Flow-induced endothelial surface reorganization and minimization of entropy generation rate

Effects of hydrodynamic shear on the shape of the endothelial surface are examined based on evaluations of the rate of entropy generation at the cell surface. A linear solution of the flow over a sinusoidally varying endothelial surface is used to evaluate the entropy generation rate on the cell surface for which measured cell dimensions are available. Both the local rate of entropy generation (equivalent to the rate of energy dissipation by viscous shear) at the peak of a cell and the total entropy generation rate over the cell surface are minimized under conditions of a constant cell surface area and a constant cell peak height; which yields horizontal cell dimensions that are close to those obtained experimentally.     

The hidden code in genomics: a tool for gene discovery.

Among new insights coming from the completion of sequencing of the human genome, reported in Nature and Science, are clues of how evolution has increased the complexity of species, and in particular how the genetic code has enabled this process. It is clear that life has not only evolved by increasing the number of genes, but also by ingeniously evolving an efficient code for expressing diversity in the building blocks (i.e. the amino acids). The rules of nucleic acid base pairing and the classification of amino acids according to hydrophobicity/hydrophilicity relationships define a binary DNA code, which determines the general biophysical characteristics of proteins. Sense and antisense strands can encode protein segments having inverted and complementary hydropathy. The underlying binary code controls association and dissociation of proteins and presumably represents a primordial code that might have emerged in the early stages of self-organizing biochemical cycles. It is the purpose of this communication to provide a perspective of the code in the context of a binary language from its primordial origin to its present day format and to propose to use this code as a genomic mining tool.     

HaMStR: Profile hidden markov model based search for orthologs in ESTs

Background  

EST sequencing is a versatile approach for rapidly gathering protein coding sequences. They provide direct access to an organism's gene repertoire bypassing the still error-prone procedure of gene prediction from genomic data. Therefore, ESTs are often the only source for biological sequence data from taxa outside mainstream interest. The widespread use of ESTs in evolutionary studies and particularly in molecular systematics studies is still hindered by the lack of efficient and reliable approaches for automated ortholog predictions in ESTs. Existing methods either depend on a known species tree or cannot cope with redundancy in EST data.     

IGENT: efficient entropy based algorithm for genome-wide gene-gene interaction analysis

Background

With the development of high-throughput genotyping and sequencing technology, there are growing evidences of association with genetic variants and complex traits. In spite of thousands of genetic variants discovered, such genetic markers have been shown to explain only a very small proportion of the underlying genetic variance of complex traits. Gene-gene interaction (GGI) analysis is expected to unveil a large portion of unexplained heritability of complex traits.

Methods

In this work, we propose IGENT, Information theory-based GEnome-wide gene-gene iNTeraction method. IGENT is an efficient algorithm for identifying genome-wide gene-gene interactions (GGI) and gene-environment interaction (GEI). For detecting significant GGIs in genome-wide scale, it is important to reduce computational burden significantly. Our method uses information gain (IG) and evaluates its significance without resampling.

Results

Through our simulation studies, the power of the IGENT is shown to be better than or equivalent to that of that of BOOST. The proposed method successfully detected GGI for bipolar disorder in the Wellcome Trust Case Control Consortium (WTCCC) and age-related macular degeneration (AMD).

Conclusions

The proposed method is implemented by C++ and available on Windows, Linux and MacOSX.

     

Intercalation binding of 6-substituted naphthothiopheneamides to DNA: enthalpy and entropy components.

N-(3-dimethylaminopropyl)naphtho[2,1-b]thiophene-4-carboxamide and the 6-substituted methoxy, methyl, fluoro, chloro, bromo, trifluoromethyl, and cyano derivatives have been shown to bind to DNA via intercalation with binding constants in the 35-900 X 10(3) range at 25 degrees C, pH 7, and [Na+] = 0.019M. Both electron-donating and -withdrawing substituents enhance intercalation binding, but the binding affinity is most enhanced by the cyano substituent. Calorimetric titrations for calf thymus DNA differ dramatically from those reported for ethidium [Hopkins et al. (1990) Biopolymers Vol. 29, pp. 449-459]. Apparent enthalpy parameters (delta HB) for intercalation are constant only at low coverage of sites and become much more positive as saturation is approached. In the plateau region, delta HB values for the parent and the cyano-, fluoro-, chloro-, and bromo-substituted compounds are nearly the same (approximately -5.9 kcal/mol). For the methyl- (-6.8 kcal/mol) and methoxy- (-7.5 kcal/mol) substituted compounds, the delta HB values are more exothermic than that for the unsubstituted compound, whereas delta HB for the trifluoromethyl compound is approximately 1 kcal/mol less exothermic. The corresponding delta SB values, corrected for mixing effects, are in the 7-15-cal/deg/mol range and are approximately linearly related to delta HB if the cyano derivative is excluded.     

An efficient code searching for sequence homology and DNA duplication

This paper presents a very simple and efficient algorithm that searches for sequence homology and gene duplication. The code finds the best alignment of two, short or long, sequences without having to specify how many unmatched bases are allowed to be looped out. Following Needleman & Wunsch (1970), Sellers (1974), Sankoff (1972) and Smith, Waterman & Fitch (1981) gap constraints are incorporated into the program and may be employed. The availability of such a fast computer code enables detection of homologous genes which may fulfill a different function at present, but have arisen from a common gene-ancestor. The code is extremely fast and runs in O(n3/2) units of time. It was applied to the phi X174 sequence.     

An indirect method for absorption rate estimation: Flurothyl-induced seizures

This paper develops a method to estimate a minimal amount of flurothyl necessary to induce the seizures (the seizure threshold). A simple mathematical model is proposed which permits one to determine the drug absorption rate from the amount which has been administered and from the measured latency to onset of seizure. Experimental animal (rats) were exposed to a continuous intake of flurothyl in two different situations: either being alone in the airtight chamber or sharing it in a pair. In the latter case, we assume that the two rats uniformly share the infused drug. Our calculations estimate that approximately 20 μl of flurothyl is necessary to induced twitches, whereas 25 μl of flurothyl is the dose required for the induction of clonic seizures. The model can be used to estimate the threshold amounts of any drug producing obvious behavioral changes irrespective of the route of administration.     

Load minimization of the genetic code: history does not explain the pattern

The average effect of errors acting on a genetic code (the change in amino-acid meaning resulting from point mutation and mistranslation) may be quantified as its ''load''. The natural genetic code shows a clear property of minimizing this load when compared against randomly generated variant codes. Two hypotheses may be considered to explain this property. First, it is possible that the natural code is the result of selection to minimize this load. Second, it is possible that the property is an historical artefact. It has previously been reported that amino acids that have been assigned to codons starting with the same base come from the same biosynthetic pathway. This probably reflects the manner in which the code evolved from a simpler code, and says more about the physicochemical mechanisms of code assembly than about selection. The apparent load minimization of the code may therefore follow as a consequence of the fact that the code could not have evolved any other way than to allow biochemically related amino acids to have related codons. Here then, we ask whether this ''historical'' force alone can explain the efficiency of the natural code in minimizing the effects of error. We therefore compare the error-minimizing ability of the natural code with that of alternative codes which, rather than being a random selection, are restricted such that amino acids from the same biochemical pathway all share the same first base. We find that although on average the restricted set of codes show a slightly higher efficiency than random ones, the real code remains extremely efficient relative to this subset P = 0.0003. This indicates that for the most part historical features do not explain the load- minimization property of the natural code. The importance of selection is further supported by the finding that the natural code''s efficiency improves relative to that of historically related codes after allowance is made for realistic mutational and mistranslational biases. Once mistranslational biases have been considered, fewer than four per 100,000 alternative codes are better than the natural code.     

SMOTIF: efficient structured pattern and profile motif search

Background  

A structured motif allows variable length gaps between several components, where each component is a simple motif, which allows either no gaps or only fixed length gaps. The motif can either be represented as a pattern or a profile (also called positional weight matrix). We propose an efficient algorithm, called SMOTIF, to solve the structured motif search problem, i.e., given one or more sequences and a structured motif, SMOTIF searches the sequences for all occurrences of the motif. Potential applications include searching for long terminal repeat (LTR) retrotransposons and composite regulatory binding sites in DNA sequences.     

Competitive virus and host RNAs: the interplay of a hidden virus and host interaction

During virus infection, viral RNAs and mRNAs function as blueprints for viral protein synthesis and possibly as pathogen-associated molecular patterns (PAMPs) in innate immunity. Here, considering recent research progress in microRNAs (miRNAs) and competitive endogenous RNAs (ceRNAs), we speculate that viral RNAs act as sponges and can sequester endogenous miRNAs within infected cells, thus cross-regulating the stability and translational efficiency of host mRNAs with shared miRNA response elements. This cross-talk and these reciprocal interactions between viral RNAs and host mRNAs are termed “competitive viral and host RNAs” (cvhRNAs). We further provide recent experimental evidence for the existence of cvhRNAs networks in hepatitis B virus (HBV), as well as Herpesvirus saimiri (HVS), lytic murine cytomegalovirus (MCMV) and human cytomegalovirus (HCMV) infections. In addition, the cvhRNA hypothesis also predicts possible cross-regulation between host and other viruses, such as hepatitis C virus (HCV), HIV, influenza virus, human papillomaviruses (HPV). Since the interaction between miRNAs and viral RNAs also inevitably leads to repression of viral RNA function, we speculate that virus may evolve either to employ cvhRNA networks or to avoid miRNA targeting for optimal fitness within the host. CvhRNA networks may therefore play a fundamental role in the regulation of viral replication, infection establishment, and viral pathogenesis.     

A computational model of visual marking using an inter-connected network of spiking neurons: the spiking search over time & space model (sSoTS).

In the real world, visual information is selected over time as well as space, when we prioritise new stimuli for attention. Watson and Humphreys [Watson, D., Humphreys, G.W., 1997. Visual marking: prioritizing selection for new objects by top-down attentional inhibition of old objects. Psychological Review 104, 90-122] presented evidence that new information in search tasks is prioritised by (amongst other processes) active ignoring of old items - a process they termed visual marking. In this paper we present, for the first time, an explicit computational model of visual marking using biologically plausible activation functions. The "spiking search over time and space" model (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca(2+)] sensitive K(+) current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. We show that, when coupled with a process of active inhibition applied to old items, frequency adaptation leads to old items being de-prioritised (and new items prioritised) across time in search. Furthermore, the time course of these processes mimics the time course of the preview effect in human search. The results indicate that the sSoTS model can provide a biologically plausible account of human search over time as well as space.     

Fragrep： An Efficient Search Tool for Fragmented Patterns in Genomic Sequences

Many classes of non-coding RNAs （ncRNAs; including Y RNAs, vault RNAs, RNase P RNAs, and MRP RNAs, as well as a novel class recently discovered in Dictyostelium discoideum） can be characterized by a pattern of short but well-conserved sequence elements that are separated by poorly conserved regions of sometimes highly variable lengths. Local alignment algorithms such as BLAST are therefore ill-suited for the discovery of new homologs of such ncRNAs in genomic sequences. The Fragrep tool instead implements an efficient algorithm for detecting the pattern fragments that occur in a given order. For each pattern fragment, the mismatch tolerance and bounds on the length of the intervening sequences can be specified separately. Furthermore, matches can be ranked by a statistically well-motivated scoring scheme.     

The tubulin code: Molecular components,readout mechanisms,and functions

Microtubules are cytoskeletal filaments that are dynamically assembled from α/β-tubulin heterodimers. The primary sequence and structure of the tubulin proteins and, consequently, the properties and architecture of microtubules are highly conserved in eukaryotes. Despite this conservation, tubulin is subject to heterogeneity that is generated in two ways: by the expression of different tubulin isotypes and by posttranslational modifications (PTMs). Identifying the mechanisms that generate and control tubulin heterogeneity and how this heterogeneity affects microtubule function are long-standing goals in the field. Recent work on tubulin PTMs has shed light on how these modifications could contribute to a “tubulin code” that coordinates the complex functions of microtubules in cells.

Introduction

Microtubules are key elements of the eukaryotic cytoskeleton that dynamically assemble from heterodimers of α- and β-tubulin. The structure of microtubules, as well as the protein sequences of α- and β-tubulin, is highly conserved in evolution, and consequently, microtubules look alike in almost all species. Despite the high level of conservation, microtubules adapt to a large variety of cellular functions. This adaptation can be mediated by a large panel of microtubule-associated proteins (MAPs), including molecular motors, as well as by mechanisms that directly modify the microtubules, thus either changing their biophysical properties or attracting subsets of MAPs that convey specific functions to the modified microtubules. Two different mechanism can generate microtubule diversity: the expression of different α- and β-tubulin genes, referred to as tubulin isotypes, and the generation of posttranslational modifications (PTMs) on α- and β-tubulin (Figs. 1 and ​and2).2). Although known for several decades, deciphering how tubulin heterogeneity controls microtubule functions is still largely unchartered. This review summarizes the current advances in the field and discusses new concepts arising.Open in a separate windowFigure 1.Tubulin heterogeneity generated by PTMs. (A) Schematic representation of the distribution of different PTMs of tubulin on the α/β-tubulin dimer with respect to their position in the microtubule lattice. Acetylation (Ac), phosphorylation (P), and polyamination (Am) are found within the tubulin bodies that assemble into the microtubule lattice, whereas polyglutamylation, polyglycylation, detyrosination, and C-terminal deglutamylation take place within the C-terminal tubulin tails that project away from the lattice surface. The tubulin dimer represents TubA1A and TubB2B (Fig. 2), and modification sites for polyglutamylation and polyglycylation have been randomly chosen. (B) Chemical structure of the branched peptide formed by polyglutamylation and polyglycylation, using the γ-carboxyl groups of the modified glutamate residues as acceptor sites for the isopeptide bonds. Note that in the case of polyglutamylation, the elongation of the side chains generates classical peptide bonds (Redeker et al., 1991).Open in a separate windowFigure 2.Heterogeneity of C-terminal tails of tubulin isotypes and their PTMs. The amino acid sequences of all tubulin genes found in the human genome are indicated, starting at the last amino acid of the folded tubulin bodies. Amino acids are represented in single-letter codes and color coded according to their biochemical properties. Known sites for polyglutamylation are indicated (Eddé et al., 1990; Alexander et al., 1991; Rüdiger et al., 1992). Potential modification sites (all glutamate residues) are indicated. Known C-terminal truncation reactions of α/β-tubulin (tub) are indicated. The C-terminal tails of the yeast Saccharomyces cerevisiae are shown to illustrate the phylogenetic diversity of these domains.

Tubulin isotypes

The cloning of the first tubulin genes in the late 1970’s (Cleveland et al., 1978) revealed the existence of multiple genes coding for α- or β-tubulin (Ludueña and Banerjee, 2008) that generate subtle differences in their amino acid sequences, particularly in the C-terminal tails (Fig. 2). It was assumed that tubulin isotypes, as they were named, assemble into discrete microtubule species that carry out unique functions. This conclusion was reinforced by the observation that some isotypes are specifically expressed in specialized cells and tissues and that isotype expression changes during development (Lewis et al., 1985; Denoulet et al., 1986). These high expectations were mitigated by a subsequent study showing that all tubulin isotypes freely copolymerize into heterogeneous microtubules (Lewis et al., 1987). To date, only highly specialized microtubules, such as ciliary axonemes (Renthal et al., 1993; Raff et al., 2008), neuronal microtubules (Denoulet et al., 1986; Joshi and Cleveland, 1989), and microtubules of the marginal band of platelets (Wang et al., 1986; Schwer et al., 2001) are known to depend on some specific (β) tubulin isotypes, whereas the function of most other microtubules appears to be independent of their isotype composition.More recently, a large number of mutations in single tubulin isotypes have been linked to deleterious neurodevelopmental disorders (Keays et al., 2007; Fallet-Bianco et al., 2008; Tischfield et al., 2010; Cederquist et al., 2012; Niwa et al., 2013). Mutations of a single tubulin isotype could lead to an imbalance in the levels of tubulins as a result of a lack of incorporation of mutant isoforms into the microtubule lattice or to incorporation that perturbs the architecture or dynamics of the microtubules. The analysis of tubulin disease mutations is starting to reveal how subtle alterations of the microtubule cytoskeleton can lead to functional aberrations in cells and organisms and might provide novel insights into the roles of tubulin isotypes that have so far been considered redundant.

Tubulin PTMs

Tubulin is subject to a large range of PTMs (Fig. 1), from well-known ones, such as acetylation or phosphorylation, to others that have so far mostly been found on tubulin. Detyrosination/tyrosination, polyglutamylation, and polyglycylation, for instance, might have evolved to specifically regulate tubulin and microtubule functions, in particular in cilia and flagella, as their evolution is closely linked to these organelles. The strong link between those modifications and tubulin evolution has led to the perception that they are tubulin PTMs; however, apart from detyrosination/tyrosination, most of them have other substrates (Regnard et al., 2000; Xie et al., 2007; van Dijk et al., 2008; Rogowski et al., 2009).

Tubulin acetylation.

Tubulin acetylation was discovered on lysine 40 (K40; Fig. 1 A) of flagellar α-tubulin in Chlamydomonas reinhardtii (L’Hernault and Rosenbaum, 1985) and is generally enriched on stable microtubules in cells. Considering that K40 acetylation per se has no effect on the ultrastructure of microtubules (Howes et al., 2014), it is rather unlikely that it directly stabilizes microtubules. As a result of its localization at the inner face of microtubules (Soppina et al., 2012), K40 acetylation might rather affect the binding of microtubule inner proteins, a poorly characterized family of proteins (Nicastro et al., 2011; Linck et al., 2014). Functional experiments in cells have further suggested that K40 acetylation regulates intracellular transport by regulating the traffic of kinesin motors (Reed et al., 2006; Dompierre et al., 2007). These observations could so far not be confirmed by biophysical measurements in vitro (Walter et al., 2012; Kaul et al., 2014), suggesting that in cells, K40 acetylation might affect intracellular traffic by indirect mechanisms.Enzymes involved in K40 acetylation are HDAC6 (histone deacetylase family member 6; Hubbert et al., 2002) and Sirt2 (sirtuin type 2; North et al., 2003). Initial functional studies used overexpression, depletion, or chemical inhibition of these enzymes. These studies should be discussed with care, as both HDAC6 and Sirt2 deacetylate other substrates and have deacetylase-independent functions and chemical inhibition of HDAC6 is not entirely selective for this enzyme (Valenzuela-Fernández et al., 2008). In contrast, acetyl transferase α-Tat1 (or Mec-17; Akella et al., 2010; Shida et al., 2010) specifically acetylates α-tubulin K40 (Fig. 3), thus providing a more specific tool to investigate the functions of K40 acetylation. Knockout mice of α-Tat1 are completely void of K40-acetylated tubulin; however, they show only slight phenotypic aberrations, for instance, in their sperm flagellum (Kalebic et al., 2013). A more detailed analysis of α-Tat1 knockout mice demonstrated that absence of K40 acetylation leads to reduced contact inhibition in proliferating cells (Aguilar et al., 2014). In migrating cells, α-Tat1 is targeted to microtubules at the leading edge by clathrin-coated pits, resulting in locally restricted acetylation of those microtubules (Montagnac et al., 2013). A recent structural study of α-Tat1 demonstrated that the low catalytic rate of this enzyme, together with its localization inside the microtubules, caused acetylation to accumulate selectively in stable, long-lived microtubules (Szyk et al., 2014), thus explaining the link between this PTM and stable microtubules in cells. However, the direct cellular function of K40 acetylation on microtubules is still unclear.Open in a separate windowFigure 3.Enzymes involved in PTM of tubulin. Schematic representation of known enzymes (mammalian enzymes are shown) involved in the generation and removal of PTMs shown in Fig. 1. Note that some enzymes still remain unknown, and some modifications are irreversible. (*CCP5 preferentially removes branching points [Rogowski et al., 2010]; however, the enzyme can also hydrolyze linear glutamate chains [Berezniuk et al., 2013]).Recent discoveries have brought up the possibility that tubulin could be subject to multiple acetylation events. A whole-acetylome study identified >10 novel sites on α- and β-tubulin (Choudhary et al., 2009); however, none of these sites have been confirmed. Another acetylation event has been described at lysine 252 (K252) of β-tubulin. This modification is catalyzed by the acetyltransferase San (Fig. 3) and might regulate the assembly efficiency of microtubules as a result of its localization at the polymerization interface (Chu et al., 2011).

Tubulin detyrosination.

Most α-tubulin genes in different species encode a C-terminal tyrosine residue (Fig. 2; Valenzuela et al., 1981). This tyrosine can be enzymatically removed (Hallak et al., 1977) and religated (Fig. 3; Arce et al., 1975). Mapping of tyrosinated and detyrosinated microtubules in cells using specific antibodies (Gundersen et al., 1984; Geuens et al., 1986; Cambray-Deakin and Burgoyne, 1987a) revealed that subsets of interphase and mitotic spindle microtubules are detyrosinated (Gundersen and Bulinski, 1986). As detyrosination was mostly found on stable and long-lived microtubules, especially in neurons (Cambray-Deakin and Burgoyne, 1987b; Robson and Burgoyne, 1989; Brown et al., 1993), it was assumed that this modification promotes microtubule stability (Gundersen et al., 1987; Sherwin et al., 1987). Although a direct stabilization of the microtubule lattice was considered unlikely (Khawaja et al., 1988), it was found more recently that detyrosination protects cellular microtubules from the depolymerizing activity of kinesin-13–type motor proteins, such as KIF2 or MCAK, thus increasing their longevity (Peris et al., 2009; Sirajuddin et al., 2014).Besides kinesin-13 motors, plus end–tracking proteins with cytoskeleton-associated protein glycine-rich (CAP-Gly) domains, such as CLIP170 or p150/glued, specifically interact with tyrosinated microtubules (Peris et al., 2006; Bieling et al., 2008) via this domain (Honnappa et al., 2006). In contrast, kinesin-1 moves preferentially on detyrosinated microtubules tracks in cells (Liao and Gundersen, 1998; Kreitzer et al., 1999; Konishi and Setou, 2009). The effect of detyrosination on kinesin-1 motor behavior was recently measured in vitro, and a small but significant increase in the landing rate and processivity of the motor has been found (Kaul et al., 2014). Such subtle changes in the motor behavior could, in conjunction with other factors, such as regulatory MAPs associated with cargo transport complexes (Barlan et al., 2013), lead to a preferential use of detyrosinated microtubules by kinesin-1 in cells.Despite the early biochemical characterization of a detyrosinating activity, the carboxypeptidase catalyzing detyrosination of α-tubulin has yet to be identified (Hallak et al., 1977; Argaraña et al., 1978, 1980). In contrast, the reverse enzyme, tubulin tyrosine ligase (TTL; Fig. 3; Raybin and Flavin, 1975; Deanin and Gordon, 1976; Argaraña et al., 1980), has been purified (Schröder et al., 1985) and cloned (Ersfeld et al., 1993). TTL modifies nonpolymerized tubulin dimers exclusively. This selectivity is determined by the binding interface between the TTL and tubulin dimers (Szyk et al., 2011, 2013; Prota et al., 2013). In contrast, the so far unidentified detyrosinase acts preferentially on polymerized microtubules (Kumar and Flavin, 1981; Arce and Barra, 1983), thus modifying a select population of microtubules within cells (Gundersen et al., 1987).In most organisms, only one unique gene for TTL exists. Consequently, TTL knockout mice show a huge accumulation of detyrosinated and particularly Δ2-tubulin (see next section). TTL knockout mice die before birth (Erck et al., 2005) with major developmental defects in the nervous system that might be related to aberrant neuronal differentiation (Marcos et al., 2009). TTL is strictly tubulin specific (Prota et al., 2013), indicating that all observed defects in TTL knockout mice are directly related to the deregulation of the microtubule cytoskeleton.

Δ2-tubulin and further C-terminal modification.

A biochemical study of brain tubulin revealed that ∼35% of α-tubulin cannot be retyrosinated (Paturle et al., 1989) because of the lack of the penultimate C-terminal glutamate residue of the primary protein sequence (Fig. 2; Paturle-Lafanechère et al., 1991). This so-called Δ2-tubulin (for two C-terminal amino acids missing) cannot undergo retyrosination as a result of structural constraints within TTL (Prota et al., 2013) and thus is considered an irreversible PTM.Δ2-tubulin accumulates in long-lived microtubules of differentiated neurons, axonemes of cilia and flagella, and also in cellular microtubules that have been artificially stabilized, for instance, with taxol (Paturle-Lafanechère et al., 1994). The generation of Δ2-tubulin requires previous detyrosination of α-tubulin; thus, the levels of this PTM are indirectly regulated by the detyrosination/retyrosination cycle. This mechanistic link is particularly apparent in the TTL knockout mice, which show massive accumulation of Δ2-tubulin in all tested tissues (Erck et al., 2005). Loss of TTL and the subsequent increase of Δ2-tubulin levels were also linked to tumor growth and might contribute to the aggressiveness of the tumors by an as-yet-unknown mechanism (Lafanechère et al., 1998; Mialhe et al., 2001). To date, no specific biochemical role of Δ2-tubulin has been determined; thus, one possibility is that the modification simply locks tubulin in the detyrosinated state.The enzymes responsible for Δ2-tubulin generation are members of a family of cytosolic carboxypeptidases (CCPs; Fig. 3; Kalinina et al., 2007; Rodriguez de la Vega et al., 2007), and most of them also remove polyglutamylation from tubulin (see next section; Rogowski et al., 2010). These enzymes are also able to generate Δ3-tubulin (Fig. 1 A; Berezniuk et al., 2012), indicating that further degradation of the tubulin C-terminal tails are possible; however, the functional significance of this event is unknown.

Polyglutamylation.

Polyglutamylation is a PTM that occurs when secondary glutamate side chains are formed on γ-carboxyl groups of glutamate residues in a protein (Fig. 1, A and B). The modification was first discovered on α- and β-tubulin from the brain (Eddé et al., 1990; Alexander et al., 1991; Rüdiger et al., 1992; Mary et al., 1994) as well as on axonemal tubulin from different species (Mary et al., 1996, 1997); however, it is not restricted to tubulin (Regnard et al., 2000; van Dijk et al., 2008). Using a glutamylation-specific antibody, GT335 (Wolff et al., 1992), it was observed that tubulin glutamylation increases during neuronal differentiation (Audebert et al., 1993, 1994) and that axonemes of cilia and flagella (Fouquet et al., 1994), as well as centrioles of mammalian centrosomes (Bobinnec et al., 1998), are extensively glutamylated.Enzymes catalyzing polyglutamylation belong to the TTL-like (TTLL) family (Regnard et al., 2003; Janke et al., 2005). In mammals, nine glutamylases exist, each of them showing intrinsic preferences for modifying either α- or β-tubulin as well as for initiating or elongating glutamate chains (Fig. 3; van Dijk et al., 2007). Two of the six well-characterized TTLL glutamylases also modify nontubulin substrates (van Dijk et al., 2008).Knockout or depletion of glutamylating enzymes in different model organisms revealed an evolutionarily conserved role of glutamylation in cilia and flagella. In motile cilia, glutamylation regulates beating behavior (Janke et al., 2005; Pathak et al., 2007; Ikegami et al., 2010) via the regulation of flagellar dynein motors (Kubo et al., 2010; Suryavanshi et al., 2010). Despite the expression of multiple glutamylases in ciliated cells and tissues, depletion or knockout of single enzymes often lead to ciliary defects, particularly in motile cilia (Ikegami et al., 2010; Vogel et al., 2010; Bosch Grau et al., 2013; Lee et al., 2013), suggesting essential and nonredundant regulatory functions of these enzymes in cilia.Despite the enrichment of polyglutamylation in neuronal microtubules (Audebert et al., 1993, 1994), knockout of TTLL1, the major polyglutamylase in brain (Janke et al., 2005), did not show obvious neuronal defects in mice (Ikegami et al., 2010; Vogel et al., 2010). This suggests a tolerance of neuronal microtubules to variations in polyglutamylation.Deglutamylases, the enzymes that reverse polyglutamylation, were identified within a novel family of CCPs (Kimura et al., 2010; Rogowski et al., 2010). So far, three out of six mammalian CCPs have been shown to cleave C-terminal glutamate residues, thus catalyzing both the reversal of polyglutamylation and the removal of gene-encoded glutamates from the C termini of proteins (Fig. 3). The hydrolysis of gene-encoded glutamate residues is not restricted to tubulin, in which it generates Δ2- and Δ3-tubulin, but has also been reported for other proteins such as myosin light chain kinase (Rusconi et al., 1997; Rogowski et al., 2010). One enzyme of the CCP family, CCP5, preferentially removes branching points generated by glutamylation, thus allowing the complete reversal of the polyglutamylation modification (Kimura et al., 2010; Rogowski et al., 2010). However, CCP5 can also hydrolyze C-terminal glutamate residues from linear peptide chains similar to other members of the CCP family (Berezniuk et al., 2013).CCP1 is mutated in a well-established mouse model for neurodegeneration, the pcd (Purkinje cell degeneration) mouse (Mullen et al., 1976; Greer and Shepherd, 1982; Fernandez-Gonzalez et al., 2002). The absence of a key deglutamylase leads to strong hyperglutamylation in brain regions that undergo degeneration, such as the cerebellum and the olfactory bulb (Rogowski et al., 2010). When glutamylation levels were rebalanced by depletion or knockout of the major brain polyglutamylase TTLL1 (Rogowski et al., 2010; Berezniuk et al., 2012), Purkinje cells survived. Although the molecular mechanisms of hyperglutamylation-induced degeneration remain to be elucidated, perturbation of neuronal transport, as well as changes in the dynamics and stability of microtubules, is expected to be induced by hyperglutamylation. Increased polyglutamylation levels have been shown to affect kinesin-1–mediated transport in cultured neurons (Maas et al., 2009), and the turnover of microtubules can also be regulated by polyglutamylation via the activation of microtubule-severing enzymes such as spastin (Lacroix et al., 2010).Subtle differences in polyglutamylation can be seen on diverse microtubules in different cell types. The functions of these modifications remain to be studied; however, its wide distribution strengthens the idea that it could be involved in fine-tuning a range of microtubule functions.

Polyglycylation.

Tubulin polyglycylation or glycylation, like polyglutamylation, generates side chains of glycine residues within the C-terminal tails of α- and β-tubulin (Fig. 1, A and B). The modification sites of glycylation are considered to be principally the same as for glutamylation, and indeed, both PTMs have been shown to be interdependent in cells (Rogowski et al., 2009; Wloga et al., 2009). Initially discovered on Paramecium tetraurelia tubulin (Redeker et al., 1994), glycylation has been extensively studied using two antibodies, TAP952 and AXO49 (Bressac et al., 1995; Levilliers et al., 1995; Bré et al., 1996). In contrast to polyglutamylation, glycylation is restricted to cilia and flagella in most organisms analyzed so far.Glycylating enzymes are also members of the TTLL family, and homologues of these enzymes have so far been found in all organisms with proven glycylation of ciliary axonemes (Rogowski et al., 2009; Wloga et al., 2009). In mammals, initiating (TTLL3 and TTLL8) and elongating (TTLL10) glycylases work together to generate polyglycylation (Fig. 3). In contrast, the two TTLL3 orthologues from Drosophila melanogaster can both initiate and elongate glycine side chains (Rogowski et al., 2009).In mice, motile ependymal cilia in brain ventricles acquire monoglycylation upon maturation, whereas polyglycylation is observed only after several weeks (Bosch Grau et al., 2013). Sperm flagella, in contrast, acquire long glycine chains much faster, suggesting that the extent of polyglycylation could correlate with the length of the axonemes (Rogowski et al., 2009). Depletion of glycylases in mice (ependymal cilia; Bosch Grau et al., 2013), zebrafish (Wloga et al., 2009; Pathak et al., 2011), Tetrahymena thermophila (Wloga et al., 2009), and D. melanogaster (Rogowski et al., 2009) consistently led to ciliary disassembly or severe ciliary defects. How glycylation regulates microtubule functions remains unknown; however, the observation that glycylation-depleted axonemes disassemble after initial assembly (Rogowski et al., 2009; Bosch Grau et al., 2013) suggests a role of this PTM in stabilizing axonemal microtubules. Strikingly, human TTLL10 is enzymatically inactive; thus, humans have lost the ability to elongate glycine side chains (Rogowski et al., 2009). This suggests that the elongation of the glycine side chains is not an essential aspect of the function of this otherwise critical tubulin PTM.

Other tubulin PTMs.

Several other PTMs have been found on tubulin. Early studies identified tubulin phosphorylation (Eipper, 1974; Gard and Kirschner, 1985; Díaz-Nido et al., 1990); however, no specific functions were found. The perhaps best-studied phosphorylation event on tubulin takes place at serine S172 of β-tubulin (Fig. 1 A), is catalyzed by the Cdk1 (Fig. 3), and might regulate microtubule dynamics during cell division (Fourest-Lieuvin et al., 2006; Caudron et al., 2010). Tubulin can be also modified by the spleen tyrosine kinase Syk (Fig. 3; Peters et al., 1996), which might play a role in immune cells (Faruki et al., 2000; Sulimenko et al., 2006) and cell division (Zyss et al., 2005; Sulimenko et al., 2006).Polyamination has recently been discovered on brain tubulin (Song et al., 2013), after having been overlooked for many years as a result of the low solubility of polyaminated tubulin. Among several glutamine residues of α- and β-tubulin that can be polyaminated, Q15 of β-tubulin is considered the primary modification site (Fig. 1 A). Polyamination is catalyzed by transglutaminases (Fig. 3), which modify free tubulin as well as microtubules in an irreversible manner, and most likely contribute to the stabilization of microtubules (Song et al., 2013).Tubulin was also reported to be palmitoylated (Caron, 1997; Ozols and Caron, 1997; Caron et al., 2001), ubiquitinated (Ren et al., 2003; Huang et al., 2009; Xu et al., 2010), glycosylated (Walgren et al., 2003; Ji et al., 2011), arginylated (Wong et al., 2007), methylated (Xiao et al., 2010), and sumoylated (Rosas-Acosta et al., 2005). These PTMs have mostly been reported without follow-up studies, and some of them are only found in specific cell types or organisms and/or under specific metabolic conditions. Further studies will be necessary to gain insights into their potential roles for the regulation of the microtubule cytoskeleton.

Current advances and future perspectives

The molecular heterogeneity of microtubules, generated by the expression of different tubulin isotypes and by the PTM of tubulin has fascinated the scientific community for ∼40 years. Although many important advances have been made in the past decade, the dissection of the molecular mechanisms and a comprehensive understanding of the biological functions of tubulin isotypes and PTMs will be a challenging field of research in the near future.

Direct measurements of the impact of tubulin heterogeneity.

The most direct and reliable type of experiments to determine the impact of tubulin heterogeneity on microtubule behavior are in vitro measurements with purified proteins. However, most biophysical work on microtubules has been performed with tubulin purified from bovine, ovine, or porcine brains, which can be obtained in large quantities and with a high degree of purity and activity (Vallee, 1986; Castoldi and Popov, 2003). Brain tubulin is a mixture of different tubulin isotypes and is heavily posttranslationally modified and thus inept for investigating the functions of tubulin heterogeneity (Denoulet et al., 1986; Cambray-Deakin and Burgoyne, 1987b; Paturle et al., 1989; Eddé et al., 1990). Thus, pure, recombinant tubulin will be essential to dissect the roles of different tubulin isoforms and PTMs.Attempts to produce recombinant, functional α- and β-tubulin in bacteria have failed so far (Yaffe et al., 1988), most likely because of the absence of the extensive tubulin-specific folding machinery (Yaffe et al., 1992; Gao et al., 1993; Tian et al., 1996; Vainberg et al., 1998) in prokaryotes. An alternative source of tubulin with less isotype heterogeneity and with almost no PTMs is endogenous tubulin from cell lines such as HeLa, which in the past has been purified using a range of biochemical procedures (Bulinski and Borisy, 1979; Weatherbee et al., 1980; Farrell, 1982; Newton et al., 2002; Fourest-Lieuvin, 2006). Such tubulin can be further modified with tubulin-modifying enzymes, such as polyglutamylases, either by expressing those enzymes in the cells before tubulin purification (Lacroix and Janke, 2011) or in vitro with purified enzymes (Vemu et al., 2014). Despite some technical limitations of these methods, HeLa tubulin modified in cells has been successfully used in an in vitro study on the role of polyglutamylation in microtubule severing (Lacroix et al., 2010).Naturally occurring variants of tubulin isotypes and PTMs can be purified from different organisms, organs, or cell types, but obviously, only some combinations of tubulin isotypes and PTMs can be obtained by this approach. The recent development of an affinity purification method using the microtubule-binding TOG (tumor overexpressed gene) domain of yeast Stu2p has brought a new twist to this approach, as it allows purifying small amounts of tubulin from any cell type or tissue (Widlund et al., 2012).The absence of tubulin heterogeneity in yeast has made budding and fission yeast potential expression systems for recombinant, PTM-free tubulin (Katsuki et al., 2009; Drummond et al., 2011; Johnson et al., 2011). However, the expression of mammalian tubulin in this system has remained impossible. This problem was then partially circumvented by expressing tubulin chimeras that consist of a yeast tubulin body fused to mammalian C-terminal tubulin tails, thus mimicking different tubulin isotypes (Sirajuddin et al., 2014). Moreover, detyrosination can be generated by deleting the key C-terminal residue from endogenous or chimeric α-tubulin (Badin-Larçon et al., 2004), and polyglutamylation is generated by chemically coupling glutamate side chains to specifically engineered tubulin chimeras (Sirajuddin et al., 2014). These approaches allowed the first direct measurements of the impact of tubulin isotypes and PTMs on the behavior of molecular motors in vitro (Sirajuddin et al., 2014) and the analysis of the effects of tubulin heterogeneity on microtubule behavior and interactions inside the yeast cell (Badin-Larçon et al., 2004; Aiken et al., 2014).Currently, the most promising development has been the successful purification of fully functional recombinant tubulin from the baculovirus expression system (Minoura et al., 2013). Using this system, defined α/β-tubulin dimers can be obtained using two different epitope tags on α- and β-tubulin, respectively. Although these epitope tags are essential for separating recombinant from the endogenous tubulin, they could also affect tubulin assembly or microtubule–MAP interactions. Thus, future developments should focus on eliminating these tags.Current efforts have brought the possibility of producing recombinant tubulin into reach. Further improvement and standardization of these methods will certainly provide a breakthrough in understanding the mechanisms by which tubulin heterogeneity contributes to microtubule functions.

Complexity of tubulin—understanding the regulatory principles.

The diversity of tubulin genes (isotypes) and the complexity of tubulin PTMs have led to the proposal of the term “tubulin code” (Verhey and Gaertig, 2007; Wehenkel and Janke, 2014), in analogy to the previously coined histone code (Jenuwein and Allis, 2001). Tubulin molecules consist of a highly structured and thus evolutionarily conserved tubulin body and the unstructured and less conserved C-terminal tails (Nogales et al., 1998). As PTMs and sequence variations within the tubulin body are expected to affect the conserved tubulin fold and therefore the properties of the microtubule lattice, they are not likely to be involved in generating the tubulin code. In contrast, modulations of the C-terminal tails could encode signals on the microtubule surface without perturbing basic microtubule functions and properties (Figs. 1 A and ​and4).4). Indeed, the highest degree of gene-encoded diversity (Fig. 2) and the highest density and complexity of PTMs (Fig. 1) are found within these tail domains.Open in a separate windowFigure 4.Molecular components of the tubulin code. Schematic representation of potential coding elements that could generate specific signals for the tubulin code. (A) The length of the C-terminal tails of different tubulin isotypes differ significantly (Fig. 2) and could have an impact on the interactions between microtubules and MAPs. (B) Tubulin C-terminal tails are rich in charged amino acid residues. The distribution of these residues and local densities of charges could influence the electrostatic interactions with the tails and the readers. (C) Although each glutamate residue within the C-terminal tails could be considered a potential modification site, only some sites have been found highly occupied in tubulin purifications from native sources. This indicates selectivity of the modification reactions, which can participate in the generation of specific modification patterns (see D). Modification sites might be distinguished by their neighboring amino acid residues, which could create specific modification epitopes. (D) As a result of the large number of modification sites and the variability of side chains, a large variety of modification patterns could be generated within a single C-terminal tail of tubulin. (E) Modification patterns as shown in D can be distinct between α- and β-tubulin. These modification patterns could be differentially distributed at the surface of the microtubule lattice, thus generating a higher-order patterning. Tub, tubulin. For color coding, see Fig. 2.Considering the number of tubulin isotypes plus all potential combinations of PTMs (e.g., each glutamate residue within the C-terminal tubulin tail could be modified by either polyglutamylation or polyglycylation, each of them generating side chains of different lengths; Fig. 4), the number of distinct signals generated by the potential tubulin code would be huge. However, as many of these potential signals represent chemical structures that are similar and might not be reliably distinguished by readout mechanisms, it is possible that the tubulin code generates probabilistic signals. In this scenario, biochemically similar modifications would have similar functional readouts, and marginal differences between those signals would only bias biological processes but not determine them. This stands in contrast to the concept of the histone code, in which precise patterns of different PTMs on the histone proteins encode distinct biological signals.The concept of probabilistic signaling is already inscribed in the machinery that generates the tubulin code. Polyglutamylases and polyglycylases from the TTLL family have preferential activities for either α- or β-tubulin and for generating different lengths of the branched glutamate or glycine chains. Although under conditions of low enzyme concentrations, as found in most cells and tissues, the enzymes seem to selectively generate their preferential type of PTM, higher enzyme concentrations induce a more promiscuous behavior, leading, for instance, to a loss of selectivity for α- or β-tubulin (van Dijk et al., 2007). Similarly, the modifying enzymes might prefer certain modification sites within the C-terminal tails of tubulin but might be equally able to modify other sites, which could be locally regulated in cells. For example, β-tubulin isotypes isolated from mammalian brain were initially found to be glutamylated on single residues (Alexander et al., 1991; Rüdiger et al., 1992), which in the light of the comparably low sensitivity of mass spectrometry at the time might rather indicate a preferential than a unique modification of these sites. Nevertheless, the neuron-specific polyglutamylase for β-tubulin TTLL7 (Ikegami et al., 2006) can incorporate glutamate onto many more modification sites of β-tubulin in vitro (Mukai et al., 2009), which clearly indicates that not all of the possible modification events take place under physiological conditions.Several examples supporting a probabilistic signaling mode of the tubulin code are found in the recent literature. In T. thermophila, a ciliate without tubulin isotype diversity (Gaertig et al., 1993) but with a huge repertoire of tubulin PTMs and tubulin-modifying enzymes (Janke et al., 2005), tubulin can be easily mutagenized to experimentally eliminate sites for PTMs. Mutagenesis of the most commonly occupied glutamylation/glycylation sites within the β-tubulin tails did not generate a clear decrease of glycylation levels nor did it cause obvious phenotypic alterations. This indicates that the modifying enzymes can deviate toward alternative modification sites and that similar PTMs on different sites can compensate the functions of the mutated site. However, when all of the key modification sites were mutated, glycylation became prominently decreased, which led to severe phenotypes, including lethality (Xia et al., 2000). Most strikingly, these phenotypes could be recovered by replacing the C-terminal tail of α-tubulin with the nonmutated β-tubulin tail. This α–β-tubulin chimera became overglycylated and functionally compensated for the absence of modification sites on β-tubulin. The conclusion of this study is that PTM- and isotype-generated signals can fulfill a biological function within a certain range of tolerance.But how efficient is such compensation? The answer can be found in a variety of already described deletion mutants for tubulin-modifying enzymes in different model organisms. Most single-gene knockouts for TTLL genes (glutamylases or glycylases) did not result in prominent phenotypic alterations in mice, even for enzymes that are ubiquitously expressed. Only some highly specialized microtubule structures show functional aberrations upon the deletion of a single enzyme. These “tips of the iceberg” are usually the motile cilia and sperm flagella, which carry very high levels of polyglutamylation and polyglycylation (Bré et al., 1996; Kann et al., 1998; Rogowski et al., 2009). It thus appears that some microtubules are essentially dependent on the generation of specific PTM patterns, whereas others can tolerate changes and appear to function normally. How “normal” these functions are remains to be investigated in future studies. It is possible that defects are subtle and thus overlooked but could become functionally important under specific conditions.A tubulin code also requires readout mechanisms. The most likely “readers” of the tubulin code are MAPs and molecular motors. Considering the probabilistic signaling hypothesis, the expected effects of the signals would be in most cases rather gradual changes, for instance, to fine-tune molecular motor traffic and/or to bias motors toward defined microtubule tracks but not to obliterate motor activity or MAP binding to microtubules. An in vitro study using recombinant tubulin chimeras purified from yeast confirmed this notion (Sirajuddin et al., 2014). By analyzing which elements of the tubulin code can regulate the velocity and processivity of the molecular motors kinesin and dynein, these researchers found that the C-terminal tails of α- and β-tubulin differentially influence the kinetic parameters of the tested motors; however, the modulation was rather modest. One of their striking observations was that a single lysine residue, present in the C-terminal tails of two β-tubulin isotypes (Figs. 2 and ​and4),4), significantly affected motor traffic and that this effect can be counterbalanced by polyglutamylation. These observations are the first in vitro evidence for the interdependence of different elements of the tubulin code and provide another indication for its probabilistic mode of signaling.

Future directions.

One of the greatest technological challenges to understanding the function of the tubulin code is to detect and interpret subtle and complex regulatory events generated by this code. It will thus be instrumental to further develop tools to better distinguish graded changes in PTM levels on microtubules in cells and tissues (Magiera and Janke, 2013) and to reliably measure subtle modulations of microtubule behavior in reconstituted systems.The current advances in the field and especially the availability of whole-organism models, as well as first insights into the pathological role of tubulin mutations (Tischfield et al., 2011), are about to transform our way of thinking about the regulation of microtubule cytoskeleton. Tubulin heterogeneity generates complex probabilistic signals that cannot be clearly attributed to single biological functions in most cases and that are not essential for most cellular processes. Nevertheless, it has been conserved throughout evolution of eukaryotes and can hardly be dismissed as not important. To understand the functional implications of these processes, we might be forced to reconsider how we define biologically important events and how we measure events that might encode probabilistic signals. The answers to these questions could provide novel insights into how complex systems, such as cells and organisms, are sustained throughout difficult and challenging life cycles, resist to environmental stress and diseases, and have the flexibility needed to succeed in evolution.     

On the classes of aminoacyl-tRNA synthetases and the error minimization in the genetic code

As a consequence of the existence of two classes of aminoacyl-tRNA synthetases (aaRSs), we defined two types of mutations: g (mutations that do not change the class of the involved amino acids) and u (those which change the class). We have found that the mean chemical distance resulting from g mutations is smaller than that corresponding to u mutations, indicating that g mutations are responsible for most of the known minimization of the genetic code. This supports models for the origin and evolution of the code, in which new amino acids were added after duplications or modification of existing aaRSs.     

Genetic code symmetry and efficient design of GC-constrained coding sequences

MOTIVATION: Cloning of long DNA sequences (40-60 bases) into phage display libraries using polymerase chain reaction (PCR) is a low efficiency process, in which PCR is used to incorporate a DNA insert, coding for a certain peptide, into the amplified sequence. The PCR efficiency in this process is strongly affected by the distribution of G-C bases in the amplified sequence. As any DNA insert coding for the target peptide may be attempted, there is a flexibility in choosing part of the amplified sequence. Since the number of inserts coding for the same peptide is exponential in the peptide length, a computational problem naturally arises--that of efficiently finding an insert, whose parameters are optimal for PCR cloning. RESULTS: The GC distribution requirements are formulated as a search problem. We developed an efficient, linear time 'one pass' algorithm for this problem. Interestingly, our algorithm strongly relies on an interesting symmetry, which we observed in the standard genetic code. Most non-standard genetic codes examined possess this symmetry as well, yet some do not. We generalize the search problem and consider the case of a non-standard, or arbitrary, genetic code where this symmetry does not necessary hold. We solve the generalized problem in polynomial, but nonlinear, time. AVAILABILITY: An implementation of the proposed algorithm is available upon request from the authors.     

The hidden spiral: systematic search and path integration in desert ants,Cataglyphis fortis

The main navigational mechanism used by foraging desert ants of the genus Cataglyphis is path integration (dead reckoning). Any such egocentric system of navigation is prone to cumulative navigational errors. Hence, while homing Cataglyphis might have reset its path integration system and yet not arrived at the start of its foraging excursion, the nest entrance. Then it resorts to piloting or performs a systematic search for the nest. The search pattern consists of a system of loops of ever increasing size centred about the origin, i.e. the start of the search. Here we show that underlying the system of loops is a spiral search programme that gets transformed into the observed pattern of loops by the ant's idiosyncratic path-integration algorithm. The ant starts to follow a spiral course, then breaks off this course and walks towards the centre, i.e. to what its path-integration system has computed to be the origin of the search. This reset episode is followed by another spiral course, which is terminated by the next reset, and so forth. After each reset, the spiral gets wider, so that the whole pattern expands. Futhermore, every now and then the spiral might change its sign. Computer simulations based on these simple rules lead to search patterns of the kind actually recorded in Cataglyphis ants. These patterns ensure that those parts of the area in which the target (nest entrance) is most likely to be located are searched most heavily; in other words: the search density profile is adapted to the probability density function of the target.     

Evolution of eukaryotic translation elongation and termination factors: variations of evolutionary rate and genetic code deviations.

Translation is carried out by the ribosome and several associated protein factors through three consecutive steps: initiation, elongation, and termination. Termination remains the least understood of them, partly because of the nonuniversality of the factors involved. To get some insights on the evolution of eukaryotic translation termination, we have compared the phylogeny of the release factors eRF1 and eRF3 to that of the elongation factors EF-1alpha and EF-2, with special focus on ciliates. Our results show that these four translation proteins have experienced different modes of evolution. This is especially evident for the EF-1alpha, EF-2, and eRF1 ciliate sequences. Ciliates appear as monophyletic in the EF-2 phylogenetic tree but not in the EF-1alpha and eRF1 phylogenetic trees. This seems to be mainly because of phylogeny reconstruction artifacts (the long-branch attraction) produced by the acceleration of evolutionary rate of ciliate EF-1alpha and eRF1 sequences. Interaction with the highly divergent actin found in ciliates, or on the contrary, loss of interaction, could explain the acceleration of the evolutionary rate of the EF-1alpha sequences. In the case of ciliate eRF1 sequences, their unusually high evolutionary rate may be related to the deviations in the genetic code usage found in diverse ciliates. These deviations involve a relaxation (or even abolition) of the recognition of one or two stop codons by eRF1. To achieve this, structural changes in eRF1 are needed, and this may affect its evolutionary rate. Eukaryotic translation seems to have followed a mosaic evolution, with its different elements governed by different selective pressures. However, a correlation analysis shows that, beneath the disagreement shown by the different translation proteins, their concerted evolution can still be made apparent when they are compared with other proteins that are not involved in translation.     

Chagas disease vaccine design: the search for an efficient Trypanosoma cruzi immune-mediated control

Chagas disease is currently endemic to 21 Latin-American countries and has also become a global concern because of globalization and mass migration of chronically infected individuals. Prophylactic and therapeutic vaccination might contribute to control the infection and the pathology, as complement of other strategies such as vector control and chemotherapy. Ideal prophylactic vaccine would produce sterilizing immunity; however, a reduction of the parasite burden would prevent progression from Trypanosoma cruzi infection to Chagas disease. A therapeutic vaccine for Chagas disease may improve or even replace the treatment with current drugs which have several side effects and require long term treatment that frequently leads to therapeutic withdrawal.Here, we will review some aspects about sub-unit vaccines, the rationale behind the selection of the immunogen, the role of adjuvants, the advantages and limitations of DNA-based vaccines and the idea of therapeutic vaccines. One of the main limitations to advance vaccine development against Chagas disease is the high number of variables that must be considered and the lack of uniform criteria among research laboratories. To make possible comparisons, much of this review will be focused on experiments that kept many variables constant including antigen mass/doses, type of eukaryotic plasmid, DNA-delivery system, mice strain and sex, lethal and sublethal model of infection, and similar immunogenicity and efficacy assessments.     

Spook and Spookier code for stage-specific components of the ecdysone biosynthetic pathway in Diptera

Ecdysteroids regulate many key developmental events in arthropods including molting and metamorphosis. Recently, members of the Drosophila Halloween group of genes, that are required for embryonic viability and cuticle deposition, have been shown to code for several cytochrome P450 enzymes that catalyze the terminal hydroxylation steps in the conversion of cholesterol to the molting hormone 20-hydroxyecdysone. These P450s are conserved in other insects and each is thought to function throughout development as the sole mediator of a particular biosynthetic step since, where analyzed, each is expressed at all stages of development and shows no closely related homolog in their respective genomes. In contrast, we show here that several dipteran genomes encode two novel, highly related, microsomal P450 enzymes, Cyp307A1 and Cyp307A2, that likely participate as stage-specific components of the ecdysone biosynthetic machinery. This hypothesis comes from the observation that Cyp307A1 is encoded by the Halloween gene spook (spo), but unlike other Halloween class genes, Dmspo is not expressed during the larval stages. In contrast, Cyp307a2, dubbed spookier (spok), is expressed primarily during larval stages within the prothoracic gland cells of the ring gland. RNAi mediated reduction in the expression of this heterochromatin localized gene leads to arrest at the first instar stage which can be rescued by feeding the larva 20E, E or ketodiol but not 7dC. In addition, spok expression is eliminated in larvae carrying mutations in molting defective (mld), a gene encoding a nuclear zinc finger protein that is required for production of ecdysone during Drosophila larval development. Intriguingly, mld is not present in the Bombyx mori genome, and we have identified only one spook homolog in both Bombyx and Manduca that is expressed in both embryos and larva. These studies suggest an evolutionary split between Diptera and Lepidoptera in how the ecdysone biosynthetic pathway is regulated during development.