In neurodegenerative diseases, changes in neuronal proteins in the cerebrospinal fluid and blood are viewed as potential biomarkers of the primary pathology in the central nervous system (CNS). Recent reports suggest, however, that level of neuronal proteins in fluids also alters in several types of epilepsy in various age groups, including children. With increasing evidence supporting clinical and sub-clinical seizures in Alzheimer’s disease, Lewy body dementia, Parkinson’s disease, and in other less common neurodegenerative conditions, these findings call into question the specificity of neuronal protein response to neurodegenerative process and urge analysis of the effects of concomitant epilepsy and other comorbidities. In this article, we revisit the evidence for alterations in neuronal proteins in the blood and cerebrospinal fluid associated with epilepsy with and without neurodegenerative diseases. We discuss shared and distinctive characteristics of changes in neuronal markers, review their neurobiological mechanisms, and consider the emerging opportunities and challenges for their future research and diagnostic use. Neurodegenerative diseases are characterized by progressive age-dependent death of neurons in the central nervous system (CNS) with related decline of specific brain functions. Two distinctive features make neurons particularly susceptible to degeneration: 1) incompetence for self-renewal and 2) deterioration in homeostatic mechanisms over lifetime [ incompet deteriorPost-mortem histopathological examination remains the gold standard for differential diagnosis of neurodegenerative diseases Fig. . As the Notwithstanding major advantages, molecular biomarkers of neurodegenerative diseases have considerable limitations, which include relative specificity and significant variability of the readouts, partly because of the overt and latent comorbidities , 23, 30.In neurodegenerative diseases, an increase in the level of neuronal proteins and their fragments in CSF and blood are viewed as markers of injury and loss of nerve cells. Due to differential distribution in various neuronal compartments and the specific role played in pathobiology, some of the changes in neuronal proteins can provide additional clues about the type of pathology and the extent of the damage. Alterations in Aβ and tau, for instance, are explored primarily as indicators of amyloid and neurofibrillary tangle pathology and related neuronal loss, while the increase in α-synuclein, neurogranin, synaptic vesicle glycoprotein 2A and synaptosomal-associated protein 25 kD (SNAP-25) are viewed as markers of synaptic damage. The rise in neurofilament light chain (NF-L) level in fluids, on the other hand, is taken predominantly as a marker of axonal injury leading to a collapse of long-range connections [In early preclinical and advanced stages of AD, most reports show a notable reduction in the level of Aβ1-42 in CSF and serum, with alternatively cleaved amyloid precursor protein (APP) fragments also reduced compared to age matched controls –38. The Despite important differences in their molecular pathology and clinical presentation, neurodegenerative diseases share important aspects of their pathobiology, leading to neuronal death. Some neurodegenerative diseases also share comorbidities, which can influence the molecular pathology and profiles of biomarkers. With aging and neurodegenerative disease-related increase in the odds of epilepsy, the impact of seizures on neuronal protein changes has become of major research and clinical interest. In AD, for instance, the risk of seizures can be as high as 35–50% –56. HighIt has long been known that AD and temporal lobe epilepsy share several histopathological features, including neuronal injury, gliosis, inflammation, and amyloid pathology , 58. Senper se do not alter Aβ1-40 and Aβ1-42 in CSF, in AD patients with epileptic seizures, the level of CSF Aβ1-42 is lower as compared to those without seizures.While the mechanisms for the convergence of histopathological features of AD and epilepsy brain samples remain elusive, growing data imply that neuronal hyperactivity associated with seizures can influence APP processing, as reflected in changes of Aβ isoforms and fragments of soluble APP in CSF . Shahim Several reports have shown that the level of t-tau and p-tau is enhanced in the CSF and blood of patients with a single episode of self-limiting , 66 or rTau profile has been also analyzed in SE using a lumbar puncture, with patients stratified based on their response to ASM, disabilities, and epilepsy outcomes . The levNF-L is another neuronal protein explored as a biomarker of neurodegenerative diseases, with single episodes and reoccurring seizures causing its increase in CSF and blood –76 Tabl. Like stA comparative analysis of several neuronal and glial proteins in adults with new-onset self-limiting seizures, chronic epilepsy, and PSE showed significant differences in NF-L between these conditions, with at least 2 years of follow-up demonstrating higher NF-L in PSE vs. self-limiting single seizure cases, and with overall levels of NF-L in patients with chronic epilepsy and PSE exceeding those in patients with single seizure episodes . The samIt is interesting to note that in young children (6 months to 5 years), measurements of serum NF-L associated with febrile and epileptic seizures within a few hours after the convulsion revealed no difference as compared to age-matched controls . In multNeurogranin and α-synuclein are other two neuronal proteins explored as biomarkers of neurodegenerative diseases. Regulation of calmodulin activity in dendritic spines of glutamatergic synapses makes neurogranin an important molecular switch of synaptic plasticity , 81. AssAs opposed to neurogranin, α-synuclein is enriched in presynaptic terminals of axons, with evidence suggesting its upregulation in neurons of preclinical models of epilepsy . Clinica2+ as well as by cell stress response, which are key characteristics of the pathobiology of epilepsy [2+ during intense neuronal activity, in fact, is required for induction of the physiological release of peptides, hormones, and trophic factors from neurons and other secretory cells [Although the increase of neuronal proteins in biological fluids of patients with neurodegenerative diseases is viewed primarily in association with the breakdown of neurons and synaptic connections , 86, impepilepsy –102. Thery cells –95, 103.ry cells , 104 couIt should be noted that in addition to the rate of release from hyperactive and damaged neurons, changes in neuronal proteins in CSF and peripheral circulation may be also influenced by the speed of their exchange between the two compartments, as well as by their degradation by extracellular proteases –107. AloEpilepsy is among the most prevalent comorbidities of neurodegenerative diseases. Given the global aging population and neurodegenerative diseases on the rise, their intersection with epilepsy has become of major research and clinical interest. Recent data suggest that the incidents of epilepsy in older age and patients with neurodegenerative diseases are widely underrated, mainly due to poor screening and subclinical forms of epilepsy. The mounting clinical evidence implies a complex and dynamic relationship between these morbidities, with both sub-clinical and clinical seizures accelerating the progression and exacerbating outcomes of neurodegenerative diseases Fig. .Fig. 2ScThroughout this study, we discussed reports of changes in neuronal proteins in CSF and blood associated with different types of epilepsy with and without neurodegenerative diseases. Based on the dynamics of neuronal markers in fluids and putative release mechanisms of peptides and proteins from neurons, as well as on the lack of evidence for neuronal degeneration in most types of epilepsy, it is reasonable to assume that the transient changes of neuronal markers in CSF and blood related with self-limiting and tonic-clinic seizures could reflect (1) increase in protein metabolism and release from hyperactive neurons, (2) vesicular  discharge from stressed and hyperactive neurons, and (3) seizure-related changes in the rate of neuronal protein exchange between CSF and blood. In contrast, the strong and lasting increase of NF-L and tau in SE is likely indicate the extent of the cellular injury with degeneration and associated breakout of neuronal proteins.With growing recognition of the prevalence of sub-clinical and clinical seizures in the most common neurodegenerative diseases and increasing use of neuronal protein changes as disease biomarkers, addressing the underlying mechanisms and clinical implications are well warranted. Combined with studies of the effects of ASM on dynamics of neuronal proteins and neurodegenerative process, the elucidation of the key mechanistic and translational aspects of neuronal biomarkers shared by epilepsy and neurodegenerative disease are likely to set us on a course to better diagnosis and therapies of these conditions.


Solvent retention capacity (SRC) is a test for the solvation of wheat flour. Its functional contribution was predicted according to the swelling behavior of different diagnostic solvents to different polymeric components of wheat. Ten commercial wheat flour varieties were used as raw materials in this study. The flour quality, gluten aggregation and solvent retention capacity, and their correlations were analyzed. The results showed that protein content, wet gluten content, dry gluten content and the swelling index of glutenin were positively correlated with torque maximum (BEM), torque 15 s before maximum torque (AM), torque 15 s after maximum torque (PM) and gluten aggregation energy (AGGEN). Moreover, they were significantly correlated with the solvent retention capacity. BEM, AM, PM and AGGEN were positively correlated with standard solvent water-SRC (WSRC) and lactic acid-SRC (LASRC). For supplemental solvents, ethanol-SRC (EthSRC) was positively correlated with AGGEN. Sodium dodecyl sulphate-SRC (SDSSRC) was highly correlated with peak maximum time (PMT). Metabisulfite-SRC (MBSSRC) and MBS + SDSSRC were also significantly correlated with BEM, AM, PM and AGGEN sodium metabisulfite. There were significant correlations between gluten aggregation characteristic, standard SRC solvent and supplemental solvent. This study provides a theoretical basis for the evaluation of wheat flour quality. Wheat flour plays an important role in the daily human diet, providing essential energy of the body . As the w/w lactic acid, 5% w/w sodium carbonate and 50% w/w sucrose. Of these, water  and 5% w/w lactic acid solution (for glutenin) were closely related to wheat protein. The four SRC solvents were considered ideal for evaluating the quality of soft wheat flour. They could not be used to evaluate the function of gluten in durum wheat flour because the individual contribution of the gluten subunit was not fully evaluated in a 5% lactic acid solution [To some extent, the solvent retention capacity (SRC) (AACC method 56-11.02) had been proposed as a specific diagnostic tool for predicting individual functional components of flour. Briefly, the SRC was a method to assess the swelling behavior of flour polymerization components in the presence of excess diagnostic solvents. The four standard solvents for the SRC method were water, 5% solution . Gliadinsolution . TherefoTo date, a number of studies had used standard solvents to predict the quality of soft and durum wheat flours ,9. The rThe samples were different gluten wheat flour sold by COFCO brand, Meimei brand, Jinxiang brand, Xiangxue brand and Zhongyu brand. Ten samples were arranged from high to low protein content and stored at 4 °C until use.Moisture content was determined gravimetrically according to the AACC 44-15.02 method . Wheat fg for 300 s, then the supernatant was pipetted. Then samples were centrifuged at 450× g for another 180 s, then the supernatant was aspirated. The tube weight was determined, and the SIG value was calculated as a percentage of the initial flour weight on a 14% moisture basis.The swelling index of glutenin (SIG) was determined by the method of Wang et al. . Lactic SH(free)(μmol/g) = A/εbC [A is the absorbance value, ε is the extinction coefficient of 13,600, and b is the cell path length. For the measurement of total SH contents, the 1 mL supernatant was added with 0.05 mL β-mercaptoethanol and 4 mL of 0.2 M Tris-Gly buffer. Vortex mixer was used to rotate the suspension at high speed for 1 min. The sample was then vibrated for 60 min (250 r/min), adding trichloroacetic acid  and then vibrating for 60 min. The precipitates were collected by centrifugation for 15 min at 10,000 g. The pellet was washed twice with 6 mL of 13% trichloroacetic acid (13%), adding 10 mL of 0.2 M Tris-Gly buffer) and 0.1 mL of 10 mM DTNB. The absorbance was determined at 412 nm by UV photometer. The SS group content was calculated according to Equation: Free sulfhydryl (SH) and disulfide bond (SS) were measured according to the method reported by Wang et al. . Flour w) = A/εb . A is thGluten aggregation was determined according to the method of Wang et al.  with sli2.Peak maximum time (PMT) corresponds to the time required to reach maximum torque; expressed in seconds. Torque maximum (BEM) corresponds to maximum torque of gluten; expressed in GPU. Torque 15 s before maximum torque (AM) corresponds to the torque value 15 s before maximum torque; expressed in GPU. Torque 15 s after maximum torque (PM) corresponds to the torque value 15 s after maximum torque; expressed in GPU. The GlutoPeak aggregation energy (AGGEN) is automatically calculated from the area of the curve obtained with the device; expressed in cmSolvent retention capacity (SRC) of flour samples were determined according to the AACC 56-11.02 . The floWSDS: water-SRC, LASRC: lactic acid-SRC, EthSRC: ethanol-SRC, SDSSRC: sodium dodecylsulphate-SRC, MBSSRC: metabisulfite-SRC, SDS + MBSSRC: Sodium dodecylsulphate + metabisulfite-SRC.p ≤ 0.05. The correlations between the qualities of the 10 samples were determined using the Pearson correlation coefficient method (p ≤ 0.05 (*) and p ≤ 0.01 (**)). Principal component analysis (PCA) was also performed using Origin 18.Each experiment was repeated more than three times. The data presented are averages of measurements ± standard deviations. The results were compared with the LSD test at Change of free sulfhydryl (SH) and disulfide bonds (SS) content plays a vital role in wheat gluten polymerization . When diGlutoPeak is a rapid shear-based method that can measure the aggregation behavior of gluten to assess wheat flour quality . In the 2. In addition, AGGEN was positively correlated with protein content, wet, dry gluten content and the swelling index of glutenin.AM is the torque to reach the first 15 s of BEM. It represents the point at which gliadin and wheat gluten start to polymerize, i.e., the initial formation of gluten network. After reaching BEM, the gluten network is broken and the torque value decreases. The value of 15 s after BEM is called PM. AM reflects the gluten strength of flour before the formation of the gluten network, and it is the best index to predict the volume of bread . The AM The SRC value can determine the effect of different functional components on flour. Moreover, the SRC value can reflect the quality characteristics of flour. For standard solvents, the gluten properties of wheat flour can be evaluated using the LASRC value. The higher the LASRC value in a certain range, the better the soft gluten quality . Kweon eSupplemental solvents had been identified and expanded based on polymer solubility, solvent similarity of gluten, and gluten components. The values of EthSRC, MSSRC, SDSSRC and MBS + SDSSRC were 53.5~73.15%, 52.13~71.14%, 77.01~106.76% and 53.75~74.94%, respectively. In accordance with the results of standard solvents, EthSRC, MSSRC and SDS + MSSRC of sample 1 were the highest among ten wheat flour samples, which were 67.32%, 73.73% and 74.94%, respectively. Samples 3 and 9 had the lowest EthSRC. A total of 55% EthSRC was related to the composition of gliadin . Wheat fWSRC and LASRC were closely related to gluten strength of wheat flour. According to In order to consider all data simultaneously, principal component analysis was performed on the test data of the wheat flour. The variance was 71.8% for PC1 and 13.3% for PC2 . In the In this study, the gluten aggregation characteristics in wheat flour with different gluten strength, the retention capacity of standard and supplemental solvents and their correlations were analyzed. The SRC diagnostic solvent and gluten aggregation characteristics were used to predict the gluten characteristics of wheat flour, and their correlations were analyzed. The results showed that wheat flour with higher protein content, wet gluten content, dry gluten content and swelling index of glutenin had higher BEM, AM, PM and AGGEN values. BEM, AM, PM and AGGEN were correlated with standard solvents WSRC and LASRC. The supplemental solvent EthSRC was associated with AGGEN. SDSSRC was highly correlated with PMT. MBSSRC and MBS + SDSSRC were also significantly associated with BEM, AM, PM and AGGEN. It was concluded that the standard SRC and supplemental solvents were significantly correlated with gluten aggregation characteristics, which provided a theoretical basis for wheat flour quality evaluation.


Arids- contains 15 members that have almost exclusively been described as DNA-binding proteins. Interestingly, a decade ago the family member Arid5a was found to bind and stabilize mRNAs of immune system key players and thereby account for driving inflammatory and autoimmune diseases. How exactly binding to DNA and RNA is coordinated by the Arid5a ARID domain remains unknown, mainly due to the lack of atom-resolved information on nucleic acid-binding. This in particular applies to the protein’s ARID domain, despite the comfortable size of its core unit for NMR-based investigations. Furthermore, the core domain of ARID domains is found to be extended by functionally relevant, often flexible stretches, but whether such elongations are present and crucial for the versatile Arid5a functions is unknown. We here provide a near-complete NMR backbone resonance assignment of the Arid5a ARID domain with N- and C-terminal extensions, which serves as a basis for further studies of its nucleic acid-binding preferences and targeted inhibition by means of NMR. Our data thus significantly contribute to unravelling mechanisms of Arid5a-mediated gene regulation and diseases.The family of AT-rich interactive domain (ARID) containing proteins - Within any organism, a plethora of nucleic acid-binding proteins (NBPs) exert a wide variety of functions on different levels of gene regulation. These proteins sub-classify into DNA-binding proteins (DBP)  containing proteins -termed Variants of the core ARID domain exist with extensions by additional helices, either located N- (H0) and/or C-terminally (H7)  ID: 2OEH, Cai et al. Arid5b sequence conservation between species, as well as a reasonable conservation between 5a and b. Whether and how additional segments contribute to DNA- and RNA-binding including a possible discriminative potency via the extensions remains to be elucidated for both proteins, especially taking into account their high density of charged amino acids. Similar to the definition of specific motifs above, the precise determinants of RNA- vs. DNA-recognition and motif preferences will be best understood on the residue- or atom-resolved level, e.g. using NMR.Interestingly, the structure of the closely related DNA-binding Arid5a including its N- and C-terminal elongations. With respect to their central role in specific nucleic acid-recognition, we also provide assignments of 6 out of 7 sidechain amides. We clearly define the core domain boundary and show that extensions do not interfere with the fold and remain flexible in the absence of nucleic acids. The herein provided chemical shifts serve a desirable starting point for follow-up structural and functional investigations on Arid5a alone and in complex with DNA and RNA, which will ultimately reveal its specificity on the transcriptional and post-transcriptional level.In this study, we provide the near-complete backbone assignment of the ARID domain of Arid5a amino acid (aa) sequence based on the UniProt  guided by the high sequence similarity (72.3%) to the second member of the Arid5 subfamily, Arid5b [PDB ID: 2OEH,  followed by a tobacco etch virus (TEV) protease cleavage site. The three shorter variants of ARID  were cloned accordingly, using the template of Arid5a 37–183 and the additional following oligonucleotides: 5′-CGATATCCATGGCACGCGAGGAAGAGCAGGAACGGG-3′ (49_fwd) and 5′-GTGGTGCTCGAGCTATTTGTCATCTTCGCC-3′ (152_rev).This study uses the human This construct design resulted in all four proteins containing four artificial N-terminal residues after TEV-proteolytic cleavage, termed Gly33/Gly45, Ala34/Ala46, Met35/Met47, Ala36/Ala48 for the natural termini 37 and 49, respectively.Arid5a constructs were expressed in E. coli strain BL21(DE3) in M9 minimal medium containing 1 g/L 15NH4Cl (Cambridge Isotope Laboratories) and 4 g/L α-D-glucose (for 15N-labeled protein) or 2 g/L 13C6-D-glucose (Eurisotop) (for 13C/-15N-labeled protein) supplemented with 50 µg/ml kanamycin. All proteins were expressed for 16–20 h at room temperature after induction at an OD600 of 0.6–0.8 with 1 mM isopropyl-β‐d‐thiogalactopyranoside. After expression cells were harvested by centrifugation for 10 min at 4 °C and 6000×g. Cell pellets were resuspended in 50 mM Tris pH 8, 300 mM NaCl, 10 mM imidazole, 2 mM β-mercaptoethanol and 100 µL protease inhibitor mix G (SERVA) (25 ml per 1 L of cell culture). Cells were disrupted by sonication and the lysate was cleared by centrifugation for 20 min at 20,133×g and 4 °C. The cleared lysate was passed over a Ni2+-NTA gravity flow column (Sigma-Aldrich) and the protein of interest eluted with an imidazole concentration between 150 and 300 mM. The His6-Trx-tag was cleaved while dialyzing over night at 4 °C into fresh buffer without imidazole with 0.5 mg TEV protease (produced in-house) added per 1 L of culture  on a HiLoad 16/600 SD75 column  in SEC buffer . Purity of Arid5a containing fractions was determined by SDS-PAGE, and fractions containing pure Arid5a were pooled and concentrated using Amicon® centrifugal concentrators (molecular weight cutoff: 10 kDa). Finally, SEC buffer without NaCl was added to adjust the NaCl concentration to 150 mM, and the protein solution was concentrated for subsequent NMR measurements. 1H}-15N heteronuclear (het)NOE experiment of Arid5a 37-183 was measured as an interleaved pseudo-3D TROSY-based spectrum according to , and their resonances are assigned mainly to the N- and C-terminal parts of the protein sequence. The lack of dispersion hints at these regions being unstructured. The overall good quality of the spectra allowed for the backbone amide (15N-1HN) assignment of 99 and 97% for Arid5a 49-152 and 37-183, respectively (Table Arid5a 37-183) at the N-terminal part  and W90. Possibly, the missing amides of amino acids R49, E50 and R55 overlap with other glutamate or arginine peaks within the RE-rich region  under accession numbers 51811 and 51812, respectively. The N- and C-terminal elongations to the ARID core domain had no significant influences on the fold of the core as shown in the overlay of the four 1H}-15N-hetNOE experiment for ARID 37-183 to probe the dynamics of the protein on a fast time scale  and L2 (aa 118-125), which show slightly lower ratios than the amides in adjacent helices. Furthermore, the N- and C-terminal parts to the ARID core domain show hetNOE values between 0.25 and 0.5, which indicates these regions are less rigid than the core domain, but not completely devoid of order.To further characterize the ARID domain’s N- and C-terminal extensions towards their structural content, we recorded a {Arid5a 49-152 (using aa 58-144), 37-152 (aa 34-57) and 49-183 (aa 145-183). From the SCS plot we interpreted the values towards the secondary structure of Arid5a ARID, where four consecutive residues with a positive value larger than 1 were defined as an α-helix, and three consecutive residues with a negative value below − 1 as a β-strand  plot in Fig. Arid5a with its N- and C-terminal extensions. We unambiguously provide evidence, that the ARID domain is not extended by additional helices N- or C-terminally to the core domain but represents a “minimal” core domain type of an ARID. However, the highly charged extensions are likely to carry a decisive role in nucleic acid binding towards affinity and specificity. The herein obtained assignments provide the basis for a subsequent in-depth characterization of the domain towards its discriminative interactions with DNA and RNA on the atom-resolved level. Thus, our study is an important contribution towards understanding the structure-based target specificities of a DRBP member of the Arid protein family with essential roles in gene regulation and inflammatory and autoimmune diseases (Nyati et al. In conclusion, we here provide the near complete backbone assignment of the ARID domain of


The convolutional multiple whole profile fitting method of X-ray line profile analysis using synchrotron radiation allows the experimental determination of dislocation densities separately for different Burgers vectors up to a high degree of deformation. Its reliability for Mg–Zn–Y alloys, in terms of the dislocation activity during tensile deformation, has been successfully verified by combined analysis with electron backscatter diffraction investigation and visco-plastic self-consistent simulation. a〉 dislocation slip was revealed by CMWP analysis, and Schmid factor analysis from the EBSD results supported the higher potential of non-basal dislocation slip in comparison with basal 〈a〉 dislocation slip. Moreover, the relative slip activities obtained by the VPSC simulation also show a similar trend to those obtained from the CMWP evaluation.An understanding of deformation behavior and texture development is crucial for the formability improvement of Mg alloys. X-ray line profile analysis using the convolutional multiple whole profile (CMWP) fitting method allows the experimental determination of dislocation densities separately for different Burgers vectors up to a high deformation degree. A wider use of this technique still requires exploration and testing of various materials. In this regard, the reliability of the CMWP fitting method for Mg–Zn–Y alloys, in terms of the dislocation activity during tensile deformation, was verified in the present study by the combined analysis of electron backscatter diffraction (EBSD) investigation and visco-plastic self-consistent (VPSC) simulation. The predominant activity of non-basal 〈 The alloying addition of rare-earth (RE) elements or Ca affects the microstructure and texture development in Mg alloy, and has been acknowledged as an appropriate method to overcome the low formability at room temperature  and/or computer simulations based on dislocation and elastoplastic polycrystal models of deformation and texture  model, are largely dependent on the correct approximation of the initial parameters, and the precise data of stress–strain curves and the evolution of deformation texture are needed to provide qualified information for determination of the initial parameters. On the other hand, X-ray line profile analysis using in situ hard X-ray diffraction provides information on the deformation in a relatively large sample volume due to its high penetration depth. Furthermore, it provides remarkable resolution for the analysis of high dislocation density, even at relatively high strain levels. Simultaneously, the sample preparation for such in situ X-ray line profile analysis is relatively simple, due to non-destructive testing, and there is no sample damage caused by the irradiation. The CMWP  fitting method from X-ray line profile analysis has been applied to analyze specific dislocation slip systems based on well established physical principles in crystalline materials  beamline operated by the Helmholtz-Zentrum Hereon, P07B of PETRA III at the DESY (Deutsches Elektronen-Synchrotron) facility in Hamburg, Germany. A universal testing machine was installed at the beamline for tensile tests at room temperature with a initial strain rate of 1.0 × 10−3 s−1. The tensile sample was irradiated by hard X-rays with a beam size of 0.7 mm × 0.7 mm and an energy of 87.1 keV (wavelength = 0.142 Å). Debye–Scherrer diffraction rings were collected during the sample rotation of 105° in 3° steps using an area detector (PerkinElmer XRD 1621) with a fast read-out, at various strain values up to ɛ = 0.15. The measured data were processed about the transmutation of the diffraction pattern over selected omega and azimuth angles of the Deybe–Scherrer ring using the open source software FiT2D  alloy was gravity cast at 715°C into a rectangular steel mold and was machined as a slab with a thickness of 10 mm. Homogenization annealing was carried out at 420°C for 16 h prior to the rolling process. The annealed slab was rolled at 400°C by 15 passes to the final thickness of 1.1 mm with intermediate re-heating for 5–10 min after each rolling step for a stable rolling temperature of the slab. The rolled sheet was heat-treated at 350°C for 30 min to adjust the grain size to be appropriate for the CMWP fitting method with high grain statistics. Tensile samples with a gauge length of 18 mm and a thickness of 1.1 mm were machined along the sheet rolling direction (RD). The microstructure characterization and determination of the global texture of the sheet were performed using optical microscopy and X-ray diffractometry on mechanically polished surfaces using an oxide polishing suspension. An electron backscatter diffraction (EBSD) measurement of the initial sample was carried out using a field emission gun scanning electron microscope , at an accelerating voltage of 15 kV and a working distance of 14 mm. The EBSD measurement area was 250 µm × 600 µm, measured in 0.4 µm steps, after standard sample preparation followed by electrolytic polishing at 16 V and −20°C for 60 s.3.in situ diffraction study with a beam size of 0.7 mm × 0.7 mm at the synchrotron beamline. The annealed sheet has a weak texture with the basal poles tilted from the normal direction (ND) towards the transverse direction (TD) of the sheets with a relatively low basal pole intensity, Pmax = 2.8 m.r.d (multiple of random distribution), compared with the conventional Mg alloys, e.g. AZ31  plot allows identification of whether the deformation is mainly accommodated by dislocation slip or stacking faults such as twinning. In a WH plot, when the twinning activity is dominant during the deformation, the FWHM  of the high-order diffraction peak shows a similar amount of broadening as that of its low-order peak, a). It is apparent that the overall dislocation density increases with strain during the whole deformation, from approximately 2.2 × 1014 m−2 to 5.7 × 1014 m−2. This is in a good agreement with the anticipated finding of the WH plot ]. The density of the basal 〈a〉 dislocations remains at a low value of 0.5 × 1014 m−2, whereas the non-basal 〈a〉 and pyramidal 〈c+a〉 dislocations significantly increase with tensile deformation. The density of non-basal 〈a〉 dislocations reached the maximum value of about 4.2 × 1014 m−2, as the most activated dislocation, at ɛ = 0.15. It can be seen that the non-basal 〈a〉 dislocations contribute to the strain accommodation by having a ratio of more than two to three times that of the pyramidal 〈c+a〉 dislocations during the whole deformation [Fig. 5b)].The evolution of the overall dislocation density during the tensile deformation is shown in Fig. 4ot Fig. 3. The denYoo, 1981. Besidesa〉 and 〈c+a〉 dislocation slip systems of the annealed ZW10 sheet are presented in Fig. 6a〉, {a〉, {a〉 and {c+a〉 dislocation slip systems for tensile loading along the RD. It is clearly seen that the prismatic and pyramidal I 〈a〉 slip, as well as the pyramidal II 〈c+a〉 slip systems, have a large area with the SF in the range 0.4–0.5 [Fig. 6d)]. Fig. 7a〉 slip system. Most grains with an area fraction of 88% have favorable SF values for the non-basal slip systems, while the grains having a low SF value for the prismatic 〈a〉 slip system are favorable for the basal 〈a〉 slip.EBSD inverse pole figure maps, recalculated pole figures and SF (Schmid factor) maps for the 〈et al., 1991et al., 1991et al., 2007in situ experiments. The texture measured at the initial state was reproduced using MTEX to an ensemble of 5000 grains (orientations) for the simulation. The parameters of the VPSC simulation that result in the best fit to the in situ experimental results are listed in Table 1in situ experimental results, e.g. (0001) poles broadened towards the TD and (a)]. The activities of the deformation modes show a similar trend to those obtained from the CMWP analysis. The activity of the prismatic 〈a〉 dislocation slip, considered as non-basal 〈a〉 dislocations in the CMWP analysis, rapidly increases from the beginning of the deformation and remains as the main deformation mode, while the activity of the basal 〈a〉 slip system decreases with increasing strain. That is, the VPSC simulation results verify also that the deformation is mostly accommodated by the non-basal 〈a〉 dislocations [Fig. 8c)]. The pyramidal II 〈c+a〉 dislocation slip shows a gradual increasing activity during the deformation. It is also in good agreement with results of the CMWP evaluation. It is known that the CRSS value of the basal 〈a〉 slip system is considerably lower than that of non-basal slip systems in Mg alloys. Jain & Agnew :τ0(prism):τ0(pyra) = 1:2.3:2.8 in the present study. Note that the τ0 and τ1 values used in the VPSC simulation, in Table 1a〉 dislocation slip, or the decrease in the CRSS values of the non-basal dislocations slip in the ZW10 alloy.The reliability of the results obtained by the X-ray line profile analysis was also confirmed by the VPSC simulation. A detailed explanation of the VPSC model can be found elsewhere ]. A slight increase in basal 〈a〉 dislocation slip appears at the beginning of the plastic deformation, but it is not so noticeable, while the activities of non-basal 〈a〉 dislocations slip significantly increase. The higher activities of the non-basal slip systems even at the beginning of the plastic deformation can be understood to be as a result of the higher SF of the non-basal 〈a〉 dislocations slip [Fig. 6d)]. Moreover, the advantage in CRSS and SF of non-basal dislocations of the ZW10 sheet assures high activities even at high strain. The texture evolution of the in situ experiment shows that the (0001) poles gradually broadened towards the TD with increasing strain  alloy sheet, and the results regarding active deformation modes were further analyzed in comparison with EBSD measurements and VPSC simulation.The evolution of dislocation densities with different Burgers vectors was studied using the CMWP evaluation of the 14 m−2 to 5.7 × 1014 m−2.WH plots showing the broadening of the FWHM with strain indicate that the dislocation slip plays an important role in deformation accommodation of the ZW10. The overall dislocation densities increase with increasing deformation, from approximately 2.2 × 10a〉 dislocations remains at a low value of 0.5 × 1014 m−2, whereas the non-basal dislocations significantly increase with tensile deformation, especially non-basal 〈a〉 dislocations. The texture developments corresponding to the (a〉 dislocations.The density of basal 〈a〉 slips, as well as pyramidal II 〈c+a〉 slip systems. Moreover, the VPSC simulation also shows that the deformation is mostly accommodated by the dominant non-basal 〈a〉 slip systems and pyramidal II 〈c+a〉 slip system. These results indicate that the CMWP analysis is considerably reliable for evaluating the deformation modes and their behavior in Mg alloy sheets.EBSD analysis shows that a large area fraction of the annealed sheet has an SF value within the range 0.4–0.5 for the prismatic and pyramidal I 〈5.The raw/processed data required to reproduce these findings cannot be shared at this time as the data also form part of an ongoing study.


Bacterial WxL proteins contain peptidoglycan‐binding WxL domains, which have a dual Trp‐x‐Leu motif and are involved in virulence. It was recently shown that WxL proteins occur in gene clusters, containing typically a small WxL protein (which in the mature protein consists only of a WxL domain), a large WxL protein , and a conserved protein annotated as a Domain of Unknown Function (DUF). Here we analyze this DUF and show that it contains two tandem domains—DUF916 and DUF3324—which both have an IgG‐like fold and together form a single functional unit, connected to a C‐terminal transmembrane helix. DUF3324 is a stable domain, while DUF916 is less stable and is likely to require a stabilizing interaction with WxL. The protein is suggested to have an important role to bind and stabilize WxL on the peptidoglycan surface, via the DUF916 domain, and to bind to host cells via the DUF3324 domain. AlphaFold2 predicts that a β‐hairpin strand from DUF916 inserts into WxL adjacent to its N‐terminus. We therefore propose to rename the DUF916‐DUF3324 pair as WxL Interacting Protein (WxLIP), with DUF916, DUF3324 and the transmembrane helix forming the first, second and third domains of WxLIP, which we characterize as peptidoglycan binding domain (PGBD), host binding domain (HBD), and transmembrane helix (TMH) respectively. It is a domain of 160–190 amino acids containing two conserved motifs with the sequence Trp‐x‐Leu , L. monocytogenes (LmWxLIP1 and LmWxLIP2), E. faecium DO , and E. faecalis V583 (EfsWxLIP) ; however, when it does occur alone it is generally of roughly this length. In the context of WxLIP, the PGBD domain contains a 20‐residue insert, which we describe below as a buttressing loop, which functions to restrict the relative orientations of the PGBD and HBD domains within the full‐length WxLIP protein.EfmWxLIP2, which was anomalously small at 181 residues in length, and may represent a partial loss of function arising from loss of the HBD and TM domains. Siezen et al. , BL21 gold(DE3), and BL21(DE3) lemo. Each transformation was grown at three different temperatures, for three different times with three different concentrations of IPTG for induction. The BL21(DE3) lemo cells showed best expression. pDUF916_3 (the construct encoding HBD) showed good expression at 37°C using 1 mM IPTG for 4 h, and was found in the supernatant, while the other two constructs showed optimal expression at 25°C with 0.5 mM IPTG overnight, although at much lower levels  annotation, with most WxLIP consisting of three domains: PGBD, HBD and TMH. We suggest that it has a role in anchoring WxL onto the peptidoglycan layer and in linking the bacterial cell surface to its host.44.1The sequence retrieval was done with the help of Uniprot. The accession numbers of the proteins used in this study are detailed in Table 4.2https://web.expasy.org/protparam) and are listed in Table http://cello.life.nctu.edu.tw/), TargetP 2.0 (http://www.cbs.dtu.dk/services/TargetP/), cNLS Mapper (http://nls‐mapper.iab.keio.ac.jp/cgi‐bin/NLS_Mapper_form.cgi), TMHMM server v. 2.0 , HMMTOP (http://www.enzim.hu/hmmtop/html/submit.html), and Protter (https://wlab.ethz.ch/protter/start/). Interaction networks were identified using the STRING database (https://string-db.org) with a score cut‐off value of 0.40.Physicochemical properties were determined with the ProtParam tool available from ExPASy (4.3https://www.ebi.ac.uk/interpro/result/InterProScan/), Conserved Domain Architecture Retrieval Tool (CDART) (https://www.ncbi.nlm.nih.gov/Structure/lexington/lexington.cgi), Simple Modular Architecture Research Tool (SMART) (http://smart.embl-heidelberg.de/smart/show_motifs.pl), BlastP (https://blast.ncbi.nlm.nih.gov/Blast.cg), Motif finder (https://www.genome.jp/tools/motif/), and the PFP‐FunDSeqE predictor web server. InterProScan allows the scanning of sequences against the InterPro signatures collected from different databases    Edgar,  and visuE‐value below 1 × 10−10 are included in Table A set of 5482 bacterial genomes, each representing a different species, were obtained from GenBank. These were investigated for the presence of the WxL, DUF916, and DUF3324 domains  using the hmmsearch tool from HMMER version 3.3.2 Eddy, . hmmsear4.4https://alphafold.ebi.ac.uk)     are respectively EfmWxLIP1, EfmWxLIP2, EfmWxLIP3, and EfsWxLIP. The predicted structures were obtained in April 2021.FIGURE S4. Robetta prediction of WxLIP proteins. The proteins are the same as those shown in Figure FIGURE S5. Conserved residues in WxLIP. The comparisons are done between (a) proteins in the clusters of human symbionts from Figures FIGURE S6. Design of constructs for locus C domains. (a) Sequence alignment of WxLIP proteins. EfmWxLIP1, 2, and 3 represent Locus A, B, and C of E. faecium DO, and EfsWxLIP represents DUFE from E. faecalis V583. The sequence highlighted in yellow represents the signal peptide, dark blue is PGBD and cyan is HBD. Conserved residues are highlighted in red, sequences with one variation are highlighted in purple, and the highly conserved sequence NQIDK is boxed. β‐strand is shown as a blue arrow, the green spiral represents alpha helix, and the brown spiral represents the C‐terminal transmembrane helix. The sequences highlighted in red boxes indicate the starting and ending point of the three different constructs; SAS to NE is pDUF916 1, SAS to NN is pDUF916 2, and NE to NN is pDUF916 3. (b) Protein sequences. pDUF916 1, pDUF916 2, and pDUF916 3, with the 6 His‐Tag at the N‐terminus in sky blue followed by linker in bold. (c) Properties of the three constructs. The three constructs code for EfmWxLIP3 PGBD, EfmWxLIP3 PGBD and HBD, and EfmWxLIP3 HBD  respectively.FIGURE S7. Schematic representation of the different E. faecium DO Locus C EfmWxLIP3 domain constructs in pOPINF vectors. The three vectors pDUF916 1_pOPINF, pDUF916 2_pOPINF, and pDUF916 3_pOPINF are shown; Green is respectively PGBD, PGBD + HBD, and HBD in the three constructs, with a His‐Tag on the Nterminal end in sky blue.FIGURE S8. Analysis of supernatant from expression of E. faecium in BL21 (DE3) lemo. Lane 1: DUF916_2, 1 mM IPTG, 37°C, 4 h; Lane2: pDUF916_3, 1 mM IPTG, 37°C, 4 h; Lane 3: empty; Lane 4: unrelated protein; Lane 5: pDUF916_1, 0.5 mM IPTG, 25°C overnight; Lane 6: pDUF916_2, 0.5 mM IPTG, 25°C overnight; Lane 7: pDUF916_3, 0.5 mM IPTG, 25°C overnight; Lane 8: unrelated protein; Lane 9: pDUF916_1, 1 mM IPTG, 37°C, 4 h; Lane 10: pDUF916_2, 1 mM IPTG, 37°C, 4 h; Lane11: pDUF916_3, 1 mM IPTG, 37°C, 4 h; Lane 12: unrelated protein. The arrow indicates the expected position of DUF916_3 (18.2 kDa). DUF916_1 and DUF9196_2 are expected at 20.3 and 36.3 kDa respectively.Click here for additional data file.TABLE S5:Click here for additional data file.


One widely used approach for quantifying misinformation consumption and sharing is to evaluate the quality of the news domains that a user interacts with. However, different media organizations and fact-checkers have produced different sets of news domain quality ratings, raising questions about the reliability of these ratings. In this study, we compared six sets of expert ratings and found that they generally correlated highly with one another. We then created a comprehensive set of domain ratings for use by the research community , leveraging an ensemble “wisdom of experts” approach. To do so, we performed imputation together with principal component analysis to generate a set of aggregate ratings. The resulting rating set comprises 11,520 domains—the most extensive coverage to date—and correlates well with other rating sets that have more limited coverage. Together, these results suggest that experts generally agree on the relative quality of news domains, and the aggregate ratings that we generate offer a powerful research tool for evaluating the quality of news consumed or shared and the efficacy of misinformation interventions. Researchers, policymakers, and technology companies often quantify how much misinformation people share or are exposed to by looking at the quality of the news domains that they interact with. It remains unclear, however, to what extent different experts agree on the relative quality of different domains. This study compared ratings from different media organizations and fact-checkers and found that they correlated well with one another. We then used a “wisdom of experts” approach to aggregate these ratings to create the most comprehensive set of 11,520 domain ratings to date. Our results indicate that experts generally agree on the relative quality of news domains and our new set of ratings with extensive coverage offers a tool for evaluating content quality.Misinformation is not new, but concern over the problem has grown in recent years among researchers, policymakers, and technology companies. A large body of research has focused on understanding why people consume or share misinformation , and manA common measurement challenge in studies of misinformation is quantifying information quality. Many studies have taken the approach of classifying posts flagged by third-party fact-checkers as misinformation , 10–12. To address the scalability problem when analyzing social media data, researchers from many fields have used evaluations of the quality of news sites or domains as a whole, instead of the individual pieces of content found on these sites , 13–18. https://github.com/hauselin/domain-quality-ratings). Our rating set includes 11,520 domains, spanning a comprehensive range from high quality (e.g. Reuters and Associated Press) to low quality . Given the current lack of consensus across researchers on which rating set to use, and the limited coverage of some widely used rating sets, our aggregate set of ratings addresses important measurement problems in the field, which will result in better tools for quantifying misinformation, evaluating interventions, and facilitating theory development .The relatively strong correlations observed in Fig. The distributions of the imputed ratings for the various sources Fig. A and B rThe first principal component (PC1) of the PCA performed on the imputed data set explains 68.21% of the variance in the data, and the distribution of PC1 ratings resembles the aggregate of the other sources Fig. C and D. r = 0.43, or min r = 0.67, if Iffy binary is excluded; see Fig. The PC1 ratings span a wide range from low (0) to high (1) quality , they correlated slightly worse with other sources after imputation, partly because of the increased number of tied ratings.We perform robustness checks and validations on our data. Domains vary in terms of their importance or popularity, and we examine whether the correlations that we observe in the imputed data are robust after accounting for domain importance, which we quantified using the Open PageRank metric . It usesWe find that the domain-quality ratings provided by six different expert sources correlate highly with one another. Despite using different criteria to evaluate domains, different experts produce similar relative domain rankings. This finding indicates that there are common perceptions of relative differences in journalistic standards, which suggests that these differences in domain ratings may be veridical.By showing agreement across different expert ratings for the first time, our results provide evidence for the utility of fact-checked domain ratings for evaluating content quality. Prior studies have found less agreement, because they either defined agreement as the number of overlapping domains between different fake news lists  or incluOf pragmatic significance, the list of 11,520 domains in our aggregate set is, to our knowledge, the most comprehensive list of domain ratings to date. The PC1 explained almost 70% of the variance in the data, and the PC1 ratings correlated highly with the other imputed ratings (except for the Iffy index of unreliable sources). Thus, our PC1 ratings can serve as an aggregate domain quality measure, harnessing the “wisdom of experts” to produce an ensemble rating. The benefit of this approach is that biases unique to any particular set of ratings are less likely to have an influence, and the resulting ratings cover far more domains than any of the other existing rating lists. Naturally, if biases that are present across all of the sources for domain ratings, then they will nonetheless manifest in our imputed scores.In addition to facilitating research, the aggregate ratings could also be used as part of interventions against misinformation. For example, algorithms can focus more on lower-quality domains that are important or popular (e.g. inverse of PC1 weighted by domain importance), such that content from these domains is more likely to be flagged for human fact-checking. Recent work shows that displaying quality labels on social media posts can discourage the sharing of false claims , and ourA limitation of using domain ratings is that it assumes each domain produces content of identical quality, which is rarely (and perhaps never) the case. For example, the New York Times has a relatively high PC1 rating of 0.86, but its content can sometimes be fairly left-leaning or biased, even though factually accurate . ConversIn summary, our results suggest that there is substantial agreement across different sources of domain quality ratings, and that aggregated domain ratings provide a useful tool for advancing misinformation research. Domain ratings may not be as accurate as fact-checking individual pieces of content, but they offer a convenient tool for evaluating the efficacy of antimisinformation interventions. When used alongside other approaches like misinformation detection algorithms, professional fact-checkers, digital literacy education, and crowdsourced fact-checking, domain ratings can be a valuable tool for combating and studying misinformation.https://doi.org/10.17605/osf.io/9jwzs. These sources rated overlapping sets of domains  and code can be found at NewsGuard is a journalism and technology organization that rates the credibility of news and information websites. It evaluates domains on nine apolitical criteria, which are weighted differently to create a “Nutrition Label” . A ratinhttps://mediabiasfactcheck.com) is an independent website found by Dave Van Zandt and maintained by a team of researchers and journalists. It relies on human fact-checkers affiliated with the International Fact-Checking Network to evaluate media sources along different dimensions such as factual reporting and bias (Media Bias/Fact-Check (and bias . We manahttps://adfontesmedia.com) is a public benefit corporation that rates news articles on two dimensions: reliability (“AFM reliability”) and biasedness (which we recoded as unbiasedness: “AFM unbias”). Each article is rated by at least three human analysts with balanced left, right, and center self-reported political viewpoints . We manSixty domain ratings were obtained from Pennycook and Rand , who rechttps://github.com/JanaLasser/misinformation_domains). They rated domains on accuracy, reliability, and transparency. We computed the mean (“Lasser mean”) and minimum (“Lasser minimum”) ratings using the accuracy and transparency dimensions .Lasser et al.  compiledhttps://iffy.news) is one of the most extensive lists of unreliable or fake news domains . It includes domains that have been assigned a low credibility rating by MBFC . Note that it does not incorporate MBFC's political leaning ratings and has been used in many peer-reviewed studies   to imputpgad286_Supplementary_DataClick here for additional data file.


Gluten-free bread is an important product that is under development using different sources, such as rice and starchy plants. Teosinte seeds are utilized by ethnic groups in Honduras to produce gluten-free flour to prepare traditional baked goods and beverages. The quality of gluten-free products could vary depending on flour properties, such as amylose content, particle size, and water absorption capacity. A good strategy for developing baked goods is to mix different cereal grain sources to optimize their physicochemical properties. As a result, the current study aimed to develop bread from novel flours including teosinte (TF), high-protein brown rice (BRF), and high-protein white rice (WRF). Breads were analyzed for hardness, specific volume, and color utilizing a Simplex-Centroid mixture design coupled with the desirability function. Pasting, and rheological characteristics of the flours, were also analyzed. For flour characteristics, TF addition to BRF or WRF decreased the peak, trough, breakdown, setback, and final viscosities, which would result in a more stable bread and decrease the flow index of rice flour dispersions. BRF and WRF had similar pasting properties, except that BRF had a lower breakdown viscosity. For bread characteristics, TF addition to BRF or WRF increased the specific volume and hardness of the bread compared to rice flour alone. L* of the crust and crumb a* values were increased with greater TF in the mixture, whereas TF decreased the crust a*and b* values and crumb L* values when mixed with BRF or WRF compared to rice flours alone. WRF and BRF were similar in crumb color (L* and a*), except that BRF had greater crumb yellowness (b*). Teosinte flour can be used in combination with rice flour to produce bread with good quality. Bread uses the ability of hydrated gluten to build a viscoelastic network , which cHowever, gluten in bread can cause problems in a group of consumers. Celiac disease is an autoimmune disorder seen in people who genetically have the potential to develop an immune reaction to gluten. The first place affected by this disease is the small intestine; nevertheless, it has a wide distribution that includes both intestinal and extra-intestinal symptoms . CurrentGluten helps by forming a sticky, elastic dough with gas retention, as well as shaping the structure . In the Gluten-free bread available in the market is usually obtained by replacing wheat flour with rice flour with or without corn starch. Rice flour is known for its low price and mild taste, as well as antiallergenic properties, which is why it is utilized in these products. The rice flour used to prepare gluten-free bread is mostly from white rice . HoweverDioon mejiae) as an endemic tree in Honduras is one of the dioecious trees and belongs to the category of minor cereals. Minor cereals occur only in a few parts of the world, that is why their use on a large scale is not common. In addition to Teosinte, other plants including teff, millet , fonio (black and white), jungle rice, and Job’s tears are in this category [Teosinte . The bread formula was optimized using the desirability function methodology (DOM) [gy (DOM) . The objThe amounts of each ingredient used are shown in w/w were stirred at medium speed for 15 min and heated for 30 min. Instantly, hot paste (1 mL) was placed in the rheometer. When the sample temperature reached 25 °C, rheological analysis was performed with two types of evaluation (steady shear flow as well frequency sweep) using the method from Ye et al. [The pasting properties of the flours were evaluated based on the AACC method 61.02.01  by usinge et al.  with sliThe specific volume of bread (mL/g) was measured according to the AACC method 10-05  with rapFor the simplex-centroid design, generation of the corresponding response surfaces and coefficients of the special cubic model was performed in the Minitab 17 program  to check the characteristics of bread. One-way analysis of variance (ANOVA) and Tukey’s post-hoc test were conducted.Prepared bread samples are shown in Crust lightness (L*) was lowest for TF*WRF bread, while TF*WRF*BRF bread had a greater lightness compared to bread made from BRF*TF and BRF*WRF C. Crust 3 had the lowest redness (The crumb color pattern was different from the crust pattern. The lightness of the bread crumb F was low redness G among bn = 1, which corresponds to a Newtonian fluid [The combination of the WRF and BRF increased the yield stress and flow behavior index and TF had the lowest yield stress and flow behavior index F,G. Accoan fluid .The complex viscosity A decreasThis research examined the development of gluten-free bread by using TF, BRF, and WRF to observe the effects of the different sources on bread properties. Lower pasting properties, such as breakdown and setback viscosity, indicated that TF samples would be more stable. In bread, TF had negative effects on specific volume, texture, and color of breads, resulting in a greater hardness and greater crumb darkness, but these issues can be mitigated by using a combination of brown rice flour or white rice flour with teosinte flour to make the breads.


Plexin-B1 is a receptor for the cell surface semaphorin, Sema4D. This signaling system has been implicated in a variety of human diseases, including cancer, multiple sclerosis and osteoporosis. While inhibitors of the Plexin-B1:Sema4D interaction have been previously reported, understanding their mechanism has been hindered by an incomplete structural view of Plexin-B1. In this study, we have raised and characterized a pair of nanobodies that are specific for mouse Plexin-B1 and which inhibit the binding of Sema4D to mouse Plexin-B1 and its biological activity. Structural studies of these nanobodies reveal that they inhibit the binding of Sema4D in an allosteric manner, binding to epitopes not previously reported. In addition, we report the first unbound structure of human Plexin-B1, which reveals that Plexin-B1 undergoes a conformational change on Sema4D binding. These changes mirror those seen upon binding of allosteric peptide modulators, which suggests a new model for understanding Plexin-B1 signaling and provides a potential innovative route for therapeutic modulation of Plexin-B1. The plexins are a family of cell surface single transmembrane domain receptors for cell surface and soluble semaphorins. The semaphorin–plexin signaling system has been widely studied due to its roles in a diverse set of activities, such as neuronal connectivity and growth, cancers, cell migration, and immune responses. The semaphorin–plexin system is found in both vertebrates and invertebrates, as well as in simpler single and multicellular organisms .Plexin-B1 interacts with either Sema4A , Sema4B The intracellular region of Plexin-B1 interacts directly with some members of the Rho family of small GTPases through the Rho GTPase binding domain (RBD), which splits the GTPase-activating protein (GAP) domain of Plexin-B1 into two segments. The Plexin-B1 GAP domain binds R-Ras but does not bind H-Ras . The cytA), with a large insert which gives the sema domain a distinctive, asymmetrical shape (The extracellular domains of plexins consist of three domain types: the IPT domain (immunoglobulin domain shared by plexins and transcription factors), the PSI domain , and the sema domain. The PSI domains are small, disulfide-rich adapter domains, typically found between some of the immunoglobulin-like IPT domains, as well as between the sema domain and the first IPT domain. The sema domain is a seven-bladed β-propeller domain A, with aal shape . Sema doal shape . Semaphoal shape  or autoial shape .Figure 1B).The Plexin-B1 extracellular region contains 11 separate domains, with a N-terminal sema domain, followed by a PSI (PSI1), an IPT domain (IPT1), and a second PSI domain (PSI2). Following the second PSI domain is a large, 230 amino acid mucin-like domain, which is unique to the plexin-B family. Following the mucin-like domain are a further IPT domain (IPT2), PSI domain (PSI3), and a final four IPT domains (IPT3-6) . The oveFig. 1The extracellular domains of plexins have undergone significant structural study, although the plexin-As have been more extensively studied than the plexin Bs, C, or D, and have thus served as a model for the extracellular region of the whole plexin superfamily. The ten domain extracellular region of Plexin-A1 in the apo state forms a ring-like autoinhibited conformation in both crystal structures and negative stain electron microscopy .The interaction of the sema domains of plexins and semaphorins has also been structurally studied, and this identified that the interaction between the sema domains occurs on the top face of the domain. No extensive structural changes occur in the Plexin-A2:Sema6A complex between the free and the bound states of both Plexin-A2 and Sema6A , nor is Clinicaltrials.gov identifier: NCT03268057). In addition, antibodies directed against Plexin-B1 which block the interaction of human Plexin-B1 with ErbB-2 have been developed, although these do not affect Sema4D binding ] in complex with the sema and PSI1 domains of mouse Plexin-B1, both of which appear to inhibit the binding of Sema4D to Plexin-B1 in an allosteric manner. The nanobodies bind to a conformation of the sema domain which is similar to the Sema4D bound  and macr9 clones, and ∼80% of the clones encoded a VHH, based on the results of colony PCR and sequencing of 96 random clones. Sequencing results also revealed a reasonable diversity of complementarity-determining region 3 (CDR3) sequences. Three rounds of phage display selection were carried out to enrich for Plexin-B1-specific VHHs.To generate VHHs that bind Plexin-B1 and inhibit Sema4D binding, a huarizo was immunized with mouse Plexin-B1 domains 1 and 2 . A VHH phage display library was then generated from isolated lymphocyte mRNA. The library contained 3 × 10Ninety-six random clones from each of the second and third rounds of selection were sequenced. Sequence analysis revealed ten unique CDR3 sequences from six distinct families . SequencB), whereas most of them did not recognize human Plexin-B1, with the exception of VHH16-2, which interacted weakly with human Plexin-B1 (A). VHH12 did not bind mouse Plexin-B1 in the BLI experiments. Two VHH-Fc efficiently blocked Sema4D binding to mouse Plexin-B1, identified as VHH14 and VHH15 .The biological activity of the nanobodies identified was assessed using a COS-7 collapse assay , which rectively , A and BB). Human plexins were not tested, since the nanobodies were known to not bind human Plexin-B1 from BLI experiments (A). The lack of activity of the isotype control VHH-Fc indicated that the inhibition of plexin signaling was solely due to the VHH domain of VHH14-Fc and VHH15-Fc.The specificity of the VHHs for mouse Plexin-B1 was demonstrated in the same system. Neither VHH14-Fc nor VHH15-Fc was able to inhibit Sema4D-induced cell collapse for cells transfected with mouse Plexin-B2 B. Human eriments A. The lar 5000) resulted in a change of crystal morphology, and these crystals diffracted to 2.95 Å  dextran sulfate (Mo 2.95 Å .Table 1X3OL2), with a Cα RMSD of 1.55/1.24 Å for the A and B chains, respectively, as expected given the high sequence identity of 87.6% between the human and murine domains 1 and 2. The majority of the nanobody is well defined in the complex, with the exception of the C-terminal 6xHis tag. CDR1, CDR2, and CDR3 are all well-defined, with an additional disulfide bond seen between Cys50 and Cys108, serving to anchor CDR3 to the framework on the C′ strand. CDR2 is composed exclusively of serine and glycine residues and does not interact with mPlexin-B1.The crystals contained two copies of the complex of mPlexin-B1 with VHH15 in the asymmetric unit. The two copies were highly similar, with an overall Cα RMSD of 0.754 Å between the mPlexin-B1 monomers and 0.475 Å between the VHH15 monomers, respectively. The structure of mPlexin-B1 was also highly similar to the published structure of human Plexin-B1 bound to Sema4D . VHH15 binds to one face of the sema domain of mPlexin-B1 (A and B), on the opposite face to the N terminus, and does not overlap the Sema4D binding site which is located on the top surface of the semaphorin domain . When the structure of human Plexin-B1 bound to Sema4D is compared to the structure of VHH15 bound to mouse Plexin-B1, it can be seen that there is no overlap between Sema4D and VHH15 (C and D) indicating that the VHH probably inhibits the binding of Sema4D in an allosteric manner. The nanobody interacts with blades 1, 2, 3, and 7 of the semaphorin domain (A), specifically the D7-A1 loop, B1-C1 loop, D1-A2 insertion, D2-A3 loop, B3-C3 loop, D6-A7 loop, and B7-C7 loop (A and B).The interface of mPlexin-B1 with VHH15 buries 892/904 Ålexin-B1 , A and Bmain 18, A. When tnd VHH15 , C and Dn domain A, specif-C7 loop , A and BC and D). Specifically, the interface involves Val2 from the N terminus, Gly26, Tyr31, and Tyr32 from CDR1, Arg45 from the C′ strand, Ser99, to Met111 from CDR3 and Asp112, Tyr113 and Trp114 from the G strand. The interaction surface buries 871/891 Å2 or 13.1%/13.5% of the surface area of the two copies of VHH15 present, chains B and D, respectively.The mPlexin-B1 interaction surface on VHH15 is mainly composed of residues from CDR1 and CDR3, together with residues from the N terminus, and the C′ as well as the G strand , C and DB) identified several amino acids differences, which were in close proximity to the binding interface of VHH15 with mPlexin-B1 and could contribute to the selectivity of VHH15 for murine Plexin-B1 over human. Visual inspection of the overlayed structures identified His34, which forms a hydrogen bond between the side chain and the backbone carbonyl of Tyr31 in CDR1 as being of interest. This residue is a tyrosine in human Plexin-B1, and inspection of the crystal structure indicated that the side chain of the tyrosine in human Plexin-B1 would clash with CDR1 of VHH15 in the complex (A). To test the importance of this sequence difference, a H34Y P240Q mutant of mPlexin-B1 was assayed for binding to VHH15 via biolayer interferometry and was found to show minimal detectable binding to mPlexin-B1 (D). This indicates that this single amino acid change is largely responsible for the selectivity of VHH15 for murine over human Plexin-B1.Analysis of the sequence differences in the sema domains of human and murine Plexin-B1 B identif complex A. To teslexin-B1 D. This iAttempts to obtain a well-diffracting crystal of VHH14 bound to mPlexin-B1 (20–535) were not successful, so a ternary complex of both VHH14 and VHH15 with mPlexin-B1 was pursued. Epitope binning experiments indicated that both VHH14 and VHH15 were capable of simultaneously binding to mPlexin-B1 . Size-exvia the sema domain, on the same face as VHH15 (A and B), but on the opposite side of that face to VHH15. Comparison of Sema4D bound to human Plexin-B1 with VHH14 bound to mouse Plexin-B1 showed that there was no overlap between Sema4D and VHH14 when the sema domains of Plexin-B1 were aligned (C and D). Whilst CDR3 is found in close proximity to residues 348 to 352 in human Sema4D (D), and may, partially interfere with the binding of Sema4D, overall, the suggestions that the mechanism of Sema4D-binding inhibition by VHH14 is likely to be allosteric.The binding interface of mPlexin-B1 with VHH15 was essentially unchanged from the 2.95 Å structure of the mPlexin-B1:VHH15 complex. As in the binary complex, VHH15 was well defined in the electron density, with the entire protein chain visible, apart from the C-terminal 6xHis tag. VHH14 was found to bind to mPlexin-B1 as VHH15 , A and B aligned , C and Dn Sema4D D, and maThe structure of mPlexin-B1 in the ternary complex is highly similar between the two copies of the protein in the asymmetric unit, with a Cα RMSD of 0.723 Å. The two are also highly similar to the structure of mPlexin-B1 found in the VHH15 complex, with a Cα RMSD of 0.763 Å between chain C and its most similar counterpart in the VHH15 structure (chain A), and 0.689 Å between chain F and its most similar chain in the VHH15 structure (chain B). The overall conformation of the sema domain of plexin has not changed between the single and double complex, and this is confirmed by a visual examination of the structural alignment of the different mPlexin-B1 chains. Some subtle changes are observed, particularly in the loops contacting VHH14, but the binding interface with Sema4D is essentially unchanged between the two complexes.2 on mPlexin-B1 chains C and F, respectively, or 4.1% of the surface of mPlexin-B1 D1-2. The total buried surface of the interface is very similar between VHH14 and VHH15 and is consistent with the average areas of nanobody:target interfaces (A and B). The nanobody also interacts with the N-linked glycan found on N349 through Y31 (D), with the N-acetylglucosamine moiety, and the side chain of Y31 both well defined in the electron density . The majority of VHH14 is well defined for both chains present, with a single region of poor density, Gly9-Gly16 in chain A. This region is found at the base of the nanobody and is not close to the paratope region. The interaction buries 913/923 Å2 on chains A and D, respectively, consisting of 13.9%/14.2% of the total surface area of VHH14.The interaction surface on VHH14 involves contributions from all three CDR loops, as well as contributions from the N terminus. CDR3 binds into the grove between blades 4 and 5 of the sema domain, with residues A98, A99, E101, V103, and V105, contributing to this section of the interface. CDR1 interacts with the C5-D5 insertion, primarily though Y31 interacting with the N349 glycan , C and DB) are found near the interface of VHH14 and mPlexin-B1; however, one nonconserved amino acid was identified by visual inspection of the structure as a potentially critical residue to the selectivity of VHH14 for murine Plexin-B1. Proline-240 is found in the center of the B4-C4 loop of mPlexin-B1, which binds in a cleft between the N terminus, CDR1 and CDR3. This residue is a glutamine in human Plexin-B1, which was postulated to interfere with the binding of VHH14 (B). This was tested through assessing the binding of mPlexin-B1 (20–535) H34Y P240Q to VHH14 via BLI (A and B). This revealed in a KD for the interaction of 255 nM compared to 3.13 nM WT mPlexin-B1 under the same conditions (E), suggesting that this residue is important for the selectivity of VHH14 for mPlexin-B1 over hPlexin-B1. The relatively lower effect of this mutation, compared to the H34Y mutation, may indicate that the N349 glycan makes a significant contribution to the affinity of VHH14 to mPlexin-B1 and the selectivity for mPlexin-B1 over hPlexin-B1. This glycan is absent in human Plexin-B1, as the asparagine to which the glycan is attached in mPlexin-B1 is an aspartate in hPlexin-B1 (B). The side chain of N349 in mouse Plexin-B1 is positioned over 6 Å from VHH14, and the side chain of D349 in human Plexin-B1 is positioned even further from the VHH14 binding site, indicating that the lack of the glycan in human is the key difference as opposed to the asparagine to aspartate change as significant structural re-arrangement would need to occur to allow VHH14 to contact this residue.Relatively few of the sequence differences that occur between the sema domain of murine and human Plexin-B1 B are fouof VHH14 B. This w via BLI , A and Bnditions E, suggeslexin-B1 B. The siTo further understand the mechanism of the VHHs inhibition of Sema4D binding to Plexin-B1, the structure of human Plexin-B1 (20–535) was solved by X-ray crystallography to a resolution of 2.69 Å , with th3OL2, Fig. 1A), with a Cα RMSD of 1.87/1.80 Å for chains A and B, respectively. When only the sema domains are considered, the Cα RMSD drops to 1.72/1.67 Å. These Cα RMSDs are greater than those observed for mPlexin-B1 from the VHH15 complex compared to the Sema4D bound structure of human Plexin-B1. Several cadmium ions were found in the crystal structure, some of which support the crystal packing observed.The overall structure of hPlexin-B1 was similar to the published structure of Sema4D bound hPlexin-B1  and the structures reported here, suggesting that the loops in this domain are flexible. For this reason, changes in the PSI1 domain between published and herein reported structures were not considered in the analysis.Initial Cα RMSD comparisons of the two chains found in the apo human Plexin-B1 structure revealed that the PSI domain (480–535) undergoes significant loop movements within the crystal form, as do several loops in the sema domain . This inA and B). These form concerted movements that are transmitted through the sema domain, including subtle twisting motions of the beta strands and associated blades of the sema domain. The largest movements seen are up to 15.2 Å in the position of the A5-B5 loop (A). In the apo structure, this loop is folded over and interacts with the cleft between blades 5 and 6 of the sema domain (C). This region in the structure is the site to which the allosteric inhibitory peptide PB1m6 peptide binds to which was previously thought to be a preformed cleft in the sema domain (A), and the whole loop is visible within the structure of apo hPlexin-B1 reported here (B). This loop varies significantly in length as well as sequence between the different plexin subclasses. The length of the loop between the A5 and B5 strands varies from 19 residues in murine Plexin-A2 to 11 residues in human Plexin-B1 and six residues in Plexin-C1. The intermediate loop length in Plexin-B1 provides the flexibility and length to allow these conformational changes between the apo and bound states, without forming the more stable, additional secondary structure seen in Plexin-A2.These conformational differences seen between the two copies of apo hPlexin-B1 present were used as reference points for the conformational changes observed between the apo and the Sema4D bound form. Contrary to what has been reported for Plexin-A2 , our ana-B5 loop A. In thea domain C. This ra domain . Althouga domain A, and thted here B. This lA), such as the A3-B3 loop, the B3-C3 loop, B4-C4 loop, C4-D4 loop, B5-C5 loop, and the C6-D6 loop. The C6-D6 loop is adjacent to the cleft formed by the motion of the A5-B5 loop in the Sema4D bound structure and is further retracted from this region in the apo structure, presumably to allow space for the insertion of the A5-B5 loop in the apo structure reported here (C). These additional changes are smaller in magnitude than those seen in the A5-B5 loop and do not occur in regions of the Plexin-B1 sema domain known to be involved in ligand or coreceptor binding.Regions of increased RMSD also identify that conformational changes are seen in several loops on both faces of the sema domain A, such ated here C. These 3OL2). In the C6-D6 and A5-B5 loop regions, the AlphaFold model shows a similar closed cleft to the apo structure, albeit with the C6-D6 loop inserting further into the cleft, and the A5-B5 loop in a more open conformation than the experimentally determined structure (Subsequent to the determination of the structure of apo human Plexin-B1 (20–535), a model of full-length human Plexin-B1 was determined by AlphaFold , 32. Thetructure .A). As with the apo human Plexin-B1 structure, these changes were considered to be due to the inherent flexibility of the PSI domain and its interface with the sema domain.In order to understand the allosteric mechanism of VHH14 and VHH15 inhibition of Sema4D binding, the structure of the sema domain of murine Plexin-B1 bound to both nanobodies was compared to the Sema4D bound and apo conformations of human Plexin-B1. Similar to the changes observed between the apo structures, a substantial variation was observed in the PSI domain A. As witC), was seen to adopt a conformation similar to that observed in the Sema4D-bound structure (C). A movement of up to 7.89 Å (A) was also observed in the B5-C5 loop. This loop interacts directly with VHH14, via CDR3, but the tip of the loop remains highly flexible and not visible in the electron density, as with the apo structures. In the VHH15 only complex, this loop is also flexible and is not visible in the electron density. The movements in this loop in the VHH14 complex may be involved in the inhibitory mechanism of that nanobody but do not appear to be required for the action of VHH15.Subtle changes in the positioning of the loops involved in the binding interface of Plexin-B1 with Sema4D were observed with the nanobody-bound mPlexin-B1. The degree to which these changes are responsible for the inhibition of Sema4D binding to Plexin-B1 is not clear, since these changes are small and would not cause apparent steric clashes between Sema4D and nanobody-bound Plexin-B1 . InteresFig. 10tructure C. A moveo 7.89 Å A was alsThe two inhibitory nanobodies appear to induce a mouse Plexin-B1 a conformation similar to the Sema4D-bound structure  and to tPrevious structural studies of plexins and semaphorins have concluded that their ligand binding sema domains are relatively rigid structures , with thThe work presented here questions this paradigm by showing that the sema domain of Plexin-B1 undergoes significant structural rearrangement upon semaphorin binding . This suB and 11B). It is particularly interesting that all of the allosteric inhibitors of Sema4D binding discovered to date bind to a Sema4D-bound like conformation of the sema domain of Plexin-B1. The bound conformation seen in the crystal structure is likely to be, therefore, a low-affinity conformation, perhaps allowing for the release of bound Sema4D from the complex.The structures of the nanobody complexes presented here reveal that the sema domain of Plexin-B1 has multiple allosteric sites. Indeed, had further inhibitory nanobodies been identified, additional allosteric sites may well have been discovered, since the structural changes that occur on the binding of allosteric inhibitors, as well as ligand binding, extend around the entire sema domain B and 11Bvia conformational changes and that these conformational changes are key for transmission of signals from semaphorin binding to activate the intracellular domain of Plexin-B1. This opens multiple new avenues to explore the biological activity of Plexin-Bs and suggests multiple options for the pharmaceutical modulation of Plexin-B1 activity.Overall, the results and analysis presented here indicate that the sema domain of Plexin-B1 is primed for allosteric regulation 280, aliquoted, and flash-frozen for storage at −80 °C. Purified human and murine Plexin-B1 (20–535) were analyzed by mass spectrometry and SEC-MALS to confirm identity and quality. An Avi-tagged version of mouse Plexin-B1 (20–535) was generated by insertion of the Avi-tag (GLNDIFEAQKIEWHE) between the C terminus of the Plexin-B1 fragment and the 6xHis-tag using the QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies). The resulting mouse Plexin-B1 (20–535)-Avi-6xHis construct was expressed and purified using the same method as described for nonmodified version. The in vitro biotinylation of the Avi-tagged protein was carried out using the BirA enzyme  according to the manufacturer’s protocol. Free biotin was removed by a desalting method using Zeba Spin 7K desalting columns (ThermoFisher). The biotinylation was verified by Western blotting analysis using Streptavidin-HRP conjugate . Recombinant Sema4D (1–677) with C-terminal 6xHis-tag in a pcDNA5 vector was expressed, purified, and analyzed using the method described for Plexin-B1 constructs above.A DNA sequence encoding humanPlexin-B1 (1–535) or corresponding residues of mouse Plexin-B1 (1–535) was cloned into a pcDNA5 vector with the addition of a C-terminal 6xHis-tag. The plasmids were transfected into Expi293F cells (Invitrogen) according to manufacturer’s instructions. Supernatant containing secreted Plexin-B1 (residues 20–535) was collected after 7 days and purified using two-step purification protocol. Briefly, secreted protein was captured on an Excel HisTrap  column. After washing the column with 10 column volumes of 20 mM imidazole, the protein was eluted with 250 mM imidazole. This was followed with gel filtration chromatography using a Superdex 200 16/600 column equilibrated with PBS. Protein containing fractions were analyzed on SDS-PAGE, pooled, quantified by AAn adult huarizo was subjected to four subcutaneous injections, each containing 300 μg of purified mouse Plexin-B1(20–535)-6xHis protein in emulsion of Freund’s adjuvant (CFA/IFA). The injections were administered at day 1, 28, 42, and 56 over a total period of 60 days (Preclinics). Serum from blood samples collected on day 0, 52, and 60 were titered by binding ELISA to determine the antigen-specific immune response.et al.  were used for total RNA extraction using a RNeasy Midi kit (Qiagen). Two microgram of the total RNA was converted to cDNA using the Superscript III First-strand synthesis kit (Invitrogen) with a CH2 domain gene-specific primer. Amplification of variable regions of heavy-chain immunoglobulins (VHHs) from the cDNA was performed by 2-stage PCR, as described by Ghassabeh et al.  followedBacteriophage expressing anti-Plexin-B1 VHH were produced by infecting the bacterial library with M13K07 helper phage and were precipitated from culture media with 20% (w/v) PEG 8000, 2.5 M NaCl, and resuspended in PBS. Three rounds of selection using murine Plexin-B1 (20–535) were performed. The outputs from each selection round were used to infect exponential growing TG1 cells which were plated on agar plates. Colonies from the second and third rounds were sequenced and high-frequency CDRs identified using AptaAnalyser .Plasmid DNA encoding the most frequent clone within each VHH CDR3 family was purified using the QIAprep Spin Miniprep Kit (Qiagen) following manufacturer’s instructions. VHH encoding sequences were subcloned by ligation-independent cloning into the pHCMVi-Script HuIgG1 Fc vector from pHEN1H6 plasmids encoding the VHHs. Incorporation of the correct insert into the pHCMVi vector was confirmed by DNA sequencing.Expi293F cells were transfected with 1 μg of a pHCMVi-Script plasmid encoding VHH-Fc in a 24-well plate and 1 ml final volume using the Expi293 expression system kit (Gibco) and following the manufacturer’s instructions. Five days posttransfection the cells were centrifuged, and supernatants were collected. The production of a secreted VHH-Fc was verified by SDS-PAGE under reducing and nonreducing conditions. The amount of expressed VHH-Fc in each supernatant was quantified by using Protein G biosensors on an Octet RED384 instrument (ForteBio), calibrated to previously purified isotype control VHH-Fc.VHH14-Fc and VHH15-Fc were subsequently expressed in 200 ml cultures of Expi293F cells as described above apart from using 200 μg plasmid DNA for transfection. The supernatants were collected 7 days posttransfection by centrifuging the culture and filtering the supernatant through a 0.22 μm filter unit. A two-step purification was performed for VHH14-Fc and VHH15-Fc. The supernatant was initially loaded onto a HiTrap MabSelect column (Cytiva) and eluted with 0.1 M sodium citrate pH 3.0. The eluted fractions were neutralized with 1 M Tris pH 9.2 prior to loading onto a HiLoad Superdex 200 26/600 pg column  equilibrated in PBS.pHCMVi-Script plasmids encoding VHH14 and VHH15 with C-terminal 6xHis-tag were generated using In-Fusion cloning (Clontech) by PCR amplifying DNA fragments from the pHCMVi-Script-VHH-Fc plasmids and introducing a 6xHis-tag. Correct incorporation of the insert and 6xHis-tag was confirmed by DNA sequencing.VHH14-6xHis and VHH15-6xHis were also expressed in Expi293F cells following transfection with pHCMVi-Script plasmid encoding VHH14-6xHis or VHH15-6xHis. VHH14-6xHis and VHH15-6xHis were purified from Expi293 supernatants by immobilized metal affinity and size-exclusion chromatography. The fractions containing purified protein were pooled and assessed by SDS-PAGE, with the identity of the purified protein confirmed by mass spectrometry and homogeneity of the purified protein confirmed by SEC-MALS.on and koff values.The binding experiments were carried out at 25 °C using an Octet RED384 (ForteBio). 1× Kinetics buffer (ForteBio) was used for dilutions and as the assay buffer. To characterize the interaction between mouse Plexin-B1 and purified VHH-Fcs, VHH14-Fc or VHH15-Fc were first immobilized on Protein G biosensors by incubating the sensors in 0.67 μg/ml VHH-Fc for 200s. The sensors were then incubated for 120s in the assay buffer to establish the baseline. VHH14-Fc loaded sensors were incubated in 10, 7.5, 5, and 3.75 nM mouse Plexin-B1 for 1800s followed by 7200s dissociation; VHH15-Fc loaded sensors were incubated in 1:2 serial dilutions of mouse Plexin-B1 starting from 160 nM for 600s followed by 510s dissociation. A control was run in parallel with a reference sensor with no VHH-Fc immobilized. For comparisons of mouse Plexin-B1 (20–535) wildtype and H34Y P240Q binding to VHH14-Fc and VHH15-Fc, VHH-Fc-loaded biosensors were incubated in 400 nM, 200 nM, 100 nM, 50 nM 25 nM, 12.5 nM and 6.25 nM mPlexin-B1 for 300s, followed by dissociation in assay buffer for 600s. Data were analyzed using the Kinetics module of the ForteBio Data Analysis software 11.1 and GraphPad Prism 9.4.1. Reference sensor data were subtracted from the ligand sensor data. Global analysis of multiple mouse Plexin-B1 concentrations and a 1:1 model was used to fit the data and obtain kVHH-Fc inhibition of Sema4D binding to Plexin-B1 was assayed using an Octet RED384 (ForteBio). 1× Kinetics buffer (ForteBio) was used for dilutions and as the assay buffer. Murine Plexin-B1 was immobilized on streptavidin biosensors by incubating the sensors in 50 nM biotinylated murine Plexin-B1 (25–535)-Avitag-6xHis for 300s, followed by 180s incubation of sensors in the assay buffer. The sensors were then transferred to 100 nM VHH-Fc for 300s, followed by either 10 μg/ml human Sema4D or assay buffer for 300s, and finally the assay buffer for 600s. In addition, a sensor without any VHH-Fc immobilized was included for detection of maximum Sema4D binding to murine Plexin-B1.2 and passaged at 80 to 90%. COS-7 cells were then seeded in 96-well plates (Greiner) at 6500 cells per well in a total volume of 100 μl per well and transiently transfected 24 h later with plexin pcDNA3.1 plasmids, using the X-treme Gene 9 transfection reagent according to the manufacture instructions (Sigma).Full-length mouse Plexin-B1-FLAG and Plexin-B2-FLAG pcDNA3.1 plasmids were purchased from GenScript. COS-7 cells were purchased from ATCC and cultured in high-glucose Dulbecco’s modified Eagle’s medium supplemented with GlutaMAX, pyruvates (Gibco) and 10% fetal bovine serum (Gibco). Cells were cultured at 37 °C in 10% COAfter transfection for 48 h, anti-Plexin-B1 VHH14-Fc, VHH15 -Fc nanobodies, or the isotype control nanobody-Fc at a concentration of 0.01 to 10 nM (for Plexin-B1) or 150 nM (for Plexin-B2) were added, incubated for 1 h, and followed by an additional 1 h treatment with 50 nM Sema4D (for Plexin-B1) or 150 nM Sema4D (for Plexin-B2). Cells mock-treated with media instead of VHH-Fcs were incubated with 0.08 to 50 nM (Plexin-B1) or 10 to 150 nM (Plexin-B2) Sema4D for a Sema4D dose response to confirm correct Plexin-B activity following transfection.50 values using a five-parameter equation.Cells were fixed with 4% formaldehyde, permeabilized, and incubated with an anti-FLAG antibody , followed by staining with an anti-mouse-Alexa Fluor 488 secondary antibody , Hoechst , and Phalloidin Texas Red . After staining, the plates were imaged using a high-content screening system . Images were analyzed and the number of collapsed cells per well was quantified manually. Nonlinear regression in GraphPad Prism was used to calculate ICAll single complexes of VHH-bound Plexin-B1 for crystallization were prepared by mixing a 20% molar excess of VHH with murine Plexin-B1, and 5000u of EndoH (NEB) in PBS, pH 7.4. This was dialyzed overnight at 4 °C against 25 mM Tris-HCl, pH 7.5, and 50 mM NaCl. The complex was then purified by size-exclusion chromatography using a Superdex 200 16/600 pg column , equilibrated in 25 mM Tris-HCl, pH 7.5, and 50 mM NaCl. Plexin-B1 apo samples were prepared using the same method, except that a Superdex 75 16/600 pg column  was used.2, and stored at −80 °C.The ternary complex of VHH14 and VHH15 with murine Plexin-B1 was prepared by adding a 20% molar excess of VHH15 to purified VHH14:mPlexin-B1 complex, without the addition of further EndoH, followed by purification by size-exclusion chromatography, using a Superdex 200 16/600 pg column equilibrated in 25 mM Tris-HCl, pH7.5 and 50 mM NaCl. All complexes were concentrated to 10 mg/ml using Vivaspin centrifugal concentrators (Sartorius), flash-frozen using liquid NSuitable protein concentrations for crystallization were identified using a Pre-Crystallization Test (PCT) (Hampton Research). Initial crystallization trials were performed using sitting-drop vapor diffusion and 96-well deep well block screens  at 18 °C. Crystal hits identified from screens were optimized in 15-well hanging drop plates (Qiagen).r 5000 (Hampton Research) was used to grow optimal crystals by hanging-drop vapor diffusion in 8% (w/v) PEG 8000, 0.1 M sodium citrate, pH 5.0, 1% (w/v) dextran-sulphate (Mr 5000) at a protein concentration of 5 mg/ml and 18 °C. A cryoprotectant of 22% ethylene glycol in mother liquor was used. X-ray diffraction data were collected at the BESSY II synchrotron (Berlin) using beamline 14.1  at 18 °C using the original crystal hit condition. Batch-matched dextran-sulphate Mine 14.1 .r 5000 (Hampton Research) was used to grow optimal crystals by hanging-drop vapor diffusion in 15% (w/v) PEG 6000, 0.1 M sodium citrate, pH 5.5, 3% dextran sulphate (Mr 5000) at a protein concentration of 5 mg/ml and 18 °C. A cryoprotectant of 22% ethylene glycol in mother liquor was used. X-ray diffraction data were collected at the ESRF synchrotron (Grenoble) using beamline ID23-2.For the VHH14:VHH15:mPlexin-B1 complex, additive screening was also performed using the Hampton Research Additive Screen (Hampton Research) at 18 °C using the original crystal hit condition. Batch-matched dextran-sulphate MOptimal crystals of human Plexin-B1 were grown in 1.0 M sodium acetate, 0.2 M cadmium sulphate, 0.1 M Hepes, pH 7.5, at a protein concentration of 5 mg/ml and 18 °C. The crystals were cryoprotected by increasing the sodium acetate concentration to 2.5 M, and diffraction data were collected at the Diamond Light Source  using beamline I04.X-ray diffraction images were indexed and integrated with XDS  or DIALS3OL2) using SWISS-MODEL (5TOK) as a template, were used as the search models. For the hPlexin-B1 apo structure, the hPlexin-B1 component of the deposited structure of hPlexin-B1 bound to Sema4D (PDB:3OL2) was used as the search model.For the VHH15:mPlexin-B1 complex, a model of the murine Plexin-B1 sema-PSI domain was prepared from the deposited human Plexin-B1: Sema4D complex structure , on Cα, with no cycles of outlier rejection performed. For sema domain only alignments, the final residue of the sema domain used was the conserved P478.The VHH15:mPlexin-B1, VHH14:VHH15:mPlexin-B1 and hPlexin-B1 crystal structures reported here are available in the RSCB PDB under accession codes 8BB7, 8BF4 and 8B3K, respectively.BioLayer Interferometry sensorgrams can be provided upon request.This article contains The authors declare no conflicts of interest with the contents of this article.


Mycobacterium tuberculosis, pose a significant global health challenge, with 1.6 million reported deaths in 2021, making it the most fatal disease caused by a single infectious agent. The rise of drug-resistant infectious diseases adds to the urgency of finding effective and safe intervention therapies. Antisense therapy uses antisense oligonucleotides (ASOs) that are short, chemically modified, single-stranded deoxyribonucleotide molecules complementary to their mRNA target. Due to their designed target specificity and inhibition of a disease-causing gene at the mRNA level, antisense therapy has gained interest as a potential therapeutic approach. This type of therapy is currently utilized in numerous diseases, such as cancer and genetic disorders. Currently, there are limited but steadily increasing studies available that report on the use of ASOs as treatment for infectious diseases. This review explores the sustainability of FDA-approved and preclinically tested ASOs as a treatment for infectious diseases and the adaptability of ASOs for chemical modifications resulting in reduced side effects with improved drug delivery; thus, highlighting the potential therapeutic uses of ASOs for treating infectious diseases.Infectious diseases, particularly Tuberculosis (TB) caused by  Antisense therapy involves administering antisense oligonucleotides (ASOs) to targets and inhibiting the translation of disease-associated messenger RNA (mRNA) . ASOs arASOs can be categorized into two broad modes of action based on their design: RNA cleavage and RNA blockage. ASO-mediated RNA cleavage involves molecular RNA degradation using ribonuclease RNAse-1-H  or gene The major challenge with current antimicrobial therapies for infectious diseases is the emergence of multi-drug-resistant pathogens, as seen in tuberculosis, the leading cause of global death due to drug-resistant strains . TherefoPreviously, chemically unmodified ASOs were ineffective as RNA therapeutics due to their larger size, charge, and the presence of the phosphodiester bond. These characteristics hindered the passive diffusion of ASOs into the target cell , renderiThe second generation of ASOs includes 2′-modified phosphorothioates, such as 2′-O-methyl (2′-O-Me) and 2′-O-methoxyethyl (2′-O-MOE) oligonucleotides, which have alkyl modifications at the 2′-position of the ribose . These AThe third generation comprises Phosphorodiamidate Morpholino Oligomers (PMOs) with morpholine rings as a backbone connected with Phosphorodiamidate linkages , PeptideDrug delivery to the target site poses a significant challenge in ASO therapies, primarily because ASOs must surmount biological barriers, escape lysosomal degradation, and avoid becoming trapped in secretory vesicles . To addrIn addition to GalNAc conjugation, researchers are also exploring nano-drug vehicles, such as liposomes, for ASO delivery . LiposomThe use of ASOs as a treatment for diseases offers significant advantages in therapeutics. ASOs can be specifically modified and applied for different diseases or unique genetic disorders, such as Milasen, which is tailored to individual patients . ASOs fuThe RNA-degrading ASOs rely on RNase H-mediated RNA degradation, involving the binding of the target mRNA’s RNA-DNA heteroduplex to the complementary ASO . This reRNA-blocking ASOs have been primarily used as a treatment for genetic disorders like Duchenne Muscular Dystrophy (DMD). In this approach, ASOs repair the reading frame, resulting in the production of a functional protein . ASOs’ aVitravene, also known as fomivirsen, was the pioneering ASO-approved drug, authorized in 1998 for the treatment of human cytomegalovirus (HCMV) retinitis . HCMV inAntimicrobial oligonucleotides target the pathogens’ essential genes responsible for replication, antibiotic resistance, and virulence. By targeting these genes, it is possible to augment the host’s immune response, resulting in reduced pathogen replication and proliferation.Escherichia coli . A. AMycobarophages C 97]. T. TMycobaInvestigating potential ASO therapy targets for infectious diseases has led to a focus on host factors that viral pathogens manipulate for their survival. The ability of ASOs to disrupt viral pathogenesis by silencing essential host factors has shown great potential in inhibiting viral replication and propagation, providing new possibilities for the treatment of infectious diseases.ASOs can silence viral targets using steric hindrance, thereby disrupting viral pathogenesis and rendering the virus susceptible to the host’s immune response. Antisense therapy has revolutionized the outlook for future treatments in patients with various diseases, offering the potential for personalized and accessible treatment options . One majDespite its promising potential, the clinical use of oligonucleotides has faced challenges. The delivery of first-generation oligonucleotides to specific organs and tissues has been problematic due to their weight, negative charge, and instability, resulting in poor absorption and susceptibility to nuclease degradation . HoweverAntisense therapy has undergone significant evolution over the years, with numerous advancements aimed at enhancing its efficacy and applications in the field of health sciences. The ability to modify protein expression, either by reducing or restoring it without toxicity, has presented remarkable therapeutic possibilities for numerous diseases and genetic disorders. Improved chemical modifications of ASOs have effectively addressed many concerns associated with earlier first-generation oligonucleotide therapies. From the introduction of the phosphorothioate linkage, which improved enzymatic stability, to the conjugation of cell-penetrating peptides for enhanced cellular uptake, ASOs have become more versatile and potent in their therapeutic potential.The applications of ASOs in infectious diseases have been extensively explored and discussed in this review. Most of the antimicrobials discussed have been rigorously tested in cell cultures, mouse models, and human cell lines. Notably, one significant finding in ASO applications is their potential as host-directed therapy. By targeting multiple host factors involved in viral entry and replication, complementary ASOs can effectively inhibit viral replication and growth.ASOs offer promising prospects for actively combating emerging, re-emerging, and multi-drug-resistant infectious diseases. However, there is still ample room for improvement in most antisense therapeutics. Optimizing ASO delivery to specific target organs can prevent undesirable accumulation in the kidney and liver, thus enhancing overall efficacy. Novel delivery modalities for oligonucleotide therapies can further improve their effectiveness while reducing the required drug dosage. Leveraging approved delivery strategies used in other diseases should be thoroughly explored as they may prove advantageous.In conclusion, ASO therapies hold tremendous potential for treating various diseases, including those caused by bacteria, viruses, and parasites. To fully harness this potential, addressing drug delivery challenges remains a key focus. Through ongoing research, preclinical studies, and clinical trials, the optimization of ASO design, delivery, and personalized medicine can revolutionize the treatment landscape, benefiting patients worldwide and offering new hope in the fight against infectious diseases.