Biology subjects

Pinheiro, M.

Publications and source records attributed to Pinheiro, M..

4 recordsLinked to original sources

bioRxiv2023

tRNASer overexpression induces adaptive mutations in NSCLC tumors

tRNAs are a driving force of genome evolution in Yeast and Bacteria. Their deregulation is frequently observed in tumors with Serine tRNAs being often overexpressed. This has important functional consequences, such as increased metabolism and tumor growth. In yeast, time and chemical stimulus boost alterations in the genome driven by tRNA deregulation. Therefore, we hypothesized that tRNA deregulation may contribute to the increased genome instability observed in tumors. To study the effect of tRNA deregulation in tumors, we overexpressed tRNA-Ser-AGA-2-1 in a NSCLC cell line, H460. This cell line and a Mock (control) were xenografted in nude mice and collected at 3 timepoints: T1-Naive; T2-Treated once with cisplatin/vehicle and; T3) treated twice with cisplatin/vehicle. These tumors were characterized by WES, RNAseq and Mass Spectrometry and the data obtained was integrated. The tumor mutation burden was increased in T3 tRNASerOE tumors, regardless of treatment. Although in T1 Mock and tRNASer tumors have a similar number of variants, in T2&3, tRNASerOE tumors display two times more variants than Mock tumors regardless of treatment. Interestingly, tRNASerOE exclusive variants favor proliferation and therapy resistance, which is in line with the phenotypes observed and supported by RNAseq and proteomics data. In conclusion, tRNASerOE increases the tumor mutation burden and the variants detected favor tumor growth, proving tRNA deregulation is enough to induce adaptive mutations in the genome.

cancer biology↗

bioRxiv2022

Metformin disrupts Danio rerio metabolism at environmentally relevant concentrations: A generational study

Metformin (MET) is an anti-diabetic pharmaceutical with a large-scale consumption, which is increasingly detected in surface waters. However, current knowledge on the generational effects of MET exposure in the metabolism of non-target organisms is limited. The present study aimed at investigating the effects of MET in the model freshwater teleost Danio rerio, following a generational exposure (from egg up to 9 months exposure) to environmentally relevant concentrations ranging from 361 ng/L to 13 000 ng/L. Biochemical markers were used to determine cholesterol and triglycerides levels, as well as mitochondrial complex I activity in males and females zebrafish liver. mRNA transcript changes were also assessed in the liver of both sexes by means of an exploratory RNA-seq analysis and expression levels of key genes involved in the energy metabolism and lipid homeostasis, i.e. acaca, acadm, cox5aa, idh3a, hmgcra, prkaa1, were determined using qRT-PCR analysis. The findings here reported revealed that MET was able to significantly disrupt critical biochemical and molecular processes involved in zebrafish metabolism, such as cholesterol and fatty acid biosynthesis, the mitochondrial electron transport chain and the tricarboxylic acid cycle, concomitantly to changes on the hepatosomatic index. Non-monotonic dose response curves were frequently detected in the gene expression profile, with higher effects observed for 361 ng/L and 2 166 ng/L concentrations. Collectively, the obtained results suggest that environmentally relevant concentrations of MET are able to severely disrupt D. rerio metabolism, with potential impacts at the ecological level, supporting the need to update the environmental quality standard (EQS) and predicted no-effect concentration (PNEC) for MET. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/487223v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@e9baecorg.highwire.dtl.DTLVardef@eedd72org.highwire.dtl.DTLVardef@c87a5org.highwire.dtl.DTLVardef@9d7c55_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDanio rerio was exposed to metformin for a full generation; C_LIO_LIMET affected COX I activity, as well as Chol and TGL content in zebrafish liver; C_LIO_LIMET altered mRNA levels of genes involved in energy metabolism and lipid content; C_LIO_LINon-monotonic dose-response curves were frequently detected; C_LIO_LIDue to the results obtained, MET PNEC should be reviewed. C_LI

pharmacology and toxicology↗

bioRxiv2021

Integration of differential gene expression with weighted gene correlation network analysis identifies genes whose expression is remodeled throughout physiological aging in mouse tissues

Gene expression alterations occur in all mouse tissues during aging, but recent works highlight minor rather than major dysregulation amplitude for most genes, questioning whether differentially expressed genes on their own provide deep insight into aging biology. To clarify this issue, we have combined differential gene expression with weighted gene correlation network analysis (WGCNA) to identify expression signatures accounting for the pairwise relations between gene expression profiles and the cumulative effect of genes with small fold- changes during aging in the brain, heart, liver, skeletal muscle, and pancreas of C57BL/6 mice. Functional enrichment analysis of the overlap of genes identified in both approaches showed that immunity-related responses, mitochondrial energy metabolism, tissue regeneration and detoxification are prominently altered in the brain, heart, muscle, and liver, respectively, reflecting an age-related global loss of tissue function. While data showed little overlap among the age-dysregulated genes between tissues, aging triggered common biological processes in distinct tissues, particularly proteostasis-related pathways, which we highlight as important features of murine tissue physiological aging.

genetics↗

bioRxiv2018

INSaFLU: an automated open web-based bioinformatics suite “from-reads” for influenza whole-genome-sequencing-based surveillance

A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data. Here, we launch INSaFLU (\"INSide the FLU\"), which, to the best of our knowledge, is the first influenza-specific bioinformatics free web-based suite that deals with primary data (reads) towards the automatic generation of the output data that are actually the core first-line \"genetic requests\" for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform advanced, multi-step software intensive analyses in a user-friendly manner without previous training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and highly flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus completely cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tune data analysis. This platform additionally flags samples as \"putative mixed infections\" if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional \"consensus-based\" influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants, but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission. In summary, INSaFLU supplies public health laboratories and influenza researchers with an open \"one size fits all\" framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.\n\nINSaFLU can be accessed through https://insaflu.insa.pt (see homepage view in Figure 1).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC=\"FIGDIR/small/253161_fig1.gif\" ALT=\"Figure 1\">\nView larger version (26K):\norg.highwire.dtl.DTLVardef@1111419org.highwire.dtl.DTLVardef@3e99c2org.highwire.dtl.DTLVardef@1e0a953org.highwire.dtl.DTLVardef@8c9ea6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO INSaFLU homepage\n\nC_FIG

bioinformatics↗