DNA,Flexibly Flexible

Investigators have constructed dsDNA molecules with several different base modifications and have characterized their bending and twisting flexibilities using atomic force microscopy, DNA ring closure, and single-molecule force spectroscopy with optical tweezers. The three methods provide persistence length measurements that agree semiquantitatively, and they show that the persistence length is surprisingly similar for all of the modified DNAs. The circular dichroism spectra of modified DNAs differ substantially. Simple explanations based on base stacking strength, polymer charge, or groove occupancy by functional groups cannot explain the results, which will guide further high-resolution theory and experiments.Real double-stranded DNA molecules differ from the idealized zero-Kelvin A, B, and Z forms. They can adopt deformed average conformations, as in bent A-tract DNA or protein-DNA complexes. The path of the DNA helix axis also varies due to thermal energy, so at very long lengths DNA behaves as a random coil. The term “long lengths” is relative to the persistence length P of the wormlike chain model. P is the average offset of the end of a chain along its initial direction, or alternatively the length over which the unit vectors μ1→ and μ2→ tangent to the helix axis lose colinearity according to〈μ1→⋅μ2→〉=〈cosθ〉=e−d12/P,where d₁₂ is the contour length from point 1 to point 2, as in Fig. 1. P can be measured by hydrodynamics (1), atomic force microscopy (AFM) (2), DNA ring closure (3) or protein-DNA looping (4), tethered particle microscopy (5), or single-molecule optical tweezers experiments (6). The long-range loss of memory of DNA direction grows out of local variations in the helix axis direction specified by roll, tilt, and twist angles that parameterize changes in the helix axis direction. For harmonic bending potentials, the bending persistence length is related to roll and tilt according toσroll2+σtilt2=2ℓ/P,where ℓ = 3.4 Å, so for P ∼ 50 nm (147 bp) the average standard deviations in the roll and tilt angles σ_roll and σ_tilt are ∼4.7°, although in real DNA, roll varies more than tilt. Similar relationships hold for twist flexibility (7).Open in a separate windowFigure 1The base modifications studied by Peters et al. (13,14) affect both Watson-Crick hydrogen bonding and groove occupancy. They used AFM, DNA ring closure, single-molecule force spectroscopy, and circular dichroism spectroscopy (not shown) to characterize the resulting changes in bending and twisting flexibility. DNA molecules are not shown to scale. To see this figure in color, go online.DNA flexibility can be studied at contour length scales from Ångstroms to microns. Flexibility at the atomic scale accessed by nuclear magnetic resonance, x-ray crystallography, cryo-electron microscopy, and molecular dynamics simulations (8) refers to many aspects of conformational variability. One active thread of research at this scale concerns interconversion among helical forms, base flipping, DNA kinking, changes in backbone torsion angles, and the sequence dependence of all of these local properties. Local fluctuations in the basepair roll, tilt, and twist angles do seem to predict the correct long-range behavior (9). A second thread asks whether the wormlike chain model holds at DNA lengths shorter than P (2,10); the active controversy concerning enhanced bendability at short lengths has recently been reviewed by Vologodskii and Frank-Kamenetskii (11). A third thread asks whether we can understand the underlying biophysical causes of long-range DNA flexibility. These presumably include base stacking, electrostatic repulsion along the backbone, changes in the counterion atmosphere (12), occupancy of the major and minor grooves by functional groups, conformational entropy, the strength of Watson-Crick hydrogen bonding, and water structure. Helical polymorphisms and the junctions between polymorphs presumably affect the sequence dependence of the persistence length.Peters et al. (13,14) have attempted to understand bending and twisting flexibility by characterizing a variety of modified nucleic acids using DNA ring closure, AFM, and optical tweezer methods, sketched in Fig. 1. In previous work (13), they used ring closure to show that major groove substituents that alter the charge on the polymer do not have substantial effects on the bending persistence length, and that the effects were not correlated in an obvious way to the stacking propensity of the modified bases. The work described in this issue of the Biophysical Journal (14) uses all three methods to demonstrate that DNA with 2-amino-adenosine (a.k.a., 2,6-diaminopurine) substituted for adenosine has an increased persistence length, whereas inosine substitution for guanosine reduces the persistence length, as would be expected if groove occupancy (or the number of Watson-Crick hydrogen bonds) affects flexibility. However, the authors did one experiment too many—when they measured the effects of the earlier major groove substituents (13) using AFM, the correlation with groove occupancy disappeared. This could be because changes in helical geometry, as evidenced by the circular dichroism spectroscopy also reported in the article, alter the grooves sufficiently to prevent a straightforward connection to flexibility.The magnitude of the effect of base modifications on P is the largest for the optical tweezers and the smallest for DNA ring closure, showing that no more than one of the experiments is perfect. The Supporting Material for both articles (13,14) offers valuable resources for the careful evaluation of experimental results and possible sources of error within and between experiments. For example, the DNA lengths and the ionic conditions required by the different methods differ. Ring closure results depend critically on the purity of the DNA and appropriate ligation conditions. Analysis of AFM results averaged several different statistical measures of decaying angular correlations and end-to-end distance, which did not individually always agree. In force spectroscopy there are variations in the bead attachment for each molecule, errors in the stretch modulus can affect the measured persistence length, force can induce DNA melting, and very few molecules can be observed. Rare kinking events proposed to explain enhanced bendability should affect the cyclization experiment most markedly; no evidence for enhanced flexibility was seen. Finally, Peters et al. (14) have observed that DNA twist and twisting flexibility seem to be more sensitive than the persistence length to base modifications.Taken as a whole, this extremely thorough series of experiments shows that we still do not understand the fundamental origins of the remarkable stiffness of double-stranded DNA. There may be compensating effects that make the dissection difficult. For example, changing the charge on the polymer may induce a corresponding adjustment in the counterion condensation atmosphere, leading to a relatively constant residual charge. Groove substituents that enhance basepair stability could enhance bendability for steric reasons. Stacking thermodynamics may not change very much for the very small bend angles at any individual basepair. Locally stiff regions may introduce nearby junctions that are flexible.The stiffness of DNA relative to other biopolymers inspired the development of DNA nanotechnology (although that field has adopted bridged synthetic constructs that are even more rigid). Further research on the biophysics, and specifically the long-range mechanical properties of DNA, will be essential as we build better models of DNA in the cell, which has evolved many proteins that act to increase apparent flexibility. The various aspects of DNA flexibility influence the protein-DNA complexes that mediate DNA’s informational role, the induction of and responses to supercoiling used for long-range communication among sites (15), and chromosome structure and genome organization.     

Mutations in PBP2 from ceftriaxone-resistant Neisseria gonorrhoeae alter the dynamics of the β3–β4 loop to favor a low-affinity drug-binding state

Resistance to the extended-spectrum cephalosporin ceftriaxone in the pathogenic bacteria Neisseria gonorrhoeae is conferred by mutations in penicillin-binding protein 2 (PBP2), the lethal target of the antibiotic, but how these mutations exert their effect at the molecular level is unclear. Using solution NMR, X-ray crystallography, and isothermal titration calorimetry, we report that WT PBP2 exchanges dynamically between a low-affinity state with an extended β3–β4 loop conformation and a high-affinity state with an inward β3–β4 loop conformation. Histidine-514, which is located at the boundary of the β4 strand, plays an important role during the exchange between these two conformational states. We also find that mutations present in PBP2 from H041, a ceftriaxone-resistant strain of N. gonorrhoeae, increase resistance to ceftriaxone by destabilizing the inward β3–β4 loop conformation or stabilizing the extended β3–β4 loop conformation to favor the low-affinity drug-binding state. These observations reveal a unique mechanism for ceftriaxone resistance, whereby mutations in PBP2 lower the proportion of target molecules in the high-affinity drug-binding state and thus reduce inhibition at lower drug concentrations.Keywords: PBP2, Neisseria gonorrhoeae, beta-lactam, conformational dynamics, antibiotic resistance

Neisseria gonorrhoeae is the causative agent of the sexually transmitted infection gonorrhea, with nearly 80 million cases worldwide each year (1). Without antibiotic treatment, infections persist as a chronic disease and can cause serious sequelae, including pelvic inflammatory disease, infertility, arthritis, and disseminated infections (2). For many years, N. gonorrhoeae was treated with a single dose of penicillin, and more recently, ceftriaxone. In 2012, the emergence of several high-level ceftriaxone-resistant strains led the Centers for Disease Control and Prevention to change its recommended treatment for gonorrhea from monotherapy to dual therapy with ceftriaxone and azithromycin (3, 4, 5). However, treatment failures have been reported for both agents, and in 2018, a strain with high-level resistance to both ceftriaxone and azithromycin was identified (6, 7). Concern about azithromycin resistance led the Centers for Disease Control and Prevention recently to drop the recommendation of dual therapy in favor of an increased dose (500 mg) of ceftriaxone alone (8). Both penicillin and ceftriaxone inhibit cell wall biosynthesis in N. gonorrhoeae by targeting penicillin-binding protein 2 (PBP2).PBP2 is an essential peptidoglycan transpeptidase (TPase) that crosslinks the peptide chains from adjacent peptidoglycan strands during cell-wall synthesis (9). β-lactam antibiotics, including the extended-spectrum cephalosporin (ESC) ceftriaxone, are analogs of the d-Ala-d-Ala C terminus of the peptidoglycan substrate and as such target PBP2 by binding to and reacting with the active-site serine nucleophile (Ser310 in N. gonorrhoeae PBP2) to form a covalently acylated complex (10, 11). The acylation reaction (Equation 1) proceeds first through formation of a noncovalent complex with the β-lactam (defined by the equilibrium constant, Ks), which is then attacked by the serine nucleophile to form a covalent acyl-enzyme complex (k₂). For PBPs, hydrolysis of the acyl-enzyme (k₃) is very slow compared with its formation, and the enzyme is essentially irreversibly inactivated. The acylation of PBPs by β-lactam antibiotics is therefore defined by a second-order rate constant, k₂/Ks (M⁻¹ s⁻¹), which reflects both the noncovalent binding affinity (Ks) and the first-order acylation rate (k₂):E+S↔KsE⋅S→k2E−S→k3E+P(1)The emergence of resistance to penicillin and ceftriaxone in N. gonorrhoeae occurs primarily via the acquisition of mutant alleles of the penA gene encoding PBP2 (12). These alleles are referred to as mosaic because they arise through multiple homologous recombination events with DNA released by commensal Neisseria species. PBP2 from the high-level ceftriaxone-resistant strain, H041, contains 61 mutations compared with PBP2 from the antibiotic-susceptible strain, FA19 (13, 14). Determining how these mutations lower the k₂/Ks of ceftriaxone for PBP2 by over 10,000-fold while still preserving essential TPase activity is fundamental for understanding the evolution of antibiotic resistance.Toward this goal, we have identified a subset of these mutations that, when incorporated into the penA gene from FA19, confer ∼80% of the increase in minimum inhibitory concentration for ceftriaxone relative to that of the penA gene from H041 (penA41) (15, 16). We recently reported the structures of apo and ceftriaxone-acylated PBP2 at high resolution and have detailed conformational changes in β3 and the β3–β4 loop involved in antibiotic binding and acylation (17). Intriguingly, although present in the active site region, most of the mutations conferring resistance are not in direct contact with ceftriaxone in the crystal structure of acylated PBP2 (17, 18). We have proposed that these mutations alter the binding and acylation kinetics of PBP2 with ceftriaxone by restricting protein dynamics (18).To understand further the structural and biochemical mechanisms by which these mutations lower the acylation rates of β-lactam antibiotics, we utilized a combination of solution ¹⁹F NMR, X-ray crystallography, and biochemical approaches to investigate PBP2. We report that the β3–β4 loop in the TPase domain of WT PBP2, which is known to adopt markedly different conformations in the apo versus acylated crystal structures (17), samples two major conformational states in solution. Substitutions of WT PBP2 residues with mutations in H041 that confer ceftriaxone resistance alter the conformational landscape of PBP2 by destabilizing the high-affinity state containing the inward conformation of the β3–β4 loop and stabilizing a low-affinity conformation containing an extended β3–β4 loop conformation, thereby restricting access to the inward conformation required for high-affinity drug binding. Our combined solution NMR and crystallographic analyses of PBP2 and its preacylation drug complexes further support the notion that mutations in PBP2 from ceftriaxone-resistant strains of N. gonorrhoeae confer antibiotic resistance by hindering conformational changes required to form a productive drug-binding state (18).     

Autophagy is a regulator of TGF-β1-induced fibrogenesis in primary human atrial myofibroblasts

Transforming growth factor-β₁ (TGF-β₁) is an important regulator of fibrogenesis in heart disease. In many other cellular systems, TGF-β₁ may also induce autophagy, but a link between its fibrogenic and autophagic effects is unknown. Thus we tested whether or not TGF-β₁-induced autophagy has a regulatory function on fibrosis in human atrial myofibroblasts (hATMyofbs). Primary hATMyofbs were treated with TGF-β₁ to assess for fibrogenic and autophagic responses. Using immunoblotting, immunofluorescence and transmission electron microscopic analyses, we found that TGF-β₁ promoted collagen type Iα2 and fibronectin synthesis in hATMyofbs and that this was paralleled by an increase in autophagic activation in these cells. Pharmacological inhibition of autophagy by bafilomycin-A1 and 3-methyladenine decreased the fibrotic response in hATMyofb cells. ATG7 knockdown in hATMyofbs and ATG5 knockout (mouse embryonic fibroblast) fibroblasts decreased the fibrotic effect of TGF-β₁ in experimental versus control cells. Furthermore, using a coronary artery ligation model of myocardial infarction in rats, we observed increases in the levels of protein markers of fibrosis, autophagy and Smad2 phosphorylation in whole scar tissue lysates. Immunohistochemistry for LC3β indicated the localization of punctate LC3β with vimentin (a mesenchymal-derived cell marker), ED-A fibronectin and phosphorylated Smad2. These results support the hypothesis that TGF-β₁-induced autophagy is required for the fibrogenic response in hATMyofbs.Interstitial fibrosis is common to many cardiovascular disease etiologies including myocardial infarction (MI),¹ diabetic cardiomyopathy² and hypertension.³ Fibrosis may arise due to maladaptive cardiac remodeling following injury and is a complex process resulting from activation of signaling pathways, such as TGF-β₁.⁴ TGF-β₁ signaling has broad-ranging effects that may affect cell growth, differentiation and the production of extracellular matrix (ECM) proteins.^{5, 6} Elevated TGF-β₁ is observed in post-MI rat heart⁷ and is associated with fibroblast-to-myofibroblast phenoconversion and concomitant activation of canonical Smad signaling.⁸ The result is a proliferation of myofibroblasts, which then leads to inappropriate deposition of fibrillar collagens, impaired cardiac function and, ultimately, heart failure.^{9, 10}Autophagy is necessary for cellular homeostasis and is involved in organelle and protein turnover.^{11, 12, 13, 14} Autophagy aids in cell survival by providing primary materials, for example, amino acids and fatty acids for anabolic pathways during starvation conditions.^{15, 16} Alternatively, autophagy may be associated with apoptosis through autodigestive cellular processes, cellular infection with pathogens or extracellular stimuli.^{17, 18, 19, 20} The overall control of cardiac fibrosis is likely due to the complex functioning of an array of regulatory factors, but to date, there is little evidence linking autophagy with fibrogenesis in cardiac tissue.^{11, 12, 13, 14, 15, 16, 17, 18, 21, 22}Recent studies have demonstrated that TGF-β₁ may not only promote autophagy in mouse fibroblasts and human tubular epithelial kidney cells^{15, 23, 24} but can also inhibit this process in fibroblasts extracted from human patients with idiopathic pulmonary fibrosis.²⁵ Moreover, it has recently been reported that autophagy can negatively¹⁵ and positively^{25, 26, 27} regulate the fibrotic process in different model cell systems. In this study, we have explored the putative link between autophagy and TGF-β₁-induced fibrogenesis in human atrial myofibroblasts (hATMyofbs) and in a model of MI rat heart.     

The Physical Foundation of Vasoocclusion in Sickle Cell Disease

The pathology of sickle cell disease arises from the occlusion of small blood vessels because of polymerization of the sickle hemoglobin within the red cells. We present measurements using a microfluidic method we have developed to determine the pressure required to eject individual red cells from a capillary-sized channel after the cell has sickled. We find that the maximum pressure is only ∼100 Pa, much smaller than typically found in the microcirculation. This explains why experiments using animal models have not observed occlusion beginning in capillaries. The magnitude of the pressure and its dependence on intracellular concentration are both well described as consequences of sickle hemoglobin polymerization acting as a Brownian ratchet. Given the recently determined stiffness of sickle hemoglobin gels, the observed obstruction seen in sickle cell disease as mediated by adherent cells can now be rationalized, and surprisingly suggests a window of maximum vulnerability during circulation of sickle cells.Human capillaries are narrower than the erythrocytes they convey. In sickle cell disease, red cells can become rigid in those capillaries, because the hemoglobin inside the red cell will aggregate into stiff polymers. This happens once the molecules deliver their oxygen, and led to the long-held view that capillary occlusion was central to the pathophysiology of the disease (1,2). This was challenged when microscopic study of animal model tissues perfused with sickle blood revealed blockages that began further downstream, in the somewhat larger venules (3–5), at the site of adherent red or white cells which diminished the vessel lumen without fully obstructing the flow. Yet no rationale has been presented for the failure of the prior assumption of capillary blockage. Microfluidic methods (6) are ideally suited to discover why cells don’t get stuck in the capillaries, yet occlude subsequent vessels, and we have constructed a system to address this question. Our measurements show that the pressure differences across capillaries in vivo can easily dislodge a cell sickled within a capillary, giving an experimental answer to the question of why sickled cells don’t stick in capillaries. It turns out that the pressure a cell can withstand is quantitatively explained by the Brownian ratchet behavior of sickle hemoglobin polymerization.We constructed single-cell channels in transparent polydimethylsiloxane, with a cross section (1.5 μm × 4 μm) that is smaller than the resting diameter of red cells (Fig. 1). These channels are much narrower than those that have been employed in other recent studies of the sickling process (7,8), and they resemble human capillaries in permitting only one cell at a time to pass through them. We used a laser photolysis method to create ligand free (deoxygenated) cells, and this requires that the hemoglobin bind CO, which can then be readily removed by strong illumination, in contrast to bound O₂ which is released with far lower efficiency than CO. The microfluidic chips were enclosed in a gas-tight chamber flushed with CO to avoid introduction of oxygen and keep the cells fully ligated before photolysis. The profiles of the channels were confirmed by microscopic observation. To confirm that liquid did not pass around the cells when they were trapped in the channels, fluorescent beads were introduced into some cell solutions. The beads did not pass the cells, nor did they approach the cell when it was occluded, verifying that no significant flow occurred around the cell when it was stuck.Open in a separate windowFigure 1An erythrocyte enters a channel (moving left to right) and is positioned in the center, where it will be photolyzed. The channel cross section is 1.5 μm × 4 μm, smaller than a resting red cell diameter.Optical measurements were carried out on a microspectrophotometer constructed on an optical table. The system employed ×32 LWD objectives (Leitz, Wetzlar, Germany), which were autofocused during collection of absorption spectra to minimize aberrations. Spectra were obtained using a series 300 camera (Photometrics, Tucson, AZ); video imaging was done with a high-speed camera (Photron, San Diego, CA). Photolysis was provided by a 2020 Argon Ion laser (Spectra Physics, Houston, TX). Sickle cells were obtained from patients at the Marian Anderson Sickle Cell Center at St. Christopher''s Hospital for Children, Philadelphia, PA by phlebotomy into EDTA-containing tubes. The blood was centrifuged at 5°C at 1200g for 4 min, and then the pellet was washed 4× with 15 volumes of buffer (120 mM NaCl, 2 mM KCl, 10 mM dibasic Na Phosphate, 7 mM monobasic Na Phosphate, 3.4 mM Na Bicarbonate, and 6 mM Dextrose) by repeated suspension and centrifugation at 30g for 4 min. This minimizes fibrinogen and platelets in the final suspension, to insure that these studies are controlled by the mechanical properties of the cells themselves.Our experiment began by parking a cell in the center of a channel (Fig. 1). The cell, its hemoglobin, and the microchannel environment all were saturated with CO. Because the thickness of the channel is known, we were able to determine the hemoglobin concentration inside the cell from its absorption spectrum (Fig. 2 A). Steady-state laser illumination then removed the CO, allowing the hemoglobin to polymerize, in which condition it remained while the laser was kept on. Removal of CO was confirmed by observing the spectral difference between COHb and deoxyHb. Photolysis of COHb generates negligible heating (9–11). During illumination, hydrostatic pressure was applied until the cell broke free.Open in a separate windowFigure 2(A) Absorption of the cell (points), fit to a standard spectrum (9). (B) Pressure to dislodge a cell sickled in the microchannel, as a function of intracellular concentration. Note that typical intracellular concentrations are ∼32 g/dL. (Line) Brownian-ratchet theory described in the text. The coefficient of friction (0.036) is within the observed range, and is the only parameter varied.The magnitude of the dislodging pressure, measured by simple height difference between input and output cell reservoirs, is shown in Fig. 2 B. The pressure needed to dislodge the cell increased with increasing intracellular Hb concentration, implying that an increased mass of polymerized hemoglobin is more difficult to dislodge. A clear concentration threshold for capture is apparent. While there is a well-known solubility below which polymers cannot form (18.5 g/dL for the 22°C of this experiment (12)), the threshold here is significantly higher.Central to explaining these observations is a Brownian ratchet mechanism (13) which derives from the metastable nature of this polymerization process. Unless disrupted, as by centrifugation, polymerization in sickle hemoglobin terminates before the thermodynamic limit of monomer solubility is reached (14,15). This arises from the fact that polymers only grow at their ends, which are easily occluded in the dense mass of polymers that form. This end obstruction leaves the system in a metastable state and fluctuations accordingly provide polymers with space into which they can incrementally grow. This Brownian ratchet has been shown to lead to dramatic fiber buckling when individual fibers are isolated in sickle cells (16). The force can be simply expressed as f = (kT/δ) ln S(c), where k is Boltzmann’s constant, T the absolute temperature, δ the net spatial elongation from addition of a single monomer, and S is the supersaturation of the solution when the metastable limit is reached, at monomer concentration c. In this calculation, c is taken as the terminal concentration, computed from our empirical finding (15) that in this metastable system the amount of polymerized hemoglobin Δ is Δ(∞) = 2/3 (c_o-c_s), rather than the expected thermodynamic limit c_o-c_s, where c_o is the initial concentration and c_s is the solubility.For determining the net force, the total number of fibers must be known, and can be calculated based on the double nucleation mechanism (17) which has been quantitatively successful in describing polymerization. The concentration of polymers [p(t)] initially grows exponentially, described by[p(t)]=(AB2J)exp(Bt),where A and B are parameters related to nucleation, and J is the polymer elongation rate, as described in Ferrone et al. (17). Because A and B are both extremely concentration-dependent (9), they will drop dramatically once monomers begin to add to polymers in any significant numbers, and thereby diminish the remaining monomer pool. Thanks to the extreme concentration dependence of the reaction, this rapidly shuts off further polymerization. This happens at approximately the 10th time (the time when the reaction has reached 1/10 of its maximum). Thus, the [p(t_1/10)] ≈ [p(∞)]. Moreover, at one-tenth of the reaction,Δ(t1/10)=12Aexp(Bt1/10)=Δ(∞)10,and thus[p(∞)]=(BJ)(Δ(∞)10)=(BJ)((co−cs)15).For computing the number of fibers, the volume of the cell was taken as 90 μm³. This calculation shows, as expected, that the number of polymers in the cell is highly concentration-dependent, and very few fibers are produced at concentrations just above solubility, but the number grows sharply as concentration rises. This is the main contribution to the threshold in holding force shown by the data.With the force per fiber, and the total number of fibers, the net force against the wall is known. With a coefficient of friction, this reveals the force that a trapped cell can withstand. If the force is divided by the cross-sectional area across which the force is applied, we get a prediction of the dislodging pressure, which can be compared to the data. For a quantitative comparison with the results, two further corrections, of order unity, were applied. Because only normal force will contribute to friction, the calculated force was determined by integrating cos θ. This integration is not over all angles (π) because of the possibility that large incidence angles of the fibers against the wall will lead to fiber runaway (18). Therefore, the integration described is taken to the runaway threshold, here ∼1 rad. Finally, it is necessary to assign a coefficient of friction. Known values span the range of 0.03–0.06 (19). We therefore selected a value within the range, 0.036, as the best match for the data. The predicted pressures match the measurements well, as the line in Fig. 2 B shows.Because the flow resistance is comparable for red cells traversing glass channels and endothelial-lined capillaries (20), we conclude that in vivo the pressures a sickled cell inside a capillary can withstand are no more than hundreds of Pa. This is significantly smaller than typical arteriovenous pressure differentials that have been measured, which range from 0.7 kPa (in hamster skin (21)) to 7.9 kPa (in rat mesentery (22)).Our measurements coupled with recent determination of the stiffness of sickle hemoglobin gels (23) provide the missing physical basis for the processes of vasoocclusion seen in ex vivo tissue and animal models of sickle cell disease, arguing that these observations indeed represent fundamental behavior of sickle cell disease. We now understand this behavior in terms of three possible outcomes, all intimately connected with kinetics:

• 1.Certain escape: A cell that does not polymerize until after passing the obstruction can reach the lungs where it reoxygenates and resets its polymerization clock.
• 2.Possible escape: A cell that polymerizes within the capillary will assume an elongated sausage shape. The forces that it can exert against the wall cannot hold it there, and it will emerge into the postcapillary venule. There it has some chance of passing a subsequent obstruction, though it might also obstruct flow were it to rotate before reaching the adherent cell, so as to present its long dimension to the reduced space it must traverse.
• 3.Certain occlusion: A cell that does not polymerize in the capillary reassumes a larger diameter as soon as it escapes. If the cell then polymerizes before it encounters a cell attached to the venule wall, this rigidified cell will not be able to squeeze past the adherent cell, because that kind of deformation takes MPa (23). This would precipitate the type of blockage that is observed. This suggests that there is a window of greatest vulnerability, toward which therapies might be addressed.

     

Bak apoptotic pores involve a flexible C-terminal region and juxtaposition of the C-terminal transmembrane domains

Bak and Bax mediate apoptotic cell death by oligomerizing and forming a pore in the mitochondrial outer membrane. Both proteins anchor to the outer membrane via a C-terminal transmembrane domain, although its topology within the apoptotic pore is not known. Cysteine-scanning mutagenesis and hydrophilic labeling confirmed that in healthy mitochondria the Bak α9 segment traverses the outer membrane, with 11 central residues shielded from labeling. After pore formation those residues remained shielded, indicating that α9 does not line a pore. Bak (and Bax) activation allowed linkage of α9 to neighboring α9 segments, identifying an α9:α9 interface in Bak (and Bax) oligomers. Although the linkage pattern along α9 indicated a preferred packing surface, there was no evidence of a dimerization motif. Rather, the interface was invoked in part by Bak conformation change and in part by BH3:groove dimerization. The α9:α9 interaction may constitute a secondary interface in Bak oligomers, as it could link BH3:groove dimers to high-order oligomers. Moreover, as high-order oligomers were generated when α9:α9 linkage in the membrane was combined with α6:α6 linkage on the membrane surface, the α6-α9 region in oligomerized Bak is flexible. These findings provide the first view of Bak carboxy terminus (C terminus) membrane topology within the apoptotic pore.Mitochondrial permeabilization during apoptosis is regulated by the Bcl-2 family of proteins.^{1, 2, 3} Although the Bcl-2 homology 3 (BH3)-only members such as Bid and Bim trigger apoptosis by binding to other family members, the prosurvival members block apoptosis by sequestering their pro-apoptotic relatives. Two remaining members, Bak and Bax, form the apoptotic pore within the mitochondrial outer membrane (MOM).Bak and Bax are globular proteins comprising nine α-helices.^{4, 5} They are activated by BH3-only proteins binding to the α2–α5 surface groove,^{6, 7, 8, 9, 10, 11, 12} or for Bax, to the α1/α6 ‘rear pocket''.¹³ Binding triggers dissociation of the latch domain (α6–α8) from the core domain (α2–α5), together with exposure of N-terminal epitopes and the BH3 domain.^{6, 7, 14, 15, 16} The exposed BH3 domain then binds to the hydrophobic groove in another Bak or Bax molecule to generate symmetric homodimers.^{6, 7, 14, 17, 18} In addition to dimerizing, parts of activated Bak and Bax associate with the lipid bilayer.¹⁹ In Bax, the α5 and α6 helices may insert into the MOM,²⁰ although recent studies indicate that they lie in-plane on the membrane surface, with the hydrophobic α5 sandwiched between the membrane and a BH3:groove dimer interface.^{7, 21, 22, 23} The dimers can be linked via cysteine residues placed in α6,^{18, 24, 25} and more recently via cysteine residues in either α3 or α5,^{6, 21} allowing detection of the higher-order oligomers associated with pore formation.^{26, 27} However, whether these interactions are required for high-order oligomers and pore formation remains unclear.Like most Bcl-2 members, Bak and Bax are targeted to the MOM via a hydrophobic C-terminal region. The C terminus targets Bak to the MOM in healthy cells,²⁸ whereas the Bax C terminus is either exposed²⁹ or sequestered within the hydrophobic groove until apoptotic signals trigger Bax translocation.^{5, 30, 31} The hydrophobic stretch is important, as substituting polar or charged residues decreased targeting of Bak and Bax.^{10, 32} Mitochondrial targeting is also controlled by basic residues at the far C termini,^{32, 33, 34} and by interaction with VDAC2^{35, 36} via the Bak and Bax C termini.^{37, 38} Retrotranslocation of Bak and Bax was also altered by swapping the C termini.³⁹The membrane topology of the Bak and Bax C termini before and after apoptosis has not been examined directly, due in part to difficulty in reconstituting oligomers of full-length Bak in artificial membranes. Nor is it known whether the C termini contribute to pore formation by promoting oligomerization or disturbing the membrane. To address these questions synthetic peptides based on the Bak and Bax C termini have been studied in model membranes. The peptides adopt a predominantly α-helical secondary structure,^{40, 41, 42, 43} with orientation affected by lipid composition.^{42, 44, 45} The peptides could also permeabilize lipid vesicles,^{41, 43, 46, 47} suggesting that the C termini in full-length Bak and Bax may contribute to pore formation.Here we examined the membrane topology of the C termini within full-length Bak and Bax in the MOM, both before and after apoptotic pore formation. After pore formation the α9 helices of Bak (and of Bax) became juxtaposed but did not line the surface of a pore. The α9:α9 interaction occurred after Bak activation and conformation change, but was promoted by formation of BH3:groove dimers. Combining linkage at more than one interface indicated that the Bak α9:α9 interface can link BH3:groove dimers to high-order oligomers, and moreover, that the α6–α9 region is flexible in oligomerized Bak.     

Alpha-Synuclein affects neurite morphology,autophagy, vesicle transport and axonal degeneration in CNS neurons

Many neuropathological and experimental studies suggest that the degeneration of dopaminergic terminals and axons precedes the demise of dopaminergic neurons in the substantia nigra, which finally results in the clinical symptoms of Parkinson disease (PD). The mechanisms underlying this early axonal degeneration are, however, still poorly understood. Here, we examined the effects of overexpression of human wildtype alpha-synuclein (αSyn-WT), a protein associated with PD, and its mutant variants αSyn-A30P and -A53T on neurite morphology and functional parameters in rat primary midbrain neurons (PMN). Moreover, axonal degeneration after overexpression of αSyn-WT and -A30P was analyzed by live imaging in the rat optic nerve in vivo. We found that overexpression of αSyn-WT and of its mutants A30P and A53T impaired neurite outgrowth of PMN and affected neurite branching assessed by Sholl analysis in a variant-dependent manner. Surprisingly, the number of primary neurites per neuron was increased in neurons transfected with αSyn. Axonal vesicle transport was examined by live imaging of PMN co-transfected with EGFP-labeled synaptophysin. Overexpression of all αSyn variants significantly decreased the number of motile vesicles and decelerated vesicle transport compared with control. Macroautophagic flux in PMN was enhanced by αSyn-WT and -A53T but not by αSyn-A30P. Correspondingly, colocalization of αSyn and the autophagy marker LC3 was reduced for αSyn-A30P compared with the other αSyn variants. The number of mitochondria colocalizing with LC3 as a marker for mitophagy did not differ among the groups. In the rat optic nerve, both αSyn-WT and -A30P accelerated kinetics of acute axonal degeneration following crush lesion as analyzed by in vivo live imaging. We conclude that αSyn overexpression impairs neurite outgrowth and augments axonal degeneration, whereas axonal vesicle transport and autophagy are severely altered.Growing evidence suggests that Parkinson''s disease (PD) pathology starts at the presynaptic terminals and the distal axons and is then propagated back to the soma in a ''dying back'' pattern.^{1, 2} Accordingly, at the time of clinical onset, there is only a 30% loss of total substantia nigra pars compacta neurons but a far more severe loss of striatal dopaminergic markers (70–80%), suggesting that axonal terminals of the nigrostriatal pathway are affected earlier.¹ It is thus essential to understand the pathomechanisms specifically affecting the axon in PD in order to interfere with early disease progression.Neurodegeneration in PD is accompanied by the appearance of intraneuronal protein aggregates, denoted Lewy bodies (LBs).³ Interestingly, also LB pathology is initially found in the distal axons before becoming evident in the neuronal somata, and dystrophic neurites, so called ''Lewy neurites'', outnumber LBs in the early stages of PD.^{2, 4, 5} A main component of LBs is the protein alpha-synuclein (αSyn) that is not only widely used as a histopathological marker for PD but is also believed to have a major role in PD pathogenesis.^{6, 7} The importance of αSyn is further underlined by the discovery of αSyn point mutations (e.g. Ala53Thr (A53T), Ala30Pro (A30P)) and multiplications of the αSyn gene, all of which cause autosomal dominant forms of PD.^{8, 9, 10} However, neither the physiological functions nor the pathogenetic mechanisms of αSyn are well understood.⁷The biological effects of αSyn expression strongly depend on the model system. Wild-type (WT) human αSyn does not lead to major clinical or histological abnormalities when expressed in transgenic mice,^{11, 12} but its overexpression mediated by adeno-associated viral vectors (AAV) results in severe neurodegeneration, suggesting a dose-dependent toxic effect.^{13, 14} Different human αSyn-A30P and -A53T transgenic mouse lines develop severe motor impairments, partly resembling symptoms of human PD, accompanied by a degeneration of the nigrostriatal neuronal system and LB-like pathology.^{11, 12, 15} In line with the pathological findings in human PD, the axonal compartment is affected early and most prominently in these animal models.Different putative pathomechanisms of αSyn toxicity have been explored. For example, the cytoskeleton is an important molecular target of αSyn. Multimeric forms of αSyn were shown to impair the polymerization of tubulin and microtubule formation.^{16, 17} Overexpression of αSyn increased actin instability and induced actin bundling in cultured hippocampal neurons.¹⁸ There are, however, divergent data on the resulting effects of αSyn overexpression on neurite outgrowth and integrity in different model systems.^{19, 20, 21, 22}Moreover, a dysregulation of autophagy has been implicated in PD pathology. Aberrant αSyn is normally degraded by autophagy and only to a negligible degree by the proteasome.²³ Several studies have shown that the inhibition of autophagy results in an accumulation and increased toxicity of αSyn, whereas the activation of autophagy has therapeutic effects in PD models.^{23, 24, 25, 26} However, the direct effects of αSyn and its mutants on autophagy seem to rely strongly on the model system and the published data are highly controversial.^{24, 26, 27, 28, 29, 30, 31, 32}Given the central role of axonal degeneration in PD, it is likely that disturbances of axonal transport are involved.³³ In support of this proposition, the motor protein kinesin was shown to be decreased early and stage-dependently in PD patients, preceding the loss of substantia nigra neurons.³⁴ αSyn itself is actively transported along the axons, mainly by the slow component of axonal transport, but the role of αSyn in axonal vesicle transport is unclear.³⁵Here, we present a comprehensive analysis of the effects of αSyn on neurite morphology and examine important pathomechanisms.     

Flexible open conformation of the AP-3 complex explains its role in cargo recruitment at the Golgi

Vesicle formation at endomembranes requires the selective concentration of cargo by coat proteins. Conserved adapter protein complexes at the Golgi (AP-3), the endosome (AP-1), or the plasma membrane (AP-2) with their conserved core domain and flexible ear domains mediate this function. These complexes also rely on the small GTPase Arf1 and/or specific phosphoinositides for membrane binding. The structural details that influence these processes, however, are still poorly understood. Here we present cryo-EM structures of the full-length stable 300 kDa yeast AP-3 complex. The structures reveal that AP-3 adopts an open conformation in solution, comparable to the membrane-bound conformations of AP-1 or AP-2. This open conformation appears to be far more flexible than AP-1 or AP-2, resulting in compact, intermediate, and stretched subconformations. Mass spectrometrical analysis of the cross-linked AP-3 complex further indicates that the ear domains are flexibly attached to the surface of the complex. Using biochemical reconstitution assays, we also show that efficient AP-3 recruitment to the membrane depends primarily on cargo binding. Once bound to cargo, AP-3 clustered and immobilized cargo molecules, as revealed by single-molecule imaging on polymer-supported membranes. We conclude that its flexible open state may enable AP-3 to bind and collect cargo at the Golgi and could thus allow coordinated vesicle formation at the trans-Golgi upon Arf1 activation.

Eukaryotic cells have membrane-enclosed organelles, which carry out specialized functions, including compartmentalized biochemical reactions, metabolic channeling, and regulated signaling, inside a single cell. The transport of proteins, lipids, and other molecules between these organelles is mediated largely by small vesicular carriers that bud off at a donor compartment and fuse with the target membrane to deliver their cargo. The generation of these vesicles has been subject to extensive studies and has led to the identification of numerous coat proteins that are required for their formation at different sites (1, 2). Coat proteins can be monomers, but in most cases, they consist of several proteins, which form a heteromeric complex.Heterotetrameric adapter protein (AP) complexes are required at several endomembranes for cargo binding. Five well-conserved AP-complexes with differing functions have been identified in mammalian cells, named AP-1–AP-5, of which three (AP-1–AP-3) are conserved from yeast to human (3, 4). The three conserved adapter complexes function at different membranes along the endomembrane system. AP-1 is required for cargo transport between the Golgi and the endosome, AP-2 is required for cargo recognition and transport between the plasma membrane and the early endosome. Finally, AP-3 functions between the trans Golgi and the vacuole in yeast, whereas mammalian AP-3 localizes to a tubular endosomal compartment, in addition to or instead of the TGN (2, 5, 6).Each of the complexes consists of four different subunits: two large adaptins (named α−ζ and β1-5 respectively), a medium-sized subunit (μ1-5), and a small subunit (σ1-5). While μ- and σ-subunits together with the N-termini of the large adaptins build the membrane-binding core of the complex, the C-termini of both adaptins contain the ear domains, which are connected via flexible linkers (2). The recruitment of these complexes to membranes is not entirely conserved. They all require cargo binding, yet AP-1 binds Arf1-GTP with the γ and β1 subunit and phosphatidylinositol-4-phosphate (PI4P) via a proposed conserved site on its γ-subunit (7, 8). AP-2, on the other hand, interacts with PI(4,5)P₂ at the plasma membrane via its α, β2, and μ2 subunits (9, 10, 11).Several studies have uncovered how AP-3 functions in cargo sorting in yeast. AP-3 recognizes cargo at the Golgi via two sorting motifs in the cytosolic segments of membrane proteins: a Yxxφ sorting motif, as found in yeast in the SNARE Nyv1 or the Yck3 casein kinase, which binds to a site in μ3, as shown for mammalian AP-3, which is similar to μ2 in AP-2 (12, 13, 14), and dileucine motifs as found in the yeast SNARE Vam3 or the alkaline phosphatase Pho8, potentially also at a site comparable to AP-1 and AP-2 (15, 16). Unlike AP-1 and AP-2-coated vesicles, which depend on clathrin for their formation (2, 17), AP-3 vesicle formation in yeast does not require clathrin or the HOPS subunit Vps41 (18), yet Vps41 is required at the vacuole to bind AP-3 vesicles prior to fusion (19, 20, 21, 22). Studies in metazoan cells revealed that Vps41 and AP-3 function in regulated secretion (23, 24, 25), and AP-3 is required for biogenesis of lysosome-related organelles (26). This suggests that the AP-3 complex has features that are quite different from AP-1 and AP-2 complexes, which cooperate with clathrin in vesicle formation (2).Among the three conserved AP complexes, the function of the AP-3 complex is the least understood. Arf1 is necessary for efficient AP-3 vesicle generation in mammalian cells and shows a direct interaction with the β3 and δ subunits of AP-3 (27, 28). In addition, in vitro experiments on mammalian AP-3 using liposomes or enriched Golgi membranes suggest Arf1 as an important factor in AP-3 recruitment, whereas acidic lipids do not have a major effect, in contrast to what was found for AP-1 and AP-2 (7, 11, 29, 30). Another study showed that membrane recruitment of AP-3 depends on the recognition of sorting signals in cargo tails and PI3P (31), similar to AP-1 recruitment via cargo tails, Arf1 and PI4P (32).However, since AP-1 and AP-3 are both recruited to the trans-Golgi network (TGN) in yeast (33), the mechanism of their recruitment likely differs. Even though Arf1 is required, yeast AP-3 seems to be present at the TGN before the arrival of the Arf1 guanine nucleotide exchange factor (GEF) Sec7 (33). This implies the necessity for additional factors at the TGN and a distinct mechanism to allow for spatial and temporal separation of AP-1 and AP-3 recruitment to membranes. Structural data on mammalian AP-1 and AP-2 “core” complexes without the hinge and ear domains of their large subunits revealed that both exist in at least two very defined conformational states: a “closed” cytosolic state, where the cargo-binding sites are buried within the complex, and an “open” state, where the same sites are available to bind cargo (7, 8, 10, 34, 35). Binding of Arf1 to AP-1 or PI(4,5)P₂ in case of AP-2 induces a conformational change in the complexes that enables them to bind cargo molecules carrying a conserved acidic di-Leucine or a Tyrosine-based motif, as for all three AP complexes in yeast (8, 34). Additional conformational states and intermediates have been reported for both, mammalian AP-1 and AP-2 complex. AP-1, for example, can be hijacked by the human immunodeficiency virus-1 (HIV-1) proteins viral protein u (Vpu) and negative factor (Nef), resulting in a hyper-open conformation of AP-1 (36, 37).An emerging model over the past years has suggested that APs have several binding sites that allow for the stabilization of membrane binding and the open conformation of the complexes, but there are initial interactions required that dictate their recruitment to the target membrane. Although these interaction sites for mammalian AP-1 and AP-2 have been identified in great detail based on interaction analyses and structural studies (8, 10, 11, 35, 36, 38, 39), structural data for AP-3 is largely missing. The C-terminal part of the μ-subunit of mammalian AP-3 has been crystallized together with a Yxxφ motif-containing a cargo peptide, which revealed a similar fold and cargo-binding site as shown for AP-1 and AP-2 (14). However, positively charged binding surfaces required for PIP-interaction were not well conserved. Although the “trunk” segment of AP-1 and AP-2 is known quite well by now, information on hinge and ear domains in context of these complexes is largely missing. Crystal structures of the isolated ear domains of α-, γ- and β2-adaptin have been published (40, 41, 42), and a study on mammalian AP-3 suggested a direct interaction between δ-ear and δ3 that interfered with Arf1-binding (43). Furthermore, during tethering of AP-3 vesicles with the yeast vacuole, the δ−subunit Apl5 of the yeast AP-3 complex binds to the Vps41 subunit of the HOPS complex as a prerequisite of fusion (18, 19, 21, 22).In this study, we applied single particle electron cryo-microscopy (cryo-EM) to analyze the purified full-length AP-3 complex from yeast and unraveled the factors required for AP-3 recruitment to membranes by biochemical reconstitution. Our data reveal that a surprisingly flexible AP-3 complex requires a combination of cargo, PI4P, and Arf1 for membrane binding, which explains its function in selective cargo sorting at the Golgi.     

Alzheimer's disease-related amyloid-β induces synaptotoxicity in human iPS cell-derived neurons

Human induced pluripotent stem cell (iPSC)-derived neurons have been proposed to be a highly valuable cellular model for studying the pathomechanisms of Alzheimer''s disease (AD). Studies employing patient-specific human iPSCs as models of familial and sporadic forms of AD described elevated levels of AD-related amyloid-β (Aβ). However, none of the present AD iPSC studies could recapitulate the synaptotoxic actions of Aβ, which are crucial early events in a cascade that eventually leads to vast brain degeneration. Here we established highly reproducible, human iPSC-derived cortical cultures as a cellular model to study the synaptotoxic effects of Aβ. We developed a highly efficient immunopurification procedure yielding immature neurons that express markers of deep layer cortical pyramidal neurons and GABAergic interneurons. Upon long-term cultivation, purified cells differentiated into mature neurons exhibiting the generation of action potentials and excitatory glutamatergic and inhibitory GABAergic synapses. Most interestingly, these iPSC-derived human neurons were strongly susceptible to the synaptotoxic actions of Aβ. Application of Aβ for 8 days led to a reduction in the overall FM4–64 and vGlut1 staining of vesicles in neurites, indicating a loss of vesicle clusters. A selective analysis of presynaptic vesicle clusters on dendrites did not reveal a significant change, thus suggesting that Aβ impaired axonal vesicle clusters. In addition, electrophysiological patch-clamp recordings of AMPA receptor-mediated miniature EPSCs revealed an Aβ-induced reduction in amplitudes, indicating an impairment of postsynaptic AMPA receptors. A loss of postsynaptic AMPA receptor clusters was confirmed by immunocytochemical stainings for GluA1. Incubation with Aβ for 8 days did not result in a significant loss of neurites or cell death. In summary, we describe a highly reproducible cellular AD model based on human iPSC-derived cortical neurons that enables the mechanistic analysis of Aβ-induced synaptic pathomechanisms and the development of novel therapeutic approaches.In Alzheimer''s disease (AD), synapse damage and synapse loss are thought to underlie cognitive deficits.¹ Oligomers of the amyloid-β (Aβ) peptide appear to induce synaptic failure as an early event in the etiology of AD.^{2, 3, 4} However, despite its well-established synapse-impairing effects in rodent models,^{5, 6, 7} the synaptotoxic actions of Aβ most relevant for the human disease have not been identified in a human model system. Several studies have investigated the synaptotoxic effects of Aβ in cultured rodent neurons and in transgenic mouse models revealing a multitude of potential mechanisms affecting synapses. Postsynaptic Aβ actions result in the loss of functional (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-type) glutamate receptors,^{8, 9, 10} involve long-term depression-like mechanisms,^{9, 11, 12} and lead to the degradation of the entire postsynapse (dendritic spines).^{9, 11, 13} In addition, several distinct presynaptic Aβ actions on the synaptic vesicle cycle have been described.^{10, 14} Furthermore, Aβ-induced impairments of axonal transport regulation and Aβ-induced axon degeneration have been found in rodent neurons.^{15, 16, 17} This puzzling diversity of Aβ-induced synapse-related defects raises the question whether all of them are involved in the early pathomechanisms of human AD.In addition to well-established animal systems, the modelling of human neurological disease pathologies by human induced pluripotent stem cell (hiPSC) technology¹⁸ has been proposed as an innovative approach.^{19, 20, 21} The in vitro differentiation of hiPSCs to excitable neurons has been reported using a variety of protocols.^{22, 23, 24} However, quantitative analysis of both functional glutamatergic and GABAergic synapses has been difficult to achieve.^{19, 25, 26} In addition to studying the functional properties of iPSC-derived human neurons from healthy individuals, the in vitro differentiation of patient-derived iPSCs has been used to model complex neurodevelopmental and neurodegenerative diseases.^{19, 27, 28} Recently, iPSCs derived from AD patients have been reported to exhibit increased secretion of Aβ upon in vitro neuronal differentiation; however, neither a loss of synapses nor an impairment of synapse function was detected.^{21, 29, 30, 31, 32, 33} Here we describe a hiPSC-based, carefully optimized in vitro differentiation protocol, including a novel immunopanning step, which enabled us to study the deleterious effects of application of Aβ on human cortical neurons and on human synapses.     

The Relationship Between FST and the Frequency of the Most Frequent Allele

F_ST is frequently used as a summary of genetic differentiation among groups. It has been suggested that F_ST depends on the allele frequencies at a locus, as it exhibits a variety of peculiar properties related to genetic diversity: higher values for biallelic single-nucleotide polymorphisms (SNPs) than for multiallelic microsatellites, low values among high-diversity populations viewed as substantially distinct, and low values for populations that differ primarily in their profiles of rare alleles. A full mathematical understanding of the dependence of F_ST on allele frequencies, however, has been elusive. Here, we examine the relationship between F_ST and the frequency of the most frequent allele, demonstrating that the range of values that F_ST can take is restricted considerably by the allele-frequency distribution. For a two-population model, we derive strict bounds on F_ST as a function of the frequency M of the allele with highest mean frequency between the pair of populations. Using these bounds, we show that for a value of M chosen uniformly between 0 and 1 at a multiallelic locus whose number of alleles is left unspecified, the mean maximum F_ST is ∼0.3585. Further, F_ST is restricted to values much less than 1 when M is low or high, and the contribution to the maximum F_ST made by the most frequent allele is on average ∼0.4485. Using bounds on homozygosity that we have previously derived as functions of M, we describe strict bounds on F_ST in terms of the homozygosity of the total population, finding that the mean maximum F_ST given this homozygosity is 1 − ln 2 ≈ 0.3069. Our results provide a conceptual basis for understanding the dependence of F_ST on allele frequencies and genetic diversity and for interpreting the roles of these quantities in computations of F_ST from population-genetic data. Further, our analysis suggests that many unusual observations of F_ST, including the relatively low F_ST values in high-diversity human populations from Africa and the relatively low estimates of F_ST for microsatellites compared to SNPs, can be understood not as biological phenomena associated with different groups of populations or classes of markers but rather as consequences of the intrinsic mathematical dependence of F_ST on the properties of allele-frequency distributions.DIFFERENTIATION among groups is one of the fundamental subjects of the field of population genetics. Comparisons of the level of variation among subpopulations with the level of variation in the total population have been employed frequently in population-genetic theory, in statistical methods for data analysis, and in empirical studies of distributions of genetic variation. Wright’s (Wright 1951) fixation indices, and F_ST in particular, have been central to this effort.Wright’s F_ST was originally defined as the correlation between two randomly sampled gametes from the same subpopulation when the correlation of two randomly sampled gametes from the total population is set to zero. Several definitions of F_ST or F_ST-like quantities are now available, relying on a variety of different conceptual formulations but all measuring some aspect of population differentiation (e.g., Charlesworth 1998; Holsinger and Weir 2009). Many authors have claimed that one or another formulation of F_ST is affected by levels of genetic diversity or by allele frequencies, either because the range of F_ST is restricted by these quantities or because these quantities affect the degree to which F_ST reflects population differentiation (e.g., Charlesworth 1998; Nagylaki 1998; Hedrick 1999, 2005; Long and Kittles 2003; Jost 2008; Ryman and Leimar 2008; Long 2009; Meirmans and Hedrick 2011). For example, Nagylaki (1998) and Hedrick (1999) argued that measures of F_ST may be poor measures of genetic differentiation when the level of diversity is high. Charlesworth (1998) suggested that F_ST can be inflated when diversity is low, arguing that F_ST might not be appropriate for comparing loci with substantially different levels of variation. In a provocative recent article, Jost (2008) used the diversity dependence of forms of F_ST to question their utility as differentiation measures at all.One definition that is convenient for mathematical assessment of the relationship of an F_ST-like quantity and allele frequencies is the quantity labeled G_ST by Nei (1973), which for a given locus measures the difference between the heterozygosity of the total (pooled) population, h_T, and the mean heterozygosity across subpopulations, h_S, divided by the heterozygosity of the total population:GST=hT−hShT.(1)In terms of the homozygosity of the total population, H_T = 1 − h_T, and the mean homozygosity across subpopulations, H_S = 1 − h_S, we can writeGST=HS−HT1−HT.(2)The Wahlund (1928) principle guarantees that H_S ≥ H_T and, therefore, because H_S ≤ 1 and for a polymorphic locus with finitely many alleles, 0 < H_T < 1, G_ST lies in the interval [0,1].Using G_ST for their definition of F_ST, Hedrick (1999, 2005) and Long and Kittles (2003) pointed out that because h_T < 1, F_ST cannot exceed the mean homozygosity across subpopulations, H_S:F_ST = 1 ? h_S/h_T < 1 ? h_S = H_S.(3)Hedrick (2005) obtained this result by considering a set of K equal-sized subpopulations, in which each allele is private to a single subpopulation. In the limit as K → ∞, a stronger upper bound on F_ST as a function of H_S and K reduces to Equation 3 (see also Jin and Chakraborty 1995 and Long and Kittles 2003).While Hedrick (1999, 2005) and Long and Kittles (2003) have clarified the relationship between F_ST and the mean homozygosity H_S across subpopulations, their approaches do not easily illuminate the connection between F_ST and allele frequencies themselves. A formal understanding of the relationship between F_ST and allele frequencies would make it possible to more fully understand the behavior of F_ST in situations where markers of interest differ substantially in allele frequencies or levels of genetic diversity. Our recent work on the relationship between homozygosity and the frequency of the most frequent allele (Rosenberg and Jakobsson 2008; Reddy and Rosenberg 2012) provides a mathematical approach for formal investigation of bounds on population-genetic statistics in terms of allele frequencies. In this article, we therefore seek to thoroughly examine the dependence of F_ST on allele frequencies by investigating the upper bound on F_ST in terms of the frequency M of the most frequent allele across a pair of populations. We derive bounds on F_ST given the frequency of the most frequent allele and bounds on the frequency of the most frequent allele given F_ST. We consider loci with arbitrarily many alleles in a pair of subpopulations. Using theory for the bounds on homozygosity given the frequency of the most frequent allele, we obtain strict bounds on F_ST given the homozygosity of the total population. Our analysis clarifies the relationships among F_ST, allele frequencies, and homozygosity, providing explanations for peculiar observations of F_ST that can be attributed to allele-frequency dependence.     

Inhibition of the MAP3 kinase Tpl2 protects rodent and human β-cells from apoptosis and dysfunction induced by cytokines and enhances anti-inflammatory actions of exendin-4

Proinflammatory cytokines exert cytotoxic effects on β-cells, and are involved in the pathogenesis of type I and type II diabetes and in the drastic loss of β-cells following islet transplantation. Cytokines induce apoptosis and alter the function of differentiated β-cells. Although the MAP3 kinase tumor progression locus 2 (Tpl2) is known to integrate signals from inflammatory stimuli in macrophages, fibroblasts and adipocytes, its role in β-cells is unknown. We demonstrate that Tpl2 is expressed in INS-1E β-cells, mouse and human islets, is activated and upregulated by cytokines and mediates ERK1/2, JNK and p38 activation. Tpl2 inhibition protects β-cells, mouse and human islets from cytokine-induced apoptosis and preserves glucose-induced insulin secretion in mouse and human islets exposed to cytokines. Moreover, Tpl2 inhibition does not affect survival or positive effects of glucose (i.e., ERK1/2 phosphorylation and basal insulin secretion). The protection against cytokine-induced β-cell apoptosis is strengthened when Tpl2 inhibition is combined with the glucagon-like peptide-1 (GLP-1) analog exendin-4 in INS-1E cells. Furthermore, when combined with exendin-4, Tpl2 inhibition prevents cytokine-induced death and dysfunction of human islets. This study proposes that Tpl2 inhibitors, used either alone or combined with a GLP-1 analog, represent potential novel and effective therapeutic strategies to protect diabetic β-cells.It is now clear that chronic inflammation is a hallmark of type I and type II diabetes, affecting both β-cell mass and insulin secretion.¹ Type I diabetes is characterized by drastic decreases in β-cell mass and insulin secretion, in part mediated by proinflammatory cytokines produced following autoimmune activation.¹ Proinflammatory cytokines, particularly interleukin-1β (IL-1β), in combination with interferon-γ (IFN-γ) and/or tumor necrosis factor-α (TNF-α), promote death by apoptosis and decrease function of differentiated β-cells, leading to β-cell destruction.¹ Pancreatic islet transplantation is a promising alternative therapy for some type I diabetic patients.² However, clinical outcome is not always achieved because of significant loss of islet mass during and after transplantation.³ Up to 80% of transplanted islets can die during the post-transplantation period as a result of apoptosis because of several mechanisms, notably the instant blood-mediated inflammatory response (IBMIR) and the release of a mix of cytokines including IL-1β, TNF-α and IFN-γ.⁴Immune-modulatory strategies for type I diabetes therapy and improvement of islet transplantation outcomes have emerged, targeting a single specific cytokine, such as IL-1β or TNF-α.^{2, 5} However, these strategies may only target inflammation partially.² Indeed, multiple cytokines, originating from surrounding immune cells and/or β-cells themselves, are more likely to be present simultaneously^{4, 6} and act synergistically to induce β-cell death and dysfunction.^{7, 8, 9} Preclinical and clinical studies demonstrated that glucagon-like peptide-1 (GLP-1) analogs, in addition to regulating glucose homeostasis in vivo, contribute to the restoration of normoglycemia after islet transplantation.^{10, 11, 12, 13} GLP-1 receptor (GLP-1R) analogs protect β-cell survival and function from proinflammatory cytokine attack.^{12, 14, 15} However, some studies have shown only modest and short-term anti-inflammatory effects of GLP-1 analogs when used alone.^{11, 13, 16}Mitogen-activated protein kinases (MAPKs) (i.e., extracellular-regulated kinase-1/2 (ERK1/2), c-Jun N-terminal kinase (JNK) and p38 MAPK) play important roles in cytokine-induced β-cell dysfunction and death.¹ Conversely, ERK1/2 are involved in the beneficial effects of glucose and GLP-1 analogs.^{17, 18, 19} In this context, upstream protein kinases that specifically control the activation of MAPK in response to a combination of inflammatory cytokines (IL-1β, TNF-α and IFN-γ), rather than a single cytokine, may be useful targets for therapeutic interventions against pancreatic β-cell failure.The serine/threonine kinase tumor progression locus 2 (Tpl2) (also known as COT (Cancer Osaka Thyroid) in humans) is a member of the MAP3K family (the MAP3K8) whose activation stimulates primarily the ERK1/2 pathway, but also JNK and/or p38 MAPK in some cell types, specifically in response to various inflammatory stimuli.^{20, 21, 22} Dysregulation of Tpl2 expression and signaling is associated with acute and chronic inflammatory diseases,^{20, 21, 22} and several studies highlight a critical function of Tpl2 in the control of inflammatory responses and survival in adipocytes, fibroblasts and immune and epithelial cells.^{21, 22, 23, 24}However, there is currently nothing known about the effects of Tpl2 in β-cells. The aim of this study was to determine whether Tpl2 may be a new key inflammatory regulator in β-cells or islets. We demonstrate that Tpl2 contributes to cytokine-induced β-cell apoptosis and dysfunction, and suggest that Tpl2 inhibition, either alone or combined with a GLP-1 receptor agonist, represents a potential new therapeutic strategy for the treatment of diabetes.     

Exploring the Ultrastructural Localization and Biosynthesis of β(1,4)-Galactan in Pinus radiata Compression Wood

Softwood species such as pines react to gravitropic stimuli by producing compression wood, which unlike normal wood contains significant amounts of β(1,4)-galactan. Currently, little is known regarding the biosynthesis or physiological function of this polymer or the regulation of its deposition. The subcellular location of β(1,4)-galactan in developing tracheids was investigated in Pinus radiata D. Don using anti-β(1,4)-galactan antibodies to gain insight into its possible physiological role in compression wood. β(1,4)-Galactan was prominent and evenly distributed throughout the S2 layer of developing tracheid cell walls in P. radiata compression wood. In contrast, β(1,4)-galactan was not detected in normal wood. Greatly reduced antibody labeling was observed in fully lignified compression wood tracheids, implying that lignification results in masking of the epitope. To begin to understand the biosynthesis of galactan and its regulation, an assay was developed to monitor the enzyme that elongates the β(1,4)-galactan backbone in pine. A β(1,4)-galactosyltransferase (GalT) activity capable of extending 2-aminopyridine-labeled galacto-oligosaccharides was found to be associated with microsomes. Digestion of the enzymatic products using a β(1,4)-specific endogalactanase confirmed the production of β(1,4)-galactan by this enzyme. This GalT activity was substantially higher in compression wood relative to normal wood. Characterization of the identified pine GalT enzyme activity revealed pH and temperature optima of 7.0 and 20°C, respectively. The β(1,4)-galactan produced by the pine GalT had a higher degree of polymerization than most pectic galactans found in angiosperms. This observation is consistent with the high degree of polymerization of the naturally occurring β(1,4)-galactan in pine.The ability to respond to gravitropic stimuli is important for the survival of most terrestrial plants. Arborescent angiosperm and gymnosperm species generate wood with modified properties, called reaction wood, in response to gravitropic stimuli (Timell, 1969, 1986; Du and Yamamoto, 2007). The formation of reaction wood enables the return of bent stems to a vertical orientation. Interestingly, the location and type of the reaction wood deposited in woody gymnosperms and angiosperms generally differs significantly. Gymnosperms respond to gravitropic stimuli by compression wood formation on the underside of leaning stems (Timell, 1986), and arboreal angiosperms generate reaction wood primarily in the form of tension wood on the upper side of inclined stems (Timell, 1969).Compression wood in conifers differs significantly from normal wood in its anatomical, chemical, and physical properties. Typical anatomical features of severe compression wood are short, rounded, and thick-walled tracheids with a prominent band of lignin in the outer S2 layer of the cell wall as well as spiral checks and the absence of an S3 layer (Timell, 1986). Biochemically, compression wood is characterized by high levels of lignin, rich in condensed p-hydroxyphenyl units, as well as reduced cellulose and galactoglucomannan relative to normal wood (Timell, 1986; Nanayakkara et al., 2005; Yeh et al., 2006). Most striking, though, is that β(1,4)-galactan can constitute more than 10% (w/w) of the cell wall material in severe compression wood but is virtually absent in normal wood (Nanayakkara et al., 2005; Yeh et al., 2006). Recent work suggests that β(1,4)-galactan biosynthesis represents an early step in compression wood formation and confirms that its presence is diagnostic for this wood type (Altaner et al., 2007). However, the molecular signal cascades in conifers that lead to the deposition of β(1,4)-galactan are currently not well understood.Immunological studies in conifer species using the monoclonal anti-β(1,4)-galactan LM5 antibody (Jones et al., 1997) indicate that β(1,4)-galactan in compression wood is located in the S1 and outer S2 layers of mature tracheids but is virtually absent from the primary cell walls (Schmitt et al., 2006; Altaner et al., 2007; Möller and Singh, 2007). Instead of β(1,4)-galactan, most conifers contain small amounts of arabinogalactan, a polysaccharide characterized by a highly branched β(1,3)-galactan backbone (Vikkula et al., 1997; Willför et al., 2002; Laine et al., 2004) in their primary cell walls. The ultrastructural distribution of β(1,4)-galactan in compression wood appears to be largely consistent with highly lignified cell wall layers (Möller and Singh, 2007), which might explain the involvement of β(1,4)-galactan in the formation of lignin-carbohydrate complexes (Mukoyoshi et al., 1981; Minor, 1982; Timell, 1986; Laine et al., 2004).The investigation of β(1,4)-galactan structure in preparations from Pinus sylvestris (Laine et al., 2004) and Pinus radiata (Nanayakkara 2007) revealed a linear polymer. In Pinus densiflora Siebold & Zucc., β(1,4)-galactan was found to be slightly branched at positions C2, C3, and C6 (Mukoyoshi et al., 1981). β(1,4)-Galactan in conifers display a high degree of polymerization (DP), which was originally estimated to be in the range of 200 to 300 (Timell, 1986). More recent studies with P. radiata compression wood found the native polysaccharide to have a DP of approximately 380 (Nanayakkara 2007).β(1,4)-Galactan is a very good biochemical marker for compression wood (Altaner et al., 2007), but its physiological role is currently not well understood. Various functions for β(1,4)-galactan in compression wood have been proposed, such as strengthening of the secondary cell wall, absorption of mechanical stresses, and generation of compressive forces (Möller and Singh, 2007). Furthermore, β(1,4)-galactan is also found in tension wood, with a proposed role in cross-linking cellulose microfibrils (Arend, 2008). However, all of those hypotheses on the molecular function of β(1,4)-galactan in reaction wood await experimental verification.Despite substantial efforts to characterize the biosynthesis of this polymer, β(1,4)-galactan biosynthetic enzymes and their corresponding genes are currently unknown (Peugnet et al., 2001; Geshi et al., 2002, 2004; Abdel-Massih et al., 2003; Kato et al., 2003; Ishii et al., 2004; Konishi et al., 2004, 2007; Gorshkova and Morvan, 2006). However, based on other cell wall polysaccharide biosynthetic enzymes, it is likely that the enzymes involved in the biosynthesis of β(1,4)-galactan are either Golgi localized or pass through the Golgi in transit to the apoplastic space (Reyes and Orellana, 2008).To better understand β(1,4)-galactan synthesis in compression wood formation, we sampled both normal wood and severe compression wood from two 6-year-old P. radiata trees, which displayed stark differences in lignin and carbohydrate content and composition. Using these wood samples, new insights into the subcellular localization of β(1,4)-galactan in pine were generated using confocal laser fluorescence microscopy and transmission electron microscopy. An enzyme assay was developed, based on 2-aminopyridine (2AP)-labeled galacto-oligosaccharides as acceptor molecules, which we used to identify and partially purify a robust, microsome-associated, UDP-Gal-dependent β(1,4)-galactosyltransferase (GalT) activity in compression wood that was virtually undetectable in normal wood. Assays of the partially purified GalT revealed that this enzyme has some properties similar to those of previously characterized pectic GalTs, but a marked difference was observed in the size distribution of the enzymatic products.