Search

Abstract Background There are a number of methods (also called: measures) currently in use that quantify codon usage in genes. These measures are often influenced by other sequence properties, such as length. This can introduce strong methodological bias into measurements; therefore we attempted to develop a method free from such dependencies. One of the common applications of codon usage analyses is to quantitatively predict gene expressivity. Results We compared the performance of several commonly used measures and a novel method we introduce in this paper – Measure Independent of Length and Composition (MILC). Large, randomly generated sequence sets were used to test for dependence on (i) sequence length, (ii) overall amount of codon bias and (iii) codon bias discrepancy in the sequences. A derivative of the method, named MELP (MILC-based Expression Level Predictor) can be used to quantitatively predict gene expression levels from genomic data. It was compared to other similar predictors by examining their correlation with actual, experimentally obtained mRNA or protein abundances. Conclusion We have established that MILC is a generally applicable measure, being resistant to changes in gene length and overall nucleotide composition, and introducing little noise into measurements. Other methods, however, may also be appropriate in certain applications. Our efforts to quantitatively predict gene expression levels in several prokaryotes and unicellular eukaryotes met with varying levels of success, depending on the experimental dataset and predictor used. Out of all methods, MELP and Rainer Merkl's GCB method had the most consistent behaviour. A 'reference set' containing known ribosomal protein genes appears to be a valid starting point for a codon usage-based expressivity prediction.

Background: Human mitochondrial heteroplasmy is an extensively investigated phenomenon in the context of medical diagnostics, forensic identification and molecular evolution. However, technical limitations of high-throughput sequencing hinder reliable determination of point heteroplasmies (PHPs) with minor allele frequencies (MAFs) within the noise threshold., Results: To investigate the PHP landscape at an MAF threshold down to 0.1%, we sequenced whole mitochondrial genomes at approximately 7.700x coverage, in multiple technical and biological replicates of longitudinal blood and buccal swab samples from 11 human donors (159 libraries in total). The results obtained by two independent sequencing platforms and bioinformatics pipelines indicate distinctive PHP patterns below and above the 1% MAF cut-off. We found a high inter-individual prevalence of low-level PHPs (MAF < 1%) at polymorphic positions of the mitochondrial DNA control region (CR), their tissue preference, and a tissue-specific minor allele linkage. We also established the position-dependent potential of minor allele expansion in PHPs, and short-term PHP instability in a mitotically active tissue. We demonstrate that the increase in sensitivity of PHP detection to minor allele frequencies below 1% within a robust experimental and analytical pipeline, provides new information with potential applicative value., Conclusions: Our findings reliably show different mutational loads between tissues at sub-1% allele frequencies, which may serve as an informative medical biomarker of time-dependent, tissue-specific mutational burden, or help discriminate forensically relevant tissues in a single person, close maternal relatives or unrelated individuals of similar phylogenetic background., (© 2024. The Author(s).)

The determination of the protein's intracellular localization is essential for understanding its biological function. Protein localization studies are mainly performed on primary and secondary vertebrate cell lines for which most protocols have been optimized. In spite of experimental difficulties, studies on invertebrate cells, including basal Metazoa, have greatly advanced. In recent years, the interest in studying human diseases from an evolutionary perspective has significantly increased. Sponges, placed at the base of the animal tree, are simple animals without true tissues and organs but with a complex genome containing many genes whose human homologs have been implicated in human diseases, including cancer. Therefore, sponges are an innovative model for elucidating the fundamental role of the proteins involved in cancer. In this study, we overexpressed human cancer-related proteins and their sponge homologs in human cancer cells, human fibroblasts, and sponge cells. We demonstrated that human and sponge MYC proteins localize in the nucleus, the RRAS2 in the plasma membrane, the membranes of the endolysosomal vesicles, and the DRG1 in the cell's cytosol. Despite the very low transfection efficiency of sponge cells, we observed an identical localization of human proteins and their sponge homologs, indicating their similar cellular functions.

Cancer is a disease caused by errors within the multicellular system and it represents a major health issue in multicellular organisms. Although cancer research has advanced substantially, new approaches focusing on fundamental aspects of cancer origin and mechanisms of spreading are necessary. Comparative genomic studies have shown that most genes linked to human cancer emerged during the early evolution of Metazoa. Thus, basal animals without true tissues and organs, such as sponges (Porifera), might be an innovative model system for understanding the molecular mechanisms of proteins involved in cancer biology. One of these proteins is developmentally regulated GTP-binding protein 1 (DRG1), a GTPase stabilized by interaction with DRG family regulatory protein 1 (DFRP1). This study reveals a high evolutionary conservation of DRG1 gene/protein in metazoans. Our biochemical analysis and structural predictions show that both recombinant sponge and human DRG1 are predominantly monomers that form complexes with DFRP1 and bind non-specifically to RNA and DNA. We demonstrate the conservation of sponge and human DRG1 biological features, including intracellular localization and DRG1:DFRP1 binding, function of DRG1 in α-tubulin dynamics, and its role in cancer biology demonstrated by increased proliferation, migration and colonization in human cancer cells. These results suggest that the ancestor of all Metazoa already possessed DRG1 that is structurally and functionally similar to the human DRG1, even before the development of real tissues or tumors, indicating an important function of DRG1 in fundamental cellular pathways., (© 2022. The Author(s).)

Correspondence between evolution and development has been discussed for more than two centuries. Recent work reveals that phylogeny-ontogeny correlations are indeed present in developmental transcriptomes of eukaryotic clades with complex multicellularity. Nevertheless, it has been largely ignored that the pervasive presence of phylogeny-ontogeny correlations is a hallmark of development in eukaryotes. This perspective opens a possibility to look for similar parallelisms in biological settings where developmental logic and multicellular complexity are more obscure. For instance, it has been increasingly recognized that multicellular behavior underlies biofilm formation in bacteria. However, it remains unclear whether bacterial biofilm growth shares some basic principles with development in complex eukaryotes. Here we show that the ontogeny of growing Bacillus subtilis biofilms recapitulates phylogeny at the expression level. Using time-resolved transcriptome and proteome profiles, we found that biofilm ontogeny correlates with the evolutionary measures, in a way that evolutionary younger and more diverged genes were increasingly expressed toward later timepoints of biofilm growth. Molecular and morphological signatures also revealed that biofilm growth is highly regulated and organized into discrete ontogenetic stages, analogous to those of eukaryotic embryos. Together, this suggests that biofilm formation in Bacillus is a bona fide developmental process comparable to organismal development in animals, plants, and fungi. Given that most cells on Earth reside in the form of biofilms and that biofilms represent the oldest known fossils, we anticipate that the widely adopted vision of the first life as a single-cell and free-living organism needs rethinking., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Bacilli can form dormant, highly resistant, and metabolically inactive spores to cope with extreme environmental challenges. In this study, we examined the evolutionary age of Bacillus subtilis sporulation genes using the approach known as genomic phylostratigraphy. We found that B. subtilis sporulation genes cluster in several groups that emerged at distant evolutionary time-points, suggesting that the sporulation process underwent several stages of expansion. Next, we asked whether such evolutionary stratification of the genome could be used to predict involvement in sporulation of presently uncharacterized genes (y-genes). We individually inactivated a representative sample of uncharacterized genes that arose during the same evolutionary periods as the known sporulation genes and tested the resulting strains for sporulation phenotypes. Sporulation was significantly affected in 16 out of 37 (43%) tested strains. In addition to expanding the knowledge base on B. subtilis sporulation, our findings suggest that evolutionary age could be used to help with genome mining., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

We studied the effect of microbiota on the transcriptome and weight of the urinary bladder by comparing germ-free (GF) and specific pathogen-free (SPF) housed mice. In total, 97 genes were differently expressed (fold change > ±2; false discovery rate (FDR) p -value < 0.01) between the groups, including genes regulating circadian rhythm (Per1, Per2 and Per3), extracellular matrix (Spo1, Spon2), and neuromuscular synaptic transmission (Slc18a3, Slc5a7, Chrnb4, Chrna3, Snap25). The highest increase in expression was observed for immunoglobulin genes (Igkv1-122, Igkv4-68) of unknown function, but surprisingly the absence of microbiota did not change the expression of the genes responsible for recognizing microbes and their products. We found that urinary bladder weight was approximately 25% lighter in GF mice ( p = 0.09 for males, p = 0.005 for females) and in mice treated with broad spectrum of antibiotics ( p = 0.0002). In conclusion, our data indicate that microbiota is an important determinant of urinary bladder physiology controlling its gene expression and size.

Non-integrative AAV-mediated gene therapy in the liver is effective in adult patients, but faces limitations in pediatric settings due to episomal DNA loss during hepatocyte proliferation. Gene targeting is a promising approach by permanently modifying the genome. We previously rescued neonatal lethality in Crigler-Najjar mice by inserting a promoterless human uridine glucuronosyl transferase A1 (UGT1A1) cDNA in exon 14 of the albumin gene, without the use of nucleases. To increase recombination rate and therapeutic efficacy, here we used CRISPR/SaCas9. Neonatal mice were transduced with two AAVs: one expressing the SaCas9 and sgRNA, and one containing a promoterless cDNA flanked by albumin homology regions. Targeting efficiency increased ~26-fold with an eGFP reporter cDNA, reaching up to 24% of eGFP-positive hepatocytes. Next, we fully corrected the diseased phenotype of Crigler-Najjar mice by targeting the hUGT1A1 cDNA. Treated mice had normal plasma bilirubin up to 10 months after administration, hUGT1A1 protein levels were ~6-fold higher than in WT liver, with a 90-fold increase in recombination rate. Liver histology, inflammatory markers, and plasma albumin were normal in treated mice, with no off-targets in predicted sites. Thus, the improved efficacy and reassuring safety profile support the potential application of the proposed approach to other liver diseases.

Exhaled breath temperature (EBT) is a biomarker of inflammation and vascularity of the airways already shown to predict incident COPD. This cross-sectional study was aimed to assess the potential of EBT in identifying "healthy" smokers susceptible to cigarette smoke toxicity of the airways and to the risk of developing COPD by analysing the dynamics of EBT after smoking a cigarette and its associations with their demographics (age, smoking burden) and lung function. The study included 55 current smokers of both sexes, 29-62 years of age, with median smoking exposure of 15 (10-71.8) pack-years. EBT was measured at baseline and 5, 15, 30, 45, and 60 min after smoking a single cigarette. Lung function was measured with spirometry followed by a bronchodilator test. To compare changes in EBT between repeated measurements we used the analysis of variance and the area under the curve (EBTAUC) as a dependent variable. Multivariate regression analysis was used to look for associations with patient characteristics and lung function in particular. The average (±SD) baseline EBT was 33.42±1.50 °C. The highest significant increase to 33.84 (1.25) °C was recorded 5 min after the cigarette was smoked (p=0.003), and it took one hour for it to return to the baseline. EBTAUC showed significant repeatability (ICC=0.85, p<0.001) and was significantly associated with age, body mass index, number of cigarettes smoked a day, baseline EBT, and baseline FEF75 (R2=0.39, p<0.001 for the model). Our results suggest that EBT after smoking a single cigarette could be used as early risk predictor of changes associated with chronic cigarette smoke exposure.

Heat-induced hormesis is a well-known conserved phenomenon in aging, traditionally attributed to the benefits conferred by increased amounts of heat shock (HS) proteins. Here we find that the key event for the HS-induced lifespan extension in budding yeast is the switch from glycolysis to respiratory metabolism. The resulting increase in reactive oxygen species activates the antioxidant response, supported by the redirection of glucose from glycolysis to the pentose phosphate pathway, increasing the production of NADPH. This sequence of events culminates in replicative lifespan (RLS) extension, implying decreased mortality per generation that persists even after the HS has finished. We found that switching to respiratory metabolism, and particularly the consequent increase in glutathione levels, were essential for the observed RLS extension. These results draw the focus away solely from the HS response and demonstrate that the antioxidant response has a key role in heat-induced hormesis. Our findings underscore the importance of the changes in cellular metabolic activity for heat-induced longevity in budding yeast.

Protein quality control mechanisms, required for normal cellular functioning, encompass multiple functions related to protein production and maintenance. However, the existence of communication between proteostasis and metabolic networks and its underlying mechanisms remain elusive. Here, we report that enhanced chaperone activity and consequent improved proteostasis are sensed by TORC1 via the activity of Hsp82. Chaperone enrichment decreases the level of Hsp82, which deactivates TORC1 and leads to activation of Snf1/AMPK, regardless of glucose availability. This mechanism culminates in the extension of yeast replicative lifespan (RLS) that is fully reliant on both TORC1 deactivation and Snf1/AMPK activation. Specifically, we identify oxygen consumption increase as the downstream effect of Snf1 activation responsible for the entire RLS extension. Our results set a novel paradigm for the role of proteostasis in aging: modulation of the misfolded protein level can affect cellular metabolic features as well as mitochondrial activity and consequently modify lifespan. The described mechanism is expected to open new avenues for research of aging and age-related diseases., (© 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.)

Metagenomics projects use next-generation sequencing to unravel genetic potential in microbial communities from a wealth of environmental niches, including those associated with human body and relevant to human health. In order to understand large datasets collected in metagenomics surveys and interpret them in context of how a community metabolism as a whole adapts and interacts with the environment, it is necessary to extend beyond the conventional approaches of decomposing metagenomes into microbial species' constituents and performing analysis on separate components. By applying concepts of translational optimization through codon usage adaptation on entire metagenomic datasets, we demonstrate that a bias in codon usage present throughout the entire microbial community can be used as a powerful analytical tool to predict for community lifestyle-specific metabolism. Here we demonstrate this approach combined with machine learning, to classify human gut microbiome samples according to the pathological condition diagnosed in the human host.

Unlabelled: Biological insights can be obtained through computational integration of genomics data sets consisting of diverse types of information. The integration is often hampered by a large variety of existing file formats, often containing similar information, and the necessity to use complicated tools to achieve the desired results. We have built an R package, genomation, to expedite the extraction of biological information from high throughput data. The package works with a variety of genomic interval file types and enables easy summarization and annotation of high throughput data sets with given genomic annotations., Availability and Implementation: The software is currently distributed under MIT artistic license and freely available at http://bioinformatics.mdc-berlin.de/genomation, and through the Bioconductor framework., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Cancer is a disease potentiated by mutations in somatic cells. Cancer mutations are not distributed uniformly along the human genome. Instead, different human genomic regions vary by up to fivefold in the local density of cancer somatic mutations, posing a fundamental problem for statistical methods used in cancer genomics. Epigenomic organization has been proposed as a major determinant of the cancer mutational landscape. However, both somatic mutagenesis and epigenomic features are highly cell-type-specific. We investigated the distribution of mutations in multiple independent samples of diverse cancer types and compared them to cell-type-specific epigenomic features. Here we show that chromatin accessibility and modification, together with replication timing, explain up to 86% of the variance in mutation rates along cancer genomes. The best predictors of local somatic mutation density are epigenomic features derived from the most likely cell type of origin of the corresponding malignancy. Moreover, we find that cell-of-origin chromatin features are much stronger determinants of cancer mutation profiles than chromatin features of matched cancer cell lines. Furthermore, we show that the cell type of origin of a cancer can be accurately determined based on the distribution of mutations along its genome. Thus, the DNA sequence of a cancer genome encompasses a wealth of information about the identity and epigenomic features of its cell of origin.

Exon splicing enhancers (ESEs) overlap with amino acid coding sequences implying a dual evolutionary selective pressure. In this study, we map ESEs in the placental alkaline phosphatase gene (ALPP), absent in the corresponding exon of the ancestral tissue-non-specific alkaline phosphatase gene (ALPL). The ESEs are associated with amino acid differences between the transcripts in an area otherwise conserved. We switched out the ALPP ESEs sequences with the sequence from the related ALPL, introducing the associated amino acid changes. The resulting enzymes, produced by cDNA expression, showed different kinetic characteristics than ALPL and ALPP. In the organism, this enzyme will never be subjected to selection because gene splicing analysis shows exon skipping due to loss of the ESE. Our data prove that ESEs restrict the evolution of enzymatic activity. Thus, suboptimal proteins may exist in scenarios when coding nucleotide changes and consequent amino acid variation cannot be reconciled with the splicing function., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Identifying hotspots responsible for protein interactions with other macromolecules or drugs provides insight into functional aspects of the protein network, and is a pivotal task in systems biology and drug discovery. Here, we present the protocol for the application of a machine-learning method - Random Forest - to prediction of interacting residues in proteins, based on either the structural parameters or the primary sequence alone.

TDP-43 is a multifunctional RNA-binding protein found to be a major protein component of intracellular inclusions found in neurodegenerative disorders such as Fronto Temporal Lobar Degeneration, Amyotrophic Lateral Sclerosis, and Alzheimer Disease. PRO-MINE (PROtein Mutations In NEurodegeneration) is a database populated with manually curated data from the literature regarding all TDP-43/TDP43/TARDBP gene disease-associated mutations identified to date. A web server interface has been developed to query the database and to provide tools for the analysis of already reported or novel TDP-43 gene mutations. As is usually the case with genetic association studies, assessing the potential impact of identified mutations is of crucial importance, and in order to avoid prediction biases it is essential to compare the prediction results. However, in most cases mutations have to be submitted separately to various prediction tools and the individual results manually merged together afterwards. The implemented web server aims to overcome the problem by providing simultaneous access to several prediction tools and by displaying the results into a single output. Furthermore, the results are displayed together in a comprehensive output for a more convenient analysis and are enriched with additional information about mutations. In addition, our web server can also display the mutation(s) of interest within an alignment of annotated TDP-43 protein sequences from different vertebrate species. In this way, the degree of sequence conservation where the mutation(s) occur can be easily tracked and visualized. The web server is freely available to researchers and can be accessed at http://bioinfo.hr/pro-mine., (© 2010 Wiley-Liss, Inc.)