size, gene repertoire, and GC content. Using machine leaning, we could distinguish bee-associated from non-bee-associated species with 94% accuracy, based on the absence of genes involved in metabolism, osmotic stress, or DNA repair. Moreover, we found that the most important genes for the machine learning classifier were seemingly lost, independently, in multiple bee-associated lineages. One of these genes, adhE, encodes a bifunctional aldehyde-alcohol dehydrogenase associated with the evolution of fructophily, a rare phenotypic trait that was recently identified in many floral LAB species. These results suggest that the independent evolution of distinctive phenotypes in bee-associated LAB has been largely driven by independent loss of the same set of genes.

Importance

Several lactic acid bacteria (LAB) species are intimately associated with bees and exhibit unique biochemical properties with potential for food applications and honeybee health. Using a machine-learning based approach, our study shows that adaptation of LAB to the bee environment was accompanied by a distinctive genomic trajectory deeply shaped by gene loss. Several of these gene losses occurred independently in distantly related species and are linked to some of their unique biotechnologically relevant traits, such as the preference of fructose over glucose (fructophily). This study underscores the potential of machine learning in identifying fingerprints of adaptation and detecting instances of convergent evolution. Furthermore, it sheds light onto the genomic and phenotypic particularities of bee-associated bacteria, thereby deepening the understanding of their positive impact on honeybee health.

Extensive remodeling of sugar metabolism through gene loss and horizontal gene transfer in a eukaryotic lineage

BACKGROUND

In yeasts belonging to the subphylum Saccharomycotina, genes encoding components of the main metabolic pathways, like alcoholic fermentation, are usually conserved. However, in fructophilic species belonging to the floral Wickerhamiella and Starmerella genera (W/S clade), alcoholic fermentation was uniquely shaped by events of gene loss and horizontal gene transfer (HGT).

RESULTS

Because HGT and gene losses were first identified when only eight W/S-clade genomes were available, we collected publicly available genome data and sequenced the genomes of 36 additional species. A total of 63 genomes, representing most of the species described in the clade, were included in the analyses. Firstly, we inferred the phylogenomic tree of the clade and inspected the genomes for the presence of HGT-derived genes involved in fructophily and alcoholic fermentation. We predicted nine independent HGT events and several instances of secondary loss pertaining to both pathways. To investigate the possible links between gene loss and acquisition events and evolution of sugar metabolism, we conducted phenotypic characterization of 42 W/S-clade species including estimates of sugar consumption rates and fermentation byproduct formation. In some instances, the reconciliation of genotypes and phenotypes yielded unexpected results, such as the discovery of fructophily in the absence of the cornerstone gene (FFZ1) and robust alcoholic fermentation in the absence of the respective canonical pathway.

CONCLUSIONS

These observations suggest that reinstatement of alcoholic fermentation in the W/S clade triggered a surge of innovation that goes beyond the utilization of xenologous enzymes, with fructose metabolism playing a key role.

Genomic factors shape carbon and nitrogen metabolic niche breadth across Saccharomycotina yeasts

Organisms exhibit extensive variation in ecological niche breadth, from very narrow (specialists) to very broad (generalists). Two general paradigms have been proposed to explain this variation: (i) trade-offs between performance efficiency and breadth and (ii) the joint influence of extrinsic (environmental) and intrinsic (genomic) factors. We assembled genomic, metabolic, and ecological data from nearly all known species of the ancient fungal subphylum Saccharomycotina (1154 yeast strains from 1051 species), grown in 24 different environmental conditions, to examine niche breadth evolution. We found that large differences in the breadth of carbon utilization traits between yeasts stem from intrinsic differences in genes encoding specific metabolic pathways, but we found limited evidence for trade-offs. These comprehensive data argue that intrinsic factors shape niche breadth variation in microbes.

Fossil-calibrated molecular clock data enable reconstruction of steps leading to differentiated multicellularity and anisogamy in the Volvocine algae

BACKGROUND

Throughout its nearly four-billion-year history, life has undergone evolutionary transitions in which simpler subunits have become integrated to form a more complex whole. Many of these transitions opened the door to innovations that resulted in increased biodiversity and/or organismal efficiency. The evolution of multicellularity from unicellular forms represents one such transition, one that paved the way for cellular differentiation, including differentiation of male and female gametes. A useful model for studying the evolution of multicellularity and cellular differentiation is the volvocine algae, a clade of freshwater green algae whose members range from unicellular to colonial, from undifferentiated to completely differentiated, and whose gamete types can be isogamous, anisogamous, or oogamous. To better understand how multicellularity, differentiation, and gametes evolved in this group, we used comparative genomics and fossil data to establish a geologically calibrated roadmap of when these innovations occurred.

RESULTS

Our ancestral-state reconstructions, show that multicellularity arose independently twice in the volvocine algae. Our chronograms indicate multicellularity evolved during the Carboniferous-Triassic periods in Goniaceae + Volvocaceae, and possibly as early as the Cretaceous in Tetrabaenaceae. Using divergence time estimates we inferred when, and in what order, specific developmental changes occurred that led to differentiated multicellularity and oogamy. We find that in the volvocine algae the temporal sequence of developmental changes leading to differentiated multicellularity is much as proposed by David Kirk, and that multicellularity is correlated with the acquisition of anisogamy and oogamy. Lastly, morphological, molecular, and divergence time data suggest the possibility of cryptic species in Tetrabaenaceae.

CONCLUSIONS

Large molecular datasets and robust phylogenetic methods are bringing the evolutionary history of the volvocine algae more sharply into focus. Mounting evidence suggests that extant species in this group are the result of two independent origins of multicellularity and multiple independent origins of cell differentiation. Also, the origin of the Tetrabaenaceae-Goniaceae-Volvocaceae clade may be much older than previously thought. Finally, the possibility of cryptic species in the Tetrabaenaceae provides an exciting opportunity to study the recent divergence of lineages adapted to live in very different thermal environments.

Phylogenomics reveals extensive misidentification of fungal strains from the genus Aspergillus

Modern taxonomic classification is often based on phylogenetic analyses of a few molecular markers, although single-gene studies are still common. Here, we leverage genome-scale molecular phylogenetics (phylogenomics) of species and populations to reconstruct evolutionary relationships in a dense data set of 710 fungal genomes from the biomedically and technologically important genus Aspergillus. To do so, we generated a novel set of 1,362 high-quality molecular markers specific for Aspergillus and provided profile Hidden Markov Models for each, facilitating their use by others. Examining the resulting phylogeny helped resolve ongoing taxonomic controversies, identified new ones, and revealed extensive strain misidentification (7.59% of strains were previously misidentified), underscoring the importance of population-level sampling in species classification. These findings were corroborated using the current standard, taxonomically informative loci. These findings suggest that phylogenomics of species and populations can facilitate accurate taxonomic classifications and reconstructions of the Tree of Life.IMPORTANCEIdentification of fungal species relies on the use of molecular markers. Advances in genomic technologies have made it possible to sequence the genome of any fungal strain, making it possible to use genomic data for the accurate assignment of strains to fungal species (and for the discovery of new ones). We examined the usefulness and current limitations of genomic data using a large data set of 710 publicly available genomes from multiple strains and species of the biomedically, agriculturally, and industrially important genus Aspergillus. Our evolutionary genomic analyses revealed that nearly 8% of publicly available Aspergillus genomes are misidentified. Our work highlights the usefulness of genomic data for fungal systematic biology and suggests that systematic genome sequencing of multiple strains, including reference strains (e.g., type strains), of fungal species will be required to reduce misidentification errors in public databases.

The evolution of antimicrobial peptides in Chiroptera

High viral tolerance coupled with an extraordinary regulation of the immune response makes bats a great model to study host-pathogen evolution. Although many immune-related gene gains and losses have been previously reported in bats, important gene families such as antimicrobial peptides (AMPs) remain understudied. We built an exhaustive bioinformatic pipeline targeting the major gene families of defensins and cathelicidins to explore AMP diversity and analyze their evolution and distribution across six bat families. A combination of manual and automated procedures identified 29 AMP families across queried species, with α-, β-defensins, and cathelicidins representing around 10% of AMP diversity. Gene duplications were inferred in both α-defensins, which were absent in five species, and three β-defensin gene subfamilies, but cathelicidins did not show significant shifts in gene family size and were absent in Anoura caudifer and the pteropodids. Based on lineage-specific gains and losses, we propose diet and diet-related microbiome evolution may determine the evolution of α- and β-defensins gene families and subfamilies. These results highlight the importance of building species-specific libraries for genome annotation in non-model organisms and shed light on possible drivers responsible for the rapid evolution of AMPs. By focusing on these understudied defenses, we provide a robust framework for explaining bat responses to pathogens.

Genomic and ecological factors shaping specialism and generalism across an entire subphylum

Organisms exhibit extensive variation in ecological niche breadth, from very narrow (specialists) to very broad (generalists). Paradigms proposed to explain this variation either invoke trade-offs between performance efficiency and breadth or underlying intrinsic or extrinsic factors. We assembled genomic (1,154 yeast strains from 1,049 species), metabolic (quantitative measures of growth of 843 species in 24 conditions), and ecological (environmental ontology of 1,088 species) data from nearly all known species of the ancient fungal subphylum Saccharomycotina to examine niche breadth evolution. We found large interspecific differences in carbon breadth stem from intrinsic differences in genes encoding specific metabolic pathways but no evidence of trade-offs and a limited role of extrinsic ecological factors. These comprehensive data argue that intrinsic factors driving microbial niche breadth variation.

COVID-19-Associated Pulmonary Aspergillosis Isolates Are Genomically Diverse but Similar to Each Other in Their Responses to Infection-Relevant Stresses

Secondary infections caused by the pulmonary fungal pathogen Aspergillus fumigatus are a significant cause of mortality in patients with severe coronavirus disease 19 (COVID-19). Even though epithelial cell damage and aberrant cytokine responses have been linked to susceptibility to COVID-19-associated pulmonary aspergillosis (CAPA), little is known about the mechanisms underpinning copathogenicity. Here, we analyzed the genomes of 11 A. fumigatus isolates from patients with CAPA in three centers from different European countries. CAPA isolates did not cluster based on geographic origin in a genome-scale phylogeny of representative A. fumigatus isolates. Phenotypically, CAPA isolates were more similar to the A. fumigatus A1160 reference strain than to the Af293 strain when grown in infection-relevant stresses, except for interactions with human immune cells wherein macrophage responses were similar to those induced by the Af293 reference strain. Collectively, our data indicate that CAPA isolates are genomically diverse but are more similar to each other in their responses to infection-relevant stresses. A larger number of isolates from CAPA patients should be studied to better understand the molecular epidemiology of CAPA and to identify genetic drivers of copathogenicity and antifungal resistance in patients with COVID-19. IMPORTANCE Coronavirus disease 2019 (COVID-19)-associated pulmonary aspergillosis (CAPA) has been globally reported as a life-threatening complication in some patients with severe COVID-19. Most of these infections are caused by the environmental mold Aspergillus fumigatus, which ranks third in the fungal pathogen priority list of the WHO. However, little is known about the molecular epidemiology of Aspergillus fumigatus CAPA strains. Here, we analyzed the genomes of 11 A. fumigatus isolates from patients with CAPA in three centers from different European countries, and carried out phenotypic analyses with a view to understanding the pathophysiology of the disease. Our data indicate that A. fumigatus CAPA isolates are genomically diverse but are more similar to each other in their responses to infection-relevant stresses.

OrthoSNAP: A tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

Molecular evolution studies, such as phylogenomic studies and genome-wide surveys of selection, often rely on gene families of single-copy orthologs (SC-OGs). Large gene families with multiple homologs in 1 or more species-a phenomenon observed among several important families of genes such as transporters and transcription factors-are often ignored because identifying and retrieving SC-OGs nested within them is challenging. To address this issue and increase the number of markers used in molecular evolution studies, we developed OrthoSNAP, a software that uses a phylogenetic framework to simultaneously split gene families into SC-OGs and prune species-specific inparalogs. We term SC-OGs identified by OrthoSNAP as SNAP-OGs because they are identified using a splitting and pruning procedure analogous to snapping branches on a tree. From 415,129 orthologous groups of genes inferred across 7 eukaryotic phylogenomic datasets, we identified 9,821 SC-OGs; using OrthoSNAP on the remaining 405,308 orthologous groups of genes, we identified an additional 10,704 SNAP-OGs. Comparison of SNAP-OGs and SC-OGs revealed that their phylogenetic information content was similar, even in complex datasets that contain a whole-genome duplication, complex patterns of duplication and loss, transcriptome data where each gene typically has multiple transcripts, and contentious branches in the tree of life. OrthoSNAP is useful for increasing the number of markers used in molecular evolution data matrices, a critical step for robustly inferring and exploring the tree of life.

BioKIT: a versatile toolkit for processing and analyzing diverse types of sequence data

Bioinformatic analysis-such as genome assembly quality assessment, alignment summary statistics, relative synonymous codon usage, file format conversion, and processing and analysis-is integrated into diverse disciplines in the biological sciences. Several command-line pieces of software have been developed to conduct some of these individual analyses, but unified toolkits that conduct all these analyses are lacking. To address this gap, we introduce BioKIT, a versatile command line toolkit that has, upon publication, 42 functions, several of which were community-sourced, that conduct routine and novel processing and analysis of genome assemblies, multiple sequence alignments, coding sequences, sequencing data, and more. To demonstrate the utility of BioKIT, we conducted a comprehensive examination of relative synonymous codon usage across 171 fungal genomes that use alternative genetic codes, showed that the novel metric of gene-wise relative synonymous codon usage can accurately estimate gene-wise codon optimization, evaluated the quality and characteristics of 901 eukaryotic genome assemblies, and calculated alignment summary statistics for 10 phylogenomic data matrices. BioKIT will be helpful in facilitating and streamlining sequence analysis workflows. BioKIT is freely available under the MIT license from GitHub (https://github.com/JLSteenwyk/BioKIT), PyPi (https://pypi.org/project/jlsteenwyk-biokit/), and the Anaconda Cloud (https://anaconda.org/jlsteenwyk/jlsteenwyk-biokit). Documentation, user tutorials, and instructions for requesting new features are available online (https://jlsteenwyk.com/BioKIT).