Edited by Norma M. Allewell Carboxysomes are compartments in bacterial cells that promote efficient carbon fixation by sequestering RubisCO and carbonic anhydrase within a protein shell that impedes CO 2 escape. The key to assembling this protein complex is CcmM, a multidomain protein whose C-terminal region is required for RubisCO recruitment. This CcmM region is built as a series of copies (generally 3-5) of a small domain, CcmM S , joined by unstructured linkers. CcmM S domains have weak, but significant, sequence identity to RubisCO's small subunit, RbcS, suggesting that CcmM binds RubisCO by displacing RbcS. We report here the 1.35-Å structure of the first Thermosynechococcus elongatus CcmM S domain, revealing that it adopts a compact, well-defined structure that resembles that of RbcS. CcmM S , however, lacked key RbcS RubisCO-binding determinants, most notably an extended N-terminal loop. Nevertheless, individual CcmM S domains are able to bind RubisCO in vitro with 1.16 M affinity. Two or four linked CcmM S domains did not exhibit dramatic increases in this affinity, implying that short, disordered linkers may frustrate successive CcmM S domains attempting to simultaneously bind a single RubisCO oligomer. Size-exclusion chromatography-coupled right-angled light scattering (SEC-RALS) and native MS experiments indicated that multiple CcmM S domains can bind a single RubisCO holoenzyme and, moreover, that RbcS is not released from these complexes. CcmM S bound equally tightly to a RubisCO variant in which the ␣/ domain of RbcS was deleted, suggesting that CcmM S binds RubisCO independently of its RbcS subunit. We propose that, instead, the electropositive CcmM S may bind to an extended electronegative pocket between RbcL dimers.Cyanobacteria are oxygenic photosynthetic bacteria that, like higher plants, fix carbon dioxide using the Calvin cycle with ribulose-bisphosphate carboxylase/oxygenase (RubisCO; 2 EC 4.1.1.39) catalyzing the key inorganic carbon fixation reaction (1). RubisCO catalyzes a chemically challenging reaction made more difficult by modern low ambient CO 2 and high O 2 concentrations, the latter acting as a competing substrate that results in an unwanted side product that requires energy to recycle (2). Cyanobacteria enhance the efficiency of this reaction by expending energy to concentrate intracellular inorganic carbon using a varied set of CO 2 and HCO 3 Ϫ pumps (3). Because CO 2 is lipophilic and readily escapes through cellular membranes, cyanobacteria accumulate only HCO 3 Ϫ in the cytosol and encapsulate RubisCO behind a secondary, (relatively) CO 2impermeable protein barrier to form a carboxysome (5-7). Carbonic anhydrase (EC 4.2.1.1), the enzyme that interconverts CO 2 and HCO 3 Ϫ , is also encapsulated so that HCO 3 Ϫ pumped into the cell only evolves into CO 2 once within the carboxysome shell (8). Carboxysomes are polyphyletic with two deeply divergent lineages, termed ␣and -carboxysomes. ␣-Carboxysomes, which contain form 1A RubisCO, likely originated in chemoautotrophic ␣-prot...
Bacterial cell division is an essential and highly coordinated process. It requires the polymerization of the tubulin homologue FtsZ to form a dynamic ring (Z-ring) at midcell. Z-ring formation relies on a group of FtsZ-associated proteins (Zap) for stability throughout the process of division. In Escherichia coli, there are currently five Zap proteins (ZapA through ZapE), of which four (ZapA, ZapB, ZapC, and ZapD) are small soluble proteins that act to bind and bundle FtsZ filaments. In particular, ZapD forms a functional dimer and interacts with the C-terminal tail of FtsZ, but little is known about its structure and mechanism of action. Here, we present the crystal structure of Escherichia coli ZapD and show it forms a symmetrical dimer with centrally located ␣-helices flanked by -sheet domains. Based on the structure of ZapD and its chemical cross-linking to FtsZ, we targeted nine charged ZapD residues for modification by site-directed mutagenesis. Using in vitro FtsZ sedimentation assays, we show that residues R56, R221, and R225 are important for bundling FtsZ filaments, while transmission electron microscopy revealed that altering these residues results in different FtsZ bundle morphology compared to those of filaments bundled with wild-type ZapD. ZapD residue R116 also showed altered FtsZ bundle morphology but levels of FtsZ bundling similar to that of wild-type ZapD. Together, these results reveal that ZapD residues R116, R221, and R225 likely participate in forming a positively charged binding pocket that is critical for bundling FtsZ filaments. IMPORTANCEZ-ring assembly underpins the formation of the essential cell division complex known as the divisome and is required for recruitment of downstream cell division proteins. ZapD is one of several proteins in E. coli that associates with the Z-ring to promote FtsZ bundling and aids in the overall fitness of the division process. In the present study, we describe the dimeric structure of E. coli ZapD and identify residues that are critical for FtsZ bundling. Together, these results advance our understanding about the formation and dynamics of the Z-ring prior to bacterial cell division. Bacterial cell division is an essential and complex process that requires the coordinated assembly of a multiprotein molecular machine termed the divisome. The divisome is responsible for constriction of the inner and outer membranes, synthesis of septal peptidoglycan, and subsequent septum formation. In Escherichia coli, divisome proteins are recruited in a hierarchical manner and can be divided into three main groups based on their order of assembly: (i) the proto-ring, (ii) early divisome proteins, and (iii) late divisome proteins (1, 2). The successful assembly of the divisome depends on the initial formation of the Z-ring, which is comprised of the 40-kDa bacterial tubulin homologue FtsZ. FtsZ assembles into filaments in a GTP-dependent manner and a headto-tail fashion (3-6). The filaments are then tethered to the membrane, forming the Z-ring. They act as the...
Magnetite nanoparticles (Fe3O4), average particle size of 12.9 nm, were synthesized de novo from ferrous and ferric iron salt solutions (total iron salt concentration of 3.8 mM) using steady-state headspace NH3(g), 3.3% v/v, at room temperature and pressure, without mechanical agitation, resulting in >99.9% yield. Nanoparticles size distributions were based on enumeration of TEM images and chemical compositions analyzed by: XRD, EDXRF, and FT-IR; super-paramagnetic properties were analyzed by magnetization saturation (74 emu/g). Studies included varying headspace [NH3(g)] (1.6, 3.3, 8.4% v/v), and total iron concentrations (1.0 mM, 3.8 mM, 10.0 mM, and >>10 mM). An application of the unmodified synthesized magnetite nanoparticles included analyses of tetracycline’s (50, 100, 200, 300, and 400 ppb) in aqueous, which was compared to the same tetracycline concentrations prepared in aqueous synthesis suspension with >97% extraction, analyzed with LC-MS/MS.
Background Bacterial enumeration data are typically log transformed to realize a more normal distribution and stabilize the variance. Unfortunately, statistical results from log transformed data are often misinterpreted as data within the arithmetic domain. Objective To explore the implication of slope and intercept from an unweighted linear regression and compare it to the results of the regression of log transformed data. Method Mathematical formulae inferencing explained using real dataset. Results For y=Ax+B+ε, where y is the recovery (CFU/g) and x is the target concentration (CFU/g) with error ε homogeneous across x. When B=0, slope A estimates percent recovery R. In the regression of log transformed data, logy=αlogx+β+εz (equivalent to equation y=Axα·ω), it is the intercept β=logyx=logA that estimates the percent recovery in logarithm when slope α=1, which means that R doesn’t vary over x. Error term ω is multiplicative to x, while εz or log(ω) is additive to log(x). Whether the data should be transformed or not is not a choice, but a decision based on the distribution of the data. Significant difference was not found between the five models (the linear regression of log transformed data, three generalized linear models and a nonlinear model) regarding their predicted percent recovery when applied to our data. An acceptable regression model should result in approximately the best normal distribution of residuals. Conclusions Statistical procedures making use of log transformed data should be studied separately and documented as such, not collectively reported and interpreted with results studied in arithmetic domain. Highlights The way to interpret statistical results developed from arithmetic domain does not apply to that of the log transformed data.
Edamame milk is a protein‐dense milk derived from green soybeans harvested before they mature. Being a legume of soy origin, it contains antinutritional factors for example, serine protease inhibitors, which hinder its in vitro digestibility. The objective of this study was to evaluate the effect of microwave processing techniques in improving the in vitro digestibility (IVPD %) of edamame milk protein by varying processing time and temperature. Conventional and microwave‐assisted processing was employed to investigate the effect on in vitro protein digestibility (IVPD %), using temperatures 70°Ϲ, 85°Ϲ, and 100°Ϲ for 5, 10, and 15 min, respectively. Fourier‐transform infrared (FTIR) data showed microwave and conventional treatments significantly modified the Amide I region of the edamame milk protein and the extent of modification varied with variation in the treatment temperature. In the FTIR analysis β‐sheet content was observed to change little with an increase in the temperature, suggesting similarity in the surface hydrophobicity of the protein leading to similar IVPD % values for all treatment temperatures. The experiment resulted in increased in vitro digestibility with increasing time and temperature during microwave processing conditions and conventional thermal conditions. It was also observed that the trypsin inhibitor activity decreased with an increase in processing time and temperature.
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