Phylogenetic Analyses: A Toolbox Expanding towards Bayesian Methods

The reconstruction of phylogenies is becoming an increasingly simple activity. This is mainly due to two reasons: the democratization of computing power and the increased availability of sophisticated yet user-friendly software. This review describes some of the latest additions to the phylogenetic toolbox, along with some of their theoretical and practical limitations. It is shown that Bayesian methods are under heavy development, as they offer the possibility to solve a number of long-standing issues and to integrate several steps of the phylogenetic analyses into a single framework. Specific topics include not only phylogenetic reconstruction, but also the comparison of phylogenies, the detection of adaptive evolution, and the estimation of divergence times between species

Mining-impacted rice paddies select for Archaeal methylators and reveal a putative (Archaeal) regulator of mercury methylation

ABSTRACT: Methylmercury (MeHg) is a microbially produced neurotoxin derived from inorganic mercury (Hg), which accumulation in rice represents a major health concern to humans. However, the microbial control of MeHg dynamics in the environment remains elusive. Here, leveraging three rice paddy fields with distinct concentrations of Hg (Total Hg (THg): 0.21−513 mg kg−1 dry wt. soil; MeHg: 1.21−6.82 ng g−1 dry wt. soil), we resorted to metagenomics to determine the microbial determinants involved in MeHg production under contrasted contamination settings. We show that Hg methylating Archaea, along with methane-cycling genes, were enriched in severely contaminated paddy soils. Metagenome-resolved Genomes of novel putative Hg methylators belonging to Nitrospinota (UBA7883), with poorly resolved taxonomy despite high completeness, showed evidence of facultative anaerobic metabolism and adaptations to fluctuating redox potential. Furthermore, we found evidence of environmental filtering effects that influenced the phylogenies of not only hgcA genes under different THg concentrations, but also of two housekeeping genes, rpoB and glnA, highlighting the need for further experimental validation of whether THg drives the evolution of hgcAB. Finally, assessment of the genomic environment surrounding hgcAB suggests that this gene pair may be regulated by an archaeal toxin-antitoxin (TA) system, instead of the more frequently found arsR-like genes in bacterial methylators. This suggests the presence of distinct hgcAB regulation systems in bacteria and archaea. Our results support the emerging role of Archaea in MeHg cycling under mining-impacted environments and shed light on the differential control of the expression of genes involved in MeHg formation between Archaea and Bacteria

Dating Phylogenies with Hybrid Local Molecular Clocks

BACKGROUND: Because rates of evolution and species divergence times cannot be estimated directly from molecular data, all current dating methods require that specific assumptions be made before inferring any divergence time. These assumptions typically bear either on rates of molecular evolution (molecular clock hypothesis, local clocks models) or on both rates and times (penalized likelihood, Bayesian methods). However, most of these assumptions can affect estimated dates, oftentimes because they underestimate large amounts of rate change. PRINCIPAL FINDINGS: A significant modification to a recently proposed ad hoc rate-smoothing algorithm is described, in which local molecular clocks are automatically placed on a phylogeny. This modification makes use of hybrid approaches that borrow from recent theoretical developments in microarray data analysis. An ad hoc integration of phylogenetic uncertainty under these local clock models is also described. The performance and accuracy of the new methods are evaluated by reanalyzing three published data sets. CONCLUSIONS: It is shown that the new maximum likelihood hybrid methods can perform better than penalized likelihood and almost as well as uncorrelated Bayesian models. However, the new methods still tend to underestimate the actual amount of rate change. This work demonstrates the difficulty of estimating divergence times using local molecular clocks

The Metabolic Consequences of Hepatic AMP-Kinase Phosphorylation in Rainbow Trout

AMP-activated protein kinase (AMPK), a phylogenetically conserved serine/threonine protein kinase, is proposed to function as a “fuel gauge” to monitor cellular energy status in response to nutritional environmental variations. However, in fish, few studies have addressed the metabolic consequences related to the activation of this kinase. This study demonstrates that the rainbow trout (Oncorhynchus mykiss) possesses paralogs of the three known AMPK subunits that co-diversified, that the AMPK protein is present in the liver and in isolated hepatocytes, and it does change in response to physiological (fasting-re-feeding cycle) and pharmacological (AICAR and metformin administration and incubations) manipulations. Moreover, the phosphorylation of AMPK results in the phosphorylation of acetyl-CoA carboxylase, a main downstream target of AMPK in mammals. Other findings include changes in hepatic glycogen levels and several molecular actors involved in hepatic glucose and lipid metabolism, including mRNA transcript levels for glucokinase, glucose-6-phosphatase and fatty acid synthase both in vivo and in vitro. The fact that most results presented in this study are consistent with the recognized role of AMPK as a master regulator of energy homeostasis in living organisms supports the idea that these functions are conserved in this piscine model

The nonadaptive nature of the H1N1 2009 Swine Flu pandemic contrasts with the adaptive facilitation of transmission to a new host

<p>Abstract</p> <p>Background</p> <p>The emergence of the 2009 H1N1 Influenza pandemic followed a multiple reassortment event from viruses originally circulating in swines and humans, but the adaptive nature of this emergence is poorly understood.</p> <p>Results</p> <p>Here we base our analysis on 1180 complete genomes of H1N1 viruses sampled in North America between 2000 and 2010 in swine and human hosts. We show that while transmission to a human host might require an adaptive phase in the HA and NA antigens, the emergence of the 2009 pandemic was essentially nonadaptive. A more detailed analysis of the NA protein shows that the 2009 pandemic sequence is characterized by novel epitopes and by a particular substitution in loop 150, which is responsible for a nonadaptive structural change tightly associated with the emergence of the pandemic.</p> <p>Conclusions</p> <p>Because this substitution was not present in the 1918 H1N1 pandemic virus, we posit that the emergence of pandemics is due to epistatic interactions between sites distributed over different segments. Altogether, our results are consistent with population dynamics models that highlight the epistatic and nonadaptive rise of novel epitopes in viral populations, followed by their demise when the resulting virus is too virulent.</p

Early Evolution of Ionotropic GABA Receptors and Selective Regimes Acting on the Mammalian-Specific Theta and Epsilon Subunits

BACKGROUND: The amino acid neurotransmitter GABA is abundant in the central nervous system (CNS) of both invertebrates and vertebrates. Receptors of this neurotransmitter play a key role in important processes such as learning and memory. Yet, little is known about the mode and tempo of evolution of the receptors of this neurotransmitter. Here, we investigate the phylogenetic relationships of GABA receptor subunits across the chordates and detail their mode of evolution among mammals. PRINCIPAL FINDINGS: Our analyses support two major monophyletic clades: one clade containing GABA(A) receptor alpha, gamma, and epsilon subunits, and another one containing GABA(A) receptor rho, beta, delta, theta, and pi subunits. The presence of GABA receptor subunits from each of the major clades in the Ciona intestinalis genome suggests that these ancestral duplication events occurred before the divergence of urochordates. However, while gene divergence proceeded at similar rates on most receptor subunits, we show that the mammalian-specific subunits theta and epsilon experienced an episode of positive selection and of relaxed constraints, respectively, after the duplication event. Sites putatively under positive selection are placed on a three-dimensional model obtained by homology-modeling. CONCLUSIONS: Our results suggest an early divergence of the GABA receptor subunits, before the split from urochordates. We show that functional changes occurred in the lineages leading to the mammalian-specific subunit theta, and we identify the amino acid sites putatively responsible for the functional divergence. We discuss potential consequences for the evolution of mammals and of their CNS

Machine Learning Algorithms Associate Case Numbers with SARS-CoV-2 Variants Rather Than with Impactful Mutations

During the SARS-CoV-2 pandemic, much effort has been geared towards creating models to predict case numbers. These models typically rely on epidemiological data, and as such overlook viral genomic information, which could be assumed to improve predictions, as different variants show varying levels of virulence. To test this hypothesis, we implemented simple models to predict future case numbers based on the genomic sequences of the Alpha and Delta variants, which were co-circulating in Texas and Minnesota early during the pandemic. Sequences were encoded, matched with case numbers at a future time based on collection date, and used to train two algorithms: one based on random forests and one based on a feed-forward neural network. While prediction accuracies were ≥93%, explainability analyses showed that the models were not associating case numbers with mutations known to have an impact on virulence, but with individual variants. This work highlights the necessity of gaining a better understanding of the data used for training and of conducting explainability analysis to assess whether model predictions are misleading

Phylodynamics of the Emergence of Influenza Viruses after Cross-Species Transmission

<div><p>Human populations are constantly exposed to emerging pathogens such as influenza A viruses that result from cross-species transmissions. Generally these sporadic events are evolutionary dead-ends, but occasionally, viruses establish themselves in a new host that offers a novel genomic context to which the virus must adjust to avoid attenuation. However, the dynamics of this process are unknown. Here we present a novel method to characterize the time it takes to G+C composition at third codon positions (GC3 content) of influenza viruses to adjust to that of a new host. We compare the inferred dynamics in two subtypes, H1N1 and H3N2, based on complete genomes of viruses circulating in humans, swine and birds between 1900–2009. Our results suggest that both subtypes have the same fast-adjusting genes, which are not necessarily those with the highest absolute rates of evolution, but those with the most relaxed selective pressures. Our analyses reveal that NA and NS2 genes adjust the fastest to a new host and that selective pressures of H3N2 viruses are relaxed faster than for H1N1. The asymmetric nature of these processes suggests that viruses with the greatest adjustment potential to humans are coming from both birds and swine for H3N2, but only from birds for H1N1.</p></div