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Objectives: To verify the analytical performance of the HepatoPredict kit, a novel tool developed to stratify Hepatocellular Carcinoma (HCC) patients according to their risk of relapse after a Liver Transplantation (LT)., Methods: The HepatoPredict tool combines clinical variables and a gene expression signature in an ensemble of machine-learning algorithms to forecast the benefit of a LT in HCC patients. To ensure the accuracy and reliability of this method, extensive analytical validation was conducted to verify its specificity and robustness. The experiments were designed following the guidelines for multi-target genomic assays such as ISO201395-2019, MIQE, CLSI-MM16, CLSI-MM17, and CLSI-EP17-A. The validation process included reproducibility between operators and between RNA extractions and RT-qPCR runs, and interference of input RNA levels or varying reagent levels. A recently retrained version of the HepatoPredict algorithms was also tested., Results: The validation process demonstrated that the HepatoPredict kit met the required standards for robustness (p > 0.05), analytical specificity (inclusivity of 95 %), and sensitivity (LoB, LoD, linear range, and amplification efficiency between 90 and 110 %). The operator, equipment, input RNA, and reagents used had no significant effect on the HepatoPredict results. Additionally, the testing of a recently retrained version of the HepatoPredict algorithm, showed that this new version further improved the accuracy of the kit and performed better than existing clinical criteria in accurately identifying HCC patients who are more likely to benefit LT., Conclusions: Even with the introduced variations in molecular and clinical variables, the HepatoPredict kit's prognostic information remains consistent. It can accurately identify HCC patients who are more likely to benefit from a LT. Its robust performance also confirms that it can be easily integrated into standard diagnostic laboratories., Competing Interests: The work described here is subject to patent WO 2021/064230 A1; JPL, JC, and HPM declare an ownership interest in the company Ophiomics – Precision Medicine. MGR, DP, LPF, and JLN are employees at Ophiomics – Precision Medicine. SS has no competing interests., (© 2024 Ophiomics. Published by Elsevier B.V.)

Genetic testing for susceptibility genes through next‑generation sequencing (NGS) has become a widely used technique. Using this, a number of genetic variants have been identified, several of which are variants of unknown significance (VUS). These VUS can either be pathogenic or benign. However, since their biological effect remains unclear, functional assays are required to classify their functional nature. As the use of NGS becomes more mainstream as a diagnostic tool in clinical practice, the number of VUS is expected to increase. This necessitates their biological and functional classification. In the present study, a VUS was identified in the BRCA1 gene (NM_007294.3:c.1067A>G) in two women at risk for breast cancer, for which no functional data has been reported. Therefore, peripheral lymphocytes were isolated from the two women and also from two women without the VUS. DNA from all samples were sequenced by NGS of a breast cancer clinical panel. Since the BRCA1 gene is involved in DNA repair and apoptosis, the functional assays chromosomal aberrations, cytokinesis‑blocked micronucleus, comet, γH2AX, caspase and TUNEL assays were then conducted on these lymphocytes after a genotoxic challenge by ionizing radiation or doxorubicin to assess the functional role of this VUS. The micronucleus and TUNEL assays revealed a lower degree of DNA induced‑damage in the VUS group compared with those without the VUS. The other assays showed no significant differences between the groups. These results suggested that this BRCA1 VUS is likely benign, since the VUS carriers were apparently protected from deleterious chromosomal rearrangements, subsequent genomic instability and activation of apoptosis.

Objective: To propose a new decision algorithm combining biomarkers measured in a tumor biopsy with clinical variables, to predict recurrence after liver transplantation (LT)., Background: Liver cancer is one of the most frequent causes of cancer-related mortality. LT is the best treatment for hepatocellular carcinoma (HCC) patients but the scarcity of organs makes patient selection a critical step. In addition, clinical criteria widely applied in patient eligibility decisions miss potentially curable patients while selecting patients that relapse after transplantation., Methods: A literature systematic review singled out candidate biomarkers whose RNA levels were assessed by quantitative PCR in tumor tissue from 138 HCC patients submitted to LT (>5 years follow up, 32% beyond Milan criteria). The resulting 4 gene signature was combined with clinical variables to develop a decision algorithm using machine learning approaches. The method was named HepatoPredict., Results: HepatoPredict identifies 99% disease-free patients (>5 year) from a retrospective cohort, including many outside clinical criteria (16%-24%), thus reducing the false negative rate. This increased sensitivity is accompanied by an increased positive predictive value (88.5%-94.4%) without any loss of long-term overall survival or recurrence rates for patients deemed eligible by HepatoPredict; those deemed ineligible display marked reduction of survival and increased recurrence in the short and long term., Conclusions: HepatoPredict outperforms conventional clinical-pathologic selection criteria (Milan, UCSF), providing superior prognostic information. Accurately identifying which patients most likely benefit from LT enables an objective stratification of waiting lists and information-based allocation of optimal versus suboptimal organs., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc.)

Gut microbiota modulation might constitute a mechanism mediating the effects of beer on health. In this randomized, double-blinded, two-arm parallel trial, 22 healthy men were recruited to drink 330 mL of nonalcoholic beer (0.0% v/v) or alcoholic beer (5.2% v/v) daily during a 4-week follow-up period. Blood and faecal samples were collected before and after the intervention period. Gut microbiota was analyzed by 16S rRNA gene sequencing. Drinking nonalcoholic or alcoholic beer daily for 4 weeks did not increase body weight and body fat mass and did not changed significantly serum cardiometabolic biomarkers. Nonalcoholic and alcoholic beer increased gut microbiota diversity which has been associated with positive health outcomes and tended to increase faecal alkaline phosphatase activity, a marker of intestinal barrier function. These results suggest the effects of beer on gut microbiota modulation are independent of alcohol and may be mediated by beer polyphenols.

Hepatocellular carcinoma (HCC) is amongst the cancers with highest mortality rates and is the most common malignancy of the liver. Early detection is vital to provide the best treatment possible and liquid biopsies combined with analysis of circulating tumour DNA methylation show great promise as a non-invasive approach for early cancer diagnosis and monitoring with low false negative rates. To identify reliable diagnostic biomarkers of early HCC, we performed a systematic analysis of multiple hepatocellular studies and datasets comprising > 1500 genome-wide DNA methylation arrays, to define a methylation signature predictive of HCC in both tissue and cell-free DNA liquid biopsy samples. Our machine learning pipeline identified differentially methylated regions in HCC, some associated with transcriptional repression of genes related with cancer progression, that benchmarked positively against independent methylation signatures. Combining our signature of 38 DNA methylation regions, we derived a HCC detection score which confirmed the utility of our approach by identifying in an independent dataset 96% of HCC tissue samples with a precision of 98%, and most importantly successfully separated cfDNA of tumour samples from healthy controls. Notably, our risk score could identify cell-free DNA samples from patients with other tumours, including colorectal cancer. Taken together, we propose a comprehensive HCC DNA methylation fingerprint and an associated risk score for detection of HCC from tissue and liquid biopsies., (© 2022. The Author(s).)

The Mediterranean diet (MD) has been recommended for type 2 diabetes (T2D) treatment. The impact of diet in shaping the gut microbiota is well known, particularly for MD. However, the link between MD and diabetes outcome improvement is not completely clear. This study aims to evaluate the role of microbiota modulation by a nonpharmacological intervention in patients with T2D. In this 12-week single-arm pilot study, nine participants received individual nutritional counseling sessions promoting MD. Gut microbiota, biochemical parameters, body composition, and blood pressure were assessed at baseline, 4 weeks, and 12 weeks after the intervention. Adherence to MD [assessed by Mediterranean Diet Adherence Screener (MEDAS) score] increased after the intervention. Bacterial richness increased after 4 weeks of intervention and was negatively correlated with fasting glucose levels and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). Prevotella to Bacteroides ratio also increased after 4 weeks. In contrast, glycated haemoglobin (HbA1c) and HOMA-IR were only decreased at the end of study. Alkaline phosphatase activity was assessed in fecal samples and was negatively correlated with HbA1c and positively correlated with bacterial diversity. The results of this study reinforce that MD adherence results in a better glycemic control in subjects with T2D. Changes in gut bacterial richness caused by MD adherence may be relevant in mediating the metabolic impact of this dietary intervention.

One of the most prominent manifestations of climate change is the changing Arctic sea-ice regime with a reduction in the summer sea-ice extent and a shift from thicker, perennial multiyear ice towards thinner, first-year ice. These changes in the physical environment are likely to impact microbial communities, a key component of Arctic marine food webs and biogeochemical cycles. During the Norwegian young sea ICE expedition (N-ICE2015) north of Svalbard, seawater samples were collected at the surface (5 m), subsurface (20 or 50 m), and mesopelagic (250 m) depths on 9 March, 27 April, and 16 June 2015. In addition, several physical and biogeochemical data were recorded to contextualize the collected microbial communities. Through the massively parallel sequencing of the small subunit ribosomal RNA amplicon and metagenomic data, this work allows studying the Arctic's microbial community structure during the late winter to early summer transition. Results showed that, at compositional level, Alpha- (30.7%) and Gammaproteobacteria (28.6%) are the most frequent taxa across the prokaryotic N-ICE2015 collection, and also the most phylogenetically diverse. Winter to early summer trends were quite evident since there was a high relative abundance of thaumarchaeotes in the under-ice water column in late winter while this group was nearly absent during early summer. Moreover, the emergence of Flavobacteria and the SAR92 clade in early summer might be associated with the degradation of a spring bloom of Phaeocystis. High relative abundance of hydrocarbonoclastic bacteria, particularly Alcanivorax (54.3%) and Marinobacter (6.3%), was also found. Richness showed different patterns along the depth gradient for prokaryotic (highest at mesopelagic depth) and protistan communities (higher at subsurface depths). The microbial N-ICE2015 collection analyzed in the present study provides comprehensive new knowledge about the pelagic microbiota below drifting Arctic sea-ice. The higher microbial diversity found in late winter/early spring communities reinforces the need to continue with further studies to properly characterize the winter microbial communities under the pack-ice.

Disulfiram (DSF) can help treat alcohol dependency by inhibiting aldehyde dehydrogenase (ALDH). Genomic analysis revealed that Francisella tularensis, the causative agent of tularemia, has lost all but one ALDH-like domain and that this domain retains the target of DSF. In this study, minimum inhibitory concentration (MIC) assays demonstrated that both DSF and its primary metabolite diethyldithiocarbamate (DDC) have strong antimicrobial activity against F. tularensis strain SCHU S4, with the MIC of DSF determined as 2 µg/mL in comparison with 8 µg/mL for DDC. The activity of DSF was further confirmed using an in vitro human macrophage infection assay. Francisella tularensis bacteria in DSF-treated cells were reduced in comparison with untreated and DDC-treated cells, comparable with that observed in doxycycline-treated cells. This suggests that DSF may be suitable for further investigation as an in vivo therapy for tularemia., (Crown Copyright © 2019. Published by Elsevier B.V. All rights reserved.)

The centrosome is composed of two centrioles surrounded by a microtubule-nucleating pericentriolar material (PCM). Although centrioles are known to regulate PCM assembly, it is less known whether and how the PCM contributes to centriole assembly. Here we investigate the interaction between centriole components and the PCM by taking advantage of fission yeast, which has a centriole-free, PCM-containing centrosome, the SPB. Surprisingly, we observed that several ectopically-expressed animal centriole components such as SAS-6 are recruited to the SPB. We revealed that a conserved PCM component, Pcp1/pericentrin, interacts with and recruits SAS-6. This interaction is conserved and important for centriole assembly, particularly its elongation. We further explored how yeasts kept this interaction even after centriole loss and showed that the conserved calmodulin-binding region of Pcp1/pericentrin is critical for SAS-6 interaction. Our work suggests that the PCM not only recruits and concentrates microtubule-nucleators, but also the centriole assembly machinery, promoting biogenesis close by., Competing Interests: DI, SZ, SJ, PD, JS, ZC, JP, MF, MB No competing interests declared, (© 2019, Ito et al.)

Centrosome abnormalities are a typical hallmark of human cancers. However, the origin and dynamics of such abnormalities in human cancer are not known. In this study, we examined centrosomes in Barrett's esophagus tumorigenesis, a well-characterized multistep pathway of progression, from the premalignant condition to the metastatic disease. This human cancer model allows the study of sequential steps of progression within the same patient and has representative cell lines from all stages of disease. Remarkably, centrosome amplification was detected as early as the premalignant condition and was significantly expanded in dysplasia. It was then present throughout malignant transformation both in adenocarcinoma and metastasis. The early expansion of centrosome amplification correlated with and was dependent on loss of function of the tumor suppressor p53 both through loss of wild-type expression and hotspot mutations. Our work shows that centrosome amplification in human tumorigenesis can occur before transformation, being repressed by p53. These findings suggest centrosome amplification in humans can contribute to tumor initiation and progression., (© 2018 Lopes et al.)

Prokaryote genomes are the result of a dynamic flux of genes, with increases achieved via horizontal gene transfer and reductions occurring through gene loss. The ecological and selective forces that drive this genomic flexibility vary across species. Bacillus subtilis is a naturally competent bacterium that occupies various environments, including plant-associated, soil, and marine niches, and the gut of both invertebrates and vertebrates. Here, we quantify the genomic diversity of B. subtilis and infer the genome dynamics that explain the high genetic and phenotypic diversity observed. Phylogenomic and comparative genomic analyses of 42 B. subtilis genomes uncover a remarkable genome diversity that translates into a core genome of 1,659 genes and an asymptotic pangenome growth rate of 57 new genes per new genome added. This diversity is due to a large proportion of low-frequency genes that are acquired from closely related species. We find no gene-loss bias among wild isolates, which explains why the cloud genome, 43% of the species pangenome, represents only a small proportion of each genome. We show that B. subtilis can acquire xenologous copies of core genes that propagate laterally among strains within a niche. While not excluding the contributions of other mechanisms, our results strongly suggest a process of gene acquisition that is largely driven by competence, where the long-term maintenance of acquired genes depends on local and global fitness effects. This competence-driven genomic diversity provides B. subtilis with its generalist character, enabling it to occupy a wide range of ecological niches and cycle through them., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Studies of the role of actin in tumour progression have highlighted its key contribution in cell softening associated with cell invasion. Here, using a human breast cell line with conditional Src induction, we demonstrate that cells undergo a stiffening state prior to acquiring malignant features. This state is characterized by the transient accumulation of stress fibres and upregulation of Ena/VASP-like (EVL). EVL, in turn, organizes stress fibres leading to transient cell stiffening, ERK-dependent cell proliferation, as well as enhancement of Src activation and progression towards a fully transformed state. Accordingly, EVL accumulates predominantly in premalignant breast lesions and is required for Src-induced epithelial overgrowth in Drosophila. While cell softening allows for cancer cell invasion, our work reveals that stress fibre-mediated cell stiffening could drive tumour growth during premalignant stages. A careful consideration of the mechanical properties of tumour cells could therefore offer new avenues of exploration when designing cancer-targeting therapies.

Summary: The Rab family of small GTPases regulates and provides specificity to the endomembrane trafficking system; each Rab subfamily is associated with specific pathways. Thus, characterization of Rab repertoires provides functional information about organisms and evolution of the eukaryotic cell. Yet, the complex structure of the Rab family limits the application of existing methods for protein classification. Here, we present a major redesign of the Rabifier, a bioinformatic pipeline for detection and classification of Rab GTPases. It is more accurate, significantly faster than the original version and is now open source, both the code and the data, allowing for community participation., Availability and Implementation: Rabifier and RabDB are freely available through the web at http://rabdb.org . The Rabifier package can be downloaded from the Python Package Index at https://pypi.python.org/pypi/rabifier , the source code is available at Github https://github.com/evocell/rabifier ., Contact: jsurkont@igc.gulbenkian.pt or jleal@igc.gulbenkian.pt., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com)

Barrett's esophagus is the major risk factor for esophageal adenocarcinoma. It has a low but non-neglectable risk, high surveillance costs and no reliable risk stratification markers. We sought to identify early biomarkers, predictive of Barrett's malignant progression, using a meta-analysis approach on gene expression data. This in silico strategy was followed by experimental validation in a cohort of patients with extended follow up from the Instituto Português de Oncologia de Lisboa de Francisco Gentil EPE (Portugal). Bioinformatics and systems biology approaches singled out two candidate predictive markers for Barrett's progression, CYR61 and TAZ. Although previously implicated in other malignancies and in epithelial-to-mesenchymal transition phenotypes, our experimental validation shows for the first time that CYR61 and TAZ have the potential to be predictive biomarkers for cancer progression. Experimental validation by reverse transcriptase quantitative PCR and immunohistochemistry confirmed the up-regulation of both genes in Barrett's samples associated with high-grade dysplasia/adenocarcinoma. In our cohort CYR61 and TAZ up-regulation ranged from one to ten years prior to progression to adenocarcinoma in Barrett's esophagus index samples. Finally, we found that CYR61 and TAZ over-expression is correlated with early focal signs of epithelial to mesenchymal transition. Our results highlight both CYR61 and TAZ genes as potential predictive biomarkers for stratification of the risk for development of adenocarcinoma and suggest a potential mechanistic route for Barrett's esophagus neoplastic progression., Competing Interests: Authors JC and JPL received funding from commercial company Ophiomics Precision Medicine, for this study. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials.

The branch-site test of positive selection is a standard approach to detect past episodic positive selection in a priori-specified branches of a gene phylogeny. Here, we ask if differences in the topology of the gene tree have any influence on the ability to infer positively selected sites. Using simulated sequences, we compare the results obtained for true and rearranged topologies. We find a strong relationship between "conflicting branch length," which occurs when the set of sequences that experiences selection for a given topology and foreground is changed, and the ability to predict positively selected sites. Moreover, by reanalyzing a previously published data set, we show that the choice of a gene tree also affects the results obtained for real-world sequences. This is the first study to demonstrate that tree topology has a clear effect on the inference of positive selection. We conclude that the choice of a gene tree is an important factor for the branch-site analysis of positive selection.

Many important cellular processes are performed by molecular machines, composed of multiple proteins that physically interact to execute biological functions. An example is the bacterial peptidoglycan (PG) synthesis machine, responsible for the synthesis of the main component of the cell wall and the target of many contemporary antibiotics. One approach for the identification of essential components of a cellular machine involves the determination of its minimal protein composition. Staphylococcus aureus is a Gram-positive pathogen, renowned for its resistance to many commonly used antibiotics and prevalence in hospitals. Its genome encodes a low number of proteins with PG synthesis activity (9 proteins), when compared to other model organisms, and is therefore a good model for the study of a minimal PG synthesis machine. We deleted seven of the nine genes encoding PG synthesis enzymes from the S. aureus genome without affecting normal growth or cell morphology, generating a strain capable of PG biosynthesis catalyzed only by two penicillin-binding proteins, PBP1 and the bi-functional PBP2. However, multiple PBPs are important in clinically relevant environments, as bacteria with a minimal PG synthesis machinery became highly susceptible to cell wall-targeting antibiotics, host lytic enzymes and displayed impaired virulence in a Drosophila infection model which is dependent on the presence of specific peptidoglycan receptor proteins, namely PGRP-SA. The fact that S. aureus can grow and divide with only two active PG synthesizing enzymes shows that most of these enzymes are redundant in vitro and identifies the minimal PG synthesis machinery of S. aureus. However a complex molecular machine is important in environments other than in vitro growth as the expendable PG synthesis enzymes play an important role in the pathogenicity and antibiotic resistance of S. aureus.

Here, we report two genome sequences of endospore-forming bacteria isolated from the rice fields of Comporta, Portugal, identified as Bacillus aryabhattai C765 and Bacillus aerophilus C772. Both species were previously identified in air samples from the upper atmosphere, but our findings suggest their presence in a wider range of environmental niches., (Copyright © 2015 Ramos-Silva et al.)

The bioinformatic annotation of Rab GTPases is important, for example, to understand the evolution of the endomembrane system. However, Rabs are particularly challenging for standard annotation pipelines because they are similar to other small GTPases and form a large family with many paralogous subfamilies. Here, we describe a bioinformatic annotation pipeline specifically tailored to Rab GTPases. It proceeds in two steps: first, Rabs are distinguished from other proteins based on GTPase-specific motifs, overall sequence similarity to other Rabs, and the occurrence of Rab-specific motifs. Second, Rabs are classified taking either a more accurate but slower phylogenetic approach or a slightly less accurate but much faster bioinformatic approach. All necessary steps can either be performed locally or using the referenced online tools. An implementation of a slightly more involved version of the pipeline presented here is available at RabDB.org.

All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.

Hundreds of genetic variants have been associated to common diseases through genome-wide association studies (GWAS), yet there are limits to current approaches in detecting true small effect risk variants against a background of false positive findings. Here we addressed the missing heritability problem, aiming to test whether there are indeed risk variants within GWAS statistical noise and to develop a systematic strategy to retrieve these hidden variants. Employing an integrative approach, which combines protein-protein interactions with association data from GWAS for 6 common diseases, we found that associated-genes at less stringent significance levels (p < 0.1) with any of these diseases are functionally connected beyond noise expectation. This functional coherence was used to identify disease-relevant subnetworks, which were shown to be enriched in known genes, outperforming the selection of top GWAS genes. As a proof of principle, we applied this approach to breast cancer, supporting well-known breast cancer genes, while pinpointing novel susceptibility genes for experimental validation. This study reinforces the idea that GWAS are under-analyzed and that missing heritability is rather hidden. It extends the use of protein networks to reveal this missing heritability, thus leveraging the large investment in GWAS that produced so far little tangible gain.

Background: Cork oak (Quercus suber) is one of the rare trees with the ability to produce cork, a material widely used to make wine bottle stoppers, flooring and insulation materials, among many other uses. The molecular mechanisms of cork formation are still poorly understood, in great part due to the difficulty in studying a species with a long life-cycle and for which there is scarce molecular/genomic information. Cork oak forests are of great ecological importance and represent a major economic and social resource in Southern Europe and Northern Africa. However, global warming is threatening the cork oak forests by imposing thermal, hydric and many types of novel biotic stresses. Despite the economic and social value of the Q. suber species, few genomic resources have been developed, useful for biotechnological applications and improved forest management., Results: We generated in excess of 7 million sequence reads, by pyrosequencing 21 normalized cDNA libraries derived from multiple Q. suber tissues and organs, developmental stages and physiological conditions. We deployed a stringent sequence processing and assembly pipeline that resulted in the identification of ~159,000 unigenes. These were annotated according to their similarity to known plant genes, to known Interpro domains, GO classes and E.C. numbers. The phylogenetic extent of this ESTs set was investigated, and we found that cork oak revealed a significant new gene space that is not covered by other model species or EST sequencing projects. The raw data, as well as the full annotated assembly, are now available to the community in a dedicated web portal at http://www.corkoakdb.org., Conclusions: This genomic resource represents the first trancriptome study in a cork producing species. It can be explored to develop new tools and approaches to understand stress responses and developmental processes in forest trees, as well as the molecular cascades underlying cork differentiation and disease response.

The interdisciplinary nature of bioinformatics makes it an ideal framework to develop activities enabling enquiry-based learning. We describe here the development and implementation of a pilot project to use bioinformatics-based research activities in high schools, called "Bioinformatics@school." It includes web-based research projects that students can pursue alone or under teacher supervision and a teacher training program. The project is organized so as to enable discussion of key results between students and teachers. After successful trials in two high schools, as measured by questionnaires, interviews, and assessment of knowledge acquisition, the project is expanding by the action of the teachers involved, who are helping us develop more content and are recruiting more teachers and schools.

Background: Tuberculosis is currently the second highest cause of death from infectious diseases worldwide. The emergence of multi and extensive drug resistance is threatening to make tuberculosis incurable. There is growing evidence that the genetic diversity of Mycobacterium tuberculosis may have important clinical consequences. Therefore, combining genetic, clinical and socio-demographic data is critical to understand the epidemiology of this infectious disease, and how virulence and other phenotypic traits evolve over time. This requires dedicated bioinformatics platforms, capable of integrating and enabling analyses of this heterogeneous data., Results: We developed inTB, a web-based system for integrated warehousing and analysis of clinical, socio-demographic and molecular data for Mycobacterium sp. isolates. As a database it can organize and display data from any of the standard genotyping methods (SNP, MIRU-VNTR, RFLP and spoligotype), as well as an extensive array of clinical and socio-demographic variables that are used in multiple countries to characterize the disease. Through the inTB interface it is possible to insert and download data, browse the database and search specific parameters. New isolates are automatically classified into strains according to an internal reference, and data uploaded or typed in is checked for internal consistency. As an analysis framework, the system provides simple, point and click analysis tools that allow multiple types of data plotting, as well as simple ways to download data for external analysis. Individual trees for each genotyping method are available, as well as a super tree combining all of them. The integrative nature of inTB grants the user the ability to generate trees for filtered subsets of data crossing molecular and clinical/socio-demografic information. inTB is built on open source software, can be easily installed locally and easily adapted to other diseases. Its design allows for use by research laboratories, hospitals or public health authorities. The full source code as well as ready to use packages is available at http://www.evocell.org/inTB., Conclusions: To the best of our knowledge, this is the only system capable of integrating different types of molecular data with clinical and socio-demographic data, empowering researchers and clinicians with easy to use analysis tools that were not possible before.

Bacterial endospores are the most resistant cell type known to humans, as they are able to withstand extremes of temperature, pressure, chemical injury, and time. They are also of interest because the endospore is the infective particle in a variety of human and livestock diseases. Endosporulation is characterized by the morphogenesis of an endospore within a mother cell. Based on the genes known to be involved in endosporulation in the model organism Bacillus subtilis, a conserved core of about 100 genes was derived, representing the minimal machinery for endosporulation. The core was used to define a genomic signature of about 50 genes that are able to distinguish endospore-forming organisms, based on complete genome sequences, and we show this 50-gene signature is robust against phylogenetic proximity and other artifacts. This signature includes previously uncharacterized genes that we can now show are important for sporulation in B. subtilis and/or are under developmental control, thus further validating this genomic signature. We also predict that a series of polyextremophylic organisms, as well as several gut bacteria, are able to form endospores, and we identified 3 new loci essential for sporulation in B. subtilis: ytaF, ylmC, and ylzA. In all, the results support the view that endosporulation likely evolved once, at the base of the Firmicutes phylum, and is unrelated to other bacterial cell differentiation programs and that this involved the evolution of new genes and functions, as well as the cooption of ancestral, housekeeping functions.

Cells compartmentalize their biochemical functions in a variety of ways, notably by creating physical barriers that separate a compartment via membranes or proteins. Eukaryotes have a wide diversity of membrane-based compartments, many that are lineage- or tissue-specific. In recent years, it has become increasingly evident that membrane-based compartmentalization of the cytosolic space is observed in multiple prokaryotic lineages, giving rise to several types of distinct prokaryotic organelles. Endosymbionts, previously believed to be a hallmark of eukaryotes, have been described in several bacteria. Protein-based compartments, frequent in bacteria, are also found in eukaryotes. In the present review, we focus on selected intracellular compartments from each of these three categories, membrane-based, endosymbiotic and protein-based, in both prokaryotes and eukaryotes. We review their diversity and the current theories and controversies regarding the evolutionary origins. Furthermore, we discuss the evolutionary processes acting on the genetic basis of intracellular compartments and how those differ across the domains of life. We conclude that the distinction between eukaryotes and prokaryotes no longer lies in the existence of a compartmentalized cell plan, but rather in its complexity.

Bacillus subtilis is a Gram-positive, rod-shaped, spore-forming bacterium. We present the genome sequence of an undomesticated strain, BSP1, isolated from poultry. The sequence of the BSP1 genome supports the view that B. subtilis has a biphasic lifestyle, cycling between the soil and the animal gastrointestinal tract, and it provides molecular-level insight into the adaptation of B. subtilis to life under laboratory conditions.

Heme-copper oxygen reductases (HCO) reduce O(2) to water being the last enzymatic complexes of most aerobic respiratory chains. These enzymes promote energy conservation coupling the catalytic reaction to charge separation and charge translocation across the prokaryotic cytoplasmatic or mitochondrial membrane. In this way they contribute to the establishment and maintenance of the transmembrane difference of electrochemical potential, which is vital for solute/nutrient cell import, synthesis of ATP and motility. The HCO enzymes most probably share with the nitric oxide reductases, NORs, a common ancestor. We have proposed the classification of HCOs into three different types, A, B and C; based on the constituents of their proton channels (Pereira, Santana and Teixeira (2001) Biochim Biophys Acta, 1505, 185-208). This classification was recently challenged by the suggestion of other different types of HCOs. Using an enlarged sampling we performed an exhaustive bioinformatic reanalysis of HCOs family. Our results strengthened our previously proposed classification and showed no need for the existence of more divisions. Now, we analyze the taxonomic distribution of HCOs and NORs and the congruence of their sequence trees with the 16S rRNA tree. We observed that HCOs are widely distributed in the two prokaryotic domains and that the different types of enzymes are not confined to a specific taxonomic group or environmental niche., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Rab proteins are small GTPases that act as essential regulators of vesicular trafficking. 44 subfamilies are known in humans, performing specific sets of functions at distinct subcellular localisations and tissues. Rab function is conserved even amongst distant orthologs. Hence, the annotation of Rabs yields functional predictions about the cell biology of trafficking. So far, annotating Rabs has been a laborious manual task not feasible for current and future genomic output of deep sequencing technologies. We developed, validated and benchmarked the Rabifier, an automated bioinformatic pipeline for the identification and classification of Rabs, which achieves up to 90% classification accuracy. We cataloged roughly 8.000 Rabs from 247 genomes covering the entire eukaryotic tree. The full Rab database and a web tool implementing the pipeline are publicly available at www.RabDB.org. For the first time, we describe and analyse the evolution of Rabs in a dataset covering the whole eukaryotic phylogeny. We found a highly dynamic family undergoing frequent taxon-specific expansions and losses. We dated the origin of human subfamilies using phylogenetic profiling, which enlarged the Rab repertoire of the Last Eukaryotic Common Ancestor with Rab14, 32 and RabL4. Furthermore, a detailed analysis of the Choanoflagellate Monosiga brevicollis Rab family pinpointed the changes that accompanied the emergence of Metazoan multicellularity, mainly an important expansion and specialisation of the secretory pathway. Lastly, we experimentally establish tissue specificity in expression of mouse Rabs and show that neo-functionalisation best explains the emergence of new human Rab subfamilies. With the Rabifier and RabDB, we provide tools that easily allows non-bioinformaticians to integrate thousands of Rabs in their analyses. RabDB is designed to enable the cell biology community to keep pace with the increasing number of fully-sequenced genomes and change the scale at which we perform comparative analysis in cell biology.

The kinesin-8 family of microtubule motors plays a critical role in microtubule length control in cells. These motors have complex effects on microtubule dynamics: they destabilize growing microtubules yet stabilize shrinking microtubules. The budding yeast kinesin-8, Kip3, accumulates on plus ends of growing but not shrinking microtubules. Here we identify an essential role of the tail domain of Kip3 in mediating both its destabilizing and its stabilizing activities. The Kip3 tail promotes Kip3's accumulation at the plus ends and facilitates the destabilizing effect of Kip3. However, the Kip3 tail also inhibits microtubule shrinkage and is required for promoting microtubule rescue by Kip3. These effects of the tail domain are likely to be mediated by the tubulin- and microtubule-binding activities that we describe. We propose a concentration-dependent model for the coordination of the destabilizing and stabilizing activities of Kip3 and discuss its relevance to cellular microtubule organization., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Centrioles/basal bodies (CBBs) are microtubule-based cylindrical organelles that nucleate the formation of centrosomes, cilia, and flagella. CBBs, cilia, and flagella are ancestral structures; they are present in all major eukaryotic groups. Despite the conservation of their core structure, there is variability in their architecture, function, and biogenesis. Recent genomic and functional studies have provided insight into the evolution of the structure and function of these organelles.

Background: Heme-copper oxygen reductases (HCOs) are the last enzymatic complexes of most aerobic respiratory chains, reducing dioxygen to water and translocating up to four protons across the inner mitochondrial membrane (eukaryotes) or cytoplasmatic membrane (prokaryotes). The number of completely sequenced genomes is expanding exponentially, and concomitantly, the number and taxonomic distribution of HCO sequences. These enzymes were initially classified into three different types being this classification recently challenged., Methodology: We reanalyzed the classification scheme and developed a new bioinformatics classifier for the HCO and Nitric oxide reductases (NOR), which we benchmark against a manually derived gold standard sequence set. It is able to classify any given sequence of subunit I from HCO and NOR with a global recall and precision both of 99.8%. We use this tool to classify this protein family in 552 completely sequenced genomes., Conclusions: We concluded that the new and broader data set supports three functional and evolutionary groups of HCOs. Homology between NORs and HCOs is shown and NORs closest relationship with C Type HCOs demonstrated. We established and made available a classification web tool and an integrated Heme-Copper Oxygen reductase and NOR protein database (www.evocell.org/hco).

Biological systems evolved to be functionally robust in uncertain environments, but also highly adaptable. Such robustness is partly achieved by genetic redundancy, where the failure of a specific component through mutation or environmental challenge can be compensated by duplicate components capable of performing, to a limited extent, the same function. Highly variable environments require very robust systems. Conversely, predictable environments should not place a high selective value on robustness. Here we test this hypothesis by investigating the evolutionary dynamics of genetic redundancy in extremely reduced genomes, found mostly in intracellular parasites and endosymbionts. By combining data analysis with simulations of genome evolution we show that in the extensive gene loss suffered by reduced genomes there is a selective drive to keep the diversity of protein families while sacrificing paralogy. We show that this is not a by-product of the known drivers of genome reduction and that there is very limited convergence to a common core of families, indicating that the repertoire of protein families in reduced genomes is the result of historical contingency and niche-specific adaptations. We propose that our observations reflect a loss of genetic redundancy due to a decreased selection for robustness in a predictable environment.

The centriole and basal body (CBB) structure nucleates cilia and flagella, and is an essential component of the centrosome, underlying eukaryotic microtubule-based motility, cell division and polarity. In recent years, components of the CBB-assembly machinery have been identified, but little is known about their regulation and evolution. Given the diversity of cellular contexts encountered in eukaryotes, but the remarkable conservation of CBB morphology, we asked whether general mechanistic principles could explain CBB assembly. We analysed the distribution of each component of the human CBB-assembly machinery across eukaryotes as a strategy to generate testable hypotheses. We found an evolutionarily cohesive and ancestral module, which we term UNIMOD and is defined by three components (SAS6, SAS4/CPAP and BLD10/CEP135), that correlates with the occurrence of CBBs. Unexpectedly, other players (SAK/PLK4, SPD2/CEP192 and CP110) emerged in a taxon-specific manner. We report that gene duplication plays an important role in the evolution of CBB components and show that, in the case of BLD10/CEP135, this is a source of tissue specificity in CBB and flagella biogenesis. Moreover, we observe extreme protein divergence amongst CBB components and show experimentally that there is loss of cross-species complementation among SAK/PLK4 family members, suggesting species-specific adaptations in CBB assembly. We propose that the UNIMOD theory explains the conservation of CBB architecture and that taxon- and tissue-specific molecular innovations, gained through emergence, duplication and divergence, play important roles in coordinating CBB biogenesis and function in different cellular contexts.

Purpose: Mutations of the CHM gene underlie the X-linked chorioretinal degeneration choroideremia (CHM). The affected gene product, Rab Escort Protein (REP)1, mediates the posttranslational prenyl modification of Rab GTPases. In patients with CHM, the related REP2 partially compensates for the loss of function of REP1. The objective of this investigation was to study the natural history of disease in a zebrafish model of CHM., Methods: Zebrafish chm(-/-) were bred and subjected to extensive histologic analysis and TUNEL assays, and cellular extracts were used for immunoblot and in vitro prenylation assays. A detailed evolutionary analysis was performed on the REP family., Results: The retina of chm(-/-) zebrafish develops normally for the first 4 days postfertilization (dpf) but that catastrophic multilayer degeneration synchronous with severe multisystem disease follows. Mean survival time is 4.8 dpf. At the onset of generalized disease, a significant reduction in rep expression levels and activity, with unprenylated rabs accumulating in the cytosol was demonstrated. Extensive bioinformatic analysis of the REP family of proteins revealed a single rep isoform in fish and other nonmammalian vertebrates and invertebrates that is similar to mammalian REP1., Conclusions: REP1 appears to be the ancestral gene in the family, whereas the intronless REP2 gene is restricted to the mammalian lineage. The results of this study propose that in chm(-/-) zebrafish, maternally derived rep allows initial successful development of the embryo, but its gradual loss leads to multisystem disease and invariably to lethality. In its current form, the chm(-/-) zebrafish has limited usefulness.

The evolution of the eukaryotic endomembrane system and the transport pathways of their vesicular intermediates are poorly understood. A common set of organelles and pathways seems to be present in all free-living eukaryotes, but different branches of the tree of life have a variety of diverse, specialized organelles. Rab/Ypt proteins are small guanosine triphosphatases with tissue-specific and organelle-specific localization that emerged as markers for organelle diversity. Here, I characterize the Rab/Ypt family in the kingdom Fungi, a sister kingdom of Animals. I identify and annotate these proteins in 26 genomes representing near one billion years of evolution, multiple lifestyles and cellular types. Surprisingly, the minimal set of Rab/Ypt present in fungi is similar to, perhaps smaller than, the predicted eukaryotic ancestral set. This suggests that the saprophytic fungal lifestyle, multicellularity as well as the highly polarized secretion associated with hyphal growth did not require any major innovation in the molecular machinery that regulates protein trafficking. The Rab/Ypt and other protein traffic-related families are kept small, not paralleling increases in genome size, in contrast to the expansion of such components observed in other branches of the tree of life, such as the animal and plant kingdoms. This analysis suggests that multicellularity and cellular diversity in fungi followed different routes from those followed by plants and metazoa.

A functional module can be defined as a spatially or chemically isolated set of functionally associated components that accomplishes a discrete biological process. Modularity is a key attribute of cellular systems, but the mechanisms that underlie the evolution of functional modules are largely unknown. Duplication of modules has been shown to be an efficient mechanism for the generation of functional innovation in the field of artificial intelligence, but has not been studied in biological networks. Therefore, we ask whether module duplication occurs in cellular networks. We developed a generic framework for the analysis of module duplication, and use it in a large-scale analysis of Saccharomyces cerevisiae protein complexes. Protein complexes are well defined, experimentally derived, functional modules. We observe that at least 6%-20% of the protein complexes have strong similarity to other complexes; thus a considerable fraction has evolved by duplication. Our results indicate that many complexes evolved by step-wise partial duplications. We show that duplicated complexes retain the same overall function, but have different binding specificities and regulation, revealing that duplication of these modules is associated with functional specialization.

Protein interactions in the budding yeast have been shown to form a scale-free network, a feature of other organized networks such as bacterial and archaeal metabolism and the World Wide Web. Here, we study the connections established by yeast proteins and discover a preferential attachment between essential proteins. The essential-essential connections are long ranged and form a subnetwork where the giant component includes 97% of these proteins. Unexpectedly, this subnetwork displays an exponential connectivity distribution, in sharp contrast to the scale-free topology of the complete network. Furthermore, the wide phylogenetic extent of these core proteins and interactions provides evidence that they represent the ancestral state of the yeast protein interaction network. Finally, we propose that this core exponential network may represent a generic scaffold around which organism-specific and taxon-specific proteins and interactions coalesce.

Protein interactions are central to most biological processes. We investigated the dynamics of emergence of the protein interaction network of Saccharomyces cerevisiae by mapping origins of proteins on an evolutionary tree. We demonstrate that evolutionary periods are characterized by distinct connectivity levels of the emerging proteins. We found that the most-connected group of proteins dates to the eukaryotic radiation, and the more ancient group of pre-eukaryotic proteins is less connected. We show that functional classes have different average connectivity levels and that the time of emergence of these functional classes parallels the observed connectivity variation in evolution. We take these findings as evidence that the evolution of function might be the reason for the differences in connectivity throughout evolutionary time. We propose that the understanding of the mechanisms that generate the scale-free protein interaction network, and possibly other biological networks, requires consideration of protein function.

We examine the structural and functional classifications of the protein universe, providing an overview of the existing classification schemes, their features and inter-relationships. We argue that a unified scheme should be based on a natural classification approach and that more comparative analyses of the present schemes are required both to understand their limitations and to help delimit the number of known protein folds and their corresponding functional roles in cells.

Rab proteins are a large family of monomeric GTPases with 60 members identified in the human genome. Rab GTPases require an isoprenyl modification to their C-terminus for membrane association and function in the regulation of vesicular trafficking pathways. This reaction is catalysed by Rab geranylgeranyl transferase, which recognises as protein substrate any given Rab in a 1:1 complex with Rab Escort Protein (REP). REP is therefore able to bind many distinct Rab proteins but the molecular basis for this activity is still unclear. We recently identified conserved motifs in Rabs termed RabF motifs, which we proposed to mediate a conserved mode of interaction between Rabs and REPs. Here, we tested this hypothesis. We first used REP1 as a bait in the yeast two-hybrid system and isolated strictly full-length Rabs, suggesting that REP recognises multiple regions within and properly folded Rabs. We introduced point mutations in Rab3a as a model Rab and assessed the ability of the mutants to interact with REP using the yeast two-hybrid system and an in vitro prenylation assay. We identified several residues that affect REP:Rab binding in the RabF1, RabF3, and RabF4 regions (which include parts of the switch I and II regions), but not other RabF regions. These results support the hypothesis that Rabs bind REP via conserved RabF motifs and provide a molecular explanation for the preferential recognition of the GDP-bound conformation of Rab by REP.