Biology subjects

Szöllosi, G. J.

Publications and source records attributed to Szöllosi, G. J..

9 recordsLinked to original sources

bioRxiv2026

Improved ancestral genome reconstruction using a learned gene-content grammar

Ancestral gene content inferences allow inferring the set of genes - and by extension, the cellular features and metabolic capabilities - of ancestral organisms, based on data from modern genomes. Current methods differ in their approach to ancestral inferences and the kinds of errors they make: reconciliation methods map gene trees onto species trees, and tend to under-estimate ancestral contents due to phylogenetic noise; profile methods model the evolution of phylogenetic profiles (presence-absence or count data) on the species tree, and tend to return inflated ancestors because they ignore gene trees and as a result can only account for horizontal gene transfer (HGT) in a limited manner. For reasons of tractability, both approaches also share a core limitation: neither uses the fact that genes do not act alone but belong to operons, protein complexes, and metabolic pathways that may be gained and lost together or experience shared selective constraints. Here, we show that this context - the grammar of gene content - provides a rich source of information that can be used to greatly improve ancestral gene content inference and metabolic reconstruction under both the reconciliation- and profile-based approaches. We model this structure as an Ising model and infer its parameters from 113,104 bacterial and archaeal genomes (one per species representative in GTDB). We validate the model on extant taxa using phylum-level holdout (i.e. using test data from different prokaryotic phyla than training data), showing that it can accurately "denoise", i.e., reconstruct gene repertoires from highly fragmented and noisy input data, learning about protein-protein interactions and gene essentiality during the training process. When applied to ancestral reconstructions, the denoiser fills gaps in conservative reconstructions and removes excess genes from overly-generous ones, such that different reconstruction methods converge to broadly concordant conclusions. By using this gene content grammar, patchy method-dependent ancestral reconstructions can be turned into organism-like ones, and yield agreement on the gene families, cell-biological features, and metabolic capabilities of the deepest nodes in the tree of life.

evolutionary biology↗

bioRxiv2023

An evolutionary timescale for Bacteria calibrated using the Great Oxidation Event

Most of lifes diversity and history is microbial but it has left a meagre fossil record, greatly hindering understanding of evolution in deep time. However, the co-evolution of life and the Earth system has left signatures of bacterial metabolism in the geochemical record, most conspicuously the Great Oxidation Event (GOE) [~]2.33 billion years ago (Ga, (Poulton et al. 2021)), in which oxygenic photosynthesis and tectonism (Eguchi, Seales, and Dasgupta 2019) transformed Earths biosphere from dominantly anaerobic to aerobic. Here, we combine machine learning and phylogenetic reconciliation to infer ancestral transitions to aerobic lifestyles during bacterial evolution. Linking these transitions to the GOE provides new constraints to infer the timetree of Bacteria. We find that extant bacterial phyla are truly ancient, having radiated in the Archaean and the Proterozoic: the oldest include Bacillota (Firmicutes), which radiated 3.1-3.7 Ga, Cyanobacteria (3.3-3.5 Ga) and Patescibacteria (3-3.5 Ga). We show that most bacterial phyla were ancestrally anaerobic and that most transitions to an aerobic lifestyle post-dated the GOE. Our analyses trace oxygen production and consumption back to Cyanobacteria. From that starting point, horizontal transfer seeded aerobic lifestyles across bacterial diversity over hundreds of millions of years. Our analyses demonstrate that the diversification of aerobes proceeded in two waves corresponding to the GOE and to a second sustained rise in atmospheric O2 at the dawn of the Palezoic (Krause et al. 2022).

evolutionary biology↗

bioRxiv2022

Compositionally constrained sites drive long branch attraction

AO_SCPLOWBSTRACTC_SCPLOWAccurate phylogenies are fundamental to our understanding of the pattern and process of evolution. Yet, phylogenies at deep evolutionary timescales, with correspondingly long branches, have been fraught with controversy resulting from conflicting estimates from models with varying complexity and goodness of fit. Analyses of historical as well as current empirical datasets, such as alignments including Microsporidia, Nematoda or Platyhelminthes, have demonstrated that inadequate modeling of across-site compositional heterogeneity, which is the result of biochemical constraints that lead to varying patterns of accepted amino acids along sequences, can lead to erroneous topologies that are strongly supported. Unfortunately, models that adequately account for across-site compositional heterogeneity remain computationally challenging or intractable for an increasing fraction of contemporary datasets. Here, we introduce "compositional constraint analysis", a method to investigate the effect of site-specific constraints on amino acid composition on phylogenetic inference. We show that more constrained sites with lower diversity and less constrained sites with higher diversity exhibit ostensibly conflicting signal under models ignoring across-site compositional heterogeneity that lead to long branch attraction artifacts and demonstrate that more complex models accounting for across-site compositional heterogeneity can ameliorate this bias. We present CAT-PMSF, a pipeline for diagnosing and resolving phylogenetic bias resulting from inadequate modeling of across-site compositional heterogeneity based on the CAT model. CAT-PMSF is robust against long branch attraction in all alignments we have examined. We suggest using CAT-PMSF when convergence of the CAT model cannot be assured. We find evidence that compositionally constrained sites are driving long branch attraction in two metazoan datasets and recover evidence for Porifera as the sister group to all other animals.

evolutionary biology↗

bioRxiv2021

Divergent evolutionary trajectories of bryophytes and tracheophytes from a complex common ancestor of land plants

The origin of plants and their colonization of land resulted in the transformation of the terrestrial environment. Here we investigate the evolution of the land plants (embryophytes) and their two main lineages, the tracheophytes (vascular plants) and bryophytes (non-vascular plants). We used new fossil calibrations, relative lineage dating implied by horizontal gene transfer, and new phylogenomic methods for mapping gene family origins. Distinct rooting strategies resolve tracheophytes and bryophytes as monophyletic sister groups that diverged during the Cambrian, 515-494 Ma. The embryophyte stem is characterised by a burst of gene innovation, while bryophytes subsequently experienced a no less dramatic episode of reductive genome evolution in which they lost genes associated with the elaboration of vasculature and the stomatal complex. Overall, our analyses confirm that extant tracheophytes and bryophytes are both highly derived; as a result, understanding the origin of land plants requires tracing character evolution across the diversity of modern lineages.

evolutionary biology↗

bioRxiv2021

Simultaneous estimation of per cell division mutation rate and turnover rate from bulk tumour sequence data

Tumors often harbor orders of magnitude more mutations than healthy tissues. The increased number of mutations may be due to an elevated mutation rate or frequent cell death and correspondingly rapid cell turnover, or a combination of the two. It is difficult to disentangle these two mechanisms based on widely available bulk sequencing data, where sequences from individual cells are intermixed and, thus, the cell lineage tree of the tumor cannot be resolved. Here we present a method that can simultaneously estimate the cell turnover rate and the rate of mutations from bulk sequencing data. Our method works by simulating tumor growth and finding the parameters with which the observed data can be reproduced with maximum likelihood. Applying this method to a real tumor sample, we find that both the mutation rate and the frequency of death may be high. Author SummaryTumors frequently harbor an elevated number of mutations, compared to healthy tissue. These extra mutations may be generated either by an increased mutation rate or the presence of cell death resulting in increased cellular turnover and additional cell divisions for tumor growth. Separating the effects of these two factors is a nontrivial problem. Here we present a method which can simultaneously estimate cell turnover rate and genomic mutation rate from bulk sequencing data. Our method is based on the estimation of the parameters of a generative model of tumor growth and mutations. Applying our method to a human hepatocellular carcinoma sample reveals an elevated per cell division mutation rate and high cell turnover.

bioinformatics↗

bioRxiv2021

How plants minimize somatic evolution

A remarkable property of plants is their ability to accumulate mutations at a very slow pace despite their potentially long lifespans, during which they continually form buds, each with the potential to become a new branch. Because replication errors in cell division represent an unavoidable source of mutations, minimizing mutation accumulation requires the minimization of cell divisions. Here we show that there exists a well defined theoretical minimum for the branching cost, defined as the number of cell divisions necessary for the creation of each branch. Most importantly, we also show that this theoretical minimum can be closely approached by a simple pattern of cell divisions in the meristematic tissue of apical buds during the generation of novel buds. Both the optimal pattern of cell divisions and the associated branching cost are consistent with recent experimental data, suggesting that plant evolution has led to the discovery of this mechanism.

evolutionary biology↗

bioRxiv2021

Universal markers support a long inter-domain branch between Archaea and Bacteria

Core gene phylogenies provide a window into early evolution, but different gene sets and analytical methods have yielded substantially different views of the tree of life. Trees inferred from a small set of universal core genes have typically supported a long branch separating the archaeal and bacterial domains. By contrast, recent analyses of a broader set of non-ribosomal genes have suggested that Archaea may be less divergent from Bacteria, and that estimates of inter-domain distance are inflated due to accelerated evolution of ribosomal proteins along the inter-domain branch. Resolving this debate is key to determining the diversity of the archaeal and bacterial domains, the shape of the tree of life, and our understanding of the early course of cellular evolution. Here, we investigate the evolutionary history of the marker genes key to the debate. We show that estimates of a reduced Archaea-Bacteria (AB) branch length result from inter-domain gene transfers and hidden paralogy in the expanded marker gene set. By contrast, analysis of a broad range of manually curated marker gene datasets from an evenly sampled set of 700 Archaea and Bacteria reveal that current methods likely underestimate the AB branch length due to substitutional saturation and poor model fit; that the best-performing phylogenetic markers tend to support longer inter-domain branch lengths; and that the AB branch lengths of ribosomal and non-ribosomal marker genes are statistically indistinguishable. Furthermore, our phylogeny inferred from the 27 highest-ranked marker genes recovers a clade of DPANN at the base of the Archaea, and places CPR within Bacteria as the sister group to the Chloroflexota.

evolutionary biology↗

bioRxiv2020

Trade-off between reducing mutational load and increasing commitment to differentiation determines tissue organization

Species-specific differences control cancer risk across orders of magnitude variation in body size and lifespan, e.g., by varying the copy numbers of tumor suppressor genes. It is unclear, however, how different tissues within an organism can control somatic evolution despite being subject to markedly different constraints, but sharing the same genome. Hierarchical differentiation, characteristic of self-renewing tissues, can restrain somatic evolution both by limiting divisional load, thereby reducing mutation accumulation, and by increasing cells commitment to differentiation, which can "wash out" mutants. Here, we explore the organization of hierarchical tissues that have evolved to limit their lifetime incidence of cancer. Estimating the likelihood of cancer in the presence of mutations that enhance self-proliferation, we demonstrate that a trade-off exists between mutation accumulation and the strength of washing out. Our results explain differences in the organization of widely different hierarchical tissues, such as colon and blood.

evolutionary biology↗

bioRxiv2020

A rooted phylogeny resolves early bacterial evolution

Bacteria are the most abundant and metabolically diverse cellular lifeforms on Earth. A rooted bacterial phylogeny provides a framework to interpret this diversity and to understand the nature of early life. Inferring the position of the bacterial root is complicated by incomplete taxon sampling and the long branch to the archaeal outgroup. To circumvent these limitations, we model bacterial genome evolution at the level of gene duplication, transfer and loss events, allowing outgroup-free inference of the root1. We infer a rooted bacterial tree on which 68% of gene transmission events are vertical. Our analyses reveal a basal split between Terrabacteria and Gracilicutes, which together encompass almost all known bacterial diversity. However, the position of one phylum, Fusobacteriota, could not be resolved in relation to these two major clades. In contrast to recent proposals, our analyses strongly reject a root between the Candidate Phyla Radiation (CPR) and all other Bacteria. Instead, we find that the CPR is a sister lineage to the Chloroflexota within the Terrabacteria. We predict that the last bacterial common ancestor was a free-living flagellated, rod-shaped cell featuring a double membrane with a lipopolysaccharide outer layer, a Type III CRISPR-Cas system, Type IV pili, and the ability to sense and respond via chemotaxis.

evolutionary biology↗