Identification of Apolipoprotein N-Acyltransferase (Lnt) in Mycobacteria

Lipoproteins of Gram-negative and Gram-positive bacteria carry a thioether-bound diacylglycerol but differ by a fatty acid amide bound to the α-amino group of the universally conserved cysteine. In Escherichia coli the N-terminal acylation is catalyzed by the N-acyltransferase Lnt. Using E. coli Lnt as a query in a BLASTp search, we identified putative lnt genes also in Gram-positive mycobacteria. The Mycobacterium tuberculosis lipoprotein LppX, heterologously expressed in Mycobacterium smegmatis, was N-acylated at the N-terminal cysteine, whereas LppX expressed in a M. smegmatis lnt::aph knock-out mutant was accessible for N-terminal sequencing. Western blot analyses of a truncated and tagged form of LppX indicated a smaller size of about 0.3 kDa in the lnt::aph mutant compared with the parental strain. Matrix-assisted laser desorption ionization time-of-flight/time-of-flight analyses of a trypsin digest of LppX proved the presence of the diacylglycerol modification in both strains, the parental strain and lnt::aph mutant. N-Acylation was found exclusively in the M. smegmatis parental strain. Complementation of the lnt::aph mutant with M. tuberculosis ppm1 restored N-acylation. The substrate for N-acylation is a C16 fatty acid, whereas the two fatty acids of the diacylglycerol residue were identified as C16 and C19:0 fatty acid, the latter most likely tuberculostearic acid. We demonstrate that mycobacterial lipoproteins are triacylated. For the first time to our knowledge, we identify Lnt activity in Gram-positive bacteria and assigned the responsible genes. In M. smegmatis and M. tuberculosis the open reading frames are annotated as MSMEG_3860 and M. tuberculosis ppm1, respectively.Proteins of various organisms are modified in numerous ways, one of them is lipidation. Lipid modification of proteins is common in eucaryal and bacterial organisms and can involve myristoyl, palmitoyl, and isoprenyl polymers of various lengths or aminoglycan-linked phospholipids (1, 2). Lipoprotein modifications investigated here are restricted to bacteria.The lipoprotein biosynthesis pathway is a major virulence factor in Mycobacterium tuberculosis, the causative agent of human tuberculosis. Every year 1.6 million people fall prey to tuberculosis and one-third of the population of the world are infected. Thus, tuberculosis is responsible for 2.5% of deaths in the world, which is the highest rate claimed by a single infectious agent. An M. tuberculosis knock-out mutant deficient in lipoprotein signal peptidase lspA showed reduced multiplication in bone marrow-derived macrophages, complete absence of lung pathology and a 1000-fold reduced number of colony forming units in a mouse model of infection (3, 4). Likewise, lipoprotein synthesis contributes to virulence of other Gram-positive pathogens, Listeria, Staphylococci, and Streptococci (5).Bacterial lipoproteins are a functionally diverse class of lipidated proteins involved in cell wall synthesis, nutrient uptake, adhesion, and transmembrane signaling (6) and about 2% of open reading frames encode this kind of proteins (7). Lipidation allows anchoring of these proteins to the cell surface. Lipoproteins are characterized by the presence of a consensus sequence, the “lipobox,” located in the C-terminal part of the leader sequence and consisting of four amino acids (LVI/ASTVI/GAS/C) (7). Precursor lipoproteins are mainly translocated in a Sec-dependent manner across the plasma membrane and modified subsequently on the universally conserved, essential cysteine residue located in the lipobox motif. The modifications taking place after translocation are consecutively mediated by three enzymes: 1) formation of a thioether linkage between the conserved cysteine residue and a diacylglycerol catalyzed by phosphatidylglycerol:pre-prolipoprotein diacylglycerol transferase (Lgt), 2) cleavage of the N-terminal signal peptide by the prolipoprotein signal peptidase/signal peptidase II (LspA), and 3) in the case of Gram-negative bacteria, aminoacylation of the N-terminal cysteine residue by phospholipid:apolipoprotein N-acyltransferase (Lnt) (6–8). In Escherichia coli, most of the mature triacylated lipoproteins are finally transported across the periplasm by the LolABCDE transport system (9). Homologues of the Lol-transport system are absent in Mycobacteria. Although lipoprotein modifying enzymes act sequentially, Lgt-independent LspA-mediated signal sequence cleavage has recently been demonstrated in Listeria monocytogenes (10). Although Lgt and LspA are universally present in both Gram-positive and Gram-negative bacteria, Lnt has been reported to be restricted to Gram-negative bacteria (11), although some indications for N-acylation in Bacillus subtilis and Staphylococcus aureus were reported (12–15).Mycobacterial lipoproteins are immunodominant antigens (16) and several manipulate innate immune mechanisms and antigen presenting cells (17). It is known that mycobacterial lipoproteins, e.g. the 19-kDa lipoprotein, activate Toll-like receptor 2 (TLR2) and co-receptors TLR1, which recognize triacylated peptides, but also TLR6, which recognize diacylated peptides (18, 19). However, the lipid linkage of mycobacterial lipoproteins has not been determined.In this study, we show that Lnt activity is more widely distributed than previously assumed. We demonstrate apolipoprotein N-acyltransferase activity in a Gram-positive Mycobacterium and give complete structural information about the lipid modification of mycobacterial lipoproteins. Hereby, the functionality of Lnt homologues in actinomycetes is revealed (5). We show that mycobacterial lipoproteins are triacylated and carry mycobacteria-specific fatty acids.     

Patterns of split sex ratio in ants have multiple evolutionary causes based on different within-colony conflicts

Split sex ratio—a pattern where colonies within a population specialize in either male or queen production—is a widespread phenomenon in ants and other social Hymenoptera. It has often been attributed to variation in colony kin structure, which affects the degree of queen–worker conflict over optimal sex allocation. However, recent findings suggest that split sex ratio is a more diverse phenomenon, which can evolve for multiple reasons. Here, we provide an overview of the main conditions favouring split sex ratio. We show that each split sex-ratio type arises due to a different combination of factors determining colony kin structure, queen or worker control over sex ratio and the type of conflict between colony members.     

Chemopreventive and renal protective effects for docosahexaenoic acid (DHA): implications of CRP and lipid peroxides

Background

The fish oil-derived ω-3 fatty acids, like docosahexanoic (DHA), claim a plethora of health benefits. We currently evaluated the antitumor effects of DHA, alone or in combination with cisplatin (CP) in the EAC solid tumor mice model, and monitored concomitant changes in serum levels of C-reactive protein (CRP), lipid peroxidation (measured as malondialdehyde; MDA) and leukocytic count (LC). Further, we verified the capacity of DHA to ameliorate the lethal, CP-induced nephrotoxicity in rats and the molecular mechanisms involved therein.

Results

EAC-bearing mice exhibited markedly elevated LC (2-fold), CRP (11-fold) and MDA levels (2.7-fold). DHA (125, 250 mg/kg) elicited significant, dose-dependent reductions in tumor size (38%, 79%; respectively), as well as in LC, CRP and MDA levels. These effects for CP were appreciably lower than those of DHA (250 mg/kg). Interestingly, DHA (125 mg/kg) markedly enhanced the chemopreventive effects of CP and boosted its ability to reduce serum CRP and MDA levels. Correlation studies revealed a high degree of positive association between tumor growth and each of CRP (r = 0.85) and leukocytosis (r = 0.89), thus attesting to a diagnostic/prognostic role for CRP. On the other hand, a single CP dose (10 mg/kg) induced nephrotoxicity in rats that was evidenced by proteinuria, deterioration of glomerular filtration rate (GFR, -4-fold), a rise in serum creatinine/urea levels (2–5-fold) after 4 days, and globally-induced animal fatalities after 7 days. Kidney-homogenates from CP-treated rats displayed significantly elevated MDA- and TNF-α-, but reduced GSH-, levels. Rats treated with DHA (250 mg/kg, but not 125 mg/kg) survived the lethal effects of CP, and showed a significant recovery of GFR; while their homogenates had markedly-reduced MDA- and TNF-α-, but -increased GSH-levels. Significant association was detected between creatinine level and those of MDA (r = 0.81), TNF-α ) r = 0.92) and GSH (r = -0.82); implying causal relationships.

Conclusion

DHA elicited prominent chemopreventive effects on its own, and appreciably augmented those of CP as well. The extent of tumor progression in various mouse groups was highly reflected by CRP levels (thus implying a diagnostic/prognostic role for CRP). Further, this study is the first to reveal that DHA can obliterate the lethal CP-induced nephrotoxicity and renal tissue injury. At the molecular level, DHA appears to act by reducing leukocytosis, systemic inflammation, and oxidative stress.     

Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing-Remitting Disease from Healthy Controls

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS.     

Deletion of dop in Mycobacterium smegmatis abolishes pupylation of protein substrates in vivo

Proteasome‐bearing bacteria make use of a ubiquitin‐like modification pathway to target proteins for proteasomal turnover. In a process termed pupylation, proteasomal substrates are covalently modified with the small protein Pup that serves as a degradation signal. Pup is attached to substrate proteins by action of PafA. Prior to its attachment, Pup needs to undergo deamidation at its C‐terminal residue, converting glutamine to glutamate. This step is catalysed in vitro by Dop. In order to characterize Dop activity in vivo, we generated a dop deletion mutant in Mycobacterium smegmatis. In the Δdop strain, pupylation is severely impaired and the steady‐state levels of two known proteasomal substrates are drastically increased. Pupylation can be re‐established by complementing the mutant with either DopWt or a Pup variant carrying a glutamate at its ultimate C‐terminal position (PupGGE). Our data show that Pup is deamidated by Dop in vivo and that likely Dop alone is responsible for this activity. Furthermore, we demonstrate that a putative N‐terminal ATP‐binding motif is crucial for catalysis, as a single point mutation (E10A) in this motif abolishes Dop activity both in vivo and in vitro.     

Evolution at a High Imposed Mutation Rate: Adaptation Obscures the Load in Phage T7

Evolution at high mutation rates is expected to reduce population fitness deterministically by the accumulation of deleterious mutations. A high enough rate should even cause extinction (lethal mutagenesis), a principle motivating the clinical use of mutagenic drugs to treat viral infections. The impact of a high mutation rate on long-term viral fitness was tested here. A large population of the DNA bacteriophage T7 was grown with a mutagen, producing a genomic rate of 4 nonlethal mutations per generation, two to three orders of magnitude above the baseline rate. Fitness—viral growth rate in the mutagenic environment—was predicted to decline substantially; after 200 generations, fitness had increased, rejecting the model. A high mutation load was nonetheless evident from (i) many low- to moderate-frequency mutations in the population (averaging 245 per genome) and (ii) an 80% drop in average burst size. Twenty-eight mutations reached high frequency and were thus presumably adaptive, clustered mostly in DNA metabolism genes, chiefly DNA polymerase. Yet blocking DNA polymerase evolution failed to yield a fitness decrease after 100 generations. Although mutagenic drugs have caused viral extinction in vitro under some conditions, this study is the first to match theory and fitness evolution at a high mutation rate. Failure of the theory challenges the quantitative basis of lethal mutagenesis and highlights the potential for adaptive evolution at high mutation rates.THE evolutionary consequences of a high mutation rate are mysterious. It is widely considered that mutations are essential for adaptation, but that the rate maximizing adaptation is far below what can be tolerated (e.g., Trobner and Piechocki 1984; Sniegowski 1997, 2001). In this “twilight zone” of higher-than-optimal mutation rates, the population experiences unique challenges. In one process, the “error catastrophe,” the best genotype is driven out of the population deterministically because the onslaught of viable, mutant genotypes simply overwhelms it (Eigen et al. 1988). With Muller''s ratchet, a phenomenon of finite asexual populations, high mutation rates and genetic drift combine to cause loss of the wild-type genome, and the absence of recombination blocks its recreation (Muller 1964); fitness gradually decays as mutations continue their stochastic accumulation. Yet another high mutation rate process is the straightforward, deterministic decline in population fitness as deleterious mutations accumulate (Kimura and Maruyama 1966), leading to extinction if fecundity is too low to compensate (Maynard Smith 1978; Bull et al. 2007).The problem with our understanding of evolution at a high mutation rate is that it is piecemeal. We do not yet know how to combine these different processes nor do we know their relative importance. For example, the fitness loss at a high mutation rate can be offset both by adaptation and by the error catastrophe, but for realistic models, there is no formal basis for predicting the magnitude of adaptation or even for recognizing an error catastrophe (Bull et al. 2005, 2007). Empirical studies are needed. Several studies of viruses have explored extinction through elevated mutation rate (lethal mutagenesis) (Domingo et al. 2001; Anderson et al. 2004; also see discussion), but they have not been tied to any quantitative model. The practical value of such work is that mutagenic drugs are sometimes used to treat viral infections, yet we do not know how the elevated mutation rate is affecting the virus.Here we develop an empirical system to enforce viral evolution at a high mutation rate and test theory developed for lethal mutagenesis. A mutagen is applied to the culture in which the DNA bacteriophage T7 is grown, the mutation input per generation is measured on a genomewide scale, and the system is used to observe both molecular and fitness evolution. Comparison of data and theory provides new insights into the process that underlies lethal mutagenesis. However, existing theory must also be modified to address some empirical properties of the system.

Theory of fitness evolution at high mutation rate:

The objective is to develop a theory for data that are readily obtained. The most basic theory requires one population property (the deleterious mutation rate) to predict another population property (mean fitness), but other properties are not predicted. In experimental systems, mean fitness is easily measured, and the deleterious mutation rate can be estimated within bounds. A fully comprehensive model of evolution at a high mutation rate, one predicting full distributions of genotypes, could be developed if mutation rates and fitness effects were known for each individual mutation and for combinations of mutations, including recombination frequencies. However, the full spectrum of mutations and their fitness effects is too vast to allow those measurements in any biological system, so the only applicable theory describes just mean fitness.If the fitness (e.g., viability) of the mutation-free genotype is assigned the value 1, the mean fitness of an infinite, asexual population at equilibrium is e^−U, where U is the genomic deleterious mutation rate (discrete generations) (Kimura and Maruyama 1966). By itself, this result does not indicate whether a population will survive or not, but one simple modification extends the model to address lethal mutagenesis: fecundity. For an asexual population to survive, a minimal condition is that each parent must produce at least one surviving offspring. In the case of a virus, if each infection produces b viable progeny (in the absence of mutation), the inequality be^−U < 1 ensures eventual extinction. When this inequality is met, the number of progeny in each generation starts out smaller than the number in the parent generation, so the population size declines (Bull et al. 2007).This decline in fitness is not due to stochastic effects in small populations; extinction in this model formally requires a finite population, but the effect of deleterious mutations is treated deterministically. Finite population size can contribute to extinction at mutation rates below the threshold (e.g., from Muller''s ratchet), but we limit ourselves to nearly infinite population sizes.A useful property of the model is that the fitness effects of deleterious mutations and their individual rates need not be known, only the overall rate. Yet this elegance of the Kimura–Maruyama result starts to fade when considering empirical reality. The model considers only deleterious mutations, including lethals; neutral mutations are allowed but ignored, and beneficial mutations are not even allowed. Maximum fitness is assigned to the starting, mutation-free genotype, so any mutation that elevates fitness is excluded. Compensatory mutations that ameliorate the effect of deleterious mutations, and thus are beneficial only within mutated genomes, are also not allowed.To consider a simple model with beneficial mutations, if the initial genotype does not have maximum possible fitness, but a fitness of W relative to the starting genotype is attainable by beneficial mutations (W > 1), then a modified equilibrium is simply We^−U relative to a starting fitness of 1.0. In a virus whose initial fitness is b progeny, adaptive evolution could be accommodated in the model by increasing fecundity to B. The extent to which B exceeds b represents the extent to which the initial (wild-type) virus is poorly adapted to the mutagenic environment, which is unknown. Furthermore, this threshold relaxation omits compensatory mutations that ameliorate specific deleterious mutations and neglects any interference of deleterious mutations on the ascent of beneficial ones.Two further empirical limitations of the Kimura–Maruyama model are evident. Following the onset of an increased mutation rate, the fitness equilibrium may require few or many generations to be approached closely and potentially could require more generations than would be experienced by any real population (Crow and Kimura 1970; Bull and Wilke 2008). The rate of approach depends on the details of the mutation rate and fitness effects, whereas the equilibrium mean fitness does not. We thus attempt to carry out experiments long enough to assume that fitness has neared equilibrium. Second, the Kimura–Maruyama model was developed explicitly for asexuals; the same equilibrium applies with free recombination and no epistasis, but not necessarily when either of these conditions is violated (Maynard Smith 1978; Kondrashov 1982, 1984; Keightley and Otto 2006).In the Kimura–Maruyama model (Kimura and Maruyama 1966), fitness is measured per discrete generation as relative number of surviving offspring. In our viral study, fitness is measured as a growth rate, essentially the log of fitness in the Kimura–Maruyama model. This discrepancy can be resolved by deriving new results for growth rate, again assuming asexuality. Neglecting viral loss from death and other causes, a model of viral growth rate (r) is given by(1)where C is cell (host) density, k is the adsorption rate of virus to cells, b is burst size (average number of progeny per infected cell), and L is lysis time in minutes (Bull 2006). Cell density is assumed to be constant, and cells always outnumber virus (a condition that can be enforced experimentally). r is an exponential or geometric growth rate: at equilibrium, the number of virus at time t, N_t, as a function of initial density, N₀, is given by N_t = e^rtN₀. This model is tailored to the conditions used here, and a model for treatment of a mammalian infection would need to contend with spatial structure and the possibility that the viral population had reached a dynamic equilibrium in which exponential growth no longer applied (see also Steinmeyer and Wilke 2009).With a deleterious, genomic mutation rate U per generation, the deterministic growth rate of the mutation-free class is simply(2)By assumption, all mutation classes in the population are derived ultimately from the mutation-free class and, because all mutations in U are deleterious (neutral mutations are allowed but not counted), all mutants have slower growth rates than the mutation-free genotype. Back mutations and other forms of beneficial mutations are not allowed. It follows that the growth rate of the entire population at mutation–selection equilibrium is given by (2). This result is convenient because the average population growth rate can be understood from the growth rate of the mutation-free class. It is important to emphasize that the solution to (2) [and (1)] is an equilibrium that may require thousands of generations to be reached. Thus, if the solution is negative (r < 0), implying that the population will ultimately decline, the population may go extinct before attaining approximate equilibrium.Equation 2 does not lend itself to an explicit solution, but it is easily solved numerically. Although the parameters in (2) are meant to apply across all mutation rates, the reality for any chemical mutagen or drug is that higher doses of mutagen will not only increase U but also directly reduce viral fitness, such as by reducing burst size. To address this issue, parameters should be estimated in the mutagenic environment. In turn, estimating parameters in the mutagenic environment creates the complication that lethal mutations kill progeny and reduce the apparent burst size (when burst size is determined by plaque counts). To overcome this latter problem, we partition the total deleterious mutation rate into the sum of the lethal rate (U_X) and the nonlethal rate (U_d), U = U_X + U_d, and rewrite Equation 2 as(3)where , the viable burst size. Now, the direct effect of mutagen on burst size is inseparable from the effects of lethal mutations.

Population variation:

An important but subtle implication of the theory is that, when the mutation rate is high, the population will be genetically heterogeneous for deleterious mutations maintained at low to moderate frequencies (Haldane 1927; Crow and Kimura 1970; Eigen et al. 1988). Although every genome may contain many deleterious mutations, different genomes have different sets of deleterious mutations. Only a small proportion of the population may be of the best genotype, in which case, most individuals sampled will have lower fitness than that characterizing the population''s growth (Rouzine et al. 2003, 2008). This heterogeneity has the effect of complicating one means of estimating population fitness. When fitness involves component life history parameters such as burst size and lysis time, a fitness calculation based on separate estimates of life history components appears to underestimate actual population fitness. We have observed this effect in unpublished simulations and suspect that it is a parallel to the principle that the average of a ratio is not the ratio of averages. The T7 system that we use here has the advantage that the intrinsic mutation rate of the virus is low. Thus the starting phage and isolates are genetically uniform and are not subject to this problem. Estimation of fitness directly (as population growth rate rather than from separate fitness components) avoids this problem as well.