CMAPLE: Efficient Phylogenetic Inference in the Pandemic Era.

We have recently introduced MAPLE (MAximum Parsimonious Likelihood Estimation), a new pandemic-scale phylogenetic inference method exclusively designed for genomic epidemiology. In response to the need for enhancing MAPLE's performance and scalability, here we present two key components: (i) CMAPLE software, a highly optimized C++ reimplementation of MAPLE with many new features and advancements, and (ii) CMAPLE library, a suite of application programming interfaces to facilitate the integration of the CMAPLE algorithm into existing phylogenetic inference packages. Notably, we have successfully integrated CMAPLE into the widely used IQ-TREE 2 software, enabling its rapid adoption in the scientific community. These advancements serve as a vital step toward better preparedness for future pandemics, offering researchers powerful tools for large-scale pathogen genomic analysis.

Order of amino acid recruitment into the genetic code resolved by Last Universal Common Ancestor's protein domains.

The current "consensus" order in which amino acids were added to the genetic code is based on potentially biased criteria such as absence of sulfur-containing amino acids from the Urey-Miller experiment which lacked sulfur. Even if inferred perfectly, abiotic abundance might not reflect abundance in the organisms in which the genetic code evolved. Here, we instead exploit the fact that proteins that emerged prior to the genetic code's completion are likely enriched in early amino acids and depleted in late amino acids. We identify the most ancient protein-coding sequences born prior to the archaeal-bacterial split. Amino acid usage in protein sequences whose ancestors date back to a single homolog in the Last Universal Common Ancestor (LUCA) largely matches the consensus order. However, our findings indicate that metal-binding (cysteine and histidine) and sulfur-containing (cysteine and methionine) amino acids were added to the genetic code much earlier than previously thought. Surprisingly, even more ancient protein sequences - those that had already diversified into multiple distinct copies in LUCA - show a different pattern to single copy LUCA sequences: significantly less depleted in the late amino acids tryptophan and tyrosine, and enriched rather than depleted in phenylalanine. This is compatible with at least some of these sequences predating the current genetic code. Their distinct enrichment patterns thus provide hints about earlier, alternative genetic codes.

MAST: Phylogenetic Inference with Mixtures Across Sites and Trees.

Hundreds or thousands of loci are now routinely used in modern phylogenomic studies. Concatenation approaches to tree inference assume that there is a single topology for the entire dataset, but different loci may have different evolutionary histories due to incomplete lineage sorting, introgression, and/or horizontal gene transfer; even single loci may not be treelike due to recombination. To overcome this shortcoming, we introduce an implementation of a multi-tree mixture model that we call MAST. This model extends a prior implementation by Boussau et al. (2009) by allowing users to estimate the weight of each of a set of pre-specified bifurcating trees in a single alignment. The MAST model allows each tree to have its own weight, topology, branch lengths, substitution model, nucleotide or amino acid frequencies, and model of rate heterogeneity across sites. We implemented the MAST model in a maximum-likelihood framework in the popular phylogenetic software, IQ-TREE. Simulations show that we can accurately recover the true model parameters, including branch lengths and tree weights for a given set of tree topologies, under a wide range of biologically realistic scenarios. We also show that we can use standard statistical inference approaches to reject a single-tree model when data are simulated under multiple trees (and vice versa). We applied the MAST model to multiple primate datasets and found that it can recover the signal of incomplete lineage sorting in the Great Apes, as well as the asymmetry in minor trees caused by introgression among several macaque species. When applied to a dataset of four Platyrrhine species for which standard concatenated maximum likelihood and gene tree approaches disagree, we observe that MAST gives the highest weight (i.e. the largest proportion of sites) to the tree also supported by gene tree approaches. These results suggest that the MAST model is able to analyse a concatenated alignment using maximum likelihood, while avoiding some of the biases that come with assuming there is only a single tree. We discuss how the MAST model can be extended in the future.

AliSim-HPC: parallel sequence simulator for phylogenetics.

MOTIVATION: Sequence simulation plays a vital role in phylogenetics with many applications, such as evaluating phylogenetic methods, testing hypotheses, and generating training data for machine-learning applications. We recently introduced a new simulator for multiple sequence alignments called AliSim, which outperformed existing tools. However, with the increasing demands of simulating large data sets, AliSim is still slow due to its sequential implementation; for example, to simulate millions of sequence alignments, AliSim took several days or weeks. Parallelization has been used for many phylogenetic inference methods but not yet for sequence simulation. RESULTS: This paper introduces AliSim-HPC, which, for the first time, employs high-performance computing for phylogenetic simulations. AliSim-HPC parallelizes the simulation process at both multi-core and multi-CPU levels using the OpenMP and message passing interface (MPI) libraries, respectively. AliSim-HPC is highly efficient and scalable, which reduces the runtime to simulate 100 large gap-free alignments (30 000 sequences of one million sites) from over one day to 11 min using 256 CPU cores from a cluster with six computing nodes, a 153-fold speedup. While the OpenMP version can only simulate gap-free alignments, the MPI version supports insertion-deletion models like the sequential AliSim. AVAILABILITY AND IMPLEMENTATION: AliSim-HPC is open-source and available as part of the new IQ-TREE version v2.2.3 at https://github.com/iqtree/iqtree2/releases with a user manual at http://www.iqtree.org/doc/AliSim.

DecentTree: scalable Neighbour-Joining for the genomic era.

MOTIVATION: Neighbour-Joining is one of the most widely used distance-based phylogenetic inference methods. However, current implementations do not scale well for datasets with more than 10 000 sequences. Given the increasing pace of generating new sequence data, particularly in outbreaks of emerging diseases, and the already enormous existing databases of sequence data for which Neighbour-Joining is a useful approach, new implementations of existing methods are warranted. RESULTS: Here, we present DecentTree, which provides highly optimized and parallel implementations of Neighbour-Joining and several of its variants. DecentTree is designed as a stand-alone application and a header-only library easily integrated with other phylogenetic software (e.g. it is integral in the popular IQ-TREE software). We show that DecentTree shows similar or improved performance over existing software (BIONJ, Quicktree, FastME, and RapidNJ), especially for handling very large alignments. For example, DecentTree is up to 6-fold faster than the fastest existing Neighbour-Joining software (e.g. RapidNJ) when generating a tree of 64 000 SARS-CoV-2 genomes. AVAILABILITY AND IMPLEMENTATION: DecentTree is open source and freely available at https://github.com/iqtree/decenttree. All code and data used in this analysis are available on Github (https://github.com/asdcid/Comparison-of-neighbour-joining-software).

Maximum likelihood pandemic-scale phylogenetics.

Phylogenetics has a crucial role in genomic epidemiology. Enabled by unparalleled volumes of genome sequence data generated to study and help contain the COVID-19 pandemic, phylogenetic analyses of SARS-CoV-2 genomes have shed light on the virus's origins, spread, and the emergence and reproductive success of new variants. However, most phylogenetic approaches, including maximum likelihood and Bayesian methods, cannot scale to the size of the datasets from the current pandemic. We present 'MAximum Parsimonious Likelihood Estimation' (MAPLE), an approach for likelihood-based phylogenetic analysis of epidemiological genomic datasets at unprecedented scales. MAPLE infers SARS-CoV-2 phylogenies more accurately than existing maximum likelihood approaches while running up to thousands of times faster, and requiring at least 100 times less memory on large datasets. This extends the reach of genomic epidemiology, allowing the continued use of accurate phylogenetic, phylogeographic and phylodynamic analyses on datasets of millions of genomes.

Alpha-Glucosidase Inhibitory Activity of Saponins Isolated from Vernonia gratiosa Hance.

Species belonging to the Vernonia (Asteraceae), the largest genus in the tribe Vernonieae (consisting of about 1,000 species), are widely used in food and medicine. These plants are rich sources of bioactive sesquiterpene lactones and steroid saponins, likely including many as yet undiscovered chemical components. A phytochemical investigation resulted in the separation of three new stigmastane-type steroidal saponins (1 - 3), designated as vernogratiosides A-C, from whole plants of V. gratiosa. Their structures were elucidated based on infrared spectroscopy (IR), one-dimensional (1D) and two-dimensional nuclear magnetic resonance (2D NMR), high-resolution electrospray ionization mass spectrometry (HR-ESI-MS), and electronic circular dichroism analyses (ECD), as well as chemical reactivity. Molecular docking analysis of representative saponins with α-glucosidase inhibitory activity was performed. Additionally, the intended substances were tested for their ability to inhibit α-glucosidase activity in a laboratory setting. The results suggested that stigmastane-type steroidal saponins from V. gratiosa are promising candidate antidiabetic agents.

Atractylodes macrocephala Rhizomes Contain Anti-inflammatory Sesquiterpenes.

Two new compounds, named eudesm-4(15),7-diene-3α,9ß,11-triol (1) and eudesm-4(15),7-diene-1ß,3α,9ß,11-tetraol (2) together with three known sesquiterpene lactones (1S,5R,7R,10R)-secoatractylolactone (3), (1S,5R,7R,10R)-secoatractylolactone-11-O-ß-D-glucopyranoside (4) atractylenolide III (5) were isolated from the rhizomes of Atractylodes macrocephala. Their structures were elucidated by using one-dimensional (1D) and 2D-NMR spectra and high resolution electrospray ionization (HR-ESI)-MS data. Compound 5 exhibited the most active anti-inflammatory activity with IC50 values of 27.5 µM in inhibiting of nitric oxide production. Compounds 1, 2, and 3 showed moderate effects while compound 4 was inactive.

Updated site concordance factors minimize effects of homoplasy and taxon sampling.

MOTIVATION: Site concordance factors (sCFs) have become a widely used way to summarize discordance in phylogenomic datasets. However, the original version of sCFs was calculated by sampling a quartet of tip taxa and then applying parsimony-based criteria for discordance. This approach has the potential to be strongly affected by multiple hits at a site (homoplasy), especially when substitution rates are high or taxa are not closely related. RESULTS: Here, we introduce a new method for calculating sCFs. The updated version uses likelihood to generate probability distributions of ancestral states at internal nodes of the phylogeny. By sampling from the states at internal nodes adjacent to a given branch, this approach substantially reduces-but does not abolish-the effects of homoplasy and taxon sampling. AVAILABILITY AND IMPLEMENTATION: Updated sCFs are implemented in IQ-TREE 2.2.2. The software is freely available at https://github.com/iqtree/iqtree2/releases. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Design of novel p-n heterojunction ZnBi2O4-ZnS photocatalysts with impressive photocatalytic and antibacterial activities under visible light.

Heterojunction structures have attracted considerable attention for enhancing electron migration across interfaces. In this report, ZnBi2O4-ZnS(12%) heterojunction photocatalysts was found to be capable of degrading over 94% of indigo carmine in a 15 mg/L solution within 90 min of visible light irradiation at a catalytic dose of 1.0 g/L and pH 4. Furthermore, more than 82% of the total organic carbon (TOC) was removed, confirming the almost complete mineralization of the indigo carmine by ZnBi2O4-ZnS(12%). Moreover, the photocatalyst exhibited high stability and retained its photocatalytic activity up to the 5th cycle of operation without photocorrosion. The dramatic enhancement in the visible-light photocatalytic performance of the ZnBi2O4-ZnS heterojunctions over pristine ZnBi2O4 and ZnS was due to the formation of a superior heterojunction between the n-type semiconductor, ZnS, and the p-type semiconductor, ZnBi2O4. This heterojunction facilitated the separation and transfer of the photoinduced electron at the interfaces of the two semiconductors. Furthermore, the ZnBi2O4-ZnS(12%) exhibited an inhibition zone of 15 mm against fecal Escherichia coli (ATCC 8739), with a minimum inhibitory concentration (MIC) of 150 µg/mL. These results demonstrated that the novel ZnBi2O4-ZnS p-n-type heterojunction is a promising visible-light active photo-catalyst for the degradation of organic pollutants and inhibition of fecal E. coli.

AliSim: A Fast and Versatile Phylogenetic Sequence Simulator for the Genomic Era.

Sequence simulators play an important role in phylogenetics. Simulated data has many applications, such as evaluating the performance of different methods, hypothesis testing with parametric bootstraps, and, more recently, generating data for training machine-learning applications. Many sequence simulation programmes exist, but the most feature-rich programmes tend to be rather slow, and the fastest programmes tend to be feature-poor. Here, we introduce AliSim, a new tool that can efficiently simulate biologically realistic alignments under a large range of complex evolutionary models. To achieve high performance across a wide range of simulation conditions, AliSim implements an adaptive approach that combines the commonly used rate matrix and probability matrix approaches. AliSim takes 1.4 h and 1.3 GB RAM to simulate alignments with one million sequences or sites, whereas popular software Seq-Gen, Dawg, and INDELible require 2-5 h and 50-500 GB of RAM. We provide AliSim as an extension of the IQ-TREE software version 2.2, freely available at www.iqtree.org, and a comprehensive user tutorial at http://www.iqtree.org/doc/AliSim.

Maximum likelihood pandemic-scale phylogenetics.

Phylogenetics plays a crucial role in the interpretation of genomic data1. Phylogenetic analyses of SARS-CoV-2 genomes have allowed the detailed study of the virus's origins2, of its international3,4 and local4-9 spread, and of the emergence10 and reproductive success11 of new variants, among many applications. These analyses have been enabled by the unparalleled volumes of genome sequence data generated and employed to study and help contain the pandemic12. However, preferred model-based phylogenetic approaches including maximum likelihood and Bayesian methods, mostly based on Felsenstein's 'pruning' algorithm13,14, cannot scale to the size of the datasets from the current pandemic4,15, hampering our understanding of the virus's evolution and transmission16. We present new approaches, based on reworking Felsenstein's algorithm, for likelihood-based phylogenetic analysis of epidemiological genomic datasets at unprecedented scales. We exploit near-certainty regarding ancestral genomes, and the similarities between closely related and densely sampled genomes, to greatly reduce computational demands for memory and time. Combined with new methods for searching amongst candidate evolutionary trees, this results in our MAPLE ('MAximum Parsimonious Likelihood Estimation') software giving better results than popular approaches such as FastTree 217, IQ-TREE 218, RAxML-NG19 and UShER15. Our approach therefore allows complex and accurate probabilistic phylogenetic analyses of millions of microbial genomes, extending the reach of genomic epidemiology. Future epidemiological datasets are likely to be even larger than those currently associated with COVID-19, and other disciplines such as metagenomics and biodiversity science are also generating huge numbers of genome sequences20-22. Our methods will permit continued use of preferred likelihood-based phylogenetic analyses.

nQMaker: Estimating Time Nonreversible Amino Acid Substitution Models.

Amino acid substitution models are a key component in phylogenetic analyses of protein sequences. All commonly used amino acid models available to date are time-reversible, an assumption designed for computational convenience but not for biological reality. Another significant downside to time-reversible models is that they do not allow inference of rooted trees without outgroups. In this article, we introduce a maximum likelihood approach nQMaker, an extension of the recently published QMaker method, that allows the estimation of time nonreversible amino acid substitution models and rooted phylogenetic trees from a set of protein sequence alignments. We show that the nonreversible models estimated with nQMaker are a much better fit to empirical alignments than pre-existing reversible models, across a wide range of data sets including mammals, birds, plants, fungi, and other taxa, and that the improvements in model fit scale with the size of the data set. Notably, for the recently published plant and bird trees, these nonreversible models correctly recovered the commonly estimated root placements with very high-statistical support without the need to use an outgroup. We provide nQMaker as an easy-to-use feature in the IQ-TREE software (http://www.iqtree.org), allowing users to estimate nonreversible models and rooted phylogenies from their own protein data sets. The data sets and scripts used in this article are available at https://doi.org/10.5061/dryad.3tx95x6hx. [amino acid sequence analyses; amino acid substitution models; maximum likelihood model estimation; nonreversible models; phylogenetic inference; reversible models.].

A Comprehensive Phylogenetic Analysis of the Serpin Superfamily.

Serine protease inhibitors (serpins) are found in all kingdoms of life and play essential roles in multiple physiological processes. Owing to the diversity of the superfamily, phylogenetic analysis is challenging and prokaryotic serpins have been speculated to have been acquired from Metazoa through horizontal gene transfer due to their unexpectedly high homology. Here, we have leveraged a structural alignment of diverse serpins to generate a comprehensive 6,000-sequence phylogeny that encompasses serpins from all kingdoms of life. We show that in addition to a central "hub" of highly conserved serpins, there has been extensive diversification of the superfamily into many novel functional clades. Our analysis indicates that the hub proteins are ancient and are similar because of convergent evolution, rather than the alternative hypothesis of horizontal gene transfer. This work clarifies longstanding questions in the evolution of serpins and provides new directions for research in the field of serpin biology.

QMaker: Fast and Accurate Method to Estimate Empirical Models of Protein Evolution.

Amino acid substitution models play a crucial role in phylogenetic analyses. Maximum likelihood (ML) methods have been proposed to estimate amino acid substitution models; however, they are typically complicated and slow. In this article, we propose QMaker, a new ML method to estimate a general time-reversible $Q$ matrix from a large protein data set consisting of multiple sequence alignments. QMaker combines an efficient ML tree search algorithm, a model selection for handling the model heterogeneity among alignments, and the consideration of rate mixture models among sites. We provide QMaker as a user-friendly function in the IQ-TREE software package (http://www.iqtree.org) supporting the use of multiple CPU cores so that biologists can easily estimate amino acid substitution models from their own protein alignments. We used QMaker to estimate new empirical general amino acid substitution models from the current Pfam database as well as five clade-specific models for mammals, birds, insects, yeasts, and plants. Our results show that the new models considerably improve the fit between model and data and in some cases influence the inference of phylogenetic tree topologies.[Amino acid replacement matrices; amino acid substitution models; maximum likelihood estimation; phylogenetic inferences.].

Primate phylogenomics uncovers multiple rapid radiations and ancient interspecific introgression.

Our understanding of the evolutionary history of primates is undergoing continual revision due to ongoing genome sequencing efforts. Bolstered by growing fossil evidence, these data have led to increased acceptance of once controversial hypotheses regarding phylogenetic relationships, hybridization and introgression, and the biogeographical history of primate groups. Among these findings is a pattern of recent introgression between species within all major primate groups examined to date, though little is known about introgression deeper in time. To address this and other phylogenetic questions, here, we present new reference genome assemblies for 3 Old World monkey (OWM) species: Colobus angolensis ssp. palliatus (the black and white colobus), Macaca nemestrina (southern pig-tailed macaque), and Mandrillus leucophaeus (the drill). We combine these data with 23 additional primate genomes to estimate both the species tree and individual gene trees using thousands of loci. While our species tree is largely consistent with previous phylogenetic hypotheses, the gene trees reveal high levels of genealogical discordance associated with multiple primate radiations. We use strongly asymmetric patterns of gene tree discordance around specific branches to identify multiple instances of introgression between ancestral primate lineages. In addition, we exploit recent fossil evidence to perform fossil-calibrated molecular dating analyses across the tree. Taken together, our genome-wide data help to resolve multiple contentious sets of relationships among primates, while also providing insight into the biological processes and technical artifacts that led to the disagreements in the first place.

Newly Emerged Serotype 1c of Shigella flexneri: Multiple Origins and Changing Drug Resistance Landscape.

Bacillary dysentery caused by Shigella flexneri is a major cause of under-five mortality in developing countries, where a novel S. flexneri serotype 1c has become very common since the 1980s. However, the origin and diversification of serotype 1c remain poorly understood. To understand the evolution of serotype 1c and their antimicrobial resistance, we sequenced and analyzed the whole-genome of 85 clinical isolates from the United Kingdom, Egypt, Bangladesh, Vietnam, and Japan belonging to serotype 1c and related serotypes of 1a, 1b and Y/Yv. We identified up to three distinct O-antigen modifying genes in S. flexneri 1c strains, which were acquired from three different bacteriophages. Our analysis shows that S. flexneri 1c strains have originated from serotype 1a and serotype 1b strains after the acquisition of bacteriophage-encoding gtrIc operon. The maximum-likelihood phylogenetic analysis using core genes suggests two distinct S. flexneri 1c lineages, one specific to Bangladesh, which originated from ancestral serotype 1a strains and the other from the United Kingdom, Egypt, and Vietnam originated from ancestral serotype 1b strains. We also identified 63 isolates containing multiple drug-resistant genes in them conferring resistance against streptomycin, sulfonamide, quinolone, trimethoprim, tetracycline, chloramphenicol, and beta-lactamase. Furthermore, antibiotic susceptibility assays showed 83 (97.6%) isolates as either complete or intermediate resistance to the WHO-recommended first- and second-line drugs. This changing drug resistance pattern demonstrates the urgent need for drug resistance surveillance and renewed treatment guidelines.