<Emphasis Type="Italic">Ramaria chocoënsis</Emphasis> sp. nov., a gomphoid member of <Emphasis Type="Italic">Ramaria</Emphasis> sect. <Emphasis Type="Italic">Dendrocladium</Emphasis> from Colombia,El Chocó, with special regards to rhizomorph anatomy

The new species Ramaria chocoënsis (Gomphales, Basidiomycota) from Colombian Pacific rainforest is described. Despite the gomphoid habit, the new species is inserted in Ramaria sect. Dendrocladium due to rhizomorph anatomy. In rhizomorphs of members of Ramaria sect. Dendrocladium, as in the new species R. chocoënsis, peculiar, thick-walled, gnarled, sphere-bearing hyphae are found, a feature unknown for any other higher fungi. A short survey of hitherto known rhizomorph features within the Gomphales is given. The possibility of putting the members of Ramaria sect. Dendrocladium in a separate genus is taken into account. It would be advisable to have additional data by screening the anatomy of the rhizomorphs in other species, to more accurately predict the classification of Ramaria chocoënsis sp. nov.     

Aquatic heterotrophic bacteria have highly flexible phosphorus content and biomass stoichiometry

Bacteria are central to the cycling of carbon (C), nitrogen (N) and phosphorus (P) in every ecosystem, yet our understanding of how tightly these cycles are coupled to bacterial biomass composition is based upon data from only a few species. Bacteria are commonly assumed to have high P content, low biomass C:P and N:P ratios, and inflexible stoichiometry. Here, we show that bacterial assemblages from lakes exhibit unprecedented flexibility in their P content (3% to less than 0.01% of dry mass) and stoichiometry (C:N:P of 28: 7: 1 to more than 8500: 1200: 1). The flexibility in C:P and N:P stoichiometry was greater than any species or assemblage, including terrestrial and aquatic autotrophs, and suggests a highly dynamic role for bacteria in coupling multiple element cycles.Terrestrial ecosystems are an important source of nutrients and organic carbon (C) to freshwater rivers and lakes as well as the coastal ocean. Past work has shown that heterotrophic bacteria, a group of organisms that process terrestrial inputs of organic carbon, nitrogen (N) and phosphorus (P) (Biddanda et al., 2001), are C-poor and P-rich (Makino et al., 2003) relative to terrestrial inputs characterized by high C:P ratios. As a result, bacterial assemblages in freshwater ecosystems should experience elemental imbalance and act as efficient exporters of organic carbon to downstream ecosystems. However, freshwater ecosystems metabolize most of the organic C they receive from terrestrial ecosystems (Cole et al., 2007) and it has been shown recently that strains (Scott et al., 2012) and assemblages (Godwin and Cotner, 2014) of bacteria from lakes can be P-poor and stoichiometrically flexible. Here, we demonstrate that bacterial assemblages from lakes exhibit unprecedented plasticity in their stoichiometry and discuss the implications of flexible composition to ecosystem processes.To determine the extent of stoichiometric flexibility within assemblages, we performed two experiments in which we cultured the bacteria-sized fraction of plankton from a northern temperate lake under varying C:P supply ratios and measured their biomass composition (Supplementary Methods). We created C:P_supply ratios from 31.6:1 to more than 2 20 000:1 by manipulating the supply of phosphate in a defined medium, with all other nutrients in excess of C and P. At each level of C:P_supply, we enriched the lake assemblages in batch cultures and used these enrichments to inoculate chemostats at the same C:P_supply. The chemostats were maintained at a dilution rate (0.33 d⁻¹) that is low relative to assemblage growth rates measured in lakes (Cotner et al., 2001).The bacterial P content decreased from a mean of 3.55% of dry mass when the assemblage was C-limited to 0.006–0.05% when the assemblage was most P-limited (Figure 1). The range of P content measured in the assemblage cultures was nearly equal to the range of existing data in the literature, particularly for P relative to dry mass (Supplementary Table 6). Single-cell measurements from plankton environments indicated the potential for even lower phosphorus quotas (Norland et al., 1995; Cotner et al., 2010), although many of those cells may not be actively growing, potentially decreasing their demand for P-rich RNA, where much of the P resides in bacterial cells (Makino et al., 2003). The P relative to dry mass values measured here were lower than those reported for a bacterium grown in the absence of added phosphate and high concentrations of arsenate (0.012% of dry mass as P, Wolfe-Simon et al., 2010). The results presented here clearly demonstrate that bacteria can have P content less than 0.01% of dry mass when growing at low levels of P.Open in a separate windowFigure 1Effect of C:P_supply ratio on biomass P/cell (a), P/dry mass (b), C:P_biomass (c) and N:P_biomass (d) ratios in chemostats diluted at 0.33 d⁻¹. Data from Experiment 1 are displayed as solid circles, and open circles denote data from Experiment 2. At each level of C:P_supply, the data from replicate chemostat are staggered to improve clarity. The error bars represent the s.e. of the ratio for each chemostat, following propagation of errors from the numerator and denominator. In Experiment 1, C:P_biomass and N:P_biomass (analysis of variance, P<1 × 10^-5) increased and P/dry mass and P/cell decreased (P<0.005) significantly with increasing C:P_supply. On the basis of changes in C:P_biomass, the assemblage was defined as P-sufficient at C:P_supply of 31.6:1 and P-limited at C:P_supply of 10 000:1 and greater. At C:P_supply of 1 00 000:1, only one chemostat had P content above the analytical detection limit and only two chemostats without added P had N above the detection limit.The C:P_biomass and N:P_biomass of the bacterial assemblages increased from 28:1 and 6:1, respectively, when C-limited to a maximum of >8500:1 and >1200:1 when P-limited (Figure 1). The ranges of C:P_biomass and N:P_biomass observed in this study cover nearly the entire range of measurements recorded in previous studies for bacterial cultures and assemblages (Figure 2; Supplementary Table 6) and nearly match the ranges of C:P_biomass and N:P_biomass observed in vascular plant tissues (Elser et al., 2000; Sterner and Elser, 2002; Reich and Oleksyn, 2004). Furthermore, the bacterial assemblage (of multiple strains) exhibited greater stoichiometric plasticity than has been documented in any other species or assemblage, including terrestrial and aquatic primary producers (Sterner and Elser, 2002; Persson et al., 2010). These experiments demonstrate that previous assumptions of low and invariant C:P_biomass (Tanaka et al., 2009; Fanin et al., 2013) and high relative P content for bacteria (Wolfe-Simon et al., 2010) do not represent the physiological flexibility of bacteria in natural assemblages. Although mean cellular P content decreased under P limitation, much of the flexibility in C:P_biomass was due to a substantial increase in cellular C content (Supplementary Figure 1), likely owing to the accumulation of C-rich storage molecules (Thingstad et al., 2005).Open in a separate windowFigure 2Ranges of C:P_biomass and N:P_biomass for bacterial cultures and other organisms, with separate panels for C:P_biomass (panel a) and N:P_biomass (panel b). Data for heterotrophic bacteria are separated by sources: literature data (Supplementary Table 7), assemblage chemostat cultures (Godwin and Cotner, 2014) and this study. Ranges for other organisms were from ^a (Cross et al., 2005) and ^b (Elser et al., 2000). ^cRanges for E. coli were compiled from multiple studies (Supplementary Table 7). Seston refers to suspended particulate matter (phytoplankton, heterotrophs and detritus). The boxplots display data for individual replicate cultures where data are available, with the centerline representing the median, the edges of the box representing the 25% and 75% quantiles, and the whiskers representing the maximum and minimum values. Dashed lines indicate the Redfield ratio (C:N:P=106:16:1).The range of stoichiometric flexibility present in natural assemblages is critical to understanding homeostasis within ecosystems. Strict homeostasis of assemblage C:N:P_biomass leads to the prediction that the ratio of regenerated C:P increases dramatically with increasing resource C:P (Sterner, 1990), but flexible biomass stoichiometry allows tight coupling and negative feedback between bacterial biomass stoichiometry and resource stoichiometry, facilitating the inherent resilience of ecosystems to nutrient perturbations (Scheffer et al., 2001). It is increasingly recognized that much of the organic matter metabolized in rivers and lakes originates in terrestrial ecosystems where C:P and N:P ratios can be much higher than for organic matter originating in aquatic ecosystems (Lennon and Pfaff, 2005). The observations in this study of extreme flexibility in bacterial biomass stoichiometry are consistent with observations of higher and more variable biomass C:P and N:P in the seston (suspended particulate matter) in freshwaters than in pelagic (offshore) marine systems where terrestrial influences and nutrient gradients are less profound (Cotner et al., 2010).The bacteria in inland waters and the coastal ocean experience stoichiometric imbalance when they process terrestrial inputs of dissolved and particulate organic matter with high C:P ratios. Compared with bacteria with low and invariant C:P_biomass, assemblages that increase their C:P_biomass in response to this imbalance will remineralize less ‘excess'' C through respiration and could decrease the export of organic matter to downstream ecosystems. In ecosystems where internal nutrient cycling processes are dominant and bacteria regenerate a large fraction of available nutrients (for example, offshore marine systems), flexible bacterial stoichiometry likely stabilizes dissolved inorganic nutrient concentrations and inhibits fluctuations.The capacity of heterotrophic bacteria to continue to buffer C and nutrient feedbacks in ecosystems is likely challenged by the use of inorganic fertilizers that decrease the exported C:N and C:P ratios to aquatic systems (Arbuckle and Downing, 2001) and anthropogenic warming that increases both the export of organic carbon and the C:N:P stoichiometry of that material (Freeman et al., 2001; Urban et al., 2011). Additionally, because stoichiometric flexibility decreases with increasing relative growth rates (Makino and Cotner., 2004; Hillebrand et al., 2013), bacterial assemblages in low-temperature environments could become less flexible as the result of anthropogenic warming. By examining the capacity of aquatic bacterial assemblages to respond to C:N:P imbalance, we can evaluate the influence of stoichiometric flexibility on aquatic ecosystem productivity and the extent and periodicity of nutrient fluctuations.     

Intramembrane Proteolysis by Signal Peptide Peptidases: A Comparative Discussion of GXGD-type Aspartyl Proteases

Intramembrane-cleaving proteases are required for reverse signaling and membrane protein degradation. A major class of these proteases is represented by the GXGD-type aspartyl proteases. GXGD describes a novel signature sequence that distinguishes these proteases from conventional aspartyl proteases. Members of the family of the GXGD-type aspartyl proteases are the Alzheimer disease-related γ-secretase, the signal peptide peptidases and their homologs, and the bacterial type IV prepilin peptidases. We will describe the major biochemical and functional properties of the signal peptide peptidases and their relatives. We then compare these properties with those of γ-secretase and discuss common mechanisms but also point out a number of substantial differences.During the last years, a number of intramembrane-cleaving proteases termed I-CLiPs³ have been identified (1). I-CLiPs are generally involved in regulated intramembrane proteolysis (2). Upon shedding of a large part of the ectodomain of membrane proteins, the remaining membrane-retained stub is cleaved by specialized proteases within the hydrophobic lipid membrane. Generally, this cleavage can have two predominant biological functions: first, signaling via the liberated ICD within the substrate-expressing cell (reverse signaling) (2); and second, degradation of membrane-retained stubs, which are not required for any further biological function (3). I-CLiPs of three protease classes, metalloproteases, serine proteases, and aspartyl proteases, have been discovered so far (see accompanying minireview by Wolfe (44)).Intramembrane-cleaving aspartyl proteases are represented by the class of the GXGD-type proteases (4). These are unconventional aspartyl proteases that, like the conventional aspartyl proteases, utilize two critical aspartyl residues for peptide bond cleavage. However, in contrast to the conventional proteases, the critical aspartyl residues are located within two TMDs (Fig. 1A). Moreover, these aspartyl residues are embedded in active-site motifs that are completely different from those of conventional aspartyl proteases. The class of GXGD-type aspartyl proteases is currently represented by three different protease families, the most prominent of which is the PS family, providing the catalytically active subunit of γ-secretase (Fig. 1A) (4). PS/γ-secretase is the I-CLiP that liberates amyloid β-peptide, the major component of senile plaques in Alzheimer disease patients (5). In addition, the bacterial type IV prepilin peptidases also belong to the class of the GXGD-type proteases (6). Besides these two protease families, two additional subfamilies of related proteases that also belong to the GXGD-type aspartyl protease family have been identified. These include SPP as well as the SPP homologs, the SPP-like (SPPL) proteases (Fig. 1A) (7, 8).Open in a separate windowFIGURE 1.A, schematic representation of SPPL2a/b, a member of the SPP/SPPL family, and PS, the catalytic core of theγ-secretase. Note the opposite topology of the active sites (indicated by arrows) of the two proteases and their substrates, APP for PS and TNFα for SPPL2a/b. B, proteolytic processing of APP and TNFα. Shedding releases the extracellular part of APP (APPs) and TNFα (TNFα soluble). In the case of APP, a C-terminal fragment (APP CTF), and in case of TNFα, an N-terminal fragment (TNFα NTF) are produced. These membrane-bound fragments are substrate to intramembrane cleavage by PS or SPPL2a/b, respectively, releasing small peptides to the extracellular space (Aβ and TNFα C-domain, respectively) and to the cytosol (APP intracellular domain (AICD) and TNFα ICD), respectively). TNFα FL, full-length TNFα.We will first describe the biochemical, functional, and structural properties of SPP family members. By comparison of these properties, we will then identify common mechanisms of intramembrane proteolysis by GXGD-type proteases but also point out some fundamental differences.     

3D-SIM Super-resolution of FtsZ and Its Membrane Tethers in Escherichia coli Cells

FtsZ, a bacterial homolog of eukaryotic tubulin, assembles into the Z ring required for cytokinesis. In Escherichia coli, FtsZ interacts directly with FtsA and ZipA, which tether the Z ring to the membrane. We used three-dimensional structured illumination microscopy to compare the localization patterns of FtsZ, FtsA, and ZipA at high resolution in Escherichia coli cells. We found that FtsZ localizes in patches within a ring structure, similar to the pattern observed in other species, and discovered that FtsA and ZipA mostly colocalize in similar patches. Finally, we observed similar punctate and short polymeric structures of FtsZ distributed throughout the cell after Z rings were disassembled, either as a consequence of normal cytokinesis or upon induction of an endogenous cell division inhibitor.The assembly of the bacterial tubulin FtsZ has been well studied in vitro, but the fine structure of the cytokinetic Z ring it forms in vivo is not well defined. Super-resolution microscopy methods including photoactivated localization microscopy (PALM) and three-dimensional-structured illumination microscopy (3D-SIM) have recently provided a more detailed view of Z-ring structures. Two-dimensional PALM showed that Z rings in Escherichia coli are likely composed of loosely-bundled dynamic protofilaments (1,2). Three-dimensional PALM studies of Caulobacter crescentus initially showed that Z rings were comprised of loosely bundled protofilaments forming a continuous but dynamic ring (1–3). However, a more recent high-throughput study showed that the Z rings of this bacterium are patchy or discontinuous (4), similar to Z rings of Bacillus subtilis and Staphylococcus aureus using 3D-SIM (5). Strauss et al. (5) also demonstrated that the patches in B. subtilis Z rings are highly dynamic.Assembly of the Z ring is modulated by several proteins that interact directly with FtsZ and enhance assembly or disassembly (6). For example, FtsA and ZipA promote ring assembly in E. coli by tethering it to the cytoplasmic membrane (7,8). SulA is an inhibitor of FtsZ assembly, induced only after DNA damage, which sequesters monomers of FtsZ to prevent its assembly into a Z ring (9). Our initial goals were to visualize Z rings in E. coli using 3D-SIM, and then examine whether any FtsZ polymeric structures remain after SulA induction. We also asked whether FtsA and ZipA localized in patchy patterns similar to those of FtsZ.We used a DeltaVision OMX V4 Blaze microscope (Applied Precision, GE Healthcare, Issaquah, WA) to view the high-resolution localization patterns of FtsZ in E. coli cells producing FtsZ-GFP (Fig. 1). Three-dimensional views were reconstructed using softWoRx software (Applied Precision). To rule out GFP artifacts, we also visualized native FtsZ from a wild-type strain (WM1074) by immunofluorescence (IF).Open in a separate windowFigure 1Localization of FtsZ in E. coli. (A) Cell with a Z ring labeled with FtsZ-GFP. (B) Rotated view of Z ring in panel A. (C) Cell with a Z ring labeled with DyLight 550 (Thermo Fisher Scientific, Waltham, MA). (D) Rotated view of Z ring in panel C. (B1 and D1) Three-dimensional surface intensity plots of Z rings in panels B and D, respectively. (E) A dividing cell producing FtsZ-GFP. The cell outline is shown in the schematic. (Asterisk) Focus of FtsZ localization; (open dashed ovals) filamentous structures of FtsZ. Three-dimensional surface intensity plots were created using the software ImageJ (19). Scale bars, 1 μm.Both FtsZ-GFP (Fig. 1, A, B, and B1) and IF staining for FtsZ (Fig. 1, C, D, and D1) consistently localized to patches around the ring circumference, similar to the B. subtilis and C. crescentus FtsZ patterns (4,5). Analysis of fluorescence intensities (see Fig. S1, A and B, in the Supporting Material) revealed that the majority of Z rings contain one or more gaps in which intensity decreases to background levels (82% for FtsZ-GFP and 69% for IF). Most rings had 3–5 areas of lower intensity, but only a small percentage of these areas had fluorescence below background intensity (34% for FtsZ-GFP and 21% for IF), indicating that the majority of areas with lower intensity contain at least some FtsZ.To elucidate how FtsZ transitions from a disassembled ring to a new ring, we imaged a few dividing daughter cells before they were able to form new Z rings (Fig. 1 E). Previous conventional microscopy had revealed dynamic FtsZ helical structures (10), but the resolution had been insufficient to see further details. Here, FtsZ visualized in dividing cells by 3D-SIM localized throughout as a mixture of patches and randomly-oriented short filaments (asterisk and dashed oval in Fig. 1, respectively). These structures may represent oligomeric precursors of Z ring assembly.To visualize FtsZ after Z-ring disassembly another way, we overproduced SulA, a protein that blocks FtsZ assembly. We examined E. coli cells producing FtsZ-GFP after induction of sulA expression from a pBAD33-sulA plasmid (pWM1736) with 0.2% arabinose. After 30 min of sulA induction, Z rings remained intact in most cells (Fig. 2 A and data not shown). The proportion of cellular FtsZ-GFP in the ring before and after induction of sulA was consistent with previous data (data not shown) (1,11).Open in a separate windowFigure 2Localization of FtsZ after overproduction of SulA. (A) Cell producing FtsZ-GFP after 0.2% arabinose induction of SulA for 30 min. (B) After 45 min. (B1) Magnified cell shown in panel B. (C) Cell producing native FtsZ labeled with AlexaFluor 488 (Life Technologies, Carlsbad, CA) 30 min after induction; (D) 45 min after induction. (D1) Magnified cell shown in panel D. Scale bars, 1 μm. (Asterisk) Focus of FtsZ localization; (open dashed ovals) filamentous structures of FtsZ.Notably, after 45 min of sulA induction, Z rings were gone (Fig. 2, B and B1), replaced by numerous patches and randomly-oriented short filaments (asterisk and dashed ovals in Fig. 2), similar to those observed in a dividing cell. FtsZ normally rapidly recycles from free monomers to ring-bound polymers (11), but a critical concentration of SulA reduces the pool of available FtsZ monomers, resulting in breakdown of the Z ring (9). The observed FtsZ-GFP patches and filaments are likely FtsZ polymers that disassemble before they can organize into a ring.We confirmed this result by overproducing SulA in wild-type cells and detecting FtsZ localization by IF (Fig. 2, C, D, and D1). The overall fluorescence patterns in cells producing FtsZ-GFP versus cells producing only native FtsZ were similar (Fig. 2, B1 and D1), although we observed fewer filaments with IF, perhaps because FtsZ-GFP confers slight resistance to SulA, or because the increased amount of FtsZ in FtsZ-GFP producing cells might titrate the SulA more effectively.Additionally, we wanted to observe the localization patterns of the membrane tethers FtsA and ZipA. Inasmuch as both proteins bind to the same C-terminal conserved tail of FtsZ (12–14), they would be expected to colocalize with the circumferential FtsZ patches in the Z ring. We visualized FtsA using protein fusions to mCherry and GFP (data not shown) as well as IF using a wild-type strain (WM1074) (Fig. 3 A). We found that the patchy ring pattern of FtsA localization was similar to the FtsZ pattern. ZipA also displayed a similar patchy localization in WM1074 by IF (Fig. 3 B).Open in a separate windowFigure 3Localization of FtsA (A) and ZipA (B) by IF using AlexaFluor 488. (C) FtsA-GFP ring. (D) Same cell shown in panel C with ZipA labeled with DyLight 550. (C1 and D1) Three-dimensional surface intensity plots of FtsA ring from panel C or ZipA ring from panel D, respectively. (E) Merged image of FtsA (green) and ZipA (red) from the ring shown in panels C and D. (F) Intensity plot of FtsA (green) and ZipA (red) of ring shown in panel E. The plot represents intensity across a line drawn counterclockwise from the top of the ring around the circumference, then into its lumen. Red/green intensity plot and three-dimensional surface intensity plots were created using the software ImageJ (19). Scale bar, 1 μm.To determine whether FtsA and ZipA colocalized to these patches, we used a strain producing FtsA-GFP (WM4679) for IF staining of ZipA using a red secondary antibody. FtsA-GFP (Fig. 3 C) and ZipA (Fig. 3 D) had similar patterns of fluorescence, although the three-dimensional intensity profiles (Fig. 3, C1 and D1) reveal slight differences in intensity that are also visible in a merged image (Fig. 3 E). Quantitation of fluorescence intensities around the circumference of the rings revealed that FtsA and ZipA colocalized almost completely in approximately half of the rings analyzed (Fig. 3 F, and see Fig. S2 A), whereas in the other rings there were significant differences in localization in one or more areas (see Fig. S2 B). FtsA and ZipA bind to the same C-terminal peptide of FtsZ and may compete for binding. Cooperative self-assembly of FtsA or ZipA might result in large-scale differential localization visible by 3D-SIM.In conclusion, our 3D-SIM analysis shows that the patchy localization of FtsZ is conserved in E. coli and suggests that it may be widespread among bacteria. After disassembly of the Z ring either in dividing cells or by excess levels of the cell division inhibitor SulA, FtsZ persisted as patches and short filamentous structures. This is consistent with a highly dynamic population of FtsZ monomers and oligomers outside the ring, originally observed as mobile helices in E. coli by conventional fluorescence microscopy (10) and by photoactivation single-molecule tracking (15). FtsA and ZipA, which bind to the same segment of FtsZ and tether it to the cytoplasmic membrane, usually display a similar localization pattern to FtsZ and each other, although in addition to the differences we detect by 3D-SIM, there are also likely differences that are beyond its ∼100-nm resolution limit in the X,Y plane.As proposed previously (16), gaps between FtsZ patches may be needed to accommodate a switch from a sparse Z ring to a more condensed ring, which would provide force to drive ring constriction (17). If this model is correct, the gaps should close upon ring constriction, although this may be beyond the resolution of 3D-SIM in constricted rings. Another role for patches could be to force molecular crowding of low-abundance septum synthesis proteins such as FtsI, which depend on FtsZ/FtsA/ZipA for their recruitment, into a few mobile supercomplexes.How are FtsZ polymers organized within the Z-ring patches? Recent polarized fluorescence data suggest that FtsZ polymers are oriented both axially and circumferentially within the Z ring in E. coli (18). The seemingly random orientation of the non-ring FtsZ polymeric structures we observe here supports the idea that there is no strong constraint requiring FtsZ oligomers to follow a circumferential path around the cell cylinder. The patches of FtsZ in the unperturbed E. coli Z ring likely represent randomly oriented clusters of FtsZ filaments that are associated with ZipA, FtsA, and essential septum synthesis proteins. New super-resolution microscopy methods should continue to shed light on the in vivo organization of these protein assemblies.     

Use of Ultrasounds to Reduce the Count of Campylobacter coli in Water

The present study aimed to evaluate the effectiveness of low-frequency ultrasounds applied to eliminate Campylobacter spp. from water. The strains used in this research were isolated from water contaminated with sewage. Campylobacter coli alone was detected in the samples and used for further research. The reference strain C. coli ATCC 33559 was simultaneously tested. The isolate was exposed to ultrasounds at frequencies of 37 kHz and 80 kHz in a continuous operation device with ultrapure deionized water. After 5 min of sonication, the count of C. coli decreased by 5.78% (37 kHz) and 6.27% (80 kHz), whereas the temperature increased by 3°C (37 kHz), and 6°C (80 kHz). After 30 min of sonication, the death rates of bacterial cells were 40.15% (37 kHz) and 55.10% (80 kHz), whereas the temperature reached the maximum values of 36°C (37 kHz), and 39°C (80 kHz). Sonication at the frequency of 80 kHz reduced the bacterial count from 6.86 log CFU/ml to 3.08 log CFU/ml, whereas the frequency of 37 kHz reduced the bacterial count from 6.75 log CFU/ml to 4.04 log CFU/ml. Despite significant differences (p < 0.05) in the number of C. coli cells, the cell death rate remained at the same level. Open in a separate window     

Novel Growth Regime of MDCK II Model Tissues on Soft Substrates

It is well established that MDCK II cells grow in circular colonies that densify until contact inhibition takes place. Here, we show that this behavior is only typical for colonies developing on hard substrates and report a new growth phase of MDCK II cells on soft gels. At the onset, the new phase is characterized by small, three-dimensional droplets of cells attached to the substrate. When the contact area between the agglomerate and the substrate becomes sufficiently large, a very dense monolayer nucleates in the center of the colony. This monolayer, surrounded by a belt of three-dimensionally packed cells, has a well-defined structure, independent of time and cluster size, as well as a density that is twice the steady-state density found on hard substrates. To release stress in such dense packing, extrusions of viable cells take place several days after seeding. The extruded cells create second-generation clusters, as evidenced by an archipelago of aggregates found in a vicinity of mother colonies, which points to a mechanically regulated migratory behavior.Studying the growth of cell colonies is an important step in the understanding of processes involving coordinated cell behavior such as tissue development, wound healing, and cancer progression. Apart from extremely challenging in vivo studies, artificial tissue models are proven to be very useful in determining the main physical factors that affect the cooperativity of cells, simply because the conditions of growth can be very well controlled. One of the most established cell types in this field of research is the Madin-Darby canine kidney epithelial cell (MDCK), originating from the kidney distal tube (1). A great advantage of this polarized epithelial cell line is that it retained the ability for contact inhibition (2), which makes it a perfect model system for studies of epithelial morphogenesis.Organization of MDCK cells in colonies have been studied in a number of circumstances. For example, it was shown that in three-dimensional soft Matrigel, MDCK cells form a spherical enclosure of a lumen that is enfolded by one layer of polarized cells with an apical membrane exposed to the lumen side (3). These structures can be altered by introducing the hepatocyte growth factor, which induces the formation of linear tubes (4). However, the best-studied regime of growth is performed on two-dimensional surfaces where MDCK II cells form sheets and exhibit contact inhibition. Consequently, the obtained monolayers are well characterized in context of development (5), mechanical properties (6), and obstructed cell migration (7–9).Surprisingly, in the context of mechanics, several studies of monolayer formation showed that different rigidities of polydimethylsiloxane gels (5) and polyacrylamide (PA) gels (9) do not influence the nature of monolayer formation nor the attainable steady-state density. This is supposedly due to long-range forces between cells transmitted by the underlying elastic substrate (9). These results were found to agree well with earlier works on bovine aortic endothelial cells (10) and vascular smooth muscle cells (11), both reporting a lack of sensitivity of monolayers to substrate elasticity. Yet, these results are in stark contrast with single-cell experiments (12–15) that show a clear response of cell morphology, focal adhesions, and cytoskeleton organization to substrate elasticity. Furthermore, sensitivity to the presence of growth factors that are dependent on the elasticity of the substrate in two (16) and three dimensions (4) makes this result even more astonishing. Therefore, we readdress the issue of sensitivity of tissues to the elasticity of the underlying substrate and show that sufficiently soft gels induce a clearly different tissue organization.We plated MDCK II cells on soft PA gels (Young’s modulus E = 0.6 ± 0.2 kPa), harder PA gels (E = 5, 11, 20, 34 kPa), and glass, all coated with Collagen-I. Gels were prepared following the procedure described in Rehfeldt et al. (17); rigidity and homogeneity of the gels was confirmed by bulk and microrheology (see the Supporting Material for comparison). Seeding of MDCK II cells involved a highly concentrated solution dropped in the middle of a hydrated gel or glass sample. For single-cell experiments, cells were dispersed over the entire dish. Samples were periodically fixed up to Day 12, stained for nuclei and actin, and imaged with an epifluorescence microscope. Details are described in the Supporting Material.On hard substrates and glass it was found previously that the area of small clusters expands exponentially until the movement of the edge cannot keep up with the proliferation in the bulk (5). Consequently, the bulk density increases toward the steady state, whereas the density of the edge remains low. At the same time, the colony size grows subexponentially (5). This is what we denote “the classical regime of growth”. Our experiments support these observations for substrates with E ≥ 5 kPa. Specifically, on glass, colonies start as small clusters of very low density of 700 ± 200 cells/mm² (Fig. 1, A and B), typically surrounded by a strong actin cable (Fig. 1, B and C). Interestingly, the spreading area of single cells (Fig. 1 A) on glass was found to be significantly larger, i.e., (2.0 ± 0.9) × 10⁻³ mm². After Day 4 (corresponding cluster area of 600 ± 100 mm²), the density in the center of the colony reached the steady state with 6,800 ± 500 cells/mm², whereas the mean density of the edge profile grew to 4,000 ± 500 cells/mm². This density was retained until Day 12 (cluster area 1800 ± 100 mm²), which is in agreement with previous work (9).Open in a separate windowFigure 1Early phase of cluster growth on hard substrates. (A) Well-spread single cells, and small clusters with a visible actin cable 6 h after seeding. (B) Within one day, clusters densify and merge, making small colonies. (C) Edge of clusters from panel B.In colonies grown on 0.6 kPa gels, however, we encounter a very different growth scenario. The average spreading area of single cells is (0.34 ± 0.3) × 10⁻³ mm², which is six times smaller than on glass substrates (Fig. 2 A). Clusters of only few cells show that cells have a preference for cell-cell contacts (a well-established flat contact zone can be seen at the cell-cell interface in Fig. 2 A) rather than for cell-substrate contacts (contact zone is diffusive and the shape of the cells appears curved). The same conclusion emerges from the fact that dropletlike agglomerates, resting on the substrate, form spontaneously (Fig. 2 A), and that attempts to seed one single cluster of 90,000 cells fail, resulting in a number of three-dimensional colonies (Fig. 2 A). When the contact area with the substrate exceeds 4.7 × 10⁻³ mm², a monolayer appears in the center of such colonies (Fig. 2 B). The colonies can merge, and if individual colonies are small, the collapse into a single domain is associated with the formation of transient irregular structures (Fig. 2 B). Ultimately, large elliptical colonies (average major/minor axis of e = 1.8 ± 0.6) with a smooth edge are formed (Fig. 2 C), unlike on hard substrates where circular clusters (e = 1.06 ± 0.06) with a ragged edge comprise the characteristic phenotype.Open in a separate windowFigure 2Early phase of cluster growth on soft substrates. (A) Twelve hours after seeding, single cells remain mostly round and small. They are found as individual, or within small, three-dimensional structures (top). The latter nucleate a monolayer in their center (bottom), if the contact area with the substrate exceeds ∼5 × 10⁻³ mm². (B) Irregularly-shaped clusters appear due to merging of smaller droplets. A stable monolayer surrounded by a three-dimensional belt of densely packed cells is clearly visible, even in larger structures. (C) All colonies are recorded on Day 4.Irrespective of cluster size, in the new regime of growth, the internal structure is built of two compartments (Fig. 2 B):

• 1.The first is the edge (0.019 ± 0.05-mm wide), a three-dimensional structure of densely packed cells. This belt is a signature of the new regime because on hard substrates the edge is strictly two-dimensional (Fig. 1 C).
• 2.The other is the centrally placed monolayer with a spatially constant density that is very weakly dependent on cluster size and age (Fig. 3). The mean monolayer density is 13,000 ± 2,000 cells/mm², which is an average over 130 clusters that are up to 12 days old and have a size in the range of 10⁻³ to 10 mm², each shown by a data point in Fig. 3. This density is twice the steady-state density of the bulk tissue in the classical regime of growth.Open in a separate windowFigure 3Monolayer densities in colonies grown on 0.6 kPa substrates, as a function of the cluster size and age. Each cluster is represented by a single data point signifying its mean monolayer density. (Black lines) Bulk and (red dashed lines) edge of steady-state densities from monolayers grown on glass substrates. Error bars are omitted for clarity, but are discussed in the Supporting Material.

Until Day 4, the monolayer is very homogeneous, showing a nearly hexagonal arrangement of cells. From Day 4, however, defects start to appear in the form of small holes (typical size of (0.3 ± 0.1) × 10⁻³ mm²). These could be attributed to the extrusions of viable cells, from either the belt or areas of increased local density in the monolayer (inset in Fig. 4). This suggests that extrusions serve to release stress built in the tissue, and, as a consequence, the overall density is decreased.Open in a separate windowFigure 4Cell nuclei within the mother colony and in the neighboring archipelago of second-generation clusters grown on 0.6 kPa gels at Day 12. (Inset; scale bar = 10 μm) Scar in the tissue, a result of a cell-extrusion event. (Main image; scale bar = 100 μm) From the image of cell nuclei (left), it is clear that there are no cells within the scar, whereas the image of actin (right) shows that the cytoplasm of the cells at the edge has closed the hole.Previous reports suggest that isolated MDCK cells undergo anoikis 8 h after losing contact with their neighbors (18). However, in this case, it appears that instead of dying, the extruded cells create new colonies, which can be seen as an archipelago surrounding the mother cluster (Fig. 4). The viability of off-cast cells is further evidenced by the appearance of single cells and second-generation colonies with sizes varying over five orders of magnitude, from Day 4 until the end of the experiment, Day 12. Importantly, no morphological differences were found in the first- and second-generation colonies.In conclusion, we show what we believe to be a novel phase of growth of MDCK model tissue on soft PA gels (E = 0.6 kPa) that, to our knowledge, despite previous similar efforts (9), has not been observed before. This finding is especially interesting in the context of elasticity of real kidneys, for which a Young’s modulus has been found to be between 0.05 and 5 kPa (19,20). This coincides with the elasticity of substrates studied herein, and opens the possibility that the newly found phase of growth has a particular biological relevance. Likewise, the ability to extrude viable cells may point to a new migratory pathway regulated mechanically by the stresses in the tissue, the implication of which we hope to investigate in the future.     

Ratiometric Imaging of the T-Cell Actin Cytoskeleton Reveals the Nature of Receptor-Induced Cytoskeletal Enrichment

The T-cell actin cytoskeleton mediates adaptive immune system responses to peptide antigens by physically directing the motion and clustering of T-cell receptors (TCRs) on the cell surface. When TCR movement is impeded by externally applied physical barriers, the actin network exhibits transient enrichment near the trapped receptors. The coordinated nature of the actin density fluctuations suggests that they are composed of filamentous actin, but it has not been possible to eliminate de novo polymerization at TCR-associated actin polymerizing factors as an alternative cause. Here, we use a dual-probe cytoskeleton labeling strategy to distinguish between stable and polymerizing pools of actin. Our results suggest that TCR-associated actin consists of a relatively high proportion of the stable cytoskeletal fraction and extends away from the cell membrane into the cell. This implies that actin enrichment at mechanically trapped TCRs results from three-dimensional bunching of the existing filamentous actin network.The T-cell actin cytoskeleton is critical for proper antigen recognition by the mammalian adaptive immune system. During T-cell receptor (TCR) triggering by antigen peptides presented on major histocompatibility proteins (pMHCs) on the surfaces of antigen-presenting cells (APCs), the T-cell actin cytoskeleton adopts a pattern of centrosymmetric retrograde flow (1–3). This simultaneously promotes further TCR triggering (4) and rearranges various T-cell membrane proteins and their APC counterparts into an organized cell-cell interface termed the immunological synapse (IS) (5–7). During this process, TCRs form microclusters that move to the center of the IS in an actin-dependent manner (8,9). When engineered physical barriers interrupt the centripetal motion of TCR clusters, actin flow slows near the pinned microclusters, and the cytoskeletal network transiently accumulates and dissipates at the sites (10,11). The amplitude and duration of the induced cytoskeletal fluctuations are much greater than would be expected for a random distribution of independent objects, indicating that the actin in the local environment is coordinated. Whether this coordination arises from a rearrangement in the existing F-actin network or represents de novo polymerization of the cytoskeleton, as predicted by the association of TCRs with actin polymerizing factors (12), remains unclear. Here, we use a dual-probe cytoskeleton labeling approach that has previously been applied to distinguish between stable and dynamic populations of actin by exploiting the different relative affinities of monomeric actin and actin-binding proteins toward each population (13). This strategy reveals that TCR-associated actin is composed primarily of the stable cytoskeletal fraction and that local enrichment results from three-dimensional bunching of the existing filamentous actin network.Primary T cells from mice transgenic for the AND TCR were triggered using synthetic APCs consisting of supported lipid bilayers functionalized with pMHC and the integrin ligand intercellular adhesion molecule 1. Nanopatterned metal grids on the bilayer substrate acted as diffusion barriers that prevented lateral transport of TCR-pMHC complexes (14,15). Transient enrichment of actin at TCR clusters trapped at these barriers was visualized using fluorescent fusions of actin itself (mKate2-β-actin) and the F-actin binding domain of utrophin (EGFP-UtrCH). Such a dual-probe strategy theoretically allows for discrimination between different pools of actin: dynamic populations characterized by high polymerization and/or short filament fragments tend to be relatively better labeled by direct actin fusions whereas stable populations composed of longer filaments can support higher labeling by fluorescent fusions of F-actin binding proteins. This visualization method has been validated in Xenopus oocytes, where it distinguishes actin populations during wound healing (13). It has not been explicitly applied to T cells; however, simultaneous labeling of the Jurkat cell cytoskeleton using EGFP-actin and Alexa 568-phalloidin reveals distinct populations of actin consistent with the results expected from Xenopus (13,16).Our results show that the T-cell periphery is relatively enriched in mKate2-β-actin (Fig. 1 C, box 1), while EGFP-UtrCH dominates toward the center of the IS (Fig. 1 C, box 2). We infer from this probe distribution that the cytoskeleton at the T-cell periphery is composed of short fragments and is a site of active polymerization, whereas at the center of the IS, actin filaments are longer and predominantly stable. This is consistent with previous models of the T-cell actin network (3,16). An effective way to highlight each of these cytoskeletal regions is to consider the relative ratios of the two probes at each location. In this case, a high UtrCH/actin ratio corresponds to stable actin, and a high actin/UtrCH ratio corresponds to dynamic actin (Fig. 1 D). When T cells are treated with cytochalasin D, an inhibitor of actin polymerization, the overall UtrCH/actin ratio of the cell decreases as would be expected from a general decrease in polymerized actin (see Movie S7 and Movie S8 in the Supporting Material). However, it should be noted that photobleaching can also shift the UtrCH/actin ratio over time. We limit quantitative analysis of the ratio to its spatial gradients at a single time point, but such analysis is possible in systems that permit rigorous calibration for probe expression and photobleaching.Open in a separate windowFigure 1Ratiometric imaging of the cytoskeleton in live T cells distinguishes between dynamic and stable actin populations. (A) mKate2-β-actin, (B) EGFP-UtrCH, and (C) merged images of a triggered T cell show different actin pools. The cutouts in panel C correspond to (1) a region high in dynamic actin featuring short, polymerizing filaments and/or actin monomers and (2) a region with a stable actin population featuring longer filaments to which UtrCH can bind. (D) The UtrCH/actin ratio image highlights pools of relatively high UtrCH (red) or actin (blue). (Scale bars: 5 μm.)Actin enrichment at trapped TCR clusters incorporates both mKate2-β-actin (Fig. 2, A and C) and EGFP-UtrCH (Fig. 2, B and C). The relative UtrCH/actin ratio at these sites (Fig. 2 D, box 2) is quite high relative to nearby background areas (Fig. 2 D, box 1), indicating that the actin is derived primarily from the stable actin population.Open in a separate windowFigure 2Receptor-induced cytoskeletal enrichment at sites of pinned TCRs corresponds to a primarily stable actin fraction. (A) mKate2-β-actin, (B) EGFP-UtrCH, and (C) merged images of a triggered T cell interacting with a nanopatterned supported lipid bilayer show actin enrichment corresponding to putative sites of pinned TCRs. (D) The UtrCH/actin ratio is high at sites displaying actin enrichment, indicating a primarily stable actin fraction in (1) these regions compared to (2) nearby background areas. (Scale bars: 5 μm.)The three-dimensional distribution of TCR-associated actin was analyzed in dual-labeled live T cells using a spinning disk confocal microscope. The recordings show actin extending away from the cell membrane in the vicinity of trapped TCRs, while the rest of the actin cytoskeleton remains relatively flat (Fig. 3 and see Fig. S1 in the Supporting Material). These protrusions of actin away from the membrane surface are predominantly composed of stable, filamentous actin, as indicated by their relatively high UtrCH/actin ratio (Fig. 3 B).Open in a separate windowFigure 3Three-dimensional ratiometric imaging shows that actin enrichment extends away from the cell membrane. Single planes from (A) merged mKate2-β-actin and EGFP-UtrCH and (B) UtrCH/actin ratio three-dimensional stacks show actin enrichment at the cell membrane. Cutouts represent Z projections passing through sites of (1) enrichment and (2) nearby background regions. The color distribution in panel B is analogous to that in Figs. 1D and ​and22D, and is omitted for clarity. (Scale bar: 5 μm in the x axis only. Scale box: 1 μm.)Our interpretation of these results is that the filamentous actin network is relatively dense at sites of pinned TCRs. This is the simplest explanation out of several possibilities, one of which is formin-mediated mKate2-β-actin-deficient actin nucleation (17). Filament bunching at pinned TCRs can arise from consistent biophysical properties without assuming heterogeneity between the biochemistry of these receptors and other actin-associated proteins such as those at the cell edge, where locally high probe ratios are absent.Although TCRs are intentionally trapped as part of this experimental strategy, it is likely APCs can naturally impede TCR ligand mobilities under certain circumstances, and this has been shown to impact T-cell signaling (18,19). Actin architecture near cell surface proteins has been extensively studied in focal adhesions of fibroblasts (20), but the lack of stress fibers in T cells makes it unlikely that the two structures are similar. Thus, receptor-induced cytoskeletal enrichment at TCR clusters adds to the catalog of actin behaviors in situ, which is conveniently probed by techniques such as ratiometric dual-probe imaging in live cells. These techniques can be coupled to various spatial analysis algorithms to further extend their utility.     

Rescue of a Dominant Mutant With RNA Interference

Maize Mucronate1 is a dominant floury mutant based on a misfolded 16-kDa γ-zein protein. To prove its function, we applied RNA interference (RNAi) as a dominant suppressor of the mutant seed phenotype. A γ-zein RNAi transgene was able to rescue the mutation and restore normal seed phenotype. RNA interference prevents gene expression. In most cases, this is used to study gene function by creating a new phenotype. Here, we use it for the opposite purpose. We use it to reverse the creation of a mutant phenotype by restoring the normal phenotype. In the case of the maize Mucronate1 (Mc1) phenotype, interaction of a misfolded protein with other proteins is believed to be the basis for the Mc1 phenotype. If no misfolded protein is present, we can reverse the mutant to the normal phenotype. One can envision using this approach to study complex traits and in gene therapy.TRANSLUCENT or vitreous maize kernels are harder and able to sustain stronger mechanical strength during harvesting, transportation, and storage. There is a direct link between a vitreous seed phenotype and the type of storage proteins in the seed, collectively called zeins in maize. Zeins, encoded by a multigene family, constitute >60% of all maize seed proteins. They are classified into four groups (α-, β-, γ-, and δ-zein) on the basis of their structures (Esen 1987). Zeins are specifically synthesized in the endosperm ∼10 days after pollination (DAP) and deposited into protein bodies (Wolf et al. 1967; Burr and Burr 1976; Lending and Larkins 1992). Irregularly shaped protein bodies are found in floury or opaque kernel phenotypes (Coleman et al. 1997; Kim et al. 2004, 2006; Wu et al. 2010; Wu and Messing 2010). The terms “floury” and “opaque” were originally created on the basis of the genetic behaviors of the mutant allele causing the soft kernel texture. The floury mutants behave as semidominant or dominant mutants, as floury1 and floury2 do, while the opaque mutants are recessive, as opaque1 and opaque2 are (Hayes and East 1915; Lindstrom 1923; Emerson et al. 1935; Maize Genetics Cooperation 1939). Similar to floury2 with a single mutation in the signal peptide of a 22-kDa α-zein resulting in an unprocessed protein (Coleman et al. 1995), De*-B30 produces an unprocessed 19-kDa α-zein (Kim et al. 2004). It was hypothesized that the two mutant proteins with an unprocessed signal peptide are misfolded and docked in the membranes of the rough endoplasmic reticulum (RER), blocking the deposition of other zein proteins (Coleman et al. 1995; Kim et al. 2004). In Mucronate1 (Mc1), a 38-bp deletion in the C terminus of the 16-kDa γ-zein (γ16-zein) gene resulted in a frameshift and a protein with a different amino-acid tail. This modified 16-kDa γ-zein (Δγ16-zein) has altered solubility properties, which would explain the formation of irregular protein bodies. Because De*-B30 and Mc1 are semidominant and dominant, respectively, they belong to the floury mutant class.The γ-zein genes (γ27-zein and γ16-zein) are homologous copies because maize underwent allotetraploidization and both gene copies have been retained during diploidization (Xu and Messing 2008). The two γ-zeins and the 15-kDa β-zein have a redundant function in stabilizing protein-body formation (Wu and Messing 2010). Knockdown of both γ-zeins with a single RNA interference (RNAi) construct conditioned only partial opacity in the crown, the top of the kernel, as opposed to the remainder or gown area of the kernel. Consistent with its light kernel phenotype, protein bodies in such a γ-zein RNAi (γRNAi) mutant exhibited a slight alteration in morphology. This phenotype is clearly distinguishable from the Mc1 phenotype, which is far more severe. Therefore, if Mc1 is caused by a misfolded chimeric 16-kDa γ-zein, preventing its expression should restore normal kernel phenotype. Indeed, a simple cross of Mc1 with a maize line carrying the γRNAi transgene produced a non-floury phenotype, providing an example of RNAi as a dominant suppressor of a dominant phenotype and as a general tool in marker rescue.

Analysis of the progeny from the cross of Mc1 and γRNAi mutants:

Mc1 seeds (Stock ID U840I) were requested from the Maize Genetics Cooperation Stock Center. The γRNAi transgenic lines have been reported in previous work (Wu et al. 2010; Wu and Messing 2010). Twelve progeny kernels from the cross of the Mc1 mutant [homozygous for the dominant-negative mutant 16-kDa γ-zein alleles (Δγ16/Δγ16) and heterozygous for the γRNAi line (γRNAi/+)] were dissected at 18 DAP for segregation and mRNA accumulation analyses. For each kernel, the embryo and endosperm were separated for DNA and RNA extraction, respectively. As shown in Figure 1A, five and seven kernels were positive and negative for the amplification of the γRNAi gene with a specific primer set, exemplifying a 1:1 segregation of the γRNAi gene.Open in a separate windowFigure 1.—Segregation analysis of the accumulations of mRNAs and proteins from the cross of the Mc1 mutant and the γRNAi line by RT–PCR and SDS–PAGE. (A) γRNAi gene segregation from progeny (Δγ16/Δγ16 x γRNAi/+) by PCR amplification with a specific primer set (GFPF, ACAACCACTACCTGAGCAC and T35SHindIII, ATTAAGCTTTGCAGGTCACTGGATTTTGG). Kernels 3, 8, 9, 10, and 12 are positive for the γRNAi gene and the rest of them are negative. M, DNA markers from top to bottom band are 3, 2, 1.5, 1.4, and 1 kb. (B) RT–PCR analysis of mRNA accumulation from the normal γ16 and mutant Δγ16 alleles in the endosperms with the genotypes corresponding to the embryos analyzed above. Total RNA was extracted by using TRIzol reagent (Invitrogen). Two micrograms of RNA was digested with DNase I (Invitrogen) and then reverse-transcribed. Twenty-five nanograms of cDNA from each of the twelve endosperms was applied for PCR (25 cycles of 30 sec, 94 °C; 30 sec, 58 °C; and 1 min, 72 °C). A specific primer set (γ16F, ATGAAGGTGCTGATCGTTGC and γ16R, TCAGTAGTAGACACCGCCG) was designed for amplification of the full-length γ16-zein coding sequence (552 bp). The lower band (514 bp) from the mutant Δγ16 allele is 38 bp shorter than that from the normal allele (552 bp). Kernels 3, 8, 9, 10, and 12 with the γRNAi gene accumulated significantly less mRNA compared to those without the γRNAi gene (kernels 1, 2, 4, 5, 6, 7, and 11). BA, hybrid of B × A lines. M, DNA markers from top to bottom are 1 kb, 750 bp, and 500 bp. (C) Profile of zein accumulations of 20 kernels from the progeny as described in the text. The zein extraction method has been described elsewhere (Wu et al. 2009). The Δγ16-zein from Mc1 was not extracted by traditional total-zein extraction protocol (70% ethanol and 2% 2-mercaptoethanol). The γ27- and γ16-zeins were knocked down to a nondetectable level in kernels 1, 2, 3, 5, 7, 10, 12, 13, 16, and 20. In γRNAi-gene segregating progeny (kernels 4, 6, 8, 9, 11, 14, 15, 17, 18, and 19), the γ16-zein from the normal γ16 allele is marked by arrowheads. Protein loaded in each lane was equal to 500 μg fresh endosperm at 18 DAP. The size for each band is indicated by the numbers in the “kDa” columns. BA, hybrid of B × A lines; 1–20, kernels from the progeny described above; M, protein markers from top to bottom are 50, 25, 20, and 15 kDa.Due to the 38-bp deletion in the C terminus of the coding region, the Δγ16 allele is shorter than the normal one (Figure 1B). Therefore, most of Δγ16-zein was in the non-zein fraction. In progeny endosperms of another 20 kernels from the same cross described above segregating for the γRNAi gene, two types of γ16-zeins were synthesized: the normal γ16-zein in the ethanol-soluble zein fraction and the Δγ16-zein in the non-zein fraction. In progeny inheriting the γRNAi gene, the γ27- and γ16-zeins were reduced to nondetectable levels (Figure 1C). Although the Δγ16-zein is not in the ethanol-soluble zein fraction, the level of normal γ16-zein is a good indicator of the accumulation of the Δγ16-zein.

Rescue of protein-body morphologies in the Mc1 mutant:

Regular protein bodies are round with distinct membrane boundaries (Figure 2A) and 1–2 μm in diameter at maturity. In homozygous and heterozygous Mc1 mutants (Δγ16/Δγ16 and Δγ16/+), protein bodies were irregularly shaped, some without discrete boundaries (Figure 2, C and D), which is quite different from the absence of normal γ27- or γ16-zeins in maize endosperm (Figure 2B). Indeed, protein bodies of the Mc1 mutant, blocked in the accumulation of Δγ16-zein, showed morphologies with no discernible difference from those in the γRNAi/+ line (Figure 2, B and E).Open in a separate windowFigure 2.—Transmission electron micrographs of protein bodies. The method has been described elsewhere (Wu and Messing 2010). (A) Nontransgenic BA. (B) γRNAi transgenic line (γRNAi/+). (C) Mc1 (Δγ16/Δγ16). (D) Cross of Mc1 mutant and nontransgenic hybrid of B × A lines (Δγ16/+). (E) Cross of Mc1 mutant (Δγ16/Δγ16) and heterologous γRNAi transgenic line (γRNAi/+). PB, protein body; RER, rough endoplasmic reticulum; CW, cell wall; Mt, mitochondria; SG, starch granule. Bars, 500 nm.

Recovery of floury phenotype in progeny:

On the basis of these observations, it is reasoned that irregularly shaped protein bodies (Figure 2, C and D) in the Mc1 mutant cause the floury phenotype (Figure 3, A and B). Because knockdown of γ-zeins caused opacity only in the crown area (Figure 3C), one could envision that once the irregular protein bodies are restored, the kernel would become vitreous in the gown area of the kernel. Indeed, the progeny ear from the cross of Δγ16/Δγ16 and γRNAi/+ showed a 1:1 ratio of floury and vitreous kernels (Figure 3, D and F), and all kernels were vitreous when the Mc1 mutant was pollinated by a homozygous γRNAi line (Figure 3E).Open in a separate windowFigure 3.—Segregation of vitreous and floury kernels from a progeny ear. (A) Mc1 mutant with Δγ16/Δγ16 genotype. (B) The cross of the Mc1 mutant and the nontransgenic hybrid of B × A lines, showing floury phenotype as in A. (C) γRNAi transgenic line with partial opacity only in the crown area. (D) The cross of the Mc1 mutant (Δγ16/Δγ16) and the heterologous γRNAi transgenic line (γRNAi/+), showing a 1:1 ratio of vitreous and floury kernels. A row in the ear is marked with arrowheads and crosses to indicate vitreous and floury gowns of kernels. (E) Cross of the Mc1 mutant (Δγ16/Δγ16) and the γRNAi homozygous transgenic line (γRNAi/γRNAi), showing all vitreous kernels. (F) Truncated kernel phenotype. (Top) Mc1, cross of Mc1 × BA, and γRNAi transgenic line. (Bottom) Three vitreous and floury kernels from D.

Conclusions:

RNAi can be used to rescue mutations that are dominant negative with a single cross, providing a useful tool in genetic analysis, plant breeding, and potentially in gene therapy in general.     

Molecular Basis for Enzymatic Sulfite Oxidation: HOW THREE CONSERVED ACTIVE SITE RESIDUES SHAPE ENZYME ACTIVITY*S?

Sulfite dehydrogenases (SDHs) catalyze the oxidation and detoxification of sulfite to sulfate, a reaction critical to all forms of life. Sulfite-oxidizing enzymes contain three conserved active site amino acids (Arg-55, His-57, and Tyr-236) that are crucial for catalytic competency. Here we have studied the kinetic and structural effects of two novel and one previously reported substitution (R55M, H57A, Y236F) in these residues on SDH catalysis. Both Arg-55 and His-57 were found to have key roles in substrate binding. An R55M substitution increased K_{m(sulfite)(app)} by 2–3 orders of magnitude, whereas His-57 was required for maintaining a high substrate affinity at low pH when the imidazole ring is fully protonated. This effect may be mediated by interactions of His-57 with Arg-55 that stabilize the position of the Arg-55 side chain or, alternatively, may reflect changes in the protonation state of sulfite. Unlike what is seen for SDH^WT and SDH^Y236F, the catalytic turnover rates of SDH^R55M and SDH^H57A are relatively insensitive to pH (∼60 and 200 s^–1, respectively). On the structural level, striking kinetic effects appeared to correlate with disorder (in SDH^H57A and SDH^Y236F) or absence of Arg-55 (SDH^R55M), suggesting that Arg-55 and the hydrogen bonding interactions it engages in are crucial for substrate binding and catalysis. The structure of SDH^R55M has sulfate bound at the active site, a fact that coincides with a significant increase in the inhibitory effect of sulfate in SDH^R55M. Thus, Arg-55 also appears to be involved in enabling discrimination between the substrate and product in SDH.Sulfite-oxidizing enzymes protect cells against potentially fatal damage to DNA and proteins caused by exposure to sulfite, and consequently they are found in all forms of life (1). In bacteria, sulfite oxidation is often linked to energy-generating processes during chemolithotrophic growth on reduced sulfur compounds (2, 3), whereas both plant and vertebrate sulfite oxidases have been shown to detoxify sulfite arising from the degradation of methionine and cysteine and exposure to sulfur dioxide (4, 5).All known sulfite-oxidizing enzymes belong to the same family of mononuclear molybdenum enzymes. Their active sites contain one molybdopterin unit per molybdenum atom, and these enzymes may also contain heme groups as accessory redox centers (6–9). Examples of different types of sulfite-oxidizing molybdoenzymes are the homodimeric plant sulfite oxidase, which does not contain a heme group and uses oxygen as its preferred electron acceptor (9), the homodimeric chicken and human liver sulfite oxidases (CSO³ and HSO, respectively) (10), which are also able to use oxygen as an electron acceptor, and the bacterial sulfite dehydrogenase (SDH) isolated from the soil bacterium Starkeya novella (11, 12), which cannot donate electrons directly to oxygen. Each monomer of CSO and HSO contains a heme b center in addition to the molybdenum center, and the redox centers are located within separate, flexibly linked domains of the same protein subunit. In contrast, the bacterial enzyme is a heterodimer where each subunit of the enzyme contains one redox center. The molybdopterin cofactor is located in the larger 40.2-kDa SorA subunit, and the c-type heme is located in the smaller, 8.8-kDa SorB subunit (12). The SDH quaternary structure thus differs clearly from that of the human and chicken sulfite oxidases.Crystal structures are available for plant sulfite oxidase, CSO, and the bacterial SDH (10, 11, 13–15) and have revealed molecular details of the sulfite-oxidizing enzymes. In the CSO structure, the mobile heme b domain occupies a position too removed from the molybdenum active site to mediate efficient electron transfer (10), and indeed the kinetics of this enzyme are known to be complicated by domain movements (16). In contrast, the bacterial SDH is a tight complex with strong electrostatic interactions between the subunits, and the close approach of the redox centers (Mo–Fe distance 16.6 Å) allows for rapid electron transfer (11, 17) (Fig. 1, A and B).Open in a separate windowFIGURE 1.Details of the crystal structure of wild type SDH and comparison with CSO. A, ribbon diagram of the SDH heterodimer with the SorA and SorB subunits colored blue and cyan, respectively, and the redox cofactors in space-filling mode with the molybdenum atom colored green and the iron atom colored violet. B, ribbon diagram of a single subunit of CSO with the molybdopterin binding domain in the same orientation as SorA in A. The cytochrome domain of CSO is clearly in a different position with respect to the molybdenum cofactor than is seen for the cytochrome subunit of SDH. C, SDH molybdopterin cofactor demonstrating the geometry of the molybdenum ligands. The thiol ligands donated by the organic component of molybdopterin and the Cys-104 side chain, and the reactive oxygen ligand (O_eq) sit in the equatorial plane with the axial oxygen (O_ax) ligand at the apex of a square pyramid. Atoms are colored as follows: molybdenum (green), sulfur (orange), phosphorous (magenta), oxygen (red), nitrogen (blue), and carbon (yellow in the cofactor and white in the protein). D, hydrogen bonding network around the substrate binding site. The molybdopterin and heme cofactors are shown together with active site residues Cys-104, Arg-55, His-57, Tyr-236, and Gln-33. Figs. 1 and ​and44 were prepared using Pymol (37).Despite the overall structural differences of these proteins, the coordination geometries of the molybdenum active sites of these sulfite-oxidizing enzymes are nearly identical. The oxidized molybdenum center has a square pyramidal conformation, with three sulfur and two oxo ligands (18). Within this molybdenum center, the equatorial oxo ligand is proposed to be catalytically active, whereas the axial oxo ligand is not thought to participate directly in the reaction (Fig. 1C). During catalysis, the equatorial oxo ligand is transformed into a hydroxy/water ligand as a result of the reduction of the molybdenum center (Fig. 2), and it is in this form that it is generally observed in the CSO and SDH crystal structures.Open in a separate windowFIGURE 2.Proposed reaction mechanism for S. novella sulfite dehydrogenase. The reaction is shown in terms of the redox states of the molybdenum and heme centers present in the enzyme. Shown in boldface type and boxed are the stable redox states of the S. novella SDH. Cyt. c, a mitochondrial type cytochrome c₅₅₀ (e.g. horse heart or S. novella cytochrome c₅₅₀) that can act as the external electron acceptor.SDH, CSO, and HSO show similarly high affinities for their substrate, sulfite, and several highly conserved residues surround the substrate-binding and molybdenum active site, namely Tyr-236 (all residues given in SDH numbering (11)), Arg-55, and His-57 (Fig. 1D). Both Arg-55 and Tyr-236 form hydrogen bonds to the catalytically active equatorial Mo-oxo group, whereas His-57 is positioned close to both Arg-55 and Tyr-236 (10, 11) (Fig. 1D). In addition, the crystal structure of the bacterial SDH shows that Arg-55 interacts directly with the second SDH redox center by hydrogen bonding to heme propionate-6 (Fig. 1D) (11).As a result of the similarities in catalytic parameters and the structure of the active site, the bacterial SDH is a very good system for studies of enzymatic sulfite oxidation and especially the molecular basis for catalysis. Since this enzyme does not rely on domain movement for catalysis, it has a less complicated reaction mechanism than the vertebrate enzymes, which facilitates the interpretation of kinetic data, and it can be readily crystallized with both redox centers present in an electron transfer competent conformation. We have previously reported data on the structure, kinetics, EPR, and redox properties of a Y236F-substituted SDH (13). In addition to reduced turnover and substrate affinity, this substitution influences the reactivity of the SDH toward oxygen, turning SDH^Y236F essentially into an (albeit weak) sulfite oxidase. In order to further understand the roles of the conserved amino acids surrounding the molybdenum active site of sulfite-oxidizing enzymes, we have created two novel amino acid substitutions in the Arg-55 and His-57 residues present at the active site and have investigated their effect on catalytic and spectroscopic parameters of the bacterial SDH. We have also solved the crystal structures of the substituted enzymes, which have provided new insights into the conformation and plasticity of the active site of sulfite-oxidizing enzymes and how the conserved active site residues contribute to sulfite oxidation.     

Open and Closed Conformations of the Isolated Transmembrane Domain of Death Receptor 5 Support a New Model of Activation

It has long been presumed that activation of the apoptosis-initiating Death Receptor 5, as well as other structurally homologous members of the TNF-receptor superfamily, relies on ligand-stabilized trimerization of noninteracting receptor monomers. We and others have proposed an alternate model in which the TNF-receptor dimer—sitting at the vertices of a large supramolecular receptor network of ligand-bound receptor trimers—undergoes a closed-to-open transition, propagated through a scissorslike conformational change in a tightly bundled transmembrane (TM) domain dimer. Here we have combined electron paramagnetic resonance spectroscopy and potential-of-mean force calculations on the isolated TM domain of the long isoform of DR5. The experiments and calculations both independently validate that the opening transition is intrinsic to the physical character of the TM domain dimer, with a significant energy barrier separating the open and closed states.Death receptor 5 (DR5) is a member of the tumor necrosis factor receptor (TNFR) superfamily that mediates apoptosis when bound by its cognate ligand, TNF-related apoptosis-inducing ligand (1). Upregulated in cancer cells, DR5 is among the most actively pursued anticancer targets (2). TNF-related apoptosis-inducing ligand binds to preassembled DR5 trimers at their extracellular domains, causing the formation of oligomeric ligand-receptor networks that are held together by receptor dimers (3). In the long-isoform of DR5, this dimer is crosslinked via ligand-induced disulfide bond formation between two transmembrane (TM) domain α-helices at Cys-209, and is further stabilized by a GxxxG motif one helix-turn downstream (3).Our recent study of the structurally homologous TNFR1 showed that receptor activation involves a conformational change that propagates from the extracellular domain to the cytosolic domain through a separation (or opening) of the TM domains of the dimer (4). We have therefore hypothesized that the activation of DR5, and indeed all structurally homologous TNF-receptors, involves a scissorslike opening of the TM domain dimer (Fig. 1).Open in a separate windowFigure 1Activation model of the DR5-L TM dimer. The sequence and positions of the disulfide bond and TOAC spin label (top), along with our previously published model (bottom, left) are shown. We propose an activation model (bottom, right) in which the transmembrane dimer pivots at its disulfide bond to reach an active open conformation.Using electron paramagnetic resonance (EPR) spectroscopy, a technique that has been used previously to study TM helix architecture and dynamics (5,6), and potential-of-mean force (PMF) calculations (7,8), this study addresses the question of whether the isolated disulfide-linked DR5-L TM domain dimer occupies distinct open and closed states (Fig. 1), and how its dynamic behavior contributes to the free-energy landscape of the opening transition of the full-length receptor.The DR5-L TM domain was synthesized with TOAC, an amino acid with a nitroxide spin label rigidly fixed to the α-carbon (9), incorporated at position 32 (Fig. 1), with some minor modification to facilitate EPR measurements. Previous work confirmed that this peptide forms disulfide-linked dimers (e.g., via comparison to 2-ME treated sample) and a negligible population of higher-order oligomers (further supported by model fitting of the EPR data below). For peptide work, residues were renumbered such that Thr-204 corresponds to Thr-1, and so on. The cytosolic Cys-29 (which we previously showed does not participate in a disulfide bond in cells) was replaced with serine to prevent the formation of antiparallel disulfide-linked dimers, and Trp-34 was replaced with tyrosine to prevent intrinsic fluorescence in fluorescence studies (not published). Continuous-wave (CW) dipolar EPR (sensitive only to spin-spin distances <25 Å) was used to measure TOAC-TOAC distances within the TM dimers and revealed an ordered Gaussian distribution centered at 16 Å (full width half-maximum (FWHM) = 4 Å), corresponding to a closed state (Fig. 2 A). Double electron-electron resonance (DEER) (sensitive to spin-spin distances from 15 to 60 Å) also detected a short distance consistent with the dipolar EPR data, along with a longer, disordered component (32.9 Å, FWHM = 28 Å) (Fig. 2 B). Together, these measurements indicate the presence of a compact, ordered closed state and a broader, disordered open state. EPR on oriented membranes also indicated two structural states. Global fitting revealed two populations of spin-label tilt angles (orientation of the nitroxide principal axis relative to the membrane normal): a narrow conformation (24°, FWHM = 20°), and a disordered conformation (50°, FWHM = 48°) (Fig. 2 C). This bimodal orientational distribution (Fig. 2 C) is remarkably consistent with the bimodal distance distribution (Fig. 2 B).Open in a separate windowFigure 2EPR spectra (left) of 32-TOAC-DR5 in lipid, and resulting structural distributions (right). (A) CW dipolar EPR spectra (left) of dimer (1 mM diamide) and monomer (1 mM 2-mercaptoethanol). Best-fit spin-spin distance distribution was a single Gaussian centered at 16 ± 2 Å (right). (B) The DEER waveform (left) of 32-TOAC-DR5 dimer was best fit (right) to a two-Gaussian distribution. The short distance was constrained to agree with the CW data, because DEER has poor sensitivity for distances <20 Å. The long-distance distribution is centered at 32.9 Å and is much broader. (C) CW EPR spectra (left) of 32-TOAC-DR5, with the membrane-normal oriented parallel (red) and perpendicular (blue) to the field. Simultaneous (global) fitting of these spectra reveals narrow and broad components (right). (In panels B and C, the overall distribution is plotted as black, while the closed and open components are plotted as green and magenta, respectively.)We subsequently conducted a PMF calculation (10) using the DR5-L TM dimer starting configuration developed by our group previously (3), embedded in a DMPC bilayer, with the Leu-32/Leu-32 C_α distance as the reaction coordinate. Three calculations were run from independent starting configurations, each using 50 windows spaced in 0.5° increments, and run for 20 ns at each window (totaling 3 μs). Each of the calculations yielded a similar result, and the averaged free energy curve (Fig. 3 A) agrees remarkably well with our EPR measurements: a narrow distribution at the closed conformation (∼16 Å, Fig. 3 B) separated by an ∼3 kcal/mol energy barrier from a broad distribution of accessible open conformations at ∼27 Å, (Fig. 3 C). Each of the three individual PMF plots can be found in Fig. S1 in the Supporting Material.Open in a separate windowFigure 3(A) PMF calculation of the DR5 TM domain dimer along the Leu-32/Leu-32 distance reaction coordinate. The PMF calculation reveals a narrow closed state and a broader open state separated by a free energy barrier. Representative snapshots of the (B) closed state and (C) open state.In the closed state, the helices are tightly packed at the GxxxG interfacial motif and all the way down the juxtaposed helix faces at residues Ala-18, Leu-22, Ala-25, and Val-26. The tight packing is aided by kinking and twisting of the two helices around their common axis, increasing the interacting surface area. In the open conformations, the Ala-18, Leu-22, Ala-25, and Val-26 pairs are dissociated and, interestingly, the GxxxG motif at Gly-10 and Gly-14 remains tightly packed. The open state energy well is only slightly less favorable than the closed state (by ∼2 kcal/mol), and its free energy profile is relatively broad and flat. The increased crossing angle in the open state is facilitated by straightening of the helix kink and is not accommodated by a change in bilayer thickness (see Fig. S3, A and B).The observed change in helix-helix distance (11 Å between the two minima in the PMF) is extremely close to that observed previously in live-cell FRET studies of a constitutively active form of TNFR1 (∼8 Å change between states using large fluorescence probes at the cytosolic domains) (4). The change observed in the EPR data (17 Å) may be an overestimate because the measurement is made between TOAC spin labels that likely protrude from the two helices, depending on rotational orientation. These results collectively show that activation of these receptors requires a small, but clearly significant conformational opening of the TM domains. One important note is that our EPR experiments recapitulate the equilibrium distribution of the two states despite there being no driving force to traverse the barrier between them (∼3 kcal/mol in the closed-to-open transition and ∼1 kcal/mol in the open-to-closed transition, Fig. 3). We do not interpret the results to mean that the dimer necessarily traverses these barriers at 4°C. Rather, there likely exist multiple reaction paths for dimerization of the abstracted TM domains. Finally, in the context of the full-length receptor, how the ligand induces a conformational change capable of overcoming the closed-to-open barrier remains an important question.Whether the observed structural transition in the TM domain dimer of the long-isoform of DR5 is a ubiquitous conformational switch that acts over the entire TNFR superfamily remains unknown. Vilar et al. (11) first proposed a similar scissors-model for activation of p75 neurotrophin receptor, which has a cysteine at the center of its TM helix. The short isoform of DR5 lacks a TM domain cysteine, but does form noncovalent dimers in cells, with likely TM domain dimer contacts (3). Among the other closely related and structurally homologous members of the TNFR superfamily, TNFR1 contains a cysteine at the center of the TM domain, but lacks any discernible small residue motifs (e.g., GxxxG). TNFR2 lacks a TM cysteine on the extracellular side, but does have a GxxxG motif positioned similarly to that of DR5. On the other hand, Death Receptor 4, whose functional distinction from DR5 has remained somewhat elusive, lacks both a cysteine and any recognizable small-residue hydrophobic motif.In summary, we have extended recent findings that point to the TM domain of DR5 as an essential structural component in the conformational change associated with activation. Our findings that the DR5-L TM domain occupies distinct open and closed states, separated by a substantial energy barrier, points the way to further studies across the TNF-receptor superfamily.     

Linking soil bacterial biodiversity and soil carbon stability

Native soil carbon (C) can be lost in response to fresh C inputs, a phenomenon observed for decades yet still not understood. Using dual-stable isotope probing, we show that changes in the diversity and composition of two functional bacterial groups occur with this ‘priming'' effect. A single-substrate pulse suppressed native soil C loss and reduced bacterial diversity, whereas repeated substrate pulses stimulated native soil C loss and increased diversity. Increased diversity after repeated C amendments contrasts with resource competition theory, and may be explained by increased predation as evidenced by a decrease in bacterial 16S rRNA gene copies. Our results suggest that biodiversity and composition of the soil microbial community change in concert with its functioning, with consequences for native soil C stability.Substrate inputs can stimulate decomposition of native soil organic carbon (SOC; Kuzyakov et al., 2000), a phenomenon known as the ‘priming effect'' (Kuzyakov, 2010), and is considered large enough to influence ecosystem C balance (Wieder et al., 2013). Two functionally distinct groups of microorganisms are postulated to mediate priming: one that grows rapidly utilizing labile C, and one that grows slowly, breaking down recalcitrant SOC (Fontaine et al., 2003; Blagodatskaya et al., 2007). However, distinguishing these groups is technically challenging. Here, we used dual-stable isotope probing with ¹³C-glucose and ¹⁸O-water to identify bacteria in these two groups growing in response to single and repeated pulses of glucose. Organisms that utilize labile C for growth assimilate both ¹³C-glucose and ¹⁸O-water into their DNA, whereas organisms that grow using SOC incorporate only ¹⁸O-water. Differential isotope incorporation leads to a range of DNA densities separable through isopycnic centrifugation, which can then be characterized by sequencing (Radajewski et al., 2000).We sequenced fragments of bacterial 16S rRNA genes following single and repeated glucose pulses. We hypothesized that the single pulse of labile C would stimulate growth of opportunistic organisms, thus immobilizing nutrients and suppressing growth and diversity of the SOC-utilizing community, decreasing SOC decomposition (negative priming), a response analogous to that observed in plant communities in response to chronic N additions (Tilman, 1987; Clark and Tilman, 2008). We hypothesized that multiple glucose additions would stimulate growth of a more diverse bacterial community, including more native SOC-utilizing organisms that possess enzymes to decompose recalcitrant compounds, causing positive priming (Fontaine et al., 2003; Kuzyakov, 2010).Soil from a ponderosa pine ecosystem was amended weekly for 7 weeks with 500 μg C-glucose per gram soil (2.65 atom % ¹³C) in 100 μl deionized water or with 100 μl deionized water (n=5). Measurements of δ¹³C–CO₂ and [CO₂] enabled the partitioning of CO₂ into that derived from added glucose or from native SOC (C_SOC):where C_total is CO₂–C from glucose-amended samples, δ_total is the δ¹³C–CO₂ from glucose-amended samples, δ_glucose is the δ¹³C of the added glucose and δ_SOC is the δ¹³C–CO₂ evolved from the non-amended samples. Priming was calculated as the difference between SOC oxidation of the amended and non-amended samples. With this approach, any evolved CO₂ carrying the ¹³C signature of the added glucose is considered respiration of glucose, including ¹³C-labeled biomass and metabolites derived from prior glucose additions. Thus, this approach quantifies priming as the oxidation of SOC present at the beginning of the experiment, consistent with many other studies of priming (Cheng et al., 2003; De Graaff et al., 2010).In a parallel incubation for dual-stable isotope probing, the repeated-pulse samples received unlabeled glucose (500 μg C-glucose per gram soil) for 6 weeks while the non-amended and single-pulse samples received sterile deionized water. In week 7, samples received one of four isotope treatments (n=3): 97 atom % H₂ ¹⁸O (non-amended soil), 99 atom % ¹³C-glucose and 97 atom % H₂ ¹⁸O (single- and repeated-pulse soil), ¹²C-glucose and 97 atom % H₂ ¹⁸O (repeated-pulse soil) or ¹²C-glucose and H₂ ¹⁶O (repeated-pulse soil). After incubating for 7 days, soil was frozen at −40 °C. DNA was extracted, separated through isopycnic centrifugation, and two density ranges were sequenced for the bacterial 16S rRNA gene (Supplementary Figure 1): 1.731–1.746 g ml⁻¹ (hereafter called the SOC-utilizing community) and 1.759–1.774 g ml⁻¹ (hereafter called the glucose-utilizing community).Amplicons of the V3–V6 16S rRNA region were bar coded with broad-coverage fusion PCR primers and pooled before sequencing on a Genome Sequencer FLX instrument. These sequence data have been submitted to the GenBank database under accession number SRP043371. Data were checked for chimeras (Edgar et al., 2011), demultiplexed and quality checked (Caporaso et al., 2010). Taxonomy was assigned to genus at the ⩾80% bootstrap confidence level (Cole et al., 2009).We used the Shannon''s diversity index (H′), commonly used in microbial systems (Fierer and Jackson, 2006), to assess changes in microbial diversity. Analysis of variance was used to compare the amount of DNA within densities between isotope treatments (Supplementary Figure 2) and to test the effects of the treatments on the Shannon''s diversity (Figure 2) and Pielou''s evenness (Supplementary Figure 3) of the active bacterial communities, with post hoc Student''s t-tests, α=0.05. PRIMER 6 and PERMANOVA were used to create the nonmetric multidimensional scaling ordination and to compare bacterial communities between glucose treatments and the two sequenced density ranges.The single pulse of glucose suppressed SOC oxidation, whereas repeated pulses increased SOC oxidation (Figure 1). Few experiments to date have examined priming in response to repeated substrate amendments (Hamer and Marschner, 2005; Qiao et al., 2014), even though in nature soil receives repeated substrate pulses from litterfall and rhizodeposition. Our results demonstrate the dynamic response of SOC decomposition to repeated labile C inputs.Open in a separate windowFigure 1Weekly priming rates calculated as the difference in SOC respired between glucose-amended and non-amended soil (n=5).Dual-stable isotope probing was able to separate the growing bacteria into two groups with distinct DNA densities (P<0.001, PERMANOVA; Figure 3a), indicating differential uptake of ¹³C-glucose and ¹⁸O-water. In response to the initial glucose addition, the diversity of the growing glucose- and SOC-utilizing bacterial communities declined compared with the non-amended community (P<0.001, t-tests; Figure 2), driven by a strong decrease in evenness (Supplementary Figure 3). In the SOC-utilizing community, where DNA was labeled with ¹⁸O only, the relative abundance of Bacillus increased 4.9-fold compared with the non-amended control to constitute 31.6% of the community (Figure 3b). Bacillus survives well under low-nutrient conditions (Panikov, 1995), and is able to synthesize a suite of extracellular enzymes capable of degrading complex substrates (Priest, 1977), traits that are conducive for using SOC for growth. In the glucose-utilizing community, where DNA was labeled with both ¹³C and ¹⁸O, Arthrobacter increased 67.7-fold relative to the non-amended control to constitute 75.5% of the growing bacteria (Figure 3b). In culture experiments, Arthrobacter can rapidly take up and store glucose for later use (Panikov, 1995) and here we find it dominating the high-density DNA fractions, signifying that it is using the labeled glucose to grow. The increased biomass of Arthrobacter may have resulted in greater resource competition, thus reducing the diversity of the growing community, as is frequently found in plant communities (Bakelaar and Odum, 1978; Clark and Tilman, 2008).Open in a separate windowFigure 2Shannon''s diversity index (H′) of the non-amended, single-pulse, and repeated-pulse treatments (n=3) in the SOC- (mid-density) and glucose-utilizing (high-density) communities. Treatments with the same letter are not significantly different from each other (Student''s t, α=0.05).Open in a separate windowFigure 3(a) Nonmetric multidimensional scaling ordination showing differences in growing bacterial communities at the genus taxonomic level in the SOC-utilizing (mid-density; open symbols) and glucose-utilizing (high-density; closed symbols) groups of non-amended (Δ), single-pulse (○) and repeated-pulse (□) treatments (n=3). (b) Pie charts of genera in the SOC- and glucose-utilizing communities of the single- and repeated-pulse treatments (n=3). Genera with relative abundances >5% are listed in the figure legend.After repeated glucose amendments, the diversity of the growing community recovered to non-amendment levels (Figure 2) without strongly dominant organisms (Figure 3b and Supplementary Figure 3). The higher diversity found after repeated glucose pulses may be explained by trophic interactions where predators graze on prey populations that have been enlarged by resource addition, suppressing competition between prey species and causing secondary mobilization of nutrients (Clarholm, 1985). The decrease in total bacterial 16S rRNA gene copies in the repeated-pulse—compared with the single-pulse—treatment (Supplementary Figure 4) supports predation as a potential mechanism explaining the observed diversity increase after repeated glucose pulses.The recovery of diversity after repeated glucose pulses contrasts with resource competition theory (Tilman, 1987). When chronic additions of a limiting resource are applied, species diversity and evenness typically decrease (Bakelaar and Odum, 1978; Clark and Tilman, 2008) because competitive organisms become dominant. We observed this after the single glucose pulse, but not after repeated pulses. This diversity response may be the result of community shifts facilitated by short bacterial life cycles and the tens to hundreds of generations expected during the 7-week incubation (Behera and Wagner, 1974). In contrast, systems on which most ecological theory is based (for example, plants) might achieve perhaps 20 generations in a multi-decadal field experiment (Bakelaar and Odum, 1978; Clark and Tilman, 2008). With more generations, more community dynamics can occur, including increased resource cascades in which extracellular enzymes, metabolites or lysed cells of one functional group increase substrates for another (Blagodatskaya and Kuzyakov, 2008). Our results highlight the opportunity to test ecological theories in microbial ecosystems (Prosser et al., 2007), particularly as the short life cycles of microbes makes them well suited for pursuing ecological questions in an evolutionary framework (Jessup et al., 2004).The priming effect is ubiquitous, yet its drivers remain elusive. Our results suggest that changes in the diversity and composition of the growing bacterial community contribute to priming, and thus that ecosystem properties such as soil C storage may be sensitive to soil microbial biodiversity.     

Nanoscale Distribution of Ryanodine Receptors and Caveolin-3 in Mouse Ventricular Myocytes: Dilation of T-Tubules near Junctions

We conducted super-resolution light microscopy (LM) imaging of the distribution of ryanodine receptors (RyRs) and caveolin-3 (CAV3) in mouse ventricular myocytes. Quantitative analysis of data at the surface sarcolemma showed that 4.8% of RyR labeling colocalized with CAV3 whereas 3.5% of CAV3 was in areas with RyR labeling. These values increased to 9.2 and 9.0%, respectively, in the interior of myocytes where CAV3 was widely expressed in the t-system but reduced in regions associated with junctional couplings. Electron microscopic (EM) tomography independently showed only few couplings with caveolae and little evidence for caveolar shapes on the t-system. Unexpectedly, both super-resolution LM and three-dimensional EM data (including serial block-face scanning EM) revealed significant increases in local t-system diameters in many regions associated with junctions. We suggest that this regional specialization helps reduce ionic accumulation and depletion in t-system lumen during excitation-contraction coupling to ensure effective local Ca²⁺ release. Our data demonstrate that super-resolution LM and volume EM techniques complementarily enhance information on subcellular structure at the nanoscale.The contraction of cardiac ventricular myocytes depends on the rapid cell-wide transient increase in intracellular [Ca²⁺] upon depolarization of the cell-membrane potential. The cardiac ryanodine receptor (RyR) (1), which is the intracellular Ca²⁺ release channel in the sarcoplasmic reticulum (SR), plays a central role in shaping Ca²⁺ transients. RyRs form clusters of various sizes (2,3) with the majority located within junctions between the SR and the surface membrane and its cytoplasmic extension, the transverse tubular (t-) system. It has been suggested that some RyR clusters are associated with caveolae, a specialized signaling microdomain of the surface membrane. Previous studies were complicated by the limited resolution of optical imaging methods of ∼250 nm, much larger than the nanometer scale of RyRs and caveolae. Accordingly, these studies report varying colocalization between RyRs and caveolin-3 (CAV3), a caveolar marker also expressed in the t-system (4,5).In this work, we investigated the relative distribution of CAV3 and RyRs in mouse ventricular myocytes both in the cytosol and near the cell surface with super-resolution fluorescence microscopy that achieves a resolution approaching 30 nm. Our data revealed unexpected local t-system swellings near junctional couplings, which was supported by two different three-dimensional electron microscopy (EM) modalities with <10-nm resolution: EM tomography and serial block-face scanning EM (SBFSEM).Super-resolution images of CAV3 and RyR labeling at the surface sarcolemma of mouse myocytes showed little overlap, suggesting that few RyRs were in couplings with caveolae (Fig. 1 A, for detailed methods, see the Supporting Material). Only ∼4.8% of RyR labeling was associated with CAV3 positive areas and ∼3.5% of CAV3 associated with RyR positive areas (n = 6 cells from three animals, Fig. 1 B, see also Table S1 in the Supporting Material), broadly consistent with previous data in rats (6). To support this finding, EM tomography was applied to mouse ventricular tissue that included a part of the surface sarcolemma, to our knowledge for the first time. Segmentation of peripheral couplings (containing RyR foot structures) and surface caveolae (∼60 nm in diameter and often interconnected) confirmed that the great majority of peripheral couplings were in regions devoid of caveolae (Fig. 1 C). A few junctional couplings containing feet were between caveolae and subsarcolemmal SR (Fig. 1 D, see also Fig. S1 and Movie S1 in the Supporting Material). We conducted a similar analysis in the cytosol where CAV3 expression occurs in the t-system (5) and RyRs are abundant in dyadic junctions between the t-system and SR terminal cisterns.Open in a separate windowFigure 1Colocalization of CAV3 and RyRs at the surface sarcolemma. (A) Super-resolution micrograph of the distribution of CAV3 (green) and RyRs (red) at the surface of a mouse cardiac myocyte. (B) Analysis of the association of CAV3 with RyRs. The fraction of RyR labeling within CAV3 positive areas was ∼4.8% (front data) whereas ∼3.5% of CAV3 was found in RyR-positive membrane areas. (C) Segmented EM tomogram containing a patch of surface sarcolemma (light blue) and associated caveolae (green) as well as peripheral couplings (red). (D) Detailed view of a region with abundant caveolae. (Arrows) Couplings with caveolae.As shown in Fig. 2 A, the spatial distribution of CAV3 and RyR clusters in super-resolution micrographs taken several microns below the surface sarcolemma is consistent with this view. The association of the two labels is slightly increased (as compared to the surface), according to distance analysis with 9% of CAV3 and 9.2% of RyR labeling associating with each other (Fig. 2 B, n = 6 cells from three animals). The similarity of manually traced t-system in EM tomograms (Fig. 2 C) and super-resolved CAV3 labeling suggested that CAV3 is widely distributed in the t-system except for regions where dyadic membrane junctions occur as CAV3 labeling was much weaker in regions with strong RyR labeling. It was notable that the t-system diameter appeared to increase at regions of strong RyR labeling (Fig. 2 D), broadly consistent with the behavior seen in tomograms (Fig. 2 C). This was confirmed by a quantitative analysis of t-tubule diameters in dyadic versus extradyadic regions on the basis of CAV3 and RyR labeling, with full-width at quarter-maximum mean diameters increasing from ∼150 nm distal to dyads, to ∼190 nm (using CAV3 signal only) or ∼280 nm (using CAV3 and RyR signal) near dyads (Fig. 2, G and H, see also Methods in the Supporting Material). The combined RyR and CAV3 signals seemed to be a better representation of the entire t-system lumen near junctions (see Fig. S2).Open in a separate windowFigure 2Distribution of CAV3 and RyRs in the cell interior. (A) Super-resolution micrograph of CAV3 (green) and RyR (red) distribution at t-system. (Arrow) Direction of longitudinal cell axis. (B) Distance analysis of the CAV3 and RyR association (N = 6 cells per group). (C) Segmented EM tomogram of a similar region with three-dimensional mesh models of t-system membrane (green) and dyadic couplings (red). (D) This image illustrates the tracing (white path) of t-tubules. The label distribution was extracted and linearized along the path (E) to calculate a mask that shows the full width at quarter-maximum diameter along tubules, CAV3 (green) and RyR (red) (F). (G) Histograms of local diameters extracted from traced t-tubules. (H) Mean diameters in junctional (dyad) and nonjunctional (ex-dyad) regions. See main text and the Supporting Material for details. ^**p < 0.01.Taken together, super-resolution imaging and EM tomography strongly support the presence of local t-system dilations in regions where the t-system opposes SR at dyads and such t-system bulges are connected by narrower tubule segments. Further support was provided by SBFSEM, another volume EM technique to study larger cell volumes (albeit at the expense of a slightly lower resolution). SBFSEM clearly showed local t-system dilations were regularly involved in the architecture of most (but not all) dyads (Fig. 3, see also Fig. S3 and Movie S2), as also observed in full three-dimensional super-resolution images (see Fig. S3 C).Open in a separate windowFigure 3Segmented SBFSEM data showing t-system dilations near dyadic junctions. (A) The overview shows t-system membranes (green) and jSR (red) in a mouse myocyte. (B, enlarged inset from panel A) Thin connecting tubules (arrows) and regular swellings in junctional regions at z-lines.Our data identify local dilations of the t-system associated with dyads in mouse cardiac myocytes. Frequent tubule distensions had been observed especially at the intersections of transverse and axial tubules (7), and constrictions were seen in rabbit myocytes although their relationship to dyads was unknown (8). The increased local t-system lumen near junctions may help reduce the predicted ionic accumulation/depletion during excitation-contraction coupling (9). Alternatively, it might simply be secondary to increasing local membrane area and allow the formation of large area junctions that harbor many RyRs. In connection with this point, it would be interesting to investigate the t-system near junctions in species that have larger average tubule diameters (e.g., human and rabbit (10)), or if this architecture changes in mouse heart failure models where t-tubule diameters are often increased.Most peripheral couplings were in regions void of surface caveolae, although a small number of RyR clusters were in junctional couplings between subsarcolemmal SR and caveolae as shown both by the low colocalization between CAV3 and RyRs as well as direct evidence from EM tomography. Similarly, a relatively small fraction of CAV3 colocalized with RyR clusters in the t-system although CAV3 was expressed widely in the t-system. A structural role of CAV3 in the t-system is still unclear—t-tubules in tomogram data did not reveal distinct caveolae shapes on the t-system membrane (see Fig. S4), although this might change in pathology (11). In any case, the t-system exhibits high curvature orthogonal to the tubule axis, which may be supported by CAV3 oligomerization. In addition, the presence of CAV3 in the t-system may be important for regulating other signaling systems (e.g., adrenergic signaling).Finally, our data demonstrate that complementary data from optical super-resolution and three-dimensional EM images assists data interpretation and reliability. We suggest that truly correlative optical and EM imaging approaches should provide further information and improve our knowledge of the basis of cardiac excitation-contraction coupling.