Promoting advanced medical services in the framework of 3PM-a proof-of-concept by the "Centro" Region of Portugal

Multidisciplinary team from three universities based in the "Centro" Region of Portugal developed diverse approaches as parts of a project dedicated to enhancing and expanding Predictive, Preventive, and Personalized Medicine (3PM) in the Region. In a sense, outcomes acted as a proof-of-concept, in that they demonstrated the feasibility, but also the relevance of the approaches. The accomplishments comprise defining a new regional strategy for implementing 3PM within the Region, training of human resources in genomic sequencing, and generating good practices handbooks dedicated to diagnostic testing via next-generation sequencing, to legal and ethical concerns, and to knowledge transfer and entrepreneurship, aimed at increasing literacy on 3PM approaches. Further approaches also included support for entrepreneurship development and start-ups, and diverse and relevant initiatives aimed at increasing literacy relevant to 3PM. Efforts to enhance literacy encompassed citizens across the board, from patients and high school students to health professionals and health students. This focus on empowerment through literacy involved a variety of initiatives, including the creation of an illustrated book on genomics and the production of two theater plays centered on genetics. Additionally, authors stressed that genomic tools are relevant, but they are not the only resources 3PM is based on. Thus, they defend that other initiatives intended to enable citizens to take 3PM should include multi-omics and, having in mind the socio-economic burden of chronic diseases, suboptimal health status approaches in the 3PM framework should also be considered, in order to anticipate medical intervention in the subclinical phase.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00353-9.

miRNAs in Heart Development and Disease

Cardiovascular diseases (CVD) are a group of disorders that affect the heart and blood vessels. They include conditions such as myocardial infarction, coronary artery disease, heart failure, arrhythmia, and congenital heart defects. CVDs are the leading cause of death worldwide. Therefore, new medical interventions that aim to prevent, treat, or manage CVDs are of prime importance. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the posttranscriptional level and play important roles in various biological processes, including cardiac development, function, and disease. Moreover, miRNAs can also act as biomarkers and therapeutic targets. In order to identify and characterize miRNAs and their target genes, scientists take advantage of computational tools such as bioinformatic algorithms, which can also assist in analyzing miRNA expression profiles, functions, and interactions in different cardiac conditions. Indeed, the combination of miRNA research and bioinformatic algorithms has opened new avenues for understanding and treating CVDs. In this review, we summarize the current knowledge on the roles of miRNAs in cardiac development and CVDs, discuss the challenges and opportunities, and provide some examples of recent bioinformatics for miRNA research in cardiovascular biology and medicine.

Daphnia magna Multigeneration Exposure to Carbendazim: Gene Transcription Responses

The world population is experiencing colossal growth and thus demand for food, leading to an increase in the use of pesticides. Persistent pesticide contamination, such as carbendazim, remains a pressing environmental concern, with potentially long-term impacts on aquatic ecosystems. In the present study, Daphnia magna was exposed to carbendazim (5 µg L-1) for 12 generations, with the aim of assessing gene transcription alterations induced by carbendazim (using a D. magna custom microarray). The results showed that carbendazim caused changes in genes involved in the response to stress, DNA replication/repair, neurotransmission, ATP production, and lipid and carbohydrate metabolism at concentrations already found in the environment. These outcomes support the results of previous studies, in which carbendazim induced genotoxic effects and reproduction impairment (increasing the number of aborted eggs with the decreasing number of neonates produced). The exposure of daphnids to carbendazim did not cause a stable change in gene transcription between generations, with more genes being differentially expressed in the F0 generation than in the F12 generation. This could show some possible daphnid acclimation after 12 generations and is aligned with previous multigenerational studies where few ecotoxicological effects at the individual and populational levels and other subcellular level effects (e.g., biochemical biomarkers) were found.

Myocardial RNA Sequencing Reveals New Potential Therapeutic Targets in Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) represents a global health challenge, with limited therapies proven to enhance patient outcomes. This makes the elucidation of disease mechanisms and the identification of novel potential therapeutic targets a priority. Here, we performed RNA sequencing on ventricular myocardial biopsies from patients with HFpEF, prospecting to discover distinctive transcriptomic signatures. A total of 306 differentially expressed mRNAs (DEG) and 152 differentially expressed microRNAs (DEM) were identified and enriched in several biological processes involved in HF. Moreover, by integrating mRNA and microRNA expression data, we identified five potentially novel miRNA-mRNA relationships in HFpEF: the upregulated hsa-miR-25-3p, hsa-miR-26a-5p, and has-miR4429, targeting HAPLN1; and NPPB mRNA, targeted by hsa-miR-26a-5p and miR-140-3p. Exploring the predicted miRNA-mRNA interactions experimentally, we demonstrated that overexpression of the distinct miRNAs leads to the downregulation of their target genes. Interestingly, we also observed that microRNA signatures display a higher discriminative power to distinguish HFpEF sub-groups over mRNA signatures. Our results offer new mechanistic clues, which can potentially translate into new HFpEF therapies.

The Role of MicroRNAs in Proteostasis Decline and Protein Aggregation during Brain and Skeletal Muscle Aging

Aging can be defined as the progressive deterioration of cellular, tissue, and organismal function over time. Alterations in protein homeostasis, also known as proteostasis, are a hallmark of aging that lead to proteome imbalances and protein aggregation, phenomena that also occur in age-related diseases. Among the various proteostasis regulators, microRNAs (miRNAs) have been reported to play important roles in the post-transcriptional control of genes involved in maintaining proteostasis during the lifespan in several organismal tissues. In this review, we consolidate recently published reports that demonstrate how miRNAs regulate fundamental proteostasis-related processes relevant to tissue aging, with emphasis on the two most studied tissues, brain tissue and skeletal muscle. We also explore an emerging perspective on the role of miRNA regulatory networks in age-related protein aggregation, a known hallmark of aging and age-related diseases, to elucidate potential miRNA candidates for anti-aging diagnostic and therapeutic targets.

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

Gene expression alterations occurring with aging have been described for a multitude of species, organs, and cell types. However, most of the underlying studies rely on static comparisons of mean gene expression levels between age groups and do not account for the dynamics of gene expression throughout the lifespan. These studies also tend to disregard the pairwise relationships between gene expression profiles, which may underlie commonly altered pathways and regulatory mechanisms with age. To overcome these limitations, we have combined segmented regression analysis with weighted gene correlation network analysis (WGCNA) to identify high-confidence signatures of aging in the brain, heart, liver, skeletal muscle, and pancreas of C57BL/6 mice in a publicly available RNA-Seq dataset (GSE132040). Functional enrichment analysis of the overlap of genes identified in both approaches showed that immune- and inflammation-related responses are prominently altered in the brain and the liver, while in the heart and the muscle, aging affects amino and fatty acid metabolism, and tissue regeneration, respectively, which reflects an age-related global loss of tissue function. We also explored sexual dimorphism in the aging mouse transcriptome and found the liver and the muscle to have the most pronounced gender differences in gene expression throughout the lifespan, particularly in proteostasis-related pathways. While the data showed little overlap among the age-dysregulated genes between tissues, aging triggered common biological processes in distinct tissues, which we highlight as important features of murine tissue physiological aging.

Protein Aggregation Patterns Inform about Breast Cancer Response to Antiestrogens and Reveal the RNA Ligase RTCB as Mediator of Acquired Tamoxifen Resistance

Simple Summary

Acquired resistance to antiestrogenic therapy remains the major obstacle to curing luminal subtype breast cancer. While current treatment in acquired endocrine-resistant settings includes combined therapy with receptor tyrosine kinase or cyclin-dependent kinase inhibitors, progression to incurable disease remains possible. In recent years, the antioxidant system and the protein quality control network have been associated with the enhanced resistance of breast cancer cells to hormonal therapy. In this work, we raise the hypothesis that antiestrogen treatment induces the accumulation of protein aggregates in sensitive cells, which in turn could hinder the activation of survival pathways. We present evidence concerning a novel way to identify antiestrogen response and disclose a novel protein, RTBC, that controls acquired antiestrogen resistance. This work opens a new avenue for research towards finding breast cancer prognostic markers and therapeutic targets, where the identification of proteins prone to aggregate could help to identify antiestrogen response and understand mechanisms of disease.

Abstract

The protein quality control network, including autophagy, the proteasome and the unfolded protein response (UPR), is triggered by stress and is overactive in acquired antiestrogen therapy resistance. We show for the first time that the aggresome load correlates with apoptosis and is increased in antiestrogen-sensitive cells compared to endocrine-resistant variants. LC-MS/MS analysis of the aggregated proteins obtained after 4OH-tamoxifen and Fulvestrant treatment identified proteins with essential function in protein quality control in antiestrogen-sensitive cells, but not in resistant variants. These include the UPR modulators RTCB and PDIA6, as well as many proteasome proteins such as PSMC2 and PSMD11. RTCB is a tRNA and XBP1 ligase and its aggregation induced by antiestrogens correlated with impaired XBP1s expression in sensitive cells. Knock down of RTCB was sufficient to restore sensitivity to tamoxifen in endocrine-resistant cells and increased the formation of aggresomes, leading to apoptotic cell death. Analysis of primary human breast cancer samples and their metastases appearing after endocrine treatment showed that RTCB is only localized to aggresomes in the primary tumors, while total aggresomes, including aggregated RTCB, were significantly reduced in the metastases. Therefore, different protein aggregation patterns may indicate loss of function of essential proteins resulting in enhanced protein aggregation that can be used to identify antiestrogen-resistant breast cancer cells and improve the response to antiestrogenic therapy.

The role of non-standard translation in Candida albicans pathogenesis

Candida albicans typically resides in the human gastrointestinal tract and mucosal membranes as a commensal organism. To adapt and cope with the host immune system, it has evolved a variety of mechanisms of adaptation such as stress-induced mutagenesis and epigenetic regulation. Niche-specific patterns of gene expression also allow the fungus to fine-tune its response to specific microenvironments in the host and switch from harmless commensal to invasive pathogen. Proteome plasticity produced by CUG ambiguity, on the other hand is emerging as a new layer of complexity in C. albicans adaptation, pathogenesis, and drug resistance. Such proteome plasticity is the result of a genetic code alteration where the leucine CUG codon is translated mainly as serine (97%), but maintains some level of leucine (3%) assignment. In this review, we dissect the link between C. albicans non-standard CUG translation, proteome plasticity, host adaptation and pathogenesis. We discuss published work showing how this pathogen uses the fidelity of protein synthesis to spawn novel virulence traits.

tRNAs as a Driving Force of Genome Evolution in Yeast

Transfer RNAs (tRNAs) are widely known for their roles in the decoding of the linear mRNA information into amino acid sequences of proteins. They are also multifunctional platforms in the translation process and have other roles beyond translation, including sensing amino acid abundance, interacting with the general stress response machinery, and modulating cellular adaptation, survival, and death. In this mini-review, we focus on the emerging role of tRNA genes in the organization and modification of the genomic architecture of yeast and the role of tRNA misexpression and decoding infidelity in genome stability, evolution, and adaption. We discuss published work showing how quickly tRNA genes can mutate to meet novel translational demands, how tRNAs speed up genome evolution, and how tRNA genes can be sites of genomic instability. We highlight recent works showing that loss of tRNA decoding fidelity and small alterations in tRNA expression have unexpected and profound impacts on genome stability. By dissecting these recent evidence, we hope to lay the groundwork that prompts future investigations on the mechanistic interplay between tRNAs and genome modification that likely triggers genome evolution.

De novo sequencing of proteins by mass spectrometry

INTRODUCTION

Proteins are crucial for every cellular activity and unraveling their sequence and structure is a crucial step to fully understand their biology. Early methods of protein sequencing were mainly based on the use of enzymatic or chemical degradation of peptide chains. With the completion of the human genome project and with the expansion of the information available for each protein, various databases containing this sequence information were formed.

AREAS COVERED

De novo protein sequencing, shotgun proteomics and other mass-spectrometric techniques, along with the various software are currently available for proteogenomic analysis. Emphasis is placed on the methods for de novo sequencing, together with potential and shortcomings using databases for interpretation of protein sequence data.

EXPERT OPINION

As mass-spectrometry sequencing performance is improving with better software and hardware optimizations, combined with user-friendly interfaces, de-novo protein sequencing becomes imperative in shotgun proteomic studies. Issues regarding unknown or mutated peptide sequences, as well as, unexpected post-translational modifications (PTMs) and their identification through false discovery rate searches using the target/decoy strategy need to be addressed. Ideally, it should become integrated in standard proteomic workflows as an add-on to conventional database search engines, which then would be able to provide improved identification.

Genetic profile and patient-reported outcomes in chronic obstructive pulmonary disease: A systematic review

BACKGROUND

Chronic Obstructive Pulmonary Disease (COPD) impacts differently on patients at similar grades, suggesting that factors other than lung function may influence patients' experience of the disease. Recent studies have found associations between genetic variations and patient-reported outcomes (PROs). Identifying these associations might be fundamental to predict the disease progression and develop tailored interventions. This systematic review aimed to identify the genetic variations associated with PROs in COPD.

METHODS AND FINDINGS

Databases were searched until July 2017 (PROSPERO: CRD42016041639) and additional searches were conducted scanning the reference list of the articles. Two independent reviewers assessed the quality of studies using the Q-Genie checklist. This instrument is composed of 11 questions, each subdivided in 7 options from 1 poor-7 excellent. Thirteen studies reporting 5 PROs in association with genes were reviewed. Studies were rated between "good quality" (n = 8) and "moderate" (n = 5). The most reported PRO was frequency of exacerbations (n = 7/13), which was mainly associated with MBL2 gene variants. Other PRO's were health-related quality of life (HRQOL) (n = 4/13), depressive symptoms (n = 1/13), exacerbation severity (n = 1/13) and breathlessness, cough and sputum (n = 1/13), which were commonly associated with other genetic variants.

CONCLUSIONS

Although a limited number of PRO's have been related to genetic variations, findings suggest that there is a significant association between specific gene variants and the number/severity of exacerbations, depressive symptoms and HRQOL. Further research is needed to confirm these findings and assess the genetic influence on other dimensions of patients' lives, since it may enhance our understanding and management of COPD.

Statistical, Computational and Visualization Methodologies to Unveil Gene Primary Structure Features

Objectives: Gene sequence features such as codon bias, codon context, and codon expansion (e.g. tri-nucleotide repeats) can be better understood at the genomic scale level by combining statistical methodologies with advanced computer algorithms and data visualization through sophisticated graphical interfaces. This paper presents the ANACONDA system, a bioinformatics application for gene primary structure analysis.

Methods: Codon usage tables using absolute metrics and software for multivariate analysis of codon and amino acid usage are available in public databases. However, they do not provide easy computational and statistical tools to carry out detailed gene primary structure analysis on a genomic scale. We propose the usage of several statistical methods – contingency table analysis, residual analysis, multivariate analysis (cluster analysis) – to analyze the codon bias under various aspects (degree of association, contexts and clustering).

Results: The developed solution is a software application that provides a user-guided analysis of codon sequences considering several contexts and codon usage on a genomic scale. The utilization of this tool in our molecular biology laboratory is focused on particular genomes, especially those from Saccharomyces cerevisiae, Candida albicansand Escherichia coli. In order to illustrate the applicability and output layouts of the software these species are herein used as examples.

Conclusions: The statistical tools incorporated in the system are allowing to obtain global views of important sequence features. It is expected that the results obtained will permit identification of general rules that govern codon context and codon usage in any genome. Additionally, identification of genes containing expanded codons that arise as a consequence of erroneous DNA replication events will permit uncovering new genes associated with human disease.

Phenotypic heterogeneity promotes adaptive evolution

Genetically identical cells frequently display substantial heterogeneity in gene expression, cellular morphology and physiology. It has been suggested that by rapidly generating a subpopulation with novel phenotypic traits, phenotypic heterogeneity (or plasticity) accelerates the rate of adaptive evolution in populations facing extreme environmental challenges. This issue is important as cell-to-cell phenotypic heterogeneity may initiate key steps in microbial evolution of drug resistance and cancer progression. Here, we study how stochastic transitions between cellular states influence evolutionary adaptation to a stressful environment in yeast Saccharomyces cerevisiae. We developed inducible synthetic gene circuits that generate varying degrees of expression stochasticity of an antifungal resistance gene. We initiated laboratory evolutionary experiments with genotypes carrying different versions of the genetic circuit by exposing the corresponding populations to gradually increasing antifungal stress. Phenotypic heterogeneity altered the evolutionary dynamics by transforming the adaptive landscape that relates genotype to fitness. Specifically, it enhanced the adaptive value of beneficial mutations through synergism between cell-to-cell variability and genetic variation. Our work demonstrates that phenotypic heterogeneity is an evolving trait when populations face a chronic selection pressure. It shapes evolutionary trajectories at the genomic level and facilitates evolutionary rescue from a deteriorating environmental stress.

Phenotypic heterogeneity of genetically identical cells can generate nonheritable variation in a population. Is this heterogeneity favorable for microbes? In a changing environment, the answer is a definite yes. While scholars have argued that stochastically generated variation precedes genetic changes and thereby facilitate the evolution of complex traits, this idea has remained disputed, not least because of the shortage of experimental studies. We address this long-standing and controversial issue by integrating synthetic biology, laboratory experimental evolution, and genomic analyses. We explicitly tested the mechanisms whereby phenotypic heterogeneity may promote evolvability. Our work demonstrates that phenotypic heterogeneity facilitates evolutionary rescue from deteriorating environmental stress by generating individuals with exceptionally high fitness. Remarkably, elevated phenotypic heterogeneity evolves as a direct response to stress and thereby it promotes evolution of rare combinations of mutations. These results indicate that phenotypic heterogeneity might have an important role in the evolution of key innovations.

mRNA secondary structure optimization using a correlated stem-loop prediction

Secondary structure of messenger RNA plays an important role in the bio-synthesis of proteins. Its negative impact on translation can reduce the yield of protein by slowing or blocking the initiation and movement of ribosomes along the mRNA, becoming a major factor in the regulation of gene expression. Several algorithms can predict the formation of secondary structures by calculating the minimum free energy of RNA sequences, or perform the inverse process of obtaining an RNA sequence for a given structure. However, there is still no approach to redesign an mRNA to achieve minimal secondary structure without affecting the amino acid sequence. Here we present the first strategy to optimize mRNA secondary structures, to increase (or decrease) the minimum free energy of a nucleotide sequence, without changing its resulting polypeptide, in a time-efficient manner, through a simplistic approximation to hairpin formation. Our data show that this approach can efficiently increase the minimum free energy by >40%, strongly reducing the strength of secondary structures. Applications of this technique range from multi-objective optimization of genes by controlling minimum free energy together with CAI and other gene expression variables, to optimization of secondary structures at the genomic level.

An integrative approach for codon repeats evolutionary analyses

The relationship between genome characteristics and several human diseases has been a central research goal in genomics. Many studies have shown that specific gene patterns, such as amino acid repetitions, are associated with human diseases. However, several open questions still remain, such as, how these tandem repeats appeared in the evolutionary path or how they have evolved in orthologous genes of related organisms. In this paper, we present a computational solution that facilitates comparative studies of orthologous genes from various organisms. The application uses various web services to gather gene sequence information, local algorithms for tandem repeats identification and similarity measures for gene clustering.

EuGene: maximizing synthetic gene design for heterologous expression

Numerous software applications exist to deal with synthetic gene design, granting the field of heterologous expression a significant support. However, their dispersion requires the access to different tools and online services in order to complete one single project. Analyzing codon usage, calculating codon adaptation index (CAI), aligning orthologs and optimizing genes are just a few examples. A software application, EuGene, was developed for the optimization of multiple gene synthetic design algorithms. In a seamless automatic form, EuGene calculates or retrieves genome data on codon usage (relative synonymous codon usage and CAI), codon context (CPS and codon pair bias), GC content, hidden stop codons, repetitions, deleterious sites, protein primary, secondary and tertiary structures, gene orthologs, species housekeeping genes, performs alignments and identifies genes and genomes. The main function of EuGene is analyzing and redesigning gene sequences using multi-objective optimization techniques that maximize the coding features of the resulting sequence.

AVAILABILITY

EuGene is freely available for non-commercial use, at http://bioinformatics.ua.pt/eugene.

Large scale comparative codon-pair context analysis unveils general rules that fine-tune evolution of mRNA primary structure

Background

Codon usage and codon-pair context are important gene primary structure features that influence mRNA decoding fidelity. In order to identify general rules that shape codon-pair context and minimize mRNA decoding error, we have carried out a large scale comparative codon-pair context analysis of 119 fully sequenced genomes.

Methodologies/Principal Findings

We have developed mathematical and software tools for large scale comparative codon-pair context analysis. These methodologies unveiled general and species specific codon-pair context rules that govern evolution of mRNAs in the 3 domains of life. We show that evolution of bacterial and archeal mRNA primary structure is mainly dependent on constraints imposed by the translational machinery, while in eukaryotes DNA methylation and tri-nucleotide repeats impose strong biases on codon-pair context.

Conclusions

The data highlight fundamental differences between prokaryotic and eukaryotic mRNA decoding rules, which are partially independent of codon usage.

Computational and statistical methodologies for ORFeome primary structure analysis

Codon usage and context are biased in open reading frames (ORFs) of most genomes. Codon usage is largely influenced by biased genome G+C pressure, in particular in prokaryotes, but the general rules that govern the evolution of codon context remain largely elusive. To shed new light into this question, we have developed computational, statistical, and graphical tools for analysis of codon context on an ORFeome wide scale. Here, we describe these methodologies in detail and show how they can be used for analysis of ORFs of any genome sequenced.

Statistical, computational and visualization methodologies to unveil gene primary structure features

OBJECTIVES

Gene sequence features such as codon bias, codon context, and codon expansion (e.g. trinucleotide repeats) can be better understood at the genomic scale level by combining statistical methodologies with advanced computer algorithms and data visualization through sophisticated graphical interfaces. This paper presents the ANACONDA system, a bioinformatics application for gene primary structure analysis.

METHODS

Codon usage tables using absolute metrics and software for multivariate analysis of codon and amino acid usage are available in public databases. However, they do not provide easy computational and statistical tools to carry out detailed gene primary structure analysis on a genomic scale. We propose the usage of several statistical methods--contingency table analysis, residual analysis, multivariate analysis (cluster analysis)--to analyze the codon bias under various aspects (degree of association, contexts and clustering).

RESULTS

The developed solution is a software application that provides a user-guided analysis of codon sequences considering several contexts and codon usage on a genomic scale. The utilization of this tool in our molecular biology laboratory is focused on particular genomes, especially those from Saccharomyces cerevisiae, Candida albicans and Escherichia coli. In order to illustrate the applicability and output layouts of the software these species are herein used as examples.

CONCLUSIONS

The statistical tools incorporated in the system are allowing to obtain global views of important sequence features. It is expected that the results obtained will permit identification of general rules that govern codon context and codon usage in any genome. Additionally, identification of genes containing expanded codons that arise as a consequence of erroneous DNA replication events will permit uncovering new genes associated with human disease.

Comparative context analysis of codon pairs on an ORFeome scale

We have developed a system for comparative codon context analysis of open reading frames in whole genomes, providing insights into the rules that govern the evolution of codon-pair context.

Codon context is an important feature of gene primary structure that modulates mRNA decoding accuracy. We have developed an analytical software package and a graphical interface for comparative codon context analysis of all the open reading frames in a genome (the ORFeome). Using the complete ORFeome sequences of Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans and Escherichia coli, we show that this methodology permits large-scale codon context comparisons and provides new insight on the rules that govern the evolution of codon-pair context.

Driving change: the evolution of alternative genetic codes

Pioneering studies in the 1960s that elucidated the genetic code suggested that all extant forms of life use the same genetic code. This early presumption has subsequently been challenged by the discovery of deviations of the universal genetic code in prokaryotes, eukaryotic nuclear genomes and mitochondrial genomes. These studies have revealed that the genetic code is still evolving despite strong negative forces working against the fixation of mutations that result in codon reassignment. Recent data from in vitro, in vivo and in silico comparative genomics studies are revealing significant, previously overlooked links between modified nucleosides in tRNAs, genetic code ambiguity, genome base composition, codon usage and codon reassignment.

Yeast as a model organism for studying the evolution of nonstandard genetic codes

During the last 30 years, a number of alterations to the standard genetic code have been uncovered both in prokaryotes and eukaryotic nuclear and mitochondrial genomes. But, the study of the evolutionary pathways and molecular mechanisms of codon identity redefinition has been largely ignored due to the assumption that non-standard genetic codes can only evolve through neutral evolutionary mechanisms and that they have no functional significance. The recent discovery of a genetic code change in the genus Candida that evolved through an ambiguous messenger RNA decoding mechanism is bringing that naive assumption to an abrupt end by showing, in a rather dramatic way, that genetic code changes have profound physiological and evolutionary consequences for the species that redefine codon identity. In this paper, the recent data on the evolution of the Candida genetic code are reviewed and an experimental framework based on forced evolution, molecular genetics and comparative and functional genomics methodologies is put forward for the study of non-standard genetic codes and genetic code ambiguity in general. Additionally, the importance of using Saccharomyces cerevisiae as a model organism for elucidating the evolutionary pathway of the Candida and other genetic code changes is emphasised.

Comparative evolutionary genomics unveils the molecular mechanism of reassignment of the CTG codon in Candida spp

Using the (near) complete genome sequences of the yeasts Candida albicans, Saccharomyces cerevisiae, and Schizosaccharomyces pombe, we address the evolution of a unique genetic code change, which involves decoding of the standard leucine-CTG codon as serine in Candida spp. By using two complementary comparative genomics approaches, we have been able to shed new light on both the origin of the novel Candida spp. Ser-tRNA(CAG), which has mediated CTG reassignment, and on the evolution of the CTG codon in the genomes of C. albicans, S. cerevisiae, and S. pombe. Sequence analyses of newly identified tRNAs from the C. albicans genome demonstrate that the Ser-tRNA(CAG) is derived from a serine and not a leucine tRNA in the ancestor yeast species and that this codon reassignment occurred approximately 170 million years ago, but the origin of the Ser-tRNA(CAG) is more ancient, implying that the ancestral Leu-tRNA that decoded the CTG codon was lost after the appearance of the Ser-tRNA(CAG). Ambiguous CTG decoding by the Ser-tRNA(CAG) combined with biased AT pressure forced the evolution of CTG into TTR codons and have been major forces driving evolution of the CTN codon family in C. albicans. Remarkably, most of the CTG codons present in extant C. albicans genes are encoded by serine and not leucine codons in homologous S. cerevisiae and S. pombe genes, indicating that a significant number of serine TCN and AGY codons evolved into CTG codons either directly by simultaneous double mutations or indirectly through an intermediary codon. In either case, CTG reassignment had a major impact on the evolution of the coding component of the Candida spp. genome.

Stop codon decoding in Candida albicans: from non-standard back to standard

The human pathogen Candida albicans translates the standard leucine-CUG codon as serine. This genetic code change is mediated by a novel ser-tRNA(CAG), which induces aberrant mRNA decoding in vitro, resulting in retardation of the electrophoretic mobility of the polypeptides synthesized in its presence. These non-standard decoding events have been attributed to readthrough of the UAG and UGA stop codons encoded by the Brome Mosaic Virus RNA 4, which codes for the virion coat protein, and the rabbit globin mRNAs, respectively. In order to fully elucidate the behaviour of the C. albicans ser-tRNA(CAG) towards stop codons, we have used other cell-free translation systems and reporter genes. However, the reporter systems used encode several CUG codons, making it impossible to distinguish whether the slow migration of the polypeptides is caused by the replacement of leucines by serines at the CUG codons, readthrough, or a combination of both. Therefore, we have constructed new reporter systems lacking CUG codons and have used them to demonstrate that aberrant mRNA decoding in vitro is not a result from stop codon readthrough or any other non-standard translational event. Our data show that a single leucine to serine replacement at only one of the four CUG codons encoded by the BMV RNA-4 gene is responsible for the aberrant migration of the BMV coat protein on SDS-PAGE, suggesting that this amino acid substitution (ser for leu) significantly alters the structure of the virion coat protein. The data therefore show that the only aberrant event mediated by the ser-tRNA(CAG) is decoding of the leu-CUG codon as serine.

[Necrotizing fasciitis after varicella]

Necrotizing fasciitis is a rare and severe infection characterised by extremely rapid progressive involvement of the superficial fascias and deep dermal layers of the skin, with resultant vasculitis and necrosis. The authors present three clinical cases of necrotizing fasciitis; all three patients previously had varicella rash, rapid progressive spreading erythema with severe pain and toxic shock syndrome. Two patients had positive cultures of b-haemolytic streptococcus. Early stage differential diagnosis with celulitis, aggressive antibiotic treatment and pediatric intensive care support are essential. However, the main therapy is early extensive surgical approach involving all indurate areas, down to and including the muscle fascia.

The action of Cd, Cu, Cr, Zn, and Pb on fluid composition of Anodonta cygnea (L.): organic components

The heavy metals, Cd, Cu, Cr, Zn, and Pb, were used to incubate healthy specimens of the freshwater mussel species, Anodonta cygnea. Afterwards, their biological fluids, either haemolymph or extrapallial fluid were analyzed for the presence of several organic constituents, known to be important for biomineralization, such as proteins, glycosaminoglycans (GAGs) and glucosamine. Proteins were subjected to further study, namely through the total amino acid determination after acid hydrolysis. The most disturbing pollutants tested seem to be Pb, Zn, and Cr, which caused highly decreased overall compositions, namely with respect to protein, and glucosamine, in comparison to the control group. This suggests that this group contributes to a decrease of the metabolic activity, and thus mineralization, in the exposed animals.

Trance surgery in Brazil

This report presents the results of fieldwork in Brazil on healer-mediums who perform crude forms of surgery, often employing sharp instruments. We found that these healer-mediums were in a hyperaroused brain state while they were engaged in behaviors commonly described in the anthropology literature as "possession trance"; therefore, this practice is termed "trance surgery" in this report. The research was conducted at widely scattered sites throughout Brazil. We observed several thousand patients being treated by 9 trance surgeons and videotaped several hundred of these cases. In addition to background information and our own observational material, this paper includes 2 medical case reports, physiological data gathered from healers and patients, and results of a pathologist's examination of a surgically excised tumor. Topographic brain mapping revealed increased brain activity (36-44 Hz) when healer-mediums were engaged in trance behaviors, compared to resting baseline conditions at midline scalp locations (Cz, P < .009 and Pz, P < .004; both matched t tests). These results suggest the presence of a hyperaroused brain state associated with the trance behaviors of the healers. We believe that such a state is required for this unusual practice, but other factors may also be involved. In contrast, a small sample of patients monitored during possession trance surgical procedures revealed no high-frequency brain activity; instead, there were indications of cortical quieting, suggesting relaxation, despite the absence of anesthesia. Pathohistological examination of a tumor excised from a patient in our presence revealed a human fibroadenoma. We conclude that these practices are usually benign and that pain is often absent, despite the lack of sterile procedures and anesthesia. Although during the period of our investigation we were informed anecdotally of 3 cases involving serious complications or death, we personally observed no cases of shock, hemorrhage, or death. The cases presented in this paper, as well as others we have followed, suggest that serious illnesses, not likely to improve without treatment, may do so after trance surgery procedures are performed. If the major benefit of trance surgery is to initiate self-healing processes, it would have to do so in powerful ways, which possibly can be elucidated with positron emission tomography and functional magnetic resonance imaging scans. Positive findings would be helpful in understanding large-scale healing effects and may lead to new treatment protocols.

Organic compounds in the extrapalial fluid and haemolymph of Anodonta cygnea (L.) with emphasis on the seasonal biomineralization process

Bivalve mollusks, such as the freshwater mussel Anodonta cygnea, show seasonal changes in calcification. This cycle of calcification must either be a cause or a consequence for seasonal fluctuations in the organic composition of the animal's fluids, haemolymph and extrapallial fluid, the liquid media for biomineralization. We monitored the fluids of A. cygnea, throughout a 1-year cycle, for the presence of organic constituents, known to be important for biomineralization, such as proteins, glycosaminoglycans (GAGs) and hexosamines. Proteins were subjected to further study, namely through the total amino acid determination and fraction separation by agarose gel electrophoresis. GAG levels were fairly constant throughout the year, with a maximum concentration in July and a minimum in January, a feature also detected for glucosamine, although with higher fluctuations. Proteins showed highly increased concentrations during June and July, both in total amounts and individual fractions. All fractions showed similar trends throughout the year, with lowest general levels in October, the starting month of a period when some fractions were not detectable at all. All fractions ended this low period in May, when a sometimes-important increase could be detected. As to the total amino acid composition of the fluids, the general trend followed that of proteins, except for ornithine (Orn), a non-proteic amino acid. The overall fluctuations detected in the biological fluids of A. cygnea suggest that the main variation related to the calcification cycle must be quantitative, since no different compounds appear in specific periods, to achieve also specific results.