Molecular chaperones fold many proteins and their mutated versions in a cell and can sometimes buffer the phenotypic effect of mutations that affect protein folding. Unanswered questions about this buffering include the nature of its mechanism, its influence on the genetic variation of a population, the fitness trade-offs constraining this mechanism, and its role in expediting evolution. Answering these questions is fundamental to understand the contribution of buffering to increase genetic variation and ecological diversification. Here, we performed experimental evolution, genome resequencing, and computational analyses to determine the trade-offs and evolutionary trajectories of Escherichia coli expressing high levels of the essential chaperonin GroEL. GroEL is abundantly present in bacteria, particularly in bacteria with large loads of deleterious mutations, suggesting its role in mutational buffering. We show that groEL overexpression is costly to large populations evolving in the laboratory, leading to groE expression decline within 66 generations. In contrast, populations evolving under the strong genetic drift characteristic of endosymbiotic bacteria avoid extinction or can be rescued in the presence of abundant GroEL. Genomes resequenced from cells evolved under strong genetic drift exhibited significantly higher tolerance to deleterious mutations at high GroEL levels than at native levels, revealing that GroEL is buffering mutations in these cells. GroEL buffered mutations in a highly diverse set of proteins that interact with the environment, including substrate and ion membrane transporters, hinting at its role in ecological diversification. Our results reveal the fitness trade-offs of mutational buffering and how genetic variation is maintained in populations.

Background In recent decades, increasing longevity (among other factors) has fostered a rise in Parkinson's disease incidence. Although not exhaustively studied in this devastating disease, the impact of sex represents a critical variable in Parkinson’s disease as epidemiological and clinical features differ between males and females. Methods To study sex bias in Parkinson’s disease, we conducted a systematic review to select sex-labeled transcriptomic data from three relevant brain tissues: the frontal cortex, the striatum, and the substantia nigra. We performed differential expression analysis on each study chosen. Then we summarized the individual differential expression results with three tissue-specific meta-analyses and a global all-tissues meta-analysis. Finally, results from the meta-analysis were functionally characterized using different functional profiling approaches. Results The tissue-specific meta-analyses linked Parkinson’s disease to the enhanced expression of MED31 in the female frontal cortex and the dysregulation of 237 genes in the substantia nigra. The global meta-analysis detected 15 genes with sex-differential patterns in Parkinson’s disease, which participate in mitochondrial function, oxidative stress, neuronal degeneration, and cell death. Furthermore, functional analyses identified pathways, protein–protein interaction networks, and transcription factors that differed by sex. While male patients exhibited changes in oxidative stress based on metal ions, inflammation, and angiogenesis, female patients exhibited dysfunctions in mitochondrial and lysosomal activity, antigen processing and presentation functions, and glutamic and purine metabolism. All results generated during this study are readily available by accessing an open web resource (http://bioinfo.cipf.es/metafun-pd/) for consultation and reuse in further studies. Conclusions Our in silico approach has highlighted sex-based differential mechanisms in typical Parkinson Disease hallmarks (inflammation, mitochondrial dysfunction, and oxidative stress). Additionally, we have identified specific genes and transcription factors for male and female Parkinson Disease patients that represent potential candidates as biomarkers to diagnosis.

Background: Multiple sclerosis (MS), a chronic auto-immune, inflammatory, and degenerative disease of the central nervous system, affects both males and females; however, females suffer from a higher risk of developing MS (2-3:1 ratio relative to males). The precise sex-based factors influencing risk of MS are currently unknown. Here, we explore the role of sex in MS to identify molecular mechanisms underlying observed MS sex differences that may guide novel therapeutic approaches tailored for males or females. Methods: We performed a rigorous and systematic review of genome-wide transcriptome studies of MS that included patient sex data in the Gene Expression Omnibus and ArrayExpress databases following PRISMA statement guidelines. We analyzed differential gene expression for each selected study and performed 3 meta-analyses to evaluate common features and sex bias: the first meta-analysis of 4 neurologic tissue studies, a second in 5 blood studies, and a third integrating 9 studies from both tissues. Finally, we performed a gene set analysis on the meta-analyzed differential transcriptomic profiles of the nervous system to characterize sex differences in biological pathways and phenotypes (physiological and pathological states). Results: After screening 122 publications, the systematic review provided a selection of 9 studies (5 in blood and 4 in neurologic tissue) with a total of 474 samples (189 females with MS and 109 control females; 82 males with MS and 94 control males). Blood and nervous tissue meta-analyses identified, respectively, 1 (KIR2DL3) and 13 (ARL17B, CECR7, CEP78, IFFO2, LOC401127, NUDT18, RNF10, SLC17A5, STMP1, TRAF3IP2-AS1, UBXN2B, ZNF117, ZNF488) MS-associated genes that differed between males and females. The combined-tissue meta-analysis highlighted a single RNA gene (LOC102723701) altered according to sex in MS patients. Functional analyses revealed different altered immune patterns in females and males. A pro-inflammatory environment and innate immune responses related to myeloid linage predominate in females, while in males, adaptive responses associated with the lymphocyte linage. Additionally, females with MS displayed alterations in mitochondrial respiratory chain complexes, purine, and glutamate metabolism, while MS males displayed alterations in stress response to metal ion, amine, and amino acid transport. Conclusion: We found transcriptomic and functional differences between MS males and females (especially in the immune system), which may support the development of sex-specific treatments. Our study highlights the importance of understanding the role of biological sex in MS.

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Human bone marrow mesenchymal stem cells (BM-MSCs) and cardiac progenitor/stem cells (CPCs) have been extensively studied as a potential therapeutic treatment for myocardial infarction (MI). Previous reports suggest that lower doses of CPCs are needed to improve cardiac function relative to their bone marrow counterparts. Here, we confirmed this observations and investigated the surface protein expression profile that might explain this effect. Myocardial infarction was performed in nude rats by permanent ligation of the left coronary artery. Cardiac function and infarct size before and after cell transplantation were evaluated by echocardiography and morphometry, respectively. The CPC and BM-MSC receptome were analyzed by proteomic analysis of biotin-labeled surface proteins. Rats transplanted with CPCs showed a greater improvement in cardiac function after MI than those transplanted with BM-MSCs, and this was associated with a smaller infarct size. Analysis of the receptome of CPCs and BM-MSCs showed that gene ontology biological processes and KEGG pathways associated with adhesion mechanisms were upregulated in CPCs compared with BM-MSCs. Moreover, the membrane protein interactome in CPCs showed a strong relationship with biological processes related to cell adhesion whereas the BM-MSCs interactome was more related to immune regulation processes. We conclude that the stronger capacity of CPCs over BM-MSCs to engraft in the infarcted area is likely linked to a more pronounced cell adhesion expression program.

Background:In recent decades, increasing longevity (among other factors) has fostered a rise in Parkinson's disease incidence. Although not exhaustively studied in this devastating disease, the impact of sex represents a critical variable in Parkinson’s Disease as epidemiological and clinical features differ between males and females. Methods: To study sex bias in Parkinson’s Disease, we conducted a systematic review to select sex-labeled transcriptomic data from three relevant brain tissues: the frontal cortex, the striatum, and the substantia nigra. We performed differential expression analysis on each study chosen. Then we summarized the individual differential expression results with three tissue-specific meta-analyses and a global all-tissues meta-analysis. Finally, results from the meta-analysis were functionally characterized using different functional profiling approaches. Results: The tissue-specific meta-analyses linked Parkinson’s Disease to the enhanced expression of MED31 in the female frontal cortex and the dysregulation of 237 genes in the substantia nigra. The global meta-analysis detected 15 genes with sex-differential patterns in Parkinson’s disease, which participate in mitochondrial function, oxidative stress, neuronal degeneration, and cell death. Furthermore, functional analyses identified pathways, protein-protein interaction networks, and transcription factors that differed by sex. While male patients exhibited changes in oxidative stress based on metal ions, inflammation, and angiogenesis, female patients exhibited dysfunctions in mitochondrial and lysosomal activity, antigen processing and presentation functions, and glutamic and purine metabolism. All results generated during this study are readily available by accessing an open web resource (http://bioinfo.cipf.es/metafun-pd/) for consultation and reuse in further studies. Conclusions: Our in-silico approach has highlighted sex-based differential mechanisms in typical Parkinson Disease hallmarks (inflammation, mitochondrial dysfunction, and oxidative stress). Additionally, we have identified specific genes and transcription factors for male and female Parkinson Disease patients that represent potential candidates as biomarkers to diagnosis.

Medical texts such as radiology reports or electronic health records are a powerful source of data for researchers. Anonymization methods must be developed to de-identify documents containing personal information from both patients and medical staff. Although currently there are several anonymization strategies for the English language, they are also language-dependent. Here, we introduce a named entity recognition strategy for Spanish medical texts, translatable to other languages. We tested 4 neural networks on our radiology reports dataset, achieving a recall of 97.18% of the identifying entities. Alongside, we developed a randomization algorithm to substitute the detected entities with new ones from the same category, making it virtually impossible to differentiate real data from synthetic data. The three best architectures were tested with the MEDDOCAN challenge dataset of electronic health records as an external test, achieving a recall of 69.18%. The strategy proposed, combining named entity recognition tasks with randomization of entities, is suitable for Spanish radiology reports. It does not require a big training corpus, thus it can be easily extended to other languages and medical texts, such as electronic health records.

Background Medical texts such as radiology reports or electronic health records are a powerful source of data for researchers. Anonymization methods must be developed to de-identify documents containing personal information from both patients and medical staff. Although currently there are several anonymization strategies for the English language, they are also language-dependent. Here, we introduce a named entity recognition strategy for Spanish medical texts, translatable to other languages. Results We tested 4 neural networks on our radiology reports dataset, achieving a recall of 97.18% of the identifying entities. Alongside, we developed a randomization algorithm to substitute the detected entities with new ones from the same category, making it virtually impossible to differentiate real data from synthetic data. The three best architectures were tested with the MEDDOCAN challenge dataset of electronic health records as an external test, achieving a recall of 69.18%. Conclusions The strategy proposed, combining named entity recognition tasks with randomization of entities, is suitable for Spanish radiology reports. It does not require a big training corpus, thus it could be easily extended to other languages and medical texts, such as electronic health records.