Biology subjects

Rangel, L. T.

Publications and source records attributed to Rangel, L. T..

4 recordsLinked to original sources

bioRxiv2024

Tissue-Like Multicellular Development Triggered by Mechanical Compression in Archaea

The advent of clonal multicellularity is a critical evolutionary milestone, seen often in eukaryotes, rarely in bacteria, and only once observed in archaea. We show that uniaxial compression induces clonal multicellularity in haloarchaea, forming tissue-like structures. These archaeal tissues are mechanically and molecularly distinct from their unicellular lifestyle, mimicking several eukaryotic features. Archaeal tissues undergo a multinucleate stage followed by tubulin-independent cellularization, orchestrated by active membrane tension at a critical cell size. After cellularization, tissue junction elasticity become akin to animal tissues and give rise to two cell types--radial peribasal and central apicobasal cells-- with distinct actin and protein glycosylation polarity patterns. Our findings highlight the potential convergent evolution of a biophysical mechanism in the emergence of multicellular systems across domains of life.

cell biology↗

bioRxiv2020

Non-phylogenetic identification of co-evolving genes for reconstructing the archaeal Tree of Life

Assessing the phylogenetic compatibility between individual gene families is a crucial and often computationally demanding step in many phylogenomics analyses. Here we describe the Evolutionary Similarity Index (IES) to assess shared evolution between gene families using a weighted Orthogonal Distance Regression applied to sequence distances. This approach allows for straightforward pairing of paralogs between co-evolving gene families without resorting to multiple tests, or a priori assumptions of molecular interactions between protein products from assessed genes. The utilization of pairwise distance matrices, while less informative than phylogenetic trees, circumvents error-prone comparisons between trees whose topologies are inherently uncertain. Analyses of simulated gene family evolution datasets showed that IES was more accurate and less susceptible to noise than popular tree-based methods (Robinson-Foulds and geodesic distance) for assessing evolutionary signal compatibility, since it bypasses phylogenetic reconstruction and its inherent uncertainty. Applying IES to a real dataset of 1,322 genes from 42 archaeal genomes identified eight major clusters of gene families with compatible evolutionary trends. Four of these clusters included genes with a taxonomic distribution across all archaeal phyla, while other clusters included a subset of taxa that do not map to generally accepted archaeal clades, indicating possible shared horizontal transfers by clustered gene families. We identify one strongly connected set of 62 genes from the same cluster, occurring as both single-copy and multiple homologs per genome, with compatible phylogenetic reconstructions closely matching previously published species trees for Archaea. An IES implementation is available at https://github.com/lthiberiol/evolSimIndex.

evolutionary biology↗

bioRxiv2019

Fast-evolving alignment sites are highly informative for reconstructions of deep Tree of Life phylogenies

The trimming of fast-evolving sites, often known as \"slow-fast\" analysis, is broadly used in microbial phylogenetic reconstruction under assumption that fast-evolving sites do not retain accurate phylogenetic signal due to substitution saturation. Therefore, removing sites that have experienced multiple substitutions would improve the signal-to-noise ratio in phylogenetic analyses, with the remaining slower-evolving sites preserving a more reliable record of evolutionary relationships. Here we show that, contrary to this assumption, even the fastest evolving sites, present in conserved proteins often used in Tree of Life studies, contain reliable and valuable phylogenetic information, and that the trimming of such sites can negatively impact the accuracy of phylogenetic reconstruction. Simulated alignments modeled after ribosomal protein datasets used in Tree of Life studies consistently show that slow-evolving sites are less likely to recover true bipartitions than even the fastest-evolving sites. Furthermore, site specific substitution-rates are positively correlated with the frequency of accurately recovered short-branched bipartitions, as slowly evolving sites are less likely to have experienced substitutions along these intervals. Using published Tree of Life sequence alignment datasets, we additionally show that both slow-and fast-evolving sites contain similarly inconsistent phylogenetic signals, and that, for fast-evolving sites, this inconsistency can be attributed to poor alignment quality. Furthermore, trimming fast sites, slow sites, or both is shown to have substantial impact on phylogenetic reconstruction across multiple evolutionary models. This is perhaps most evident in the resulting placements of Eukarya and Asgardarchaeota groups, which are especially sensitive to the implementation of different trimming schemes.\n\nSignificance StatementIt is common practice among comprehensive microbial phylogenetic studies to trim fast-evolving sites from the source alignment in the expectation to increase the signal to noise ratio. Here we show that despite fast-evolving sites being more sensitive to parameter misspecifications than mid-rate evolving sites, such sensitivity is comparable, if not smaller, than what we observe among slow-evolving sites. Through the use of both empirical and simulated datasets we also show that, besides the lack of evidences regarding the noisy nature of fast-evolving sites, such sites are of core importance for the reliable the reconstruction of short-branched bipartitions. Such points are exemplified by the variations in the Eukarya+Archaea Tree of Life when subjective alignment trimming strategies are employed.

evolutionary biology↗

bioRxiv2019

Identification and characterization of putative Aeromonas spp. T3SS effectors

The genetic determinants of bacterial pathogenicity are highly variable between species and strains. However, a factor that is commonly associated with virulent Gram-negative bacteria, including many Aeromonas spp., is the type 3 secretion system (T3SS), which is used to inject effector proteins into target eukaryotic cells. In this study, we developed a bioinformatics pipeline to identify T3SS effector proteins, applied this approach to the genomes of 105 Aeromonas strains isolated from environmental, mutualistic, or pathogenic contexts and evaluated the cytotoxicity of the identified effectors through their heterologous expression in yeast. The developed pipeline uses a two-step approach, where candidate families are initially selected using HMM profiles with minimal similarity scores against the Virulence Factors DataBase (VFDB), followed by strict comparisons against positive and negative control datasets, greatly reducing the number of false positives. Using our approach, we identified 21 Aeromonas T3SS likely effector groups, of which 8 represented known or characterized effectors, while the remaining 13 had not previously been described in Aeromonas. We experimentally validated our in silico findings by assessing the cytotoxicity of representative effectors in Saccharomyces cerevisiae BY4741, with 15 out of 21 assayed proteins eliciting a cytotoxic effect in yeast. The results of this study demonstrate the utility of our approach, combining a novel in silico search method with in vivo experimental validation, and will be useful in future research aimed at identifying and authenticating bacterial effector proteins from other genera.

microbiology↗