This work simulates the plowing process of a single asperity GaAs by diamond indenter using molecular dynamics simulations. The deformation mechanism of asperity GaAs is revealed by examining the topography evolution and stress state during the plowing. This work also investigates the origin of the influence of asperity size, indenter radius and plow depth on the deformation of the asperity GaAs. We observed the initiation and propagation of cracks up to the onset of fracture and the plastic activity near the indenter, obtaining more information usually not available from planar GaAs in normal velocity plowing compared to just plastic activity. The simulations demonstrated the direct evidence of cracking in GaAs induced by plowing at an atomic level and probed the origin and extension of cracking in asperity GaAs. This finding suggests that cracking appears to be a new deformation pattern of GaAs in plowing, together with dislocation-dominated plasticity modes dominating the plowing deformation process. This work offers new insights into understanding the deformation mechanism of an asperity GaAs. It aims to find scientific clues for understanding plastic removal performed in the presence of cracking. Gallium arsenide (GaAs) has gained significant attention as a semiconductor material due to its wider energy bandgap, high frequency, higher electron mobility and other characteristic advantages compared to Si ,2. ThereMany scholars have worked in different directions in the study of atomic and close-to-atomic-scale manufacturing, which also includes extensive experiments and simulations of AFM indentations and scratches ,10,11,12In GaAs nanoscratching experiments, evidence of dispersion dislocations, plastic deformation and cracks in the scratch zone is frequently reported . AlthougMD simulations are expected to play an essential role in elucidating these mechanisms. They overcome the limitations of the experimental scale. They enable the study of material deformation behavior occurring within a few picoseconds and at the nanoscale, making it possible to investigate the microscopic nature of material frictional deformation based on computational simulations. They allow for a better decoupling of the factors influencing the deformation behavior under realistic conditions; thus, allowing for a more intrinsic mechanical response and an analysis of the material frictional deformation. They play an essential role serving as a reliable tool for analyzing the internal mechanisms of experimental phenomena at the atomic scale. MD plow simulations can be used as a model experiment to understand the GaAs’ deformation behavior and crack formation mechanism during the plowing process.In order to produce a more uniform resultant stress field and provide an extended elastoplastic regime before cracking was initiated, it was beneficial for us to use a spherical indenter . Due to From the variation of the atomic lattice state, the deformation mechanism of the GaAs peak was studied utilizing the atomic configuration. In order to investigate the crack formation process, we concentrated on the crack extension during the plowing process at the 11 nm to 12 nm moment, as shown in In As the crack propagated, the material was split into polycrystals by thin amorphous bands and cracks, as shown in In order to elucidate the atomic states in the vicinity of the crack, a local view of the crack region was observed as an example of this crack formed at the 12 nm plow moment in As shown in In order to observe the complex stress state of the cracking behavior of the rough peak surface, we described the state of the von Mises equivalent stress during the deformation of the model and the hydrostatic stress distribution at the maximum tensile stress, respectively. The von Mises stress distribution is suitable for evaluating the inelastic deformation behavior of local atoms and can be used to analyze the most dangerous areas . From thIn the hydrostatic stress distribution, we observed that the asperity that was in compressive stresses appeared on the side in contact with the indenter, while the front side of the asperity was in tension, as shown in The tangential and normal force between the indenter and the GaAs under different displacement distances are shown in After a short drop, the tangential force was followed by a very short and steady fluctuation. Then, at a plowing distance of 9 nm, the tangential force was followed by a dramatic drop event. We knew that the pop-in may be associated with a critical deformation level. Moreover, this was when cracks were observed at the contact interface, as shown in Until the plowing distance reached 13 nm, the crack was fully formed in the vertical direction, as shown in To further study the deformation and removal behavior, we analyzed the microstructure evolution of GaAs during the plowing process, as shown in In order to quantitatively understand the effect of asperity size on deformation behavior, we established a series of hemispherical asperities with different geometrical dimensions. Under the same indenter size condition, three samples with a single asperity were plowed. The asperity was selected to be small and extremely small compared to the size of the indenter. The asperity radius was 2 nm, 4 nm and 7 nm, respectively. The plowing depth was consistent with the height of asperity to ensure the rationality of deformation behavior.It can be seen that there were apparent differences in the deformation behavior of rough peaks with different sizes after plowing. From the height of the “residual roughness peak” left on the substrate surface after plowing, it can be seen that the smaller the particle size of the roughness peak, the easier it was to obtain the surface with lower surface roughness under the same size of indenter. In addition, with the increase in the rough peak size, the deformation of GaAs became more apparent, and the number of phase transition atoms and dislocation lines increased. This was because the contact area between the indenter and the rough peak increased with the rough peak radius.It was observed from Cracks such as the ones observed in GaAs were not observed in the case of ultra-small rough peaks (r = 2 nm). However, the rough peak with a height of 4 nm showed a significant crack in front of the indenter, and the rough peak with a height of 7 nm showed two cracks on either side of the advancing direction of the indenter. It was also observed that for the ultra-small rough peak (r = 2 nm), the lattice of the substrate connected with the rough body could maintain a perfect lattice after plowing. Because the deformation happened due to lattice transformation localized without disturbing the substrate material. The deformation was entirely determined by the plastic flow caused by the phase transformation.The force increased first and decreased with an increasing plowing distance, showing a similar evolution of irregularities under various rough peak scales. As shown in Further insight into the hydrostatic pressure distribution of the workpiece was obtained. For the case of In order to investigate the effect of the indenter radius on asperity deformation, we selected three indenters of different sizes to conduct the simulations. We were convinced that changing the indenter size would affect the deformation behavior. More significant cracks appeared during plowing with an indenter radius of 4.5 nm, as shown in It can be seen from the comparison in In order to further study the effect of the plow depth on the deformation of rough GaAs, different indenter plowing depth levels were implemented, as shown in With the increased deformation imposed by the indenter, ductile ploughing was observed at a 4 nm plow depth and no visible cracking was detected on the surface of the asperity. The transition between elastic and plastic domains also depended on the rheology of the scratched material. In this case, the deformation of the rough body was determined by the plastic deformation, and the edges on both sides of the plow at the top of the rough peak exhibited a uniform smeared appearance, showing a continuous plastic flow. The rough peak gradually changed from hemispherical to flattened in the plowing process between the indenter and GaAs workpiece. Ductile ploughing behavior occurred at relatively small deformation levels. Note that the GaAs rough body with a plow depth of 4 nm did not undergo cracking during the plowing process, mainly elastoplastic deformation.With the increase in the plow depth, a more significant plastic deformation occurred at the rough peak of the substrate. When the plow depth was 4 nm b, the chThe simulated force curves for GaAs under the various plow depths of 2 nm, 4 nm and 7 nm were plotted in No chips or residual imprint were observed at a small plow depth of d = 2 nm during the low-load plow, as shown in (1)The deformation of single asperity GaAs during plowing was dominated by a combination of dislocation activity and crack propagation. Single asperity GaAs still sprouted cracks in addition to ductile behavior in deformation at the nanoscale, as well as crack propagation and further fracture. The sudden drop in the force event was found to be associated with crack generation in addition to reflecting traditional microstructural events. In all cases where cracks were generated, they formed at the intersection of (111) slip bands and were terminated at the substrate surface without extending into the substrate interior. The presence of cracks added to the variability of deformation patterns in the asperity and the ability of the asperity to resist the degree of subsurface damage to the substrate.(2)The size of the indenter influenced the location, number and propagation of cracks and affected the type of defect and lattice integrity in the substrate. As the indenter size increased, the shielding effect of the primary emergent crack on the secondary emergent crack took effect, while being less likely to form chips in front of the indenter. The residual thickness and depth of the subsurface damage layer also increased, while the pile-up height decreased. For smaller indenter sizes, the formation and propagation of the second emergent crack would be more favorable, while the crack extension rate was higher. As the plow depth increased, the atomic pile-up of asperity gradually changed from a secondary symmetric distribution to an asymmetric distribution.We used MD simulations to investigate the deformation behavior of plowing-induced single asperity GaAs. We reported that plastic deformation and surface tensile cracking jointly mediated the deformation mechanism in the asperity. Furthermore, the influence of the asperity size, indenter radius and plow depth on the deformation of the asperity was also discussed. The main conclusions were as follows:


Escherichia coli that hijacks the outer membrane proteins (OMPs) TolC and BtuB to enter the cell. Here, we capture the colicin E1 translocation domain inside its membrane receptor, TolC, by high-resolution cryo-electron microscopy to obtain the first reported structure of a bacteriocin bound to TolC. Colicin E1 binds stably to TolC as an open hinge through the TolC pore—an architectural rearrangement from colicin E1’s unbound conformation. This binding is stable in live E. coli cells as indicated by single-molecule fluorescence microscopy. Finally, colicin E1 fragments binding to TolC plug the channel, inhibiting its native efflux function as an antibiotic efflux pump, and heightening susceptibility to three antibiotic classes. In addition to demonstrating that these protein fragments are useful starting points for developing novel antibiotic potentiators, this method could be expanded to other colicins to inhibit other OMP functions.The double membrane architecture of Gram-negative bacteria forms a barrier that is impermeable to most extracellular threats. Bacteriocin proteins evolved to exploit the accessible, surface-exposed proteins embedded in the outer membrane to deliver cytotoxic cargo. Colicin E1 is a bacteriocin produced by, and lethal to,  Bacteria are constantly warring with each other for space and resources. As a result, they have developed a range of molecular weapons to poison, damage or disable other cells. For instance, bacteriocins are proteins that can latch onto structures at the surface of enemy bacteria and push toxins through their outer membrane.Bacteria are increasingly resistant to antibiotics, representing a growing concern for modern healthcare. One way that they are able to survive is by using ‘efflux pumps’ studded through their external membranes to expel harmful drugs before these can cause damage. Budiardjo et al. wanted to test whether bacteriocins could interfere with this defence mechanism by blocking efflux pumps.Escherichia coli bacteria: high-resolution molecular microscopy revealed how the bacteriocin fragment binds to the pump, while fluorescent markers showed that it attached to the surface of E. coli and stopped the efflux pumps from working. As a result, lower amounts of antibiotics were necessary to kill the bacteria when bacteriocins were present.Bacteriocins are usually formed of binding elements (which recognise specific target proteins) and of a ‘killer tail’ that can stab the cell. Experiments showed that the binding parts of a bacteriocin could effectively ‘plug’ efflux pumps in The work by Budiardjo et al. could lead to new ways to combat bacteria that will reduce the need for current antibiotics. In the future, bacteriocins could also be harnessed to target other proteins than efflux pumps, allowing scientists to manipulate a range of bacterial processes. In Gram-negative bacteria, the outer membrane, cell wall, and cytoplasmic membrane form concentric barriers that protect the cell from extracellular threats. Of these protective structures, the outer membrane forms a particularly formidable obstacle , owing tEscherichia coli-specific bacteriocins, protein toxin systems through which bacteria engage in bacterial warfare with other, similar bacteria. Colicins can be divided into groups A and B based on the requirement for which periplasmic protein systems they rely on to enter cells. The cytotoxicity of group A colicins requires the Tol system  are accessible from outside the cell, bacteriophage and bacterial toxins have evolved to exploit OMPs to initiate delivering cargo across the outer membrane. Bacteriocins hijack the OMPs of a target bacterium to cross its impermeable outer membrane and kill the bacterium. Colicins are l system  which isl system . Colicinl system . Much ofl system ; this bil system . A handfl system . Colicinl system . The str species .E. coli that enters the periplasm of neighboring cells and forms a pore on the cytoplasmic membrane leading to membrane depolarization and cell death. Unlike any of the other E colicins, the T domain of Colicin E1 binds to TolC  to solve the high-resolution structure of a bacteriocin, colicin E1, bound to TolC. We find that colicin E1 binds stably to TolC, not as a helical hairpin but as a single-pass folded helix with the N-terminus inside the periplasm. Additionally, we find that the ColE1 TR domain binds TolC in vivo as well. Using single-molecule fluorescence microscopy, we find that ColE1-TR, lacking the cytotoxic domain, remains stalled on the outer membrane and does not fully translocate into cells. Lastly, we leverage this stalling of ColE1 to block the native TolC function as an antibiotic efflux pump. Because they are accessible from outside the cell, OMPs are attractive targets for the development of novel antibiotics, and research has begun to reveal the therapeutic potential of interfering with OMP structure and function. .Here by determining the structure and mechanism of ColE1 insertion, we establish an alternative approach for targeting OMPs—the development of molecular plugs that block OMP pores. Such plugs would allow for the manipulation of bacterial transport, providing a means of either starving the bacterium by preventing the import of valuable nutrients or poisoning the bacterium by preventing the export of toxins. Through real-time efflux assays and minimum inhibitory concentration (MIC) experiments, we find that ColE1-TR and ColE1-T are able to inhibit TolC-mediated efflux. We find that this plugging of TolC reduces the amount of antibiotics required to inhibit the bacterial growth—indicating that this colicin E1 fragment reduces the antibiotic resistance conferred by TolC.To determine the structural details of colicin E1 binding to TolC, we solved the cryoEM structure of TolC embedded in nanodiscs with and without added ColE1-T . We recently reported a high-yield TolC preparation by refolding from inclusion bodies  and inseWe next determined the binding of colicin E1-T domain to capture the complex for structure determination. Residues 1–190 (ColE1-T) which span the translocation domain are known to bind to TolC . We idenThe ColE1 T domain inserts into TolC with its amino terminus pointing inwards through the periplasmic iris, and 2D class averages show that the carboxy terminus of the helix continues and projects out into the extracellular space . About 8Compared to the unbound state, asymmetric ColE1 binding dilates the periplasmic TolC aperture  and, makIn solution, unbound colicin E1 is a two-helix hairpin as indicated by far UV circular dichroism (CD) . A strucTolC forms a large rigid conduit in the outer membrane and periplasm  with a wTo obtain the most accurate atomic model for interpretation of atomic interactions between peptides, we utilized map-restrained molecular dynamics in model refinement . The refThe atomic model showed significant polar interactions form between colicin E1 and TolC at the apertures and around the TolC box. The acidic patch of colicin E1 near the extracellular aperture contains two arginine residues (R129 and R131) that form hydrogen bond networks with one TolC chain each . In addiBy contrast with the β-barrel of TolC, in the interior of the periplasmic helical barrel of TolC, colicin E1 does not make full contact with the α-helical barrel interior and there is a gap between the two proteins . This isMoreover, this structure is consistent with reports that mutations at TolC site G65 or S279 abrogate ColE1 activity  as theseE. coli cells. Though ColE1 C domain activity—depolarizing the inner membrane—requires the C domain to pass through the outer membrane  exposing all cellular compartments to trypsin.When probing for the C-terminal epitope by immunoblotting, there was no detectible ColE1-T binding , left, tE. coli (containing TolC), distinct puncta   which is known to have a premature stop codon at BtuB residue 58  ; on aversidue 58 . Puncta sidue 58  ; on avetolC cells that featured puncta, ColE1-TR form puncta consistent with ~20 molecules; we never detect an isolated single ColE1-TR molecule on either WT or ΔtolC cells before photobleaching. The observed size and number of molecules agree with previous studies of BtuB clusters  showed no detectable binding either to WT or ΔlC cells , indicatΔ1–40 binds to the cell surface of WT, ΔtolC, and ΔbtuB in a similar manner as ColE1-TR -1-naphthylamine (NNN)-dye, which passively diffuses into cells and is effluxed by the AcrAB-TolC efflux pump. NNN fluoresces when it is localized in the hydrophobic interior of one of the membranes  thereby 100-143 did not show lower real-time efflux than untreated cells . An effective TolC plug will reduce the concentration required to inhibit growth as antibiotics remain trapped within the cell. WT cs alone : exposuribiotics . ExposurΔ1–40) lacking the N-terminal 40 residues including the TolA box. The MIC of ColE1-TR and ColE1-TRΔ1–40 is identical  the total thread model in which the entire colicin unfolds and threads through TolC  and (2) Though we cannot exclude the possibility that ColE1 T and R domain translocation depends on the C domain, we observe—as hypothesized by the pillar model—that colicin sits inside TolC but does not translocate. These results are in agreement with early studies of pore-forming colicins in which trypsin added to the extracellular environment can reverse colicin activity . We antitolA strain  causes membrane defects similar to those in a ΔA strain . TherefoA strain . BecauseKlebsiella pneumoniae, binds TolC from Klebsiella quasipneumoniae with a binding mode similar to that of ColE1 binding TolC . JW5503-1 is a tolC732(del)::kan from the parent strain BW25113. BL21(DE3) was used for the production of the colicin constructs and TolC. BL21(DE3) has a premature stop codon at residue 58 of the btuB gene and therefore we used it as a ΔbtuB strain for microscopy.Δ1–40 was produced by inverse PCR to delete residues corresponding to 1 through 40. All point mutants  were generated by inverse PCR with mutagenic primers.The gene for ColE1-TR was synthesized as a gBlock (Integrated DNA Technologies) and cloned into pET303. Inverse PCR was used to delete the R domain and produce colicin E1-T. Colicin E1-TR-GFP was produced by inserting GFP at the C terminus of ColE1-TR. A gBlock (Integrated DNA Technologies) was synthesized for GFP containing complementary flanking sequences to the plasmid with ColE1-TR and inserted with the omega-PCR technique. ColE1-TRE. coli BL21(DE3) cells and plated on LB+ agar + 100 μg/ml carbenicillin. Single colonies were inoculated into 50 ml LB broth with 100 μg/ml carbenicillin and grown overnight at 37°C with shaking at 250 r.p.m. Proteins were produced by inoculating 1 L of TB supplemented with 0.4% glycerol, 10 mM MgCl2, and 100 μg/ml carbenicillin with 20 ml of the overnight culture. The culture was grown at 37°C to an OD600 of 2.0 and induced with 1 mM IPTG. Expression cultures were then grown at 15°C for 24 hr and harvested at 4000g for 30 min at 4°C. Cell pellets were resuspended at 3 ml/g of cell pellet in lysis buffer  and lysed via sonication  in an ice bath. Lysates were centrifuged at 4000g for 10 min to remove un-lysed cells and debris. The supernatant was centrifuged again at 50,400g in a Beckman Coulter J2-21 for 1 hr at 4°C. Clarified lysates were applied to a 5-ml HisTrap FF column and purified using an ÄKTA FPLC system with a 20-column volume wash step with binding buffer  and eluted using a linear gradient from 0% to 50% elution buffer  in 10 column volumes. Concentrated proteins were loaded onto a HiLoad Superdex 16/60 200 pg gel filtration column and eluted into phosphate-buffered saline (PBS) pH 7.4.Plasmids were transformed into g for 30 min at 4°C. Cell pellets were resuspended in ml of lysis buffer  at 3 ml/1 g of cell pellet and lysed via sonication  in an ice bath. Cell lysates were centrifuged at 4000g for 30 min at 4°C to harvest inclusion bodies. Inclusion body pellets were resuspended in inclusion body wash buffer  and centrifuged at 4000g for 30 min at 4°C. The inclusion body wash was repeated two more times. A final wash was done in 20 mM Tris pH 8.0 and inclusion bodies were stored at –20 °C. Inclusion bodies were solubilized in 20 mM Tris pH 8.0, 8 M urea at 500 μM. N-octylpolyoxyethylene was added to 5 ml of solubilized TolC to a final concentration of 10% detergent and pipetted into a Slide-A-Lyzer G2 dialysis cassette with a 10,000 molecular weight cutoff. Refolding was initiated by dialysis in 5 L of 20 mM Tris pH 8.0, 100 mM NaCl at 4 °C with stirring overnight. TolC was centrifuged at 15,200g for 10 min at 4°C to remove aggregates. The supernatant was filtered through a 0.22-μm filter, concentrated to 2 ml, applied onto a HiLoad 16/60 Superdex 200 pg column on an ÄKTA Pure FPLC system, and eluted with 1.5 column volumes in 20 mM Tris pH 8.0, 100 mM NaCl, 0.05% n-dodecyl-β-D-maltoside. TolC containing fractions were pooled and concentrated to 300 μM in Amicon centrifugal filters with molecular weight cutoff of 30 kDa.TolC production and purification were conducted in the same manner for preparation for cryoEM and for SEC. The gene for full-length TolC (a generous gift from R. Misra) was cloned into pTrc99a with the signal sequence deleted for expression into inclusion bodies. Plasmids were transformed into BL21(DE3) and plated on LB+ agar + 100 μg/ml carbenicillin. A single colony was picked and grown in LB at 37°C with shaking at 250 r.p.m. overnight. In the morning, 1 L of LB was inoculated with 20 ml of the overnight culture and grown at 37°C with shaking at 250 r.p.m. until the culture reached an OD600 of 0.6, at which point protein expression was induced with 1 mM IPTG for an additional 4 hr. Cells were then harvested at 4000MSP1D1 in pET28a was purchased from Addgene and was expressed and purified as previously described .ColE1-T100-143 was synthesized using standard Fmoc chemistry with a CEM liberty blue microwave peptide synthesizer. The peptides were cleaved using a solution of 92.5:2.5:2.5:2.5 TFA:TIPS:H2O:DoDt and the crude peptides were purified using HPLC. Analytical HPLC traces were acquired using an Agilent 1100 quaternary pump and a Hamilton PRP-1 (polystyrene-divinylbenzene) reverse phase analytical column  with UV detection at 215 nm. The eluents were heated to 45°C to reduce separation of rotational isomers, and elution was achieved with gradients of water/acetonitrile (90:10 to 0:100 containing 0.1% TFA) over 20 min. Low-resolution mass spectra were obtained using a Waters Micromass ZQ 4000 instrument with ESI+ ionization.E. coli (BW25113) were grown in LB media at 37°C with shaking (250 r.p.m.) overnight. A 50 ml culture of LB was inoculated with 1 ml of the overnight culture and grown at 37°C with shaking (250 r.p.m.) until an OD600 of 0.6 was reached. The cultures were centrifuged at 4000g at 4°C for 10 min. For the exogenous addition of protein, cell pellets were resuspended in cold PBS (Bio-Rad) containing 10 μM of either ColE1-T or ColE1-TR protein. Cells were incubated with protein with gentle rocking for 1 hr at 37°C. After incubation with protein, the cells were collected at 4000g at 4°C for 10 min and resuspended in cold PBS without protein. The centrifugation and wash were then repeated a second time. The PBS washes are designed to remove unbound protein.5 ml overnight cultures of Each sample is split into two 1-ml aliquots. The first aliquot is the intact cell condition which is placed on ice. The second aliquot is the lysed cells that control for protease activity. This aliquot was lysed by adding 0.25 mg/ml lysozyme  and incubated at room temperature for 15 min followed by five freeze-thaw cycles in liquid nitrogen. The intact cells condition and lysed condition were both split into three 270-μl aliquots. For each triplet, trypsin was added at 5 and 20 μg/ml to digest any extracellularly exposed protein. 30 μl of PBS was added to the third aliquot of each triplet for a no trypsin sample. The three aliquots were incubated at room temperature to allow for trypsin digestion. After 30 min, 20 μl of 100 mM PMSF was added to terminate the trypsin digestion reaction. Then the samples associated with the intact cells condition were lysed. Lysozyme was added to a final concentration of 0.25 mg/ml and incubated at room temperature for 15 min followed by five freeze-thaw cycles in liquid nitrogen. All samples were stored at –20°C until ready for western blot analysis.E. coli cin proteins were probed with THE HisTag mAb mouse (GenScript). SurA was probed with anti-SurA Rabbit polyclonal (Cusabio). Western blots were imaged by fluorescence using an LI-COR Odyssey imager with secondary antibodies IRDye 800CW goat anti-mouse IgG and IRDye 800CW Donkey anti-Rabbit for Colicins and SurA, respectively.Samples were separated by SDS-PAG 548 nm=162,000 L mol–1 cm–1; ColE1-T-E192C ε280 nm=9970 L mol–1 cm–1; ColE1-TR-E366C ε280 nm=14,440 L mol–1 cm–1). Labeling efficiencies were ~75% and ~85% for ColE1-T-E192C and ColE1-TR-E366C, respectively. Protein concentrations were adjusted according to the percentage of labeled protein.Cysteine mutations were introduced at the C-terminus before the histidine tag for fluorophore conjugation. These constructs were purified as described in the Expression and purification section with the addition of 1 mM TCEP in all buffers. All subsequent steps were performed with limited exposure to light and in amber tubes. Cyanine3 (Cy3) maleimide (Lumiprobe) was reconstituted in DMSO. Fluorophore labeling was achieved by mixing a 20-fold molar excess of Cy3 maleimide to protein and incubating overnight at 4°C. Free dye was removed by gel filtration on a Sephadex NAP-10 G-25 column. Simultaneously to the dye removal, the sample was buffer exchanged into storage buffer . The degree of labeling was determined spectrophotometrically from the concentrations of the dye and protein solutions using their respective extinction coefficients, ε, as described by their manufacturers or for the proteins as estimated by Expasy ProtParam ) were grown in LB medium at 37°C with shaking (180 r.p.m.) overnight, then transferred to MOPS minimal medium (Teknova) with 0.2% glycerol and 1.32 mM K2HPO4 and grown at 37°C for 13 hr. The sample was transferred to MOPS medium and grown to turbidity at 37°C overnight. A 1-ml aliquot of culture was centrifuged for 2 min at 4850g to pellet the cells. The pellet was washed in 1 ml MOPS and centrifuged a second time. The supernatant was then removed, and the cell pellet was resuspended in 500 μl MOPS. A 1.0-μl droplet of concentrated cells was placed onto a glass slide. Then, a 1.0-μl droplet of 1 µg/ml colicin E1 protein construct stock was added to the cells. The droplet was covered by an agarose pad (1% agarose in MOPS media) and a second coverslip.Cultures of 2), and fluorescence was imaged with an Olympus IX71 inverted microscope with a 100×, 1.40-NA phase-contrast oil-immersion objective and appropriate excitation, emission, and dichroic filters. A Photometrics Evolve electron multiplying charge-coupled device (EMCCD) camera with >90% quantum efficiency captured the images at a rate of 20 frames per second. Each detector pixel corresponds to a 49 nm×49 nm area of the sample. E. coli cells were identified and fluorescent signals were detected using the Single-Molecule Localization by Local Background Subtraction (SMALL-LABS) algorithm . The protein was eluted with 1.5 column volumes into 20 mM Tris pH 8.0, 40 mM NaCl, and 0.05% n-dodecyl-β-D-maltoside for ColE1-T. For ColE1-TR, the NaCl concentration was increased to 200 mM to prevent precipitation. Elution fractions were collected every 0.5 ml. Peak fractions were concentrated to 20 μl and analyzed by 4%–20% SDS-PAGE.9 CFU/ml, untreated cells had 4.7×109 CFU/ml). The cells were incubated at 25°C with shaking at 140 r.p.m. for 2 hr. Cells were harvested at 3500g for 5 min and washed once in 20 mM potassium phosphate buffer pH 7 with 1 mM MgCl2. Cell concentrations were adjusted to OD600 1.0 and placed on ice. Then, 2 ml of the cell suspension was loaded into a quartz cuvette (Agilent Technologies). Fluorescence was measured with an Agilent Cary Eclipse fluorescence spectrophotometer with slit widths at 5 and 10 nm for excitation wavelength of 370 nm and emission wavelength of 415 nm. Fluorescence measurements were taken every 1 s. After 100 s, 50 mM glucose was added to re-energize the cells and initiate efflux, and fluorescence data were collected for an additional 600 s. Real-time efflux activity in the presence of ColE1-TR was determined as previously described with some modifications . Cells wMICs were determined using the broth dilution method  with som1 ml of TolC at 0.5 mg/ml was mixed with 0.75 ml of A8-35 (Anatrace) amphipol at 33 mg/ml for a 50-fold weight excess and incubated at room temperature for 30 min. Bio-Beads SM-2 resin that was washed in methanol and equilibrated with 20 mM Tris, 40 mM NaCl was added to the reaction mixture at 0.5 g/ml to initiate detergent exchange for A8-35 and incubated with rotation at 4°C overnight. The mixture was transferred to a tube with fresh Bio-Beads and incubated at 4°C for an additional 4 hr. The reaction mixture was loaded onto a HiLoad 16/60 Superdex 200 pg column on an ÄKTA Pure FPLC system and eluted with 1.5 column volumes in 20 mM Tris pH 8.0, 40 mM NaCl to remove free A8-35 and detergent. For colicin-bound TolC in A8-35, colicin E1-T was added to the reaction mixture at a >2 molar excess prior to gel filtration. TolC or colicin-bound TolC in A8-35 was concentrated to 2–4 mg/ml for cryoEM.POPC (Avanti Polar Lipids) in chloroform was dried under a stream of nitrogen and freeze dried to remove residual chloroform. Lipids were reconstituted to 50 mM in cholate buffer  in an amber glass vial. The vial was submerged under a stream of warm water until the solution became clear. Lipids, membrane scaffold protein, and TolC were mixed in a 36:1:0.4 ratio as previously described . Final c3 μl of protein solution (TolC/ColE1-T in amphipol or TolC/ColE1-T in nanodiscs) was diluted to approximately 1.05 mg/ml concentration, applied to a glow-discharged TEM grid, and plunge-frozen in ethane using a Vitrobot Mark IV (FEI Company) with grade 595 filter paper (Ted Pella). Glow discharge was performed in ambient atmosphere at 0.39 mBar pressure. Imaging was performed using a Talos Arctica (FEI Company) operated at 200 kV with energy filter and K2 Summit  for detection. To collect multiple images per hole while maintaining parallel illumination conditions, a nonstandard 20 μm condenser aperture was used to image TolC-ColE1-T in nanodiscs. At nominal magnification of 205,000×, images were acquired in counting mode with a calibrated pixel size of 0.6578 Å. Fresnel fringes attributable to the beam interaction with the aperture were often seen in images. Some investigators have moved the microscope stage and altered the nominal objective lens true focus point to generate a fringe-free condition . In thissphinx-emdocs.readthedocs.io). Briefly, multishot imaging was configured with 4 images per hole for each of 16 holes; intermediate-magnification montages of grid squares were acquired; points were selected manually for collection of 64 images per point; images were acquired using coma-compensated image shift as gain- and dark-corrected LZW-compressed TIFs. Side, top, and oblique views were seen in areas of thin ice. During screening, ice thickness was estimated at 17–30 nm by the method of I0/IZLP   into theab initio. The threefold-symmetrized map contains density at ~1/3rd occupancy for ColE1-T and this density contains some high-resolution information not present in the asymmetric map, except near the TolC lid regions where symmetrization overlays ColE1-T density with TolC density at a threefold-related position. First, polyalanine helices were placed in the helical density in coot. Cross-correlation coefficients for both helices are higher with the N-terminus oriented toward the periplasm. Moreover, the side chains angle slightly toward the N-terminus like the fronds of an evergreen angle toward the ground in typical ‘Christmas tree’ conformation, indicating that this is the correct chain orientation. An estimate of the register was made by visual inspection of potential anchor residues. Finally, the hinge region was filled in using phenix and coot. This completed chain was refined against the asymmetric map in ISOLDE. Iteration between phenix, coot, and ISOLDE was continued until acceptable fit to density was achieved. In the case of TolC with ColE1-T, the map was further improved by combining map information with molecular dynamics force fields  with the ‘prokaryotic’ parameter set as ‘True’.AlphaFold  was used Colicins are plasmid-encoded toxins produced by bacteria to kill closely related bacteria that compete for scarce resources. While the individual proteins used for binding and taking up colicins in target bacteria are well-known, the precise pathway that those toxins ultimately take to make it into the cell is unclear. Here the authors reveal the cryo EM structure of the outermembrane protein TolC in complex with colicin E1 toxin to shed new mechanistic insights into this toxin import mechanism. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, including David Drew as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen José Faraldo-Gómez as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Bert van den Berg (Reviewer #2); Karen Jakes (Reviewer #3).Thank you for submitting your article "Colicin E1 opens its hinge to plug TolC" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1. Membrane localization experiments with ColE1-T and ColE1-TR are described in Figure 4. However, more experimental details need to be included in the figure legends and Methods, especially regarding protein concentrations in the experiments shown in Figure 4. For example, what is analysed in intact cells? Is bound toxin washed off into the supernatant? If the toxin has very high affinity will it come off the OMP receptor(s)? The relative concentrations of the colicin constructs used is not given, so there's no way to easily interpret some of the data. Furthermore, Figure 4C shows one cell each, and one could argue that only the best data is shown involved. Could the authors (perhaps as source data) show panels with many cells to show any differences between strains more objectively?2. The Discussion section needs to better describe the differences between the "pillar" and "total-thread" models, perhaps by also including a schematic of both. Furthermore, the experimental evidence in this paper supports the total-thread model, whereas the more ambiguous experiments (trypsin digestion) are only suggestive of the pillar model. Please make the final proposed model clearer in the discussion and include how the downstream pore-forming cytotoxic domain is translocated.3. Experiments with GFP attached to colE1-TR suggest efficient uptake in a tolC-dependent process. What would be a very informative further would be to delete the TolA box from the N terminus of the T domain of the T-R construct and determine whether uptake still occurs. If so, that would argue further against a translocation model whereby the C-terminal channel-forming domain of colicin E1 slithers down the outside of TolC, with its C terminus first, as proposed by Cramer et al. (2018). Additional control would be to mutate the hinge-proline.4. The Housden klebicin paper was published very recently describing detailed studies of the interaction of TolC with another bacteriocin, including cryo-EM structures :4625). While the work described here has been carried out independently, some acknowledgement of this work in the discussion is warranted.Reviewer #1:E. coli bacteriocin that hijacks the outer membrane proteins TolC and BtuB to enter the cell. Here the authors reveal the cryo EM structure of TolC in complex with colicin E1. They show how Colicin E1 structure rearranges from a helical hairpin into an single, long extended helix that plugs the TolC pore. They further show that E. coli cells that have TolC proteins plugged with a Colicin E1 fragments are more susceptible to antibiotics. Taken together, they have outlined the structural basis for Colicin E1 recognition and shown the applicability of this approach for bacterial pathogenicity.Colicin E1 is an Overall, I can find little technical issues with the paper and I think the conclusions drawn from the experiments are sound. The paper is well-written and the figures are easy to follow. From a mechanistic viewpoint the major findings was that it was unexpected for colicin E1 to open up from a helical hairpin into a single helix inside TolC. While the author have succeeded to understanding how the toxin engages with its receptor its still unclear how the downstream pore-forming cytotoxic domain is translocated across TolC.Reviewer #2:E. coli TolC in the absence and presence of the N-terminal translocation domain of Colicin-E1 (ColE1-T). Via SEC they demonstrate that the toxin domain binds tightly to TolC. Interestingly, the structure shows that the colicin is bound inside the long TolC barrel, with most of the colicin-OMP contacts provided by the β-barrel part of TolC. The cryo-EM data are nice and the map of the complex is of very good quality and supports the ColE1-T model built by the authors. While the involvement of TolC (and another OMP named BtuB) in ColE1 cell entry was known, the structure provides in my opinion clear support for a model in which the entire ColE1 is transported into the cell via the TolC conduit, utilising the proton motive force to power translocation via TolA. This latter part is not well described by the authors and I find the discussion of the two models not very clear and too much in favor of the "pillar" model . Another major issue that needs addressing is the fact that the authors have missed (or ignored) a very similar paper that was published very recently and which describes detailed studies of the interaction of TolC with another bacteriocin (Klebicin), including cryo-EM structures :4625). Thus, in contrast to what is claimed by the authors, theirs is not the first structure of a bacteriocin bound to TolC. The authors should compare their structure with that of Housden et al. (which is very similar) and rewrite their discussion based on both papers.The paper by Slusky and colleagues presents cryo-EM structures of To support their structural data the authors also carried out membrane localization experiments with ColE1-T and ColE1-TR (includes the receptor binding domain that interacts with the primary receptor BtuB), described in Figure 4. I didn't find this very clear. In particular I'm not sure what is analysed in Figure 4B? What do you analyse in intact cells? Bound toxin that is washed off and ends up in the sup? If so, what if the toxin has very high affinity and won't come off the OMP receptor(s)? The methods section is not complete and, rather than refer to a previous paper, the procedures should be fully described here. Figure 4C shows one cell each, and one could argue that cherry picking might be involved. Could the authors (perhaps as source data) show panels with many cells to show any differences between strains more objectively?The final data provided by the authors utilises the fact that TolC is part of the AcrAB-TolC RND efflux pump that moves noxious substances including antibiotics out of the cell. They hypothesise that, when ColE1-T or ColE1-TR is bound to TolC (plugging the efflux channel), the pump should not work or work less efficiently. Indeed, MIC values for several antibiotics are lower in the presence of certain toxin fragments, showing that cells are sensitised due to reduced drug efflux. The required concentration of the colicins are high, however, suggesting that the pump is still partly functional while the colicin is bound, a notion supported by the structure. Together, these data lead to the interesting hypothesis that modified bacteriocins that hijack functionally important OMPs might be used to potentiate antibiotics. Together, this paper provides a nice advance in our thinking on how bacteriocins gain entry into cells . It is also consistent with the more detailed study by Housden et al., which is satisfying. The potential application towards potentiating antibiotics via colicin-based targeting of OMPs like TolC could be an important future area of research.Reviewer #3:E. coli by making an ion-permeable channel in their inner membrane, is clarified.Colicins are plasmid-encoded toxins produced by bacteria to kill closely related bacteria that compete for scarce resources. While the individual proteins in the target bacteria used for binding and uptake of colicins are well-known, there remains some controversy about the precise pathway that those toxins ultimately take to reach the target of their ultimate lethal act. In this work by Budiardjo et al., the path for colicin E1, which ultimately kills target All of the E colicins use the vitamin B12 receptor, BtuB, as their primary outer membrane receptor to concentrate the colicin at the cell surface via an interaction with the central receptor-binding (R) domain. The enzymatic E colicins, E2-E9, then use the trimeric porin, OmpF, and its interactions with the N-terminal translocation (T) domain of the colicin to thread through one of the three pores of OmpF to ultimately bring the catalytic, carboxy-terminal end of the colicin into the periplasm from which it ultimately reaches and crosses the inner membrane. That process has been very thoroughly examined and documented, principally by the work of Kleanthous, Housden and their co-workers, as cited in references in this manuscript and others cited in this review. Colicin E1, which kills target bacteria by making a channel in their inner membrane and thereby depolarizing the cell, also uses BtuB as its primary outer membrane receptor. But then it differs from the other E colicins in hijacking the TolC channel, whose normal role in the cell is in drug and toxin export, and uses that channel as a means to enter the target cell. The isolated colicin E1 T domain has been found to exist in solution as a helical hairpin , but whether in vivo binding to TolC occurs as that same hairpin, with both ends pointing outside the target bacterium, or whether the hairpin unfolds, possibly around a TolC box previously shown to be essential for cytotoxicity, as proposed , was not known. In this work, it is now clearly shown by cryoEM that the T domain hairpin unfolds completely and is captured inserted inside TolC. The previously identified TolC box acts as a hinge with a kink at a central proline in the 21-residue box sequence (residues 100-120). Residues in the TolC box are involved in specific interactions with residues of TolC within the channel. The interaction with the T domain peptide alone was sufficient to dilate both the periplasmic and extracellular apertures of TolC, without involvement of any other proteins or motive force, a very signficant finding. The structure and the specific residue interactions elucidated in this work help explain earlier results with mutations in TolC that block killing by colicin E1 (ref. #37). The structure reported here negates earlier arguments against models in which colicin E1 threads through TolC to enter the periplasm. The direction of insertion is with the N terminus facing the periplasmic end of TolC. This arrangement would logically be expected, since the known TolA box sequence lies very near the N terminus of the colicin E1 T domain and needs to interact in the periplasm with TolA, a bacterial protein anchored in the inner membrane which extends into the periplasm, is thought to provide the energy necessary to mobilize translocation of the colicin and has been demonstrated genetically to be absolutely required for colicin lethality.Klebsiella pneumoniae klebicinC uptake via TolC : 4625), in which the klebicinC T domain was also captured inside the channel of the K. pneumoniae TolC channel. In those experiments, the stretch of T domain bound inside of TolC was protected from digestion by trypsin, with residues at both ends protruding from TolC subject to protease digestion. Thus, these two different bacteriocins, targeting different bacteria, both insert their N-terminal translocation domains into the TolC protein of their respective targets.Budiardjo et al. have failed to acknowledge the recent publication of nearly identical results with the closely-related A second very significant result from this manuscript is that binding of colicin E1 T domain inhibits drug efflux and thereby reduces the minimum concentration of some drugs to effectively kill bacteria. A significant effect was only seen in constructs that also included the R domain of the colicin, which may simply be serving to increase the concentration of T domain at the cell surface and thereby making its interaction with TolC more efficient. A shortcoming of these experiments is that the relative concentrations of the colicin constructs used is not given, so there's no way to interpret the lack of much effect from T domain alone. But the basic result suggests that there may be a route to using the E1 T domain as a means to reduce resistance of pathogenic bacteria to standard antibiotics, as has been suggested previously .E. coli are difficult to interpret. The protocol cited in the manuscript is a general protocol, and the relative amounts of protein used are not given. It is perhaps unsurprising that no T domain is seen bound to either intact or lysed cells, while T-R is detected, since the binding of isolated T domain, via TolC, has been shown to be orders of magnitude less efficient than that of R domain to BtuB . The authors point out that the proteolysis results may just be a reflection of a small number of molecules entering the cells. Similarly, the failure to see much transport of the fluorescently-labeled colE1-TR-Cy3 may also be a reflection of a combination of inefficient binding and the bulky Cy3 label impeding passage through TolC. In fact, recent work on transport of colicin E9 through OmpF suggests that relatively small differences in the size of fluorescent labels attached to colicin domains can have a measurable effect on uptake of the labeled proteins , and the labels used in that work had lower molecular weights than the Cy3 used in the experiments described here. Experiments with GFP attached to colE1-TR suggest more efficient uptake in a tolC-dependent process. What would be a very informative further experiment would be to delete the TolA box from the N terminus of the T domain of the T-R construct and determine whether uptake still occurs. If so, that would argue further against a translocation model whereby the C-terminal channel-forming domain of colicin E1 slithers down the outside of TolC, with its C terminus first, as proposed by Cramer et al. (2018).In vivo experiments to determine whether the T domain or T-R domain were protected from trypsin digestion by virtue of having been internalized by eLife. Your revised article has been evaluated by José Faraldo-Gómez (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "Colicin E1 opens its hinge to plug TolC" for further consideration by The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:1. While we realise the PDBs were released earlier than those of Housden et al. it would be better to remove the instances of "first" in the text as, after all, they are not really needed.2. The modified text for points 23 and 24 in the previous submission was still unclear to Referee 2. We would ask you to try to re-address these points (re-pasted below for clarity).23. line 253: "need to be in close proximity for colE1 binding to occur" needs a reference.24. line 254: "when BtuB clusters together in groups of 12 or more, it may exclude TolC" needs a reference. Also, please explain "These cluster geometries would therefore lower the number of full binding sites available for the T and R domains of colicin E1."3. Throughout the manuscript, reference is made to the TolA box of colicins E3 and E9. However, neither of those colicins actually has a TolA box. Beginning with the early work of Bouveret et al.  and subsequently by others, it has been shown that what had been called the TolA box in earlier work is actually a TolB box. Colicins E2-E9 and A all interact with TolA indirectly, by binding to TolB in the periplasm, and TolB then engages TolA. The fullest picture of those interactions is in the recent work of Francis et al. (2021), which is cited in this manuscript. The only E colicin known to have a TolA box is E1. A reference  is needed when referring to the E1 TolA box. All references to a TolA box in colicins E3 or E9 need to be fixed.4. While the experimental details and source data have been expanded and clarified, the implications of both the trypsin digestion experiments and fluorescence labeling are less clear than the cryo-EM and drug efflux experiments, and some caveats should be added to the discussions of those experiments.5. The argument between the two competing models may require some further clarification. Referee 3 has made some suggestions below. Please look at these and amend appropriately as you see fit.Specific comments and corrections:Line 62: …targets and killing mechanisms. Most colicins…Lines 69-71 should read: …of ColE3 or ColE9 initiates translocation using the secondary OMP receptor/translocator, OmpF, to access the Tol-Pal system in the periplasm. For most colicins, the T domain requires an OMP distinct from the R domain target for colicin translocation.Line 72-73: …structurally characterized bound to their OMP primary receptors. . Those structures all reveal that the plugged β-barrels remain plugged upon colicin binding, so another route through the outer membrane is required.Line 75-76 ff: …that T domain can pass fully through one pore of its membrane translocator, OmpF, and loops around to insertv in a second pore of the trimer from the periplasmic side, while the R domain initially interacts with…its receptor, BtuB. Those same studies and earlier ones clearly demonstrated that full engagement of the E9 T domain with its TolB translocation partner in the periplasm results in disengagement of the R domain from BtuB . Experiments such as these and those that preceded this most recent work are the basis for the "total thread" model for colicin translocation, in which the colicin is pulled through the same pore of OmpF through which its T domain initially entered. The process is energized by the TolABQR system.Line 82: death. Unlike any of the other E colicins, the T domain of colicin E1…Line 83: …and the R domain binds BtuB, the primary receptor shared by all E colicins.Line 98: …and disrupt TolC channel conductance in vitro, in planar lipid bilayer membranes…Line 101: …in solution similar to another colicin T domain from colicin Ia, one that does not interact with TolC .Line 223: …these residues are contact sites…Line 290: Should read: Given the two-dimensional surface…Line 370: Add Francis et al., 2021 reference here.Line 376: Why was the hinge opening unanticipated?Line 378: …as the total thread model hypothesized and consistent with experimental data that support this model for colicin E9 .Line 380: …clustered and does not diffuse…Reviewer #1:I am satisfied with the revised submission and have no further concerns.Reviewer #2:The revised manuscript by Slusky has substantially improved based on the reviewer comments and in particular it is now much clearer. I have just a few remaining minor issues for consideration:eLife in this regard, and leave it up to the editor to decide.point 2: I understand the reasoning of the authors. However, I'm not sure if it is entirely appropriate to allow priority claims based on non peer-reviewed preprints. While I do realise the PDBs were released earlier than those of Housden et al., in my opinion it would be better to remove the instances of "first"  in the text as, after all, they are not really needed. I don't know what the policy is of points 23 and 24: unfortunately the modified text is still unclear to me.Reviewer #3:The authors have very thoroughly addressed all of the reviewers' comments, provided additional experiments and methodological descriptions, and fixed the reference list to remove duplications and make it a more user-friendly format.From that perspective, I should say that the paper is acceptable now. But in the process of expanding parts of the Introduction and Discussion, I feel they have done their work and the field a disservice by giving "first billing" to a model for which there is scant experimental support and giving short shrift to the model for which there is now extensive experimental support and which common sense should support.E. coli. That model was introduced simply because of the assumption by Zakharov et al. (2016) that the helical hairpin structure of the E1 T domain observed in solution from CD spectra is maintained when the T domain binds in vitro to TolC, as it was shown to do by SEC, occlusion of TolC channels in planar lipid bilayer membranes , and in vivo by protecting sensitive E. coli from killing by active colicin E1 . On the contrary, the current work has clearly demonstrated that the hairpin unfolds and inserts, amino-terminus first, into TolC., so the whole basis for a model with both N- and C-termini pointing to the outside of the target cell is gone. ). Another argument made by Zakharov et al. against insertion of the T domain into TolC was that the periplasmic aperture of the TolC channel is too narrow for a polypeptide to exit, so therefore the colicin couldn't possibly thread into the periplasm via that route. The structure shown in Figure 1B demonstrates that the binding of T domain within the channel opens that aperture; the colicin domain is easily accommodated within TolC. Thus, the colicin polypeptide or a part of it could transit through TolC.In their expanded Introduction, the authors once again lead with a lengthy elaboration of the "pillar model" for the translocation of the colicin E1 pore-forming domain across the outer membrane of target The sections on potentiation of antibiotics by the E1 T domain are additional evidence that the colicin domain is occupying TolC and inhibiting its normal role in drug efflux. It's likely that the failure to see much of an effect with T domain, as compared to R-T, is simply the result of the much tighter binding of R to BtuB, which then concentrates T domain at the cell surface and makes it more likely to find and enter a TolC channel.While the experimental details and source data have been expanded and clarified, the implications of both the trypsin digestion experiments and fluorescence labeling are less clear than the cryo-EM and drug efflux experiments, and some caveats should be added to the discussions of those experiments. It's not clear what not finding protected T domain tells us. Recently published experiments with the related KlebC and the K. quasipneumoniae TolC  clearly show that a significant segment of the KlebC T domain is protected from trypsin digestion when bound and digested in vitro. Mass spec analysis of the protease digestion products showed that the KlebC T domain extends out of the TolC channel at both the periplasmic and extracellular ends, and those parts of the peptide were degraded by trypsin, but there remained a protected band of >40 residues that coincides with residues shown inside the TolC channel in the cryoEM structure.The observation in most cases of just a single punctum from fluorescently-labeled colicin peptides is puzzling, although the presence of a fluorescent signal is clearly BtuB and TolC-dependent. Frankly, I'm not sure what we learn from these experiments. Somehow the videos referred to did not come through with the copy of the manuscript I received.The new experiments with P110A and T∆1-40 are interesting and somewhat surprising. There is nothing in the Methods about how either of those mutants was generated.Throughout the manuscript, reference is made to the TolA box of colicins E3 and E9. However, neither of those colicins actually has a TolA box! Beginning with the early work of Bouveret et al.  and subsequently by others, it has been shown that what had been called the TolA box in earlier work is actually a TolB box. Colicins E2-E9 and A all interact with TolA indirectly, by binding to TolB in the periplasm, and TolB then engages TolA. The fullest picture of those interactions is in the recent work of Francis et al. (2021), which is cited in this manuscript. The only E colicin known to have a TolA box is E1. A reference  is needed when referring to the E1 TolA box. All references to a TolA box in colicins E3 or E9 need to be fixed.I have taken the liberty of making a number of additions and corrections, in italics, to add some balance to the descriptions of the two models. Obviously, these changes are just suggestions, but I hope the authors feel they improve the paper, which is a very important addition to this field.  Essential revisions:1. Membrane localization experiments with ColE1-T and ColE1-TR are described in Figure 4. However, more experimental details need to be included in the figure legends and Methods, especially regarding protein concentrations in the experiments shown in Figure 4. For example, what is analysed in intact cells? Is bound toxin washed off into the supernatant? If the toxin has very high affinity will it come off the OMP receptor(s)? The relative concentrations of the colicin constructs used is not given, so there's no way to easily interpret some of the data.We apologize for the lack of clarity for this method. We have updated the figure 4B figure caption to read:E. coli, each construct is labeled with a C-terminal His-Tag. Periplasmic SurA was used as a membrane integrity control. After incubation with colicin fragments, cells were left intact or lysed with lysozyme. Proteins degraded by trypsin in intact cells are not protected by the outer membrane.”“(B) Extracellular protease digestion assay with two colicin E1 truncation constructs incubated with The following has been added to the results:“We assessed whether ColE1-T and ColE1-TR translocate into the cell or localize on the cell surface using an extracellular protease digestion assay . Colicin fragment stalling on the outer membrane surface would render the colicin fragments susceptible to digestion when trypsin is in the extracellular environment. Conversely, if the colicin fragment translocates into the intracellular environment, the outer membrane will shield the protein from digestion by trypsin.Colicin fragment localization was probed through western blot analysis of specific colicin fragments with C-terminal polyhistidine-tags. Cells were incubated with these colicin fragments and subsequently exposed to two different concentrations of trypsin. If the protein enters the cell, the outer membrane shields it from trypsin digestion, and a corresponding band is present on the western blot. Periplasmic protein SurA was used as a membrane integrity control. SurA digestion indicates that the periplasm was accessible to trypsin and a SurA band indicates that the periplasm was shielded from trypsin. As a trypsin activity control, half of the cell sample was lysed (lysed cell condition) exposing all cellular compartments to trypsin.”And the following was added to the methods:“Extracellular Protease Digestion.Growth, incubation with protein, and washing: 5 mL overnight cultures of E. coli (BW25113) were grown in LB meda at 37 °C with shaking (250 r.p.m.) overnight. A 50 mL culture of LB was inoculated with 1 mL of the overnight culture and grown at 37 °C with shaking (250 r.p.m.) until an OD600 of 0.6 was reached. The cultures were centrifuged at 4,000 g at 4°C for 10 minutes. For the exogenous addition of protein, cell pellets were resuspended in cold PBS (Bio-Rad) containing 10 μM of either ColE1-T or ColE1-TR protein. Cells were incubated with protein with gentle rocking for 1 hour at 37 °C. After incubation with protein, the cells were collected at 4,000 g at 4 °C for 10 minutes and resuspended in cold PBS without protein. The centrifugation and wash were then repeated a second time. The PBS washes are designed to remove unbound protein.Protease digestion of intact cells and lysed cells: Each sample is split into two-1 mL aliquots. The first aliquot is the intact cell condition which is placed on ice. The second aliquot is the lysed cells control for protease activity. This aliquot was lysed by adding 0.25 mg/mL lysozyme  glycerol) and incubated at room temperature for 15 minutes followed by five freeze-thaw cycles in liquid nitrogen. The intact cells condition and lysed condition were both split into three 270 μL aliquots. For each triplet, trypsin was added at 5 and 20 5 and 20 μg/mL s to digest any extracellularly exposed protein. 30 μL of PBS was added to the third aliquot of each triplet for a no trypsin sample. The three aliquot were incubated at room temperature to allow for trypsin digestion. After 30 minutes, 20 μL 100 mM PMSF was added to terminate the trypsin digestion reaction. Then the samples associated with the intact cells condition were lysed. Lysozyme was added to a final concentration of 0.25 mg/mL and incubated at room temperature for 15 minutes followed by five freeze-thaw cycles in liquid nitrogen. All samples were stored at -20 °C until ready for western-blot analysis.Western blot: Samples were separated by SDS-PAG E. coli cin proteins were probed with THE HisTag mAb mouse (GenScript). SurA was probed with anti-SurA Rabbit polyclonal (Cusabio). Western blots were imaged by fluorescence using a LI-COR Odyssey imager with secondary antibodies IRDye 800CW goat anti-mouse IgG and IRDye 800CW Donkey anti-Rabbit for Colicins and SurA, respectively. “Furthermore, Figure 4C shows one cell each, and one could argue that only the best data is shown involved. Could the authors (perhaps as source data) show panels with many cells to show any differences between strains more objectively?tolC, and 6 ΔbtuB cells).To address this question, we have added figure 4, supplemental figure 1 which contains images that show the variety of the original 315 images that give rise to the data summarized in Figure 4C-D. 18 Phase contrast and fluorescence images of cells are shown  are only suggestive of the pillar model. Please make the final proposed model clearer in the discussion and include how the downstream pore-forming cytotoxic domain is translocated.We have updated our discussion of the pillar vs. total thread model as follows and have added the following schematic to show the difference:et al., 2018, Jakes, 2017) and (2) the pillar model, in which colicin E1 inserts into TolC as a helical hairpin, facilitating LPS-mediated, self-translocation of the colicin cytotoxic domain . Our data support aspects of both models. The belief in a closed hinge conformation of bound ColE1 prompted two arguments against the total thread mechanism: (1) the ColE1-T closed hinge conformation is too wide to fit through TolC and (2) both ends would face the extracellular milieu . The unanticipated ColE1-T hinge opening in the bound state resolves these objections: colicin threads into the TolC barrel with the amino terminus pointing into the periplasm, as the total thread model hypothesized. Our trypsin digests show ColE1-TR stalls at the outer membrane of E. coli cells and the single-molecule fluorescence images confirm that ColE1-TR remains clustered and do not diffuse as would be expected if entering the periplasm or cytoplasm. These puncta form regardless of the presence or absence of the TolA binding region on ColE1-TR.“There are two conflicting models of ColE1 translocation: (1) the total thread model in which the entire colicin unfolds and threads through TolC . We anticipate that the stable ColE-TR:TolC complex forms regardless of the presence of the C domain.Though we cannot exclude the possibility that ColE1 T and R domain translocation depends on the C domain, we observe—as hypothesized by the pillar model—that colicin sits inside TolC but does not translocate. These results are in agreement with early studies of pore-forming colicins in which trypsin added to the extracellular environment can reverse colicin activity . Therefore, in the pillar model, colicin binding of TolA may facilitate C domain insertion through the defective membrane, whereas in the total thread model binding TolA transduces the proton motive force to unfold ColE1and pull it into the periplasm . Because we did not use the toxic C domain, our data cannot clarify what occurs after the T and R domain of full length colicin bind the outer membrane proteins. Although our studies find that ColE1-TR remains on the surface of the bacteria, it is certain that the C domain, when present, translocates across the membrane into the target bacteria to kill the cell. Our data does not exclude the possibility that the translocation of the T and R domains occurs along with the C domain in full length colicin, nor does it support T or R domain translocation. Thus, though our studies give a more complete view of the early stages of ColE1 binding the surface of its target, we cannot determine if insertion of the C domain occurs via the total thread model or via a modified pillar model.If the C domain does translocate while the T and R domains remain bound, we anticipate that the requirement for TolA is due to its role in membrane maintenance. Binding of TolA by a different group A colicin (ColE9) causes membrane defects similar to those in a Δ3. Experiments with GFP attached to colE1-TR suggest efficient uptake in a tolC-dependent process. What would be a very informative further would be to delete the TolA box from the N terminus of the T domain of the T-R construct and determine whether uptake still occurs. If so, that would argue further against a translocation model whereby the C-terminal channel-forming domain of colicin E1 slithers down the outside of TolC, with its C terminus first, as proposed by Cramer et al. (2018). Additional control would be to mutate the hinge-proline.Δ1-40-Cy3 on WT, ∆tolC, and ∆btuB cells. We find that, like ColE1-TR, ColE1-TRΔ1-40 does remains fixed on the cell in puncta.At the reviewers’ request we have deleted residues 1-40, which bind to TolA, and we have quantified single-molecule fluorescence images of ColE1-TRThe new data can now be found in the manuscript as Figure 4—source data 1.And as a gallery of the pictures as Figure 4 supplemental figure 3.We now describe this data in the manuscript as follows:Δ1-40 binds to WT, ΔtolC, and ΔbtuB in a similar manner as ColE1-TR . Cell localization of ColE1-TR matching that of translocation deficient ColE1-TRΔ1-40 suggests that ColE1-TR puncta are not within the cell and likely stalled on the outer membrane receptor.”“In binding to the cell surface, ColE1-TRWe also mutated the hinge proline (P110A) and found that ColE1-T still binds to TolC. This data has been added as Figure 3, supplemental figure 2.We added the following text to the manuscript:“These contacts are strong enough that even when the proline hinge of the TolC-box is mutated (P110A) ColE1-T still binds TolC .”4. The Housden klebicin paper was published very recently describing detailed studies of the interaction of TolC with another bacteriocin, including cryo-EM structures :4625). While the work described here has been carried out independently, some acknowledgement of this work in the discussion is warranted.We have added the following text to the discussion:Klebsiella pneumoniae, binds TolC from Klebsiella quasipneumoniae with a binding mode similar to that of ColE1 binding TolC.  KlebC is closed in the unbound state as confirmed by the high-resolution xray crystal structure which supports our proposed conformation  and opens into a single-pass, kinked-helix to bind to TolC. This suggests a conserved mechanism for bacteriocins that hijack these trimeric efflux pump proteins.”“Shortly after this work was made available, a similar structure demonstrated that KlebC, an rRNAse bacteriocin from The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:1. While we realise the PDBs were released earlier than those of Housden et al. it would be better to remove the instances of "first" in the text as, after all, they are not really needed.Though we agree it is clear that our PDB was deposited and released before that of Housden et al., our concern is that the wording “first” is unfortunately needed. Housden et al. claims specifically that, “We next set out to delineate the TolC-binding region of KlebC and determine its structure; no structure has yet been reported for any TolC-binding domain.”We are concerned Housden’s wording will perpetuate a misunderstanding in the literature as our structure had already been reported, in a preprint and a PDB. Such a misunderstanding might reduce the number of citations attributed to this work in this journal as other scientists would erroneously believe that priority should be attributed to Housden.2. The modified text for points 23 and 24 in the previous submission was still unclear to Referee 2. We would ask you to try to re-address these points (re-pasted below for clarity).23. line 253: "need to be in close proximity for colE1 binding to occur" needs a reference.24. line 254: "when BtuB clusters together in groups of 12 or more, it may exclude TolC" needs a reference. Also, please explain "These cluster geometries would therefore lower the number of full binding sites available for the T and R domains of colicin E1."We have rewritten this passage to make it clear that we are referring to the simple need for physical proximity during binding: if a substrate is binding two proteins simultaneously, then those two proteins must therefore be near to each other. Moreover, clustering multiple proteins in a small two-dimensional area leads to physical (geometric) exclusions:“Because we usually only see one punctum per cell, we anticipate that some BtuB and TolC may remain unbound because of the geometric constraints of punctum formation. ColE1 must engage both TolC and BtuB simultaneously. Therefore, both receptors must be in close proximity, similar to the ~50 Å proximity of BtuB to OmpF when both bound to a another type A colicin, ColE9 . Given the two-dimensional surface of a membrane there are restrictions to how many proteins can be within 50 Å of any other protein. For the clusters we see to occur, when BtuB clusters together in groups of approximately 20  TolC must also cluster in groups of approximately 20, ultimately requiring approximately 40 proteins in a relatively small area. The competition between the clustering of BtuB and the requirement for proximity of BtuB and TolC for binding could lower the number of BtuB/TolC sites available for the T and R domains of colicin E1 due to the relative TolC and BtuB geometries needed for ColE1 binding.”3. Throughout the manuscript, reference is made to the TolA box of colicins E3 and E9. However, neither of those colicins actually has a TolA box. Beginning with the early work of Bouveret et al.  and subsequently by others, it has been shown that what had been called the TolA box in earlier work is actually a TolB box. Colicins E2-E9 and A all interact with TolA indirectly, by binding to TolB in the periplasm, and TolB then engages TolA. The fullest picture of those interactions is in the recent work of Francis et al. (2021), which is cited in this manuscript. The only E colicin known to have a TolA box is E1. A reference  is needed when referring to the E1 TolA box. All references to a TolA box in colicins E3 or E9 need to be fixed.We thank the reviewer for this insight and have made the distinction between colicin E1 binding to TolA and colicins E3 and E9 binding to TolB. References to TolA box for colicins E3 and E9 have been corrected through the manuscript with the appropriate citations. In addition, all references to ColE1 requiring TolA now include the citation to Pilsl and Braun 1995.The text has been updated:“TolA is known to be required for ColE1 cytotoxicity . ColE1 lacking the TolA box at the N-terminal T-domain would likely be translocation incompetent due to uncoupling from TolA. Similarly, there is a loss of biological activity due to mutations in the ColE9 N-terminal region that indirectly interacts with TolA . Biological inactivation has also been caused by mutation to the Tol-Pal interacting regions of ColE3  and ColA .”“TolA is normally involved in outer membrane invagination during cell division . Like Colicin E1, Colicin E9 contains an intrinsically unstructured N-terminus that engages the Tol-Pal system once it penetrates into the periplasm . Engagement of the Tol-Pal system by the N-terminal region of colicin E9 disrupts native Tol-Pal system function leading to outer membrane defects .”“Recruitment of the Tol-Pal system by a different group A colicin (ColE9) causes membrane defects similar to those in a ΔtolA strain .”4. While the experimental details and source data have been expanded and clarified, the implications of both the trypsin digestion experiments and fluorescence labeling are less clear than the cryo-EM and drug efflux experiments, and some caveats should be added to the discussions of those experiments.We thank the reviewer for the helpful discussions of recent findings. We agree that the single puncta were a surprising finding and worth pointing out in our manuscript. Though the molecular mechanism that gives rise to these puncta remains to be explored in future projects, the error bars and detection limits of the microscopy observations indicate that this clustering is true.We also appreciate that the results of our in vivo trypsin digest were (and were expected to be) different from the recent Housden work in which trypsin digests were conducted in vitro absent any mechanism for translocation. Finally, we appreciate the reviewer for pointing out that we neglected to update our methods on the P110A mutant and the del1-40 mutant.We have added the following to the methods:“A gBlock (Integrated DNA Technologies) was synthesized for GFP containing complimentary flanking sequences to the plasmid with ColE1-TR and inserted with the omega-PCR technique.ColE1-TRΔ1-40 was produced by inverse PCR to delete residues corresponding to 1 through 40.All point mutants  were generated by inverse PCR with mutagenic primers.”5. The argument between the two competing models may require some further clarification. Referee 3 has made some suggestions below. Please look at these and amend appropriately as you see fit.Specific comments and corrections:Line 62: …targets and killing mechanisms. Most colicins…Done.Lines 69-71 should read: …of ColE3 or ColE9 initiates translocation using the secondary OMP receptor/translocator, OmpF, to access the Tol-Pal system in the periplasm. For most colicins, the T domain requires an OMP distinct from the R domain target for colicin translocation.Done.Line 72-73: …structurally characterized bound to their OMP primary receptors. . Those structures all reveal that the plugged β-barrels remain plugged upon colicin binding, so another route through the outer membrane is required.We appreciate this suggestion and we have added the Buchanan reference.Line 75-76 ff: …that T domain can pass fully through one pore of its membrane translocator, OmpF, and loops around to insertv in a second pore of the trimer from the periplasmic side, while the R domain initially interacts with…its receptor, BtuB. Those same studies and earlier ones clearly demonstrated that full engagement of the E9 T domain with its TolB translocation partner in the periplasm results in disengagement of the R domain from BtuB . Experiments such as these and those that preceded this most recent work are the basis for the "total thread" model for colicin translocation, in which the colicin is pulled through the same pore of OmpF through which its T domain initially entered. The process is energized by the TolABQR system.We appreciate this level of detail for the insertion mechanisms of all colicins but think that such descriptions might be better suited for future review articles.Line 82: death. Unlike any of the other E colicins, the T domain of colicin E1…Done.Line 83: …and the R domain binds BtuB, the primary receptor shared by all E colicins.Done.Line 98: …and disrupt TolC channel conductance in vitro, in planar lipid bilayer membranes…Done.Line 101: …in solution similar to another colicin T domain from colicin Ia, one that does not interact with TolC .Done.Line 223: …these residues are contact sites…Done.Line 290: Should read: Given the two-dimensional surface…Done.Line 370: Add Francis et al., 2021 reference here.Done.Line 376: Why was the hinge opening unanticipated?We have updated the text to explain more clearly:“The ColE1-T hinge opening in the bound state—which was unanticipated by the pillar model— resolves these objections”Line 378: …as the total thread model hypothesized and consistent with experimental data that support this model for colicin E9 .Because of the following discussion in the manuscript:“the “total thread” model  posits that the protein unfolds and passes through TolC N-terminus-first as an unstructured peptide and binds to TolA  in the periplasm. In this model the binding between the intrinsically unstructured colicin N-termini and periplasmic proteins  creates a pulling force that results in the translocation of the whole colicin.”We have not added the requested text out of concern that adding it would be overly repetitive and may frustrate the reader.Line 380: …clustered and does not diffuse…Done.


Recently, deep neural networks have been the most commonly used approach for echocardiography segmentation. However, the performance of a well-trained segmentation network may degrade in unseen domain datasets due to the distribution shift of the data. Adaptation algorithms can improve the generalization of deep neural networks to different domains. In this paper, we present a multi-space adaptation-segmentation-joint framework, named MACS, for cross-domain echocardiography segmentation. It adopts a generative adversarial architecture; the generator fulfills the segmentation task and the multi-space discriminators align the two domains on both the feature space and output space. We evaluated the MACS method on two echocardiography datasets from different medical centers and vendors, the publicly available CAMUS dataset and our self-acquired dataset. The experimental results indicated that the MACS could handle unseen domain datasets well, without requirements for manual annotations, and improve the generalization performance by 2.2% in the Dice metric.The segmentation of the left ventricle endocardium (LV However, manual echocardiography labeling requires a doctor with rich clinical expertise to spend a lot of time, which seriously affects diagnostic efficiency. Smart health [Cardiovascular disease (CVD) is the leading cause of death among adults worldwide. Echocardiography, the non-invasive imaging inspection tool, is widely applied in the clinical routine of CVDs . The anat health ,4 can ast health ,6 is notThe development of deep learning ,7 has prAs a result of the diverse imaging devices and imaging protocols, echocardiography datasets are greatly different from each other in domain styles, such as grayscale distribution. The above-mentioned domain adaptation methods perform well in natural images, but are not fully functional in medical images; this is because most medical images have low color contrast. It is difficult to maintain the key structure by the domain adaptation in the image space , and a rendo and LVepi in echocardiography. The method is named the MACS. It adopts a GAN architecture, integrating the segmentation part (generator) and domain adaptation part (multi-space discriminators) to handle the cross-domain echocardiography analysis. The segmentation part utilizes an attention mechanism to extract the multi-scale features. Then, a dual-branch prediction module decodes the features into segmentation masks, with an emphasis on both the target region and boundary. The domain adaptation part aligns the samples from different domains in both the feature space and output space, enforcing generators to refine the segmentation results. In this study, we present a multi-space adaptation-segmentation-joint network for extracting the LVendo and LVepi in multi-domain echocardiography datasets using labels of only one domain for training. Specifically, it adapts the source domain and the target domain on both the feature space and output space, which avoids the side-effect of direct translation on the original ultrasound images [Our main contributions lie in the following. The MACS achieves the segmentation of the LVd images  and imprd images  for crosThe paper is organized as follows. The MACS framework is shown in Semantic segmentation in ultrasound images is affected by ambiguous boundaries and speckle noise. The multi-scale attention mechanism ,27 has bThe ASDB extracts four feature maps of different scales using the continuous ResNeXt. The low-level and high-level features contain detailed and semantic information, respectively. The layers of features are refined by the deep attention model (DAM). Specifically, the multi-level features are fused and reweighted to form the multi-layer feature (MLF). The MLF and single-layer feature maps are fed into the DAM for the refined feature maps. The mask branch combines the original feature maps and the refined feature maps from all levels and averages them for the final segmentation prediction. The boundary branch learns from the refined feature maps of the lowest two feature layers.The loss function of the ASDB module is:Multi-space discriminators take the segmentation predictions of both the source and target domains as inputs and classify them according to their similarity of the distribution. The discrepancy between the echocardiographies from different domains mainly contains the grayscale distribution, the spatial texture, the ventricular location, the angle of probe scanning, etc. While the echocardiography may appear different, the feature and output of the segmentation share strong similarities . Therefore, adversarial learning on the feature space and output space encourages a narrowing of the distribution gap of the segmentation results between the source and target domain datasets. Then, the segmentation network overcomes the performance degradation caused by the domain migration and works on the target domain images.The well-trained segmentation without the domain adaptation tends to produce inaccurate predictions on target domain images. To obtain the semantic segmentation information from the global features extensively, we chose higher-level features, extracted by the segmentation network as inputs of the feature discriminator. As high-level features contain lots of contexts and semantic information, their alignment could force the encoded features of the source domain images and the target domain to be semantically consistent. f aligns the high-level feature distributions by classifying whether the feature is produced from the source domain or the target domain. When the discriminator cannot judge from which domain features are extracted, the source domain and target domain are successfully aligned on the feature space. Otherwise, gradients of the discriminator Df are delivered backward to encourage the features of the target domain to be more similar to the source domain.The feature discriminator Df is: M and N are the number of source domain images and target domain images, respectively; The adversarial loss of the feature discriminator DAdversarial learning on the feature space ensures the high-level feature distributions of the source domain and target domain are consistent, and encourages the segmentation network to produce a structurally correct prediction. Nevertheless, this is not enough for accurate segmentation. In addition to the high-level semantics, low-level details also have a huge impact on the segmentation predictions. Thus, adversarial learning on the output space is further used to ensure the source-target consistency on the segmentation details.e to align the entropy map calculated by the pixel-wise mask. The entropy is the expected value that measures the uncertainty of the predicted mask  and end-systole (ES). The public dataset CAMUS , collectOur self-acquired echocardiography dataset was collected from 11 subjects by Vinno© G86. The size of each image was 980 × 650 pixels. Each patient provided sequence images of multiple cardiac cycles in the A2 C view and A4 C view. The dataset was composed of images, sampled every ten frames apart from the echocardiographic sequence. We used the same contouring protocol as the CAMUS for labeling. A cardiologist labeled these images. We utilized 900 unlabeled images and 477 annotated images of this dataset to complete the following experiment. The images were interpolated or cropped to the equal length and width and resized to 256 × 256 pixels for the memory consumption reduction. Data augmentation was accomplished by random crop, adding salt pepper noise, and adjusting intensity.e and Df were optimized with the SGD optimizer. The SGD optimizer applied an initial learning rate of 10−3 and was divided by 0.2 every 100 epochs. The segmentation network ASDB was optimized with the Adam optimizer. The initial learning rate of Adam was 2.5 × 10−5. The batch size of the model was 8 and the network was trained for 200 epochs without warmup epochs. Validation ran every 10 epochs for the model selection by mean dice index.We implemented the network based on PyTorch (version 1.9.1) and trained the model on two 12 GB Nvidia© TITAN Xp GPUs. The discriminator DWe quantitatively evaluated the segmentation performance on echocardiography through the Hausdorff Distance (HD), the Dice index (DI) and the Jaccard index (JI). The HD is a metric based on the boundary of the segmentation prediction, and the DI and JI are region-based segmentation metrics.The criteria are defined as:In this section, we conduct a set of experiments on the CAMUS dataset and our self-acquired dataset to evaluate the MACS. The ablation study in endo and LVepi: w/o Domain Adaptation (DA);ASDB, w/o Entropy Domain Adaptation (EDA);ASDB + Feature discriminator, w/o Feature Domain Adaptation (FDA);ASDB + Entropy discriminator, Our proposed method (MACS).The ablation study is conducted to confirm the effectiveness of the key modules of the MACS we proposed. Specifically, we use the four following modules to segment the LVIn the ablation study, the self-acquired dataset and the CAMUS dataset are defined as the source and the target domain, respectively.endo and LVepi segmentation predictions on the CAMUS. The ASDB can recognize the ROI of the cross-domain segmentation task, but the prediction masks are not ideal. The segmentation predictions of the ASDB without any discriminator have a large structural error. Either a single discriminator in the feature space or the output space corrects the structural mistake and encourages the segmentation network to obtain accurate results. The integrated MACS with multi-space discriminators further improves the segmentation performance of the boundaries and achieves the best segmentation result of all of these modules.endo and LVepi on a single echocardiography is approximately 0.175 s.For the full MACS model, the average running time of segmenting LVVarious numbers of target domain images may affect the effect of the multi-space domain adaptation of the model and affect the segmentation on the target domain. To explore the causality between these two, we train the framework with different quantities of target domain images. In this experiment, the CAMUS dataset is the source domain dataset and the self-acquired dataset is the target domain dataset. Considering that there are a total of 1600 source domain images taking part in the training, we randomly sample 200, 400 and 800 unlabeled images from the target domain for the rate of 1:8, 1:4 and 1:2 between the target and source domain. In addition, we use 100 unlabeled target domain images to represent the situation of a small amount of data for the adaptation in order to perfect the experiment. endo and LVepi are improved. After the number of target domain images reaches more than 400, the accuracy of the segmentation tends to plateau.According to The trends of the segmentation DI are visualized in T→S, which maintain the intrinsic content while having the style of source domain images. Then, the DAF is utilized to segment the XT→S. We compare our MACS with the state-of-the-art unsupervised domain adaptation approaches: SAGAN , CUT 1919, and FThe image-to-image translation results and segmentation predictions are presented in The quantitative results from the comparative experiment are reported in endo segmentation than the other two adversarial learning methods.To confirm the effectiveness of our method, the MACS is compared with the state-of-the-art adversarial learning methods: p-SOAL  and BEALendo and LVepi areas are 0.45 and 2.8 compared with the ground truth. The plots show that the average bias of the MACS is less than the other two methods and the segmentation for the LVendo has a higher performance than for the LVepi. To show a more intuitionistic opinion of the performance, all 477 annotated images in the self-acquired dataset are used for training the MACS, and the well-trained model is tested on the CAMUS testing set. The segmentation results are compared with those of some state-of-the-art fully-supervised methods on the CAMUS and the inter/intra -observer variability, offered in . These sendo as the DI of the MACS segmentation results exceeds the inter-observer discrepancy by 2.5%. However, the segmentation prediction still has a gap with the inter-observer variability. In addition, we can observe that some of the existing state-of-the-art methods have also not attained a performance higher than the inter-observer on the CAMUS. Compared with the state-of-the-art supervised models, our MACS is trained with fewer annotated images and does not use labels of the public dataset at all.Our method achieves a segmentation accuracy comparable to the intra-observer variability; this is particularly true for the segmentation of the LVIn this work, we proposed a multi-space adaptation-segmentation-joint framework, named the MACS, for generating an accurate segmentation prediction of the unseen target domain. It addresses the challenge of enlarging the model generalizability when the domain shifts. With the domain adaptation in the feature space and the output space, the MACS trained by the source domain dataset generalizes to the target domain dataset.Current echocardiography segmentation methods mainly focus on a single dataset. However, imaging devices and medical centers affect the gap between different datasets. As a result, the current segmentation models trained by one echocardiography dataset cannot be generalized to another dataset. For a single medical center, physicians cannot apply a model trained by other center’s datasets to their own images, they have to invest a lot of time labeling their data and retraining the model. This reduces the usability of automated segmentation methods in real clinical diagnosis.The image-to-image translation is a commonly used strategy for cross-center tasks, which can visually bridge the gap between the source and target domain. However, as shown in The MACS improves the segmentation performance in the target domain via the adversarial learning between the segmentation network and discriminators. As demonstrated in Although the MACS has improved the segmentation performance on unseen domain echocardiography, there are still limitations waiting to be consummated. The feature discriminator and the entropy map discriminator are optimized independently during adversarial learning, while the high-level fused feature and the segmentation mask are not independent of each other. The relation between them may also affect the adaptation of the model. In the future, the more effective strategy will be explored to collectively optimize two discriminators to improve the segmentation performance of the model.endo and LVepi segmentation in echocardiography from different domains. The domain adaptation on both the feature space and output space in the model assists in maintaining the performance of the segmentation network on unseen domain images. Concretely, the model extracts fused features and entropy maps from different domains, then aligns them with adversarial learning. The effectiveness of each component is appraised through the ablation study. Our method outperforms the state-of-the-art methods on two datasets, which verifies the elegance and accuracy of the MACS on cross-domain echocardiography segmentation. Considering our self-acquired dataset is not able to cover various cardiac pathological situations, future research will evaluate the model on a larger dataset.We present a segmentation framework named the MACS for LV