Resultados de investigación

This database contains metadata for the study sites in Serrano et al. 2023 (Ecosphere): Latitude and longitude data for the survey transects conducted in Posidonia australis escarpments and canopies, and reef in Big Lagoon, Faure Island and Peron Peninsula in Shark Bay (Western Australia) This database contains data on habitat characteristics, including abiotic factors (habitat height, cave volume, structural complexity) and biotic variables (total species, species richness, fish density, total biomass, biomass of apex predators, carnivores, hervibores, detritivores and planktivores)., This work was supported by the ECU School of Science Collaborative Research Grant Scheme, the I+D+i projects RYC2019-027073-I and PIE HOLOCENO 20213AT014 funded by MCIN/AEI/10.13039/501100011033 and FEDER. ES was supported by a post-doctoral scholarship funded by the Spanish Government (Juan de la Cierva FJC2018-035441-I)., Peer reviewed

Additional file 1: Figure S3. SDS-PAGE displaying the protein profiles. Additional file 2: Table S4. Mascot results. Additional file 3: Table S5. Differentially expressed proteins. Additional file 4: Table S1. Description of the used seed sludge. Additional file 5: Table S2. Overview of reaction stages and reactor performance. Additional file 6: Table S6. Number of sequences and mean length for bacteria from the acidification stages. Additional file 7: Table S7. Number of reads and mean length of reads for bacteria from the methane stages. Additional file 8: Table S8. Number of reads and mean length of reads for archaea from the methane stages., Peer reviewed

Supplementary Files containing script and files needed to reproduce the analysis performed in the manuscript entitled "The all-rounder Sodalis - a new bacteriome-associated endosymbiont of lygaeoid bug Henestaris halophilus (Heteroptera: Henestarinae) and a critical examination of its evolution"., Peer reviewed

Simulated data: For all the studies protein families (DNAK, DDL, TPIS, TRPA, TRXB, SH2). - The folder “*SimulatedANDinferredDATA” includes all simulated (true) protein sequence alignments and inferred with ProtASR under MF and the empirical JTT model (both for joint and marginal ASR) - The folder “*ComputedEnergiesFromData” includes the calculated energies of sequences of every MSA (files *.dat)., Real data: Files of the analysis based on real data are shown in the folder “RealData”, for the studied protein families (DNAK, DDL, TPIS, TRPA, TRXB). MSA and phylogenetic tree are in .fas/.nex formats and Newick format, respectively. Energies are shown in the .dat file and printed on the tree in files *Energies.tre (we recommend open them with FrigTree)., The computational reconstruction of ancestral proteins provides information on past biological events and has practical implications for biomedicine and biotechnology. Currently available tools for ancestral sequence reconstruction (ASR) are often based on empirical amino acid substitution models that assume that all sites evolve at the same rate and under the same process. However, this assumption is frequently violated because protein evolution is highly heterogeneous due to different selective constraints among sites. Here, we present ProtASR, a new evolutionary framework to infer ancestral protein sequences accounting for selection on protein stability. First, ProtASR generates site-specific substitution matrices through the structurally constrained mean-field substitution model (MF), which considers both unfolding and misfolding stability. We previously showed that MF models outperform empirical amino acid substitution models, as well as other structurally constrained substitution models, both in terms of likelihood and correctly inferring amino acid distributions across sites. In the second step, ProtASR adapts a well-established maximum-likelihood (ML) ASR procedure to infer ancestral proteins under MF models. A known bias of ML ASR methods is that they tend to overestimate the stability of ancestral proteins by under-estimating the frequency of deleterious mutations. We compared ProtASR under MF to two empirical substitution models (JTT and CAT), reconstructing the ancestral sequences of simulated proteins. ProtASR yields reconstructed proteins with less biased stabilities, which are significantly closer to those of the simulated proteins. Analysis of extant protein families suggests that folding stability evolves through time across protein families, potentially reflecting neutral fluctuation. Some families exhibit a more constant protein folding stability, while others are more variable. ProtASR is freely available from https://github.com/miguelarenas/protasr and includes detailed documentation and ready-to-use examples. It runs in seconds/minutes depending on protein length and alignment size., Peer reviewed

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In the Supplemental Material we provide technical details of the properties of the position disorder, derivation and solution of the effective Hamiltonians and details of the numerical simulations presented in the main text., Peer reviewed

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Supplementary material for the journal article "De novo MYC addiction as an adaptive response of cancer cells to CDK4/6 inhibition". 13C Metabolic flux analyses of CDK4/6 knockdown HCT116 cells and control HCT116 cells performed using INCA v1.5 (Young, J. D., 2014, INCA: a computational platform for isotopically non-stationary metabolic flux analysis. Bioinformatics 30, 1333-1335; http://mfa.vueinnovations.com.) running with MATLAB R2012b. The two files were generated by INCA with the estimated flux map distributions, network model, and tracer simulations., Peer reviewed