A Gene Expression Signature to Select Hepatocellular Carcinoma Patients for Liver Transplantation.

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.

Diversity and Composition of Pelagic Prokaryotic and Protist Communities in a Thin Arctic Sea-Ice Regime.

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.

Mechanisms underlying the dual-mode regulation of microtubule dynamics by Kip3/kinesin-8.

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.

Rabifier2: an improved bioinformatic classifier of Rab GTPases.

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.

Are There Rab GTPases in Archaea?

A complex endomembrane system is one of the hallmarks of Eukaryotes. Vesicle trafficking between compartments is controlled by a diverse protein repertoire, including Rab GTPases. These small GTP-binding proteins contribute identity and specificity to the system, and by working as molecular switches, trigger multiple events in vesicle budding, transport, and fusion. A diverse collection of Rab GTPases already existed in the ancestral Eukaryote, yet, it is unclear how such elaborate repertoire emerged. A novel archaeal phylum, the Lokiarchaeota, revealed that several eukaryotic-like protein systems, including small GTPases, are present in Archaea. Here, we test the hypothesis that the Rab family of small GTPases predates the origin of Eukaryotes. Our bioinformatic pipeline detected multiple putative Rab-like proteins in several archaeal species. Our analyses revealed the presence and strict conservation of sequence features that distinguish eukaryotic Rabs from other small GTPases (Rab family motifs), mapping to the same regions in the structure as in eukaryotic Rabs. These mediate Rab-specific interactions with regulators of the REP/GDI (Rab Escort Protein/GDP dissociation Inhibitor) family. Sensitive structure-based methods further revealed the existence of REP/GDI-like genes in Archaea, involved in isoprenyl metabolism. Our analysis supports a scenario where Rabs differentiated into an independent family in Archaea, interacting with proteins involved in membrane biogenesis. These results further support the archaeal nature of the eukaryotic ancestor and provide a new insight into the intermediate stages and the evolutionary path toward the complex membrane-associated signaling circuits that characterize the Ras superfamily of small GTPases, and specifically Rab proteins.

Staphylococcus aureus Survives with a Minimal Peptidoglycan Synthesis Machine but Sacrifices Virulence and Antibiotic Resistance.

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.

Evolutionary cell biology: two origins, one objective.

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.

Coiled-coil length: Size does matter.

Protein evolution is governed by processes that alter primary sequence but also the length of proteins. Protein length may change in different ways, but insertions, deletions and duplications are the most common. An optimal protein size is a trade-off between sequence extension, which may change protein stability or lead to acquisition of a new function, and shrinkage that decreases metabolic cost of protein synthesis. Despite the general tendency for length conservation across orthologous proteins, the propensity to accept insertions and deletions is heterogeneous along the sequence. For example, protein regions rich in repetitive peptide motifs are well known to extensively vary their length across species. Here, we analyze length conservation of coiled-coils, domains formed by an ubiquitous, repetitive peptide motif present in all domains of life, that frequently plays a structural role in the cell. We observed that, despite the repetitive nature, the length of coiled-coil domains is generally highly conserved throughout the tree of life, even when the remaining parts of the protein change, including globular domains. Length conservation is independent of primary amino acid sequence variation, and represents a conservation of domain physical size. This suggests that the conservation of domain size is due to functional constraints.

Bioinformatics projects supporting life-sciences learning in high schools.

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.

A comprehensive assessment of the transcriptome of cork oak (Quercus suber) through EST sequencing.

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.

Evolution of intracellular compartmentalization.

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.

Hope for GWAS: relevant risk genes uncovered from GWAS statistical noise.

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.

Analytical validation and algorithm improvement of HepatoPredict kit to assess hepatocellular carcinoma prognosis before a liver transplantation.

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.

A genomic signature and the identification of new sporulation genes.

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.

inTB - a data integration platform for molecular and clinical epidemiological analysis of tuberculosis.

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.

The superfamily of heme-copper oxygen reductases: types and evolutionary considerations.

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.

BRCA1 VUS: A functional analysis to differentiate pathogenic from benign variants identified in clinical diagnostic panels for breast cancer.

Genetic testing for susceptibility genes through next­generation 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, cytokinesis­blocked 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 induced­damage 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.

Stepwise evolution of the centriole-assembly pathway.

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.

Loss of genetic redundancy in reductive genome evolution.

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.

Thousands of rab GTPases for the cell biologist.

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.