Towards an accurate identification of mosaic genes and partial horizontal gene transfers

Genetic characteristics of Blastocystis sp. in cattle from Hebei Province, China

Blastocystis sp. is a protozoan parasite that infects the intestines of humans and animals, causing chronic diseases such as skin rashes, abdominal pain, and irritable bowel syndrome. A survey was conducted to determine the prevalence and genetic diversity of Blastocystis sp. infection in cattle, in Hebei Province, China. 2746 cattle fecal samples were collected from 11 cities in Hebei Province and analyzed using polymerase chain reaction targeting the Blastocystis sp. barcoding gene. MEGA, PhyloSuite, and PopART were used to analyze the subtype, sequence signature, pairwise genetic distance, and genetic diversity indices. The results showed that the Blastocystis sp. detection rate was 12.60% (346/2746). The infection rate in different herds was affected by region, age, breeding mode, and variety; that is, the infection rates in areas of southern Hebei, cattle under one year old, intensive raising, and dairy cattle were higher than the infection rates in northern Hebei, cattle over one year old, scatter feeding, and beef cattle. Seven Blastocystis subtypes were identified, namely, ST1, ST2, ST5, ST10, ST14, ST21, and ST26; ST10 was the dominant subtype, and ST14 was the second most common subtype. A total of 374 polymorphic and conserved sites were obtained, including 273 invariable (monomorphic) sites and 101 variable (polymorphic) sites, accounting for 27.01% of all nucleotides. The nucleotide diversity index (Pi) was 0.07749, and the haplotype (gene) diversity index (Hd) was 0.946. This study provides the first comprehensive information on the epidemiological situation of Blastocystis sp. infection in cattle from Hebei Province, China, and revealed rich genetic diversity of Blastocystis sp.

Integrated molecular, phenotypic and epidemiological surveillance of antimicrobial resistance in Neisseria gonorrhoeae in Germany

Numbers of infections with Neisseria gonorrhoeae are among the top three sexually transmitted infections (STI) worldwide. In addition, the emergence and spread of antimicrobial resistance (AMR) in Neisseria gonorrhoeae pose an important public-health issue. The integration of genomic, phenotypic and epidemiological data to monitor Neisseria gonorrhoeae fosters our understanding of the emergence and spread of AMR in Neisseria gonorrhoeae and helps to inform therapy guidelines and intervention strategies. Thus, the Gonococcal resistance surveillance (Go-Surv-AMR) was implemented at the Robert Koch Institute in Germany in 2021 to obtain molecular, phenotypic and epidemiological data on Neisseria gonorrhoeae isolated in Germany. Here, we describe the structure and aims of Go-Surv-AMR. Furthermore, we point out future directions of Go-Surv-AMR to improve the integrated genomic surveillance of Neisseria gonorrhoeae. In this context we discuss current and prospective sequencing approaches and the information derived from their application. Moreover, we highlight the importance of combining phenotypic and WGS data to monitor the evolution of AMR in Neisseria gonorrhoeae in Germany. The implementation and constant development of techniques and tools to improve the genomic surveillance of Neisseria gonorrhoeae will be important in coming years.

Characterizing the diversity and commensal origins of penA mosaicism in the genus Neisseria

Mosaic penA alleles formed through horizontal gene transfer (HGT) have been instrumental to the rising incidence of ceftriaxone-resistant gonococcal infections. Although interspecies HGT of regions of the penA gene between Neisseria gonorrhoeae and commensal Neisseria species has been described, knowledge concerning which species are the most common contributors to mosaic penA alleles is limited, with most studies examining only a small number of alleles. Here, we investigated the origins of recombinant penA alleles through in silico analyses that incorporated 1700 penA alleles from 35 513 Neisseria isolates, comprising 15 different Neisseria species. We identified Neisseria subflava and Neisseria cinerea as the most common source of recombinant sequences in N. gonorrhoeae penA. This contrasted with Neisseria meningitidis penA, for which the primary source of recombinant DNA was other meningococci, followed by Neisseria lactamica. Additionally, we described the distribution of polymorphisms implicated in antimicrobial resistance in penA, and found that these are present across the genus. These results provide insight into resistance-related changes in the penA gene across human-associated Neisseria species, illustrating the importance of genomic surveillance of not only the pathogenic Neisseria, but also of the oral niche-associated commensals from which these pathogens are sourcing key genetic variation.

HGTphyloDetect: facilitating the identification and phylogenetic analysis of horizontal gene transfer

BACKGROUND

Horizontal gene transfer (HGT) is an important driver in genome evolution, gain-of-function, and metabolic adaptation to environmental niches. Genome-wide identification of putative HGT events has become increasingly practical, given the rapid growth of genomic data. However, existing HGT analysis toolboxes are not widely used, limited by their inability to perform phylogenetic reconstruction to explore potential donors, and the detection of HGT from both evolutionarily distant and closely related species.

RESULTS

In this study, we have developed HGTphyloDetect, which is a versatile computational toolbox that combines high-throughput analysis with phylogenetic inference, to facilitate comprehensive investigation of HGT events. Two case studies with Saccharomyces cerevisiae and Candida versatilis demonstrate the ability of HGTphyloDetect to identify horizontally acquired genes with high accuracy. In addition, HGTphyloDetect enables phylogenetic analysis to illustrate a likely path of gene transmission among the evolutionarily distant or closely related species.

CONCLUSIONS

The HGTphyloDetect computational toolbox is designed for ease of use and can accurately find HGT events with a very low false discovery rate in a high-throughput manner. The HGTphyloDetect toolbox and its related user tutorial are freely available at https://github.com/SysBioChalmers/HGTphyloDetect.

Modulating Gene Expression within a Microbiome Based on Computational Models

Simple Summary

Development of computational biology methodologies has provided comprehensive understanding of the complexity of microbiomes, and the extensive ways in which they influence their environment. This has awakened a new research goal, aiming to not only understand the mechanisms in which microbiomes function, but to actively modulate and engineer them for various purposes. However, current microbiome engineering techniques are usually manually tailored for a specific system and neglect the different interactions between the new genetic information and the bacterial population, turning a blind eye to processes such as horizontal gene transfer, mutations, and other genetic alterations. In this work, we developed a generic computational method to automatically tune the expression of heterologous genes within a microbiome according to given preferences, to allow the functionality of the engineering process to propagate in longer periods of time. This goal was achieved by treating each part of the gene individually and considering long term fitness effects on the environment, providing computational and experimental evidence for this approach.

Abstract

Recent research in the field of bioinformatics and molecular biology has revealed the immense complexity and uniqueness of microbiomes, while also showcasing the impact of the symbiosis between a microbiome and its host or environment. A core property influencing this process is horizontal gene transfer between members of the bacterial community used to maintain genetic variation. The essential effect of this mechanism is the exposure of genetic information to a wide array of members of the community, creating an additional “layer” of information in the microbiome named the “plasmidome”. From an engineering perspective, introduction of genetic information to an environment must be facilitated into chosen species which will be able to carry out the desired effect instead of competing and inhibiting it. Moreover, this process of information transfer imposes concerns for the biosafety of genetic engineering of microbiomes as exposure of genetic information into unwanted hosts can have unprecedented ecological impacts. Current technologies are usually experimentally developed for a specific host/environment, and only deal with the transformation process itself at best, ignoring the impact of horizontal gene transfer and gene-microbiome interactions that occur over larger periods of time in uncontrolled environments. The goal of this research was to design new microbiome-specific versions of engineered genetic information, providing an additional layer of compatibility to existing engineering techniques. The engineering framework is entirely computational and is agnostic to the selected microbiome or gene by reducing the problem into the following set up: microbiome species can be defined as wanted or unwanted hosts of the modification. Then, every element related to gene expression (e.g., promoters, coding regions, etc.) and regulation is individually examined and engineered by novel algorithms to provide the defined expression preferences. Additionally, the synergistic effect of the combination of engineered gene blocks facilitates robustness to random mutations that might occur over time. This method has been validated using both computational and experimental tools, stemming from the research done in the iGEM 2021 competition, by the TAU group.

Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin

BACKGROUND

The SARS-CoV-2 pandemic is one of  the greatest  global medical and social challenges that have emerged in recent history. Human coronavirus strains discovered during previous SARS outbreaks have been hypothesized to pass from bats to humans using intermediate hosts, e.g. civets for SARS-CoV and camels for MERS-CoV. The discovery of an intermediate host of SARS-CoV-2 and the identification of specific mechanism of its emergence in humans are topics of primary evolutionary importance. In this study we investigate the evolutionary patterns of 11 main genes of SARS-CoV-2. Previous studies suggested that the genome of SARS-CoV-2 is highly similar to the horseshoe bat coronavirus RaTG13 for most of the genes and to some Malayan pangolin coronavirus (CoV) strains for the receptor binding (RB) domain of the spike protein.

RESULTS

We provide a detailed list of statistically significant horizontal gene transfer and recombination events (both intergenic and intragenic) inferred for each of 11 main genes of the SARS-CoV-2 genome. Our analysis reveals that two continuous regions of genes S and N of SARS-CoV-2 may result from intragenic recombination between RaTG13 and Guangdong (GD) Pangolin CoVs. Statistically significant gene transfer-recombination events between RaTG13 and GD Pangolin CoV have been identified in region [1215-1425] of gene S and region [534-727] of gene N. Moreover, some statistically significant recombination events between the ancestors of SARS-CoV-2, RaTG13, GD Pangolin CoV and bat CoV ZC45-ZXC21 coronaviruses have been identified in genes ORF1ab, S, ORF3a, ORF7a, ORF8 and N. Furthermore, topology-based clustering of gene trees inferred for 25 CoV organisms revealed a three-way evolution of coronavirus genes, with gene phylogenies of ORF1ab, S and N forming the first cluster, gene phylogenies of ORF3a, E, M, ORF6, ORF7a, ORF7b and ORF8 forming the second cluster, and phylogeny of gene ORF10 forming the third cluster.

CONCLUSIONS

The results of our horizontal gene transfer and recombination analysis suggest that SARS-CoV-2 could not only be a chimera virus resulting from recombination of the bat RaTG13 and Guangdong pangolin coronaviruses but also a close relative of the bat CoV ZC45 and ZXC21 strains. They also indicate that a GD pangolin may be an intermediate host of this dangerous virus.

In silico functional and evolutionary analyses of rubber oxygenases (RoxA and RoxB)

The study presents an in silico identification of poly (cis-1,4-isoprene) cleaving enzymes, viz., RoxA and RoxB in bacteria, followed by their functional and evolutionary exploration using comparative genomics. The orthologs of these proteins were found to be restricted to Gram-negative beta-, gamma-, and delta-proteobacteria. Toward the evolutionary propagation, the RoxA and RoxB genes were predicted to have evolved via a common interclass route of horizontal gene transfer in the phylum Proteobacteria (delta → gamma → beta). Besides, recombination, mutation, and gene conversion were also detected in both the genes leading to their diversification. Further, the differential selective pressure is predicted to be operating on entire RoxA and RoxB genes such that the former is diversifying further, whereas the latter is evolving to reduce its genetic diversity. However, the structurally and functionally important sites/residues of these genes were found to be preventing changes implying their evolutionary conservation. Further, the phylogenetic analysis demonstrated a sharp split between the RoxA and RoxB orthologs and indicated the emergence of their variant as another type of putative rubber oxygenase (RoxC) in the class Gammaproteobacteria. A detailed in silico analysis of the signature motifs and residues of Rox sequences exhibited important differences as well as similarities among the RoxA, RoxB, and putative RoxC sequences. Although RoxC appears to be a hybrid of RoxA and RoxB, the signature motifs and residues of RoxC are more similar to RoxB.

Transfer index, NetUniFrac and some useful shortest path-based distances for community analysis in sequence similarity networks

MOTIVATION

Phylogenetic trees and the methods for their analysis have played a key role in many evolutionary, ecological and bioinformatics studies. Alternatively, phylogenetic networks have been widely used to analyze and represent complex reticulate evolutionary processes which cannot be adequately studied using traditional phylogenetic methods. These processes include, among others, hybridization, horizontal gene transfer, and genetic recombination. Nowadays, sequence similarity and genome similarity networks have become an efficient tool for community analysis of large molecular datasets in comparative studies. These networks can be used for tackling a variety of complex evolutionary problems such as the identification of horizontal gene transfer events, the recovery of mosaic genes and genomes, and the study of holobionts.

RESULTS

The shortest path in a phylogenetic tree is used to estimate evolutionary distances between species. We show how the shortest path concept can be extended to sequence similarity networks by defining five new distances, NetUniFrac, Spp, Spep, Spelp and Spinp, and the Transfer index, between species communities present in the network. These new distances can be seen as network analogs of the traditional UniFrac distance used to assess dissimilarity between species communities in a phylogenetic tree, whereas the Transfer index is intended for estimating the rate and direction of gene transfers, or species dispersal, between different phylogenetic, or ecological, species communities. Moreover, NetUniFrac and the Transfer index can be computed in linear time with respect to the number of edges in the network. We show how these new measures can be used to analyze microbiota and antibiotic resistance gene similarity networks.

AVAILABILITY AND IMPLEMENTATION

Our NetFrac program, implemented in R and C, along with its source code, is freely available on Github at the following URL address: https://github.com/XPHenry/Netfrac.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A new fast method for inferring multiple consensus trees using k-medoids

Background

Gene trees carry important information about specific evolutionary patterns which characterize the evolution of the corresponding gene families. However, a reliable species consensus tree cannot be inferred from a multiple sequence alignment of a single gene family or from the concatenation of alignments corresponding to gene families having different evolutionary histories. These evolutionary histories can be quite different due to horizontal transfer events or to ancient gene duplications which cause the emergence of paralogs within a genome. Many methods have been proposed to infer a single consensus tree from a collection of gene trees. Still, the application of these tree merging methods can lead to the loss of specific evolutionary patterns which characterize some gene families or some groups of gene families. Thus, the problem of inferring multiple consensus trees from a given set of gene trees becomes relevant.

Results

We describe a new fast method for inferring multiple consensus trees from a given set of phylogenetic trees (i.e. additive trees or X-trees) defined on the same set of species (i.e. objects or taxa). The traditional consensus approach yields a single consensus tree. We use the popular k-medoids partitioning algorithm to divide a given set of trees into several clusters of trees. We propose novel versions of the well-known Silhouette and Caliński-Harabasz cluster validity indices that are adapted for tree clustering with k-medoids. The efficiency of the new method was assessed using both synthetic and real data, such as a well-known phylogenetic dataset consisting of 47 gene trees inferred for 14 archaeal organisms.

Conclusions

The method described here allows inference of multiple consensus trees from a given set of gene trees. It can be used to identify groups of gene trees having similar intragroup and different intergroup evolutionary histories. The main advantage of our method is that it is much faster than the existing tree clustering approaches, while providing similar or better clustering results in most cases. This makes it particularly well suited for the analysis of large genomic and phylogenetic datasets.

Involvement of aph(3')-IIa in the formation of mosaic aminoglycoside resistance genes in natural environments

Intragenic recombination leading to mosaic gene formation is known to alter resistance profiles for particular genes and bacterial species. Few studies have examined to what extent aminoglycoside resistance genes undergo intragenic recombination. We screened the GenBank database for mosaic gene formation in homologs of the aph(3')-IIa (nptII) gene. APH(3')-IIa inactivates important aminoglycoside antibiotics. The gene is widely used as a selectable marker in biotechnology and enters the environment via laboratory discharges and the release of transgenic organisms. Such releases may provide opportunities for recombination in competent environmental bacteria. The retrieved GenBank sequences were grouped in three datasets comprising river water samples, duck pathogens and full-length variants from various bacterial genomes and plasmids. Analysis for recombination in these datasets was performed with the Recombination Detection Program (RDP4), and the Genetic Algorithm for Recombination Detection (GARD). From a total of 89 homologous sequences, 83% showed 99-100% sequence identity with aph(3')-IIa originally described as part of transposon Tn5. Fifty one were unique sequence variants eligible for recombination analysis. Only a single recombination event was identified with high confidence and indicated the involvement of aph(3')-IIa in the formation of a mosaic gene located on a plasmid of environmental origin in the multi-resistant isolate Pseudomonas aeruginosa PA96. The available data suggest that aph(3')-IIa is not an archetypical mosaic gene as the divergence between the described sequence variants and the number of detectable recombination events is low. This is in contrast to the numerous mosaic alleles reported for certain penicillin or tetracycline resistance determinants.

A new efficient algorithm for inferring explicit hybridization networks following the Neighbor-Joining principle

Several algorithms and software have been developed for inferring phylogenetic trees. However, there exist some biological phenomena such as hybridization, recombination, or horizontal gene transfer which cannot be represented by a tree topology. We need to use phylogenetic networks to adequately represent these important evolutionary mechanisms. In this article, we present a new efficient heuristic algorithm for inferring hybridization networks from evolutionary distance matrices between species. The famous Neighbor-Joining concept and the least-squares criterion are used for building networks. At each step of the algorithm, before joining two given nodes, we check if a hybridization event could be related to one of them or to both of them. The proposed algorithm finds the exact tree solution when the considered distance matrix is a tree metric (i.e. it is representable by a unique phylogenetic tree). It also provides very good hybrids recovery rates for large trees (with 32 and 64 leaves in our simulations) for both distance and sequence types of data. The results yielded by the new algorithm for real and simulated datasets are illustrated and discussed in detail.

Distinct molecular features facilitating ice-binding mechanisms in hyperactive antifreeze proteins closely related to an Antarctic sea ice bacterium

Antifreeze proteins or ice-binding proteins (IBPs) facilitate the survival of certain cellular organisms in freezing environment by inhibiting the growth of ice crystals in solution. Present study identifies orthologs of the IBP of Colwellia sp. SLW05, which were obtained from a wide range of taxa. Phylogenetic analysis on the basis of conserved regions (predicted as the 'ice-binding domain' [IBD]) present in all the orthologs, separates the bacterial and archaeal orthologs from that of the eukaryotes'. Correspondence analysis pointed out that the bacterial and archaeal IBDs have relatively higher average hydrophobicity than the eukaryotic members. IBDs belonging to bacterial as well as archaeal AFPs contain comparatively more strands, and therefore are revealed to be under higher evolutionary selection pressure. Molecular docking studies prove that the ice crystals form more stable complex with the bacterial as well as archaeal proteins than the eukaryotic orthologs. Analysis of the docked structures have traced out the ice-binding sites (IBSs) in all the orthologs which continue to facilitate ice-binding activity even after getting mutated with respect to the well-studied IBSs of Typhula ishikariensis and notably, all these mutations performing ice-binding using 'anchored clathrate mechanism' have been found to prefer polar and hydrophilic amino acids. Horizontal gene transfer studies point toward a strong selection pressure favoring independent evolution of the IBPs in some polar organisms including prokaryotes as well as eukaryotes because these proteins facilitate the polar organisms to acclimatize to the adversities in their niche, thus safeguarding their existence.

SigHunt: horizontal gene transfer finder optimized for eukaryotic genomes

MOTIVATION

Genomic islands (GIs) are DNA fragments incorporated into a genome through horizontal gene transfer (also called lateral gene transfer), often with functions novel for a given organism. While methods for their detection are well researched in prokaryotes, the complexity of eukaryotic genomes makes direct utilization of these methods unreliable, and so labour-intensive phylogenetic searches are used instead.

RESULTS

We present a surrogate method that investigates nucleotide base composition of the DNA sequence in a eukaryotic genome and identifies putative GIs. We calculate a genomic signature as a vector of tetranucleotide (4-mer) frequencies using a sliding window approach. Extending the neighbourhood of the sliding window, we establish a local kernel density estimate of the 4-mer frequency. We score the number of 4-mer frequencies in the sliding window that deviate from the credibility interval of their local genomic density using a newly developed discrete interval accumulative score (DIAS). To further improve the effectiveness of DIAS, we select informative 4-mers in a range of organisms using the tetranucleotide quality score developed herein. We show that the SigHunt method is computationally efficient and able to detect GIs in eukaryotic genomes that represent non-ameliorated integration. Thus, it is suited to scanning for change in organisms with different DNA composition.

AVAILABILITY AND IMPLEMENTATION

Source code and scripts freely available for download at http://www.iba.muni.cz/index-en.php?pg=research-data-analysis-tools-sighunt are implemented in C and R and are platform-independent.

CONTACT

376090@mail.muni.cz or martinkova@ivb.cz.

Inferring explicit weighted consensus networks to represent alternative evolutionary histories

BACKGROUND

The advent of molecular biology techniques and constant increase in availability of genetic material have triggered the development of many phylogenetic tree inference methods. However, several reticulate evolution processes, such as horizontal gene transfer and hybridization, have been shown to blur the species evolutionary history by causing discordance among phylogenies inferred from different genes.

METHODS

To tackle this problem, we hereby describe a new method for inferring and representing alternative (reticulate) evolutionary histories of species as an explicit weighted consensus network which can be constructed from a collection of gene trees with or without prior knowledge of the species phylogeny.

RESULTS

We provide a way of building a weighted phylogenetic network for each of the following reticulation mechanisms: diploid hybridization, intragenic recombination and complete or partial horizontal gene transfer. We successfully tested our method on some synthetic and real datasets to infer the above-mentioned evolutionary events which may have influenced the evolution of many species.

CONCLUSIONS

Our weighted consensus network inference method allows one to infer, visualize and validate statistically major conflicting signals induced by the mechanisms of reticulate evolution. The results provided by the new method can be used to represent the inferred conflicting signals by means of explicit and easy-to-interpret phylogenetic networks.

Detection of horizontal gene transfers from phylogenetic comparisons

Bacterial phylogenies have become one of the most important challenges for microbial ecology. This field started in the mid-1970s with the aim of using the sequence of the small subunit ribosomal RNA (16S) tool to infer bacterial phylogenies. Phylogenetic hypotheses based on other sequences usually give conflicting topologies that reveal different evolutionary histories, which in some cases may be the result of horizontal gene transfer events. Currently, one of the major goals of molecular biology is to understand the role that horizontal gene transfer plays in species adaptation and evolution. In this work, we compared the phylogenetic tree based on 16S with the tree based on dszC, a gene involved in the cleavage of carbon-sulfur bonds. Bacteria of several genera perform this survival task when living in environments lacking free mineral sulfur. The biochemical pathway of the desulphurization process was extensively studied due to its economic importance, since this step is expensive and indispensable in fuel production. Our results clearly show that horizontal gene transfer events could be detected using common phylogenetic methods with gene sequences obtained from public sequence databases.

T-REX: a web server for inferring, validating and visualizing phylogenetic trees and networks

T-REX (Tree and reticulogram REConstruction) is a web server dedicated to the reconstruction of phylogenetic trees, reticulation networks and to the inference of horizontal gene transfer (HGT) events. T-REX includes several popular bioinformatics applications such as MUSCLE, MAFFT, Neighbor Joining, NINJA, BioNJ, PhyML, RAxML, random phylogenetic tree generator and some well-known sequence-to-distance transformation models. It also comprises fast and effective methods for inferring phylogenetic trees from complete and incomplete distance matrices as well as for reconstructing reticulograms and HGT networks, including the detection and validation of complete and partial gene transfers, inference of consensus HGT scenarios and interactive HGT identification, developed by the authors. The included methods allows for validating and visualizing phylogenetic trees and networks which can be built from distance or sequence data. The web server is available at: www.trex.uqam.ca.

Using directed phylogenetic networks to retrace species dispersal history

Methods designed for inferring phylogenetic trees have been widely applied to reconstruct biogeographic history. Because traditional phylogenetic methods used in biogeographic reconstruction are based on trees rather than networks, they follow the strict assumption in which dispersal among geographical units have occurred on the basis of single dispersal routes across regions and are, therefore, incapable of modelling multiple alternative dispersal scenarios. The goal of this study is to describe a new method that allows for retracing species dispersal by means of directed phylogenetic networks obtained using a horizontal gene transfer (HGT) detection method as well as to draw parallels between the processes of HGT and biogeographic reconstruction. In our case study, we reconstructed the biogeographic history of the postglacial dispersal of freshwater fishes in the Ontario province of Canada. This case study demonstrated the utility and robustness of the new method, indicating that the most important events were south-to-north dispersal patterns, as one would expect, with secondary faunal interchange among regions. Finally, we showed how our method can be used to explore additional questions regarding the commonalities in dispersal history patterns and phylogenetic similarities among species.