A step towards 6D WAXD tensor tomography.

X-ray scattering/diffraction tensor tomography techniques are promising methods to acquire the 3D texture information of heterogeneous biological tissues at micrometre resolution. However, the methods suffer from a long overall acquisition time due to multi-dimensional scanning across real and reciprocal space. Here, a new approach is introduced to obtain 3D reciprocal information of each illuminated scanning volume using mathematic modeling, which is equivalent to a physical scanning procedure for collecting the full reciprocal information required for voxel reconstruction. The virtual reciprocal scanning scheme was validated by a simulated 6D wide-angle X-ray diffraction tomography experiment. The theoretical validation of the method represents an important technological advancement for 6D diffraction tensor tomography and a crucial step towards pervasive applications in the characterization of heterogeneous materials.

Multicomponent Pathogen-Mimicking Nanoparticles Induce Intestinal Immune Responses against Paratuberculosis.

Given the worldwide problem posed by enteric pathogens, the discovery of safe and efficient intestinal adjuvants combined with novel antigen delivery techniques is essential to the design of mucosal vaccines. In this work, we designed poly (lactic-co-glycolic acid) (PLGA)-based nanoparticles (NPs) to codeliver all-trans retinoic acid (atRA), novel antigens, and CpG. To address the insolubility of the intestinal adjuvant atRA, we utilized PLGA to encapsulate atRA and form a "nanocapsid" with polydopamine. By leveraging polydopamine, we adsorbed the water-soluble antigens and the TLR9 agonist CpG onto the NPs' surface, resulting in the pathogen-mimicking PLPCa NPs. In this study, the novel fusion protein (HBf), consisting of the Mycobacterium avium subspecies paratuberculosis antigens HBHA, Ag85B, and Bfra, was coloaded onto the NPs. In vitro, PLPCa NPs were shown to promote the activation and maturation of bone marrow-derived dendritic cells. Additionally, we found that PLPCa NPs created an immune-rich microenvironment at the injection site following intramuscular administration. From the results, the PLPCa NPs induced strong IgA levels in the gut in addition to enhancing powerful systemic immune responses. Consequently, significant declines in the bacterial burden and inflammatory score were noted in PLPCa NPs-treated mice. In summary, PLPCa can serve as a novel and safe vaccine delivery platform against gut pathogens, such as paratuberculosis, capable of activating both systemic and intestinal immunity.

Analysis and Prevention of Rock Burst Risk of Working Face under the Influence of Continuous Irregular Triangular Coal Pillar Stress Concentration Area.

Irregular coal pillars inevitably appear in the layout of the current long-wall mining method, which easily forms stress concentrations and becomes a heavy disaster area of rock burst. In order to solve the impact risk of irregular coal pillar working face, it is necessary to study the instability mechanism of the coal pillar and put forward effective prevention and control measures. Based on the research background of 14320 working face of the Dongtan Coal Mine in the Yanzhou mining area of China, this paper studies the prediction and prevention of rock bursts in this kind of coal pillar by means of theoretical calculation, numerical simulation, engineering analogy, and field monitoring. The results show that (1) the absolute stability of coal pillar is that the width of coal pillar B reaches twice the support pressure of 2L, and the possibility of instability from large to small is coal pillars 2, 5, 3, 1, and 4. (2) The ratio of coal pillar strength to its average load determines the stability coefficient of the coal pillar, and it is judged that coal pillars 1 and 4 are in a stable state, coal pillars 3 and 5 are in a limit equilibrium state, and coal pillar 2 is in an unstable state. The numerical simulation shows that the maximum stress value inside the coal pillar during the mining process is basically consistent with the theoretical calculation of the bearing strength of the coal pillar. (3) The new evaluation method is used to evaluate the rock burst risk degree of the working face roadway: 156.75 m is a strong rock burst risk zone, 728.18 m is a medium rock burst risk zone, and 176.88 m is a weak rock burst risk zone. (4) Regional prevention and local prevention measures are proposed for the risk of rock burst in the roadway, which reduces the stress concentration of the coal pillar. It is verified that the pressure relief effect is remarkable, and the safe mining of such an irregular coal pillar working face is completed, which provides a solution for studying and solving such rock burst risk.

Towards full-stack deep learning-empowered data processing pipeline for synchrotron tomography experiments.

Synchrotron tomography experiments are transitioning into multifunctional, cross-scale, and dynamic characterizations, enabled by new-generation synchrotron light sources and fast developments in beamline instrumentation. However, with the spatial and temporal resolving power entering a new era, this transition generates vast amounts of data, which imposes a significant burden on the data processing end. Today, as a highly accurate and efficient data processing method, deep learning shows great potential to address the big data challenge being encountered at future synchrotron beamlines. In this review, we discuss recent advances employing deep learning at different stages of the synchrotron tomography data processing pipeline. We also highlight how applications in other data-intensive fields, such as medical imaging and electron tomography, can be migrated to synchrotron tomography. Finally, we provide our thoughts on possible challenges and opportunities as well as the outlook, envisioning selected deep learning methods, curated big models, and customized learning strategies, all through an intelligent scheduling solution.

An efficient ptychography reconstruction strategy through fine-tuning of large pre-trained deep learning model.

With pre-trained large models and their associated fine-tuning paradigms being constantly applied in deep learning, the performance of large models achieves a dramatic boost, mostly owing to the improvements on both data quantity and quality. Next-generation synchrotron light sources offer ultra-bright and highly coherent X-rays, which are becoming one of the largest data sources for scientific experiments. As one of the most data-intensive scanning-based imaging methodologies, ptychography produces an immense amount of data, making the adoption of large deep learning models possible. Here, we introduce and refine the architecture of a neural network model to improve the reconstruction performance, through fine-tuning large pre-trained model using a variety of datasets. The pre-trained model exhibits remarkable generalization capability, while the fine-tuning strategy enhances the reconstruction quality. We anticipate this work will contribute to the advancement of deep learning methods in ptychography, as well as in broader coherent diffraction imaging methodologies in future.

A general image misalignment correction method for tomography experiments.

Tomography experiments generate three-dimensional (3D) reconstructed slices from a series of two-dimensional (2D) projection images. However, the mechanical system generates joint offsets that result in unaligned 2D projections. This misalignment affects the reconstructed images and reduces their actual spatial resolution. In this study, we present a novel method called outer contour-based misalignment correction (OCMC) for correcting image misalignments in tomography. We use the sample's outer contour structure as auxiliary information to estimate the extent of misalignment in each image. This method is generic and can be used with various tomography imaging techniques. We validated our method with five datasets collected from different samples and across various tomography techniques. The OCMC method demonstrated significant advantages in terms alignment accuracy and time efficiency. As an end-to-end correction method, OCMC can be easily integrated into an online tomography data processing pipeline and facilitate feedback control in future synchrotron tomography experiments.

LncRNA109897-JrCCR4-JrTLP1b forms a positive feedback loop to regulate walnut resistance against anthracnose caused by Colletotrichum gloeosporioides.

Walnut anthracnose induced by Colletotrichum gloeosporioides is a disastrous disease that severely restricts the development of the walnut industry in China. Long non-coding RNAs (lncRNAs) are involved in adaptive responses to disease, but their roles in the regulation of walnut anthracnose resistance response are not well defined. In this study, transcriptome analysis demonstrated that a C. gloeosporioides-induced lncRNA, lncRNA109897, located upstream from the target gene JrCCR4, upregulated the expression of JrCCR4. JrCCR4 interacted with JrTLP1b and promoted its transcriptional activity. In turn, JrTLP1b induced the transcription of lncRNA109897 to promote its expression. Meanwhile, transient expression in walnut leaves and stable transformation of Arabidopsis thaliana further proved that lncRNA, JrCCR4, and JrTLP1b improve the resistance of C. gloeosporioides. Collectively, these findings provide insights into the mechanism by which the lncRNA109897-JrCCR4-JrTLP1b transcriptional cascade regulates the resistance of walnut to anthracnose.

The E301R protein of African swine fever virus functions as a sliding clamp involved in viral genome replication.

IMPORTANCE: Sliding clamp is a highly conserved protein in the evolution of prokaryotic and eukaryotic cells. The sliding clamp is required for genomic replication as a critical co-factor of DNA polymerases. However, the sliding clamp analogs in viruses remain largely unknown. We found that the ASFV E301R protein (pE301R) exhibited a sliding clamp-like structure and similar functions during ASFV replication. Interestingly, pE301R is assembled into a unique ring-shaped homotetramer distinct from sliding clamps or proliferating cell nuclear antigens (PCNAs) from other species. Notably, the E301R gene is required for viral life cycle, but the pE301R function can be partially restored by the porcine PCNA. This study not only highlights the functional role of the ASFV pE301R as a viral sliding clamp analog, but also facilitates the dissection of the complex replication mechanism of ASFV, which provides novel clues for developing antivirals against ASF.

A high-throughput big-data orchestration and processing system for the High Energy Photon Source.

High-data-throughput and multimodal-acquisition experiments will prevail in next-generation synchrotron beamlines. Orchestrating dataflow pipelines connecting the data acquisition, processing, visualization and storage ends are becoming increasingly complex and essential for enhancing beamline performance. Mamba Data Worker (MDW) has been developed to address the data challenges for the forthcoming High Energy Photon Source (HEPS). It is an important component of the Mamba experimental control and data acquisition software ecosystem, which enables fast data acquisition and transmission, dynamic configuration of data processing pipelines, data multiplex in streaming, and customized data and metadata assembly. This paper presents the architecture and development plan of MDW, outlines the essential technologies involved, and illustrates its current application at the Beijing Synchrotron Radiation Facility (BSRF).

Allosteric regulation of Senecavirus A 3Cpro proteolytic activity by an endogenous phospholipid.

Seneca virus A (SVA) is an emerging novel picornavirus that has recently been identified as the causative agent of many cases of porcine vesicular diseases in multiple countries. In addition to cleavage of viral polyprotein, the viral 3C protease (3Cpro) plays an important role in the regulation of several physiological processes involved in cellular antiviral responses by cleaving critical cellular proteins. Through a combination of crystallography, untargeted lipidomics, and immunoblotting, we identified the association of SVA 3Cpro with an endogenous phospholipid molecule, which binds to a unique region neighboring the proteolytic site of SVA 3Cpro. Our lipid-binding assays showed that SVA 3Cpro displayed preferred binding to cardiolipin (CL), followed by phosphoinositol-4-phosphate (PI4P) and sulfatide. Importantly, we found that the proteolytic activity of SVA 3Cpro was activated in the presence of the phospholipid, and the enzymatic activity is inhibited when the phospholipid-binding capacity decreased. Interestingly, in the wild-type SVA 3Cpro-substrate peptide structure, the cleavage residue cannot form a covalent binding to the catalytic cysteine residue to form the acyl-enzyme intermediate observed in several picornaviral 3Cpro structures. We observed a decrease in infectivity titers of SVA mutants harboring mutations that impaired the lipid-binding ability of 3Cpro, indicating a positive regulation of SVA infection capacity mediated by phospholipids. Our findings reveal a mutual regulation between the proteolytic activity and phospholipid-binding capacity in SVA 3Cpro, suggesting that endogenous phospholipid may function as an allosteric activator that regulate the enzyme's proteolytic activity during infection.

Perovskite nanocrystal superlattices: self-assembly, collective behavior, and applications.

Metal halide perovskite nanocrystals (NCs) have been widely studied for application in photonics and optoelectronics due to their excellent photoelectric properties. Perovskite NCs with narrow luminescence linewidth and high photoluminescence quantum yield are excellent assembly modules for building large-scale NC superlattices. The coupling of optics and electricity in such excellent aggregates gives them exceptional collective photoelectric performance, such as superfluorescence, red-shifted emission, coupling-enhanced electron transport, etc. Perovskite NC superlattices are expected to become another hot research topic in optoelectronics. Here, we focus on the collective behavior of superlattices and review the recent progress of the self-assembly, collective photoelectric properties, and applications of perovskite NC superlattices. Finally, a few challenges and prospects are indicated.

Fast extraction of three-dimensional nanofiber orientation from WAXD patterns using machine learning.

Structural disclosure of biological materials can help our understanding of design disciplines in nature and inspire research for artificial materials. Synchrotron microfocus X-ray diffraction is one of the main techniques for characterizing hierarchically structured biological materials, especially the 3D orientation distribution of their interpenetrating nanofiber networks. However, extraction of 3D fiber orientation from X-ray patterns is still carried out by iterative parametric fitting, with disadvantages of time consumption and demand for expertise and initial parameter estimates. When faced with high-throughput experiments, existing analysis methods cannot meet the real time analysis challenges. In this work, using the assumption that the X-ray illuminated volume is dominated by two groups of nanofibers in a gradient biological composite, a machine-learning based method is proposed for fast and automatic fiber orientation metrics prediction from synchrotron X-ray micro-focused diffraction data. The simulated data were corrupted in the training procedure to guarantee the prediction ability of the trained machine-learning algorithm in real-world experimental data predictions. Label transformation was used to resolve the jump discontinuity problem when predicting angle parameters. The proposed method shows promise for application in the automatic data-processing pipeline for fast analysis of the vast data generated from multiscale diffraction-based tomography characterization of textured biomaterials.

Antibodies Targeting the Cell Wall Induce Protection against Virulent Mycobacterium bovis Infection.

Accumulating evidence indicates that antibodies can protect against some intracellular pathogens. Mycobacterium bovis is an intracellular bacterium, and its cell wall (CW) is essential for its virulence and survival. However, the questions of whether antibodies play a protective role in immunity against M. bovis infection and what effects antibodies specific to the CW of M. bovis have still remain unclear. Here, we report that antibodies targeting the CW of an isolated pathogenic M. bovis strain and that of an attenuated bacillus Calmette-Guérin (BCG) strain could induce protection against virulent M. bovis infection in vitro and in vivo. Further research found that the antibody-induced protection was mainly achieved by promoting Fc gamma receptor (FcγR)-mediated phagocytosis, inhibiting bacterial intracellular growth, and enhancing the fusion of phagosomes and lysosomes, and it also depended on T cells for its efficacy. Additionally, we analyzed and characterized the B-cell receptor (BCR) repertoires of CW-immunized mice via next-generation sequencing. CW immunization stimulated BCR changes in the complementarity determining region 3 (CDR3) isotype distribution, gene usage, and somatic hypermutation. Overall, our study validates the idea that antibodies targeting the CW induce protection against virulent M. bovis infection. This study highlights the importance of antibodies targeting the CW in the defense against tuberculosis. IMPORTANCE M. bovis is the causative agent of animal tuberculosis (TB) and human TB. Research on M. bovis is of great public health significance. Currently, TB vaccines are mainly aimed at eliciting protection by enhancement of cell-mediated immunity, and there are few studies on protective antibodies. This is the first report of protective antibodies against M. bovis infection, and the antibodies had both preventive and even therapeutic effects in an M. bovis infection mouse model. Additionally, we reveal the relationship between CDR3 gene diversity and the immune characteristics of the antibodies. These results will provide valuable advice for the rational development of TB vaccines.

Exploring AlphaFold2's Performance on Predicting Amino Acid Side-Chain Conformations and Its Utility in Crystal Structure Determination of B318L Protein.

Recent technological breakthroughs in machine-learning-based AlphaFold2 (AF2) are pushing the prediction accuracy of protein structures to an unprecedented level that is on par with experimental structural quality. Despite its outstanding structural modeling capability, further experimental validations and performance assessments of AF2 predictions are still required, thus necessitating the development of integrative structural biology in synergy with both computational and experimental methods. Focusing on the B318L protein that plays an essential role in the African swine fever virus (ASFV) for viral replication, we experimentally demonstrate the high quality of the AF2 predicted model and its practical utility in crystal structural determination. Structural alignment implies that the AF2 model shares nearly the same atomic arrangement as the B318L crystal structure except for some flexible and disordered regions. More importantly, side-chain-based analysis at the individual residue level reveals that AF2's performance is likely dependent on the specific amino acid type and that hydrophobic residues tend to be more accurately predicted by AF2 than hydrophilic residues. Quantitative per-residue RMSD comparisons and further molecular replacement trials suggest that AF2 has a large potential to outperform other computational modeling methods in terms of structural determination. Additionally, it is numerically confirmed that the AF2 model is accurate enough so that it may well potentially withstand experimental data quality to a large extent for structural determination. Finally, an overall structural analysis and molecular docking simulation of the B318L protein are performed. Taken together, our study not only provides new insights into AF2's performance in predicting side-chain conformations but also sheds light upon the significance of AF2 in promoting crystal structural determination, especially when the experimental data quality of the protein crystal is poor.

Automatic synchrotron tomographic alignment schemes based on genetic algorithms and human-in-the-loop software.

Tomography imaging methods at synchrotron light sources keep evolving, pushing multi-modal characterization capabilities at high spatial and temporal resolutions. To achieve this goal, small probe size and multi-dimensional scanning schemes are utilized more often in the beamlines, leading to rising complexities and challenges in the experimental setup process. To avoid spending a significant amount of human effort and beam time on aligning the X-ray probe, sample and detector for data acquisition, most attention has been drawn to realigning the systems at the data processing stages. However, post-processing cannot correct everything, and is not time efficient. Here we present automatic alignment schemes of the rotational axis and sample pre- and during the data acquisition process using a software approach which combines the advantages of genetic algorithms and human intelligence. Our approach shows excellent sub-pixel alignment efficiency for both tasks in a short time, and therefore holds great potential for application in the data acquisition systems of future scanning tomography experiments.

A dimer-monomer transition captured by the crystal structures of cyanobacterial apo flavodoxin.

In cyanobacteria and algae (but not plants), flavodoxin (Fld) replaces ferredoxin (Fd) under stress conditions to transfer electrons from photosystem I (PSI) to ferredoxin-NADP+ reductase (FNR) during photosynthesis. Fld constitutes a small electron carrier noncovalently bound to flavin mononucleotide (FMN), and also an ideal model for revealing the protein/flavin-binding mechanism because of its relative simplicity compared to other flavoproteins. Here, we report two crystal structures of apo-Fld from Synechococcus sp. PCC 7942, one dimeric structure of 2.09 Å and one monomeric structure of 1.84 Å resolution. Analytical ultracentrifugation showed that in solution, apo-Fld exists both as monomers and dimers. Our dimer structure contains two ligand-binding pockets separated by a distance of 45 Å, much longer than the previous structures of FMN-bound dimers. These results suggested a potential dimer-monomer transition mechanism of cyanobacterial apo-Fld. We further propose that the dimer represents the "standby" state to stabilize itself, while the monomer constitutes the "ready" state to bind FMN. Furthermore, we generated a new docking model of cyanobacterial Fld-FNR complex based on the recently reported cryo-EM structures, and mapped the special interactions between Fld and FNR in detail.

Structural insights into PA3488-mediated inactivation of Pseudomonas aeruginosa PldA.

PldA, a phospholipase D (PLD) effector, catalyzes hydrolysis of the phosphodiester bonds of glycerophospholipids-the main component of cell membranes-and assists the invasion of the opportunistic pathogen Pseudomonas aeruginosa. As a cognate immunity protein, PA3488 can inhibit the activity of PldA to avoid self-toxicity. However, the precise inhibitory mechanism remains elusive. We determine the crystal structures of full-length and truncated PldA and the cryogenic electron microscopy structure of the PldA-PA3488 complex. Structural analysis reveals that there are different intermediates of PldA between the "open" and "closed" states of the catalytic pocket, accompanied by significant conformational changes in the "lid" region and the peripheral helical domain. Through structure-based mutational analysis, we identify the key residues responsible for the enzymatic activity of PldA. Together, these data provide an insight into the molecular mechanisms of PldA invasion and its neutralization by PA3488, aiding future design of PLD-targeted inhibitors and drugs.

KLK12 Regulates MMP-1 and MMP-9 via Bradykinin Receptors: Biomarkers for Differentiating Latent and Active Bovine Tuberculosis.

It has been established that kallikrein12 (KLK12) expression is closely related to bovine tuberculosis (bTB) development. Herein, we sought to clarify the regulatory mechanism of KLK12 and its application in tuberculosis diagnosis. KLK12 knockdown macrophages were produced by siRNA transfection. Bradykinin receptors (BR, including B1R and B2R) were blocked with specific inhibitors. Mannose-capped lipoarabinomannan (ManLAM) was extracted from Mycobacterium bovis (M. bovis) and used to study the mechanism of KLK12 activation. In addition, we constructed different mouse models representing the latent and active stages of M. bovis infection. Mouse models and clinical serum samples were used to assess the diagnostic value of biomarkers. Through the above methods, we confirmed that KLK12 regulates MMP-1 and MMP-9 via BR. KLK12 upregulation is mediated by the M. bovis-specific antigen ManLAM. KLK12, MMP-1, and MMP-9 harbor significant value as serological markers for differentiating between latent and active bTB, especially KLK12. In conclusion, we identified a novel signaling pathway, KLK12/BR/ERK/MMPs, in M. bovis-infected macrophages, which is activated by ManLAM. From this signaling pathway, KLK12 can be used as a serological marker to differentiate between latent and active bTB. Importantly, KLK12 also has enormous potential for the clinical diagnosis of human tuberculosis (TB).

Genomic and transcriptomic analyses provide insights into valuable fatty acid biosynthesis and environmental adaptation of yellowhorn.

Yellowhorn (Xanthoceras sorbifolium) is an oil-bearing tree species growing naturally in poor soil. The kernel of yellowhorn contains valuable fatty acids like nervonic acid. However, the genetic basis underlying the biosynthesis of valued fatty acids and adaptation to harsh environments is mainly unexplored in yellowhorn. Here, we presented a haplotype-resolved chromosome-scale genome assembly of yellowhorn with the size of 490.44 Mb containing scaffold N50 of 34.27 Mb. Comparative genomics, in combination with transcriptome profiling analyses, showed that expansion of gene families like long-chain acyl-CoA synthetase and ankyrins contribute to yellowhorn fatty acid biosynthesis and defense against abiotic stresses, respectively. By integrating genomic and transcriptomic data of yellowhorn, we found that the transcription of 3-ketoacyl-CoA synthase gene XS04G00959 was consistent with the accumulation of nervonic and erucic acid biosynthesis, suggesting its critical regulatory roles in their biosynthesis. Collectively, these results enhance our understanding of the genetic basis underlying the biosynthesis of valuable fatty acids and adaptation to harsh environments in yellowhorn and provide foundations for its genetic improvement.

Morinda officinalis oligosaccharides increase serotonin in the brain and ameliorate depression via promoting 5-hydroxytryptophan production in the gut microbiota.

Morinda officinalis oligosaccharides (MOO) are an oral drug approved in China for the treatment of depression in China. However, MOO is hardly absorbed so that their anti-depressant mechanism has not been elucidated. Here, we show that oral MOO acted on tryptophan â†’ 5-hydroxytryptophan (5-HTP) â†’ serotonin (5-HT) metabolic pathway in the gut microbiota. MOO could increase tryptophan hydroxylase levels in the gut microbiota which accelerated 5-HTP production from tryptophan; meanwhile, MOO inhibited 5-hydroxytryptophan decarboxylase activity, thus reduced 5-HT generation, and accumulated 5-HTP. The raised 5-HTP from the gut microbiota was absorbed to the blood, and then passed across the blood-brain barrier to improve 5-HT levels in the brain. Additionally, pentasaccharide, as one of the main components in MOO, exerted the significant anti-depressant effect through a mechanism identical to that of MOO. This study reveals for the first time that MOO can alleviate depression via increasing 5-HTP in the gut microbiota.