Mode Of Recognition Research Articles

Potent neutralization of SARS-CoV-2 variants of concern by an antibody with an uncommon genetic signature and structural mode of spike recognition.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages that are more transmissible and resistant to currently approved antibody therapies poses a considerable challenge to the clinical treatment of coronavirus disease (COVID-19). Therefore, the need for ongoing discovery efforts to identify broadly reactive monoclonal antibodies to SARS-CoV-2 is of utmost importance. Here, we report a panel of SARS-CoV-2 antibodies isolated using the linking B cell receptor to antigen specificity through sequencing (LIBRA-seq) technology from an individual who recovered from COVID-19. Of these antibodies, 54042-4 shows potent neutralization against authentic SARS-CoV-2 viruses, including variants of concern (VOCs). A cryoelectron microscopy (cryo-EM) structure of 54042-4 in complex with the SARS-CoV-2 spike reveals an epitope composed of residues that are highly conserved in currently circulating SARS-CoV-2 lineages. Further, 54042-4 possesses uncommon genetic and structural characteristics that distinguish it from other potently neutralizing SARS-CoV-2 antibodies. Together, these findings provide motivation for the development of 54042-4 as a lead candidate to counteract current and future SARS-CoV-2 VOCs.

Impact-slip experiments and systematic study of coal gangue “category” recognition technology part II: Improving effect of the proposed parallel voting system method on coal gangue “category” recognition accuracy based on impact-slip experiments

The research on coal gangue “category” recognition via single classification algorithm for single-channel signal data shows that the classification and recognition capabilities of different algorithms on different channel signals and data types exhibit significant differences. In order to improve coal gangue classification and recognition effect, a coal gangue classification and recognition method of “multi-information fusion” based on the “parallel voting system (PVS)” was proposed in this study. The joint judgment of coal gangue “category” was completed through the combination of multiple algorithms or channel signal data with stronger recognition ability according to the voting principle of “the minority is subordinate to the majority”. Based on the signal characteristics data obtained from the impact-slip test between coal gangue and the hydraulic support, three different modes of PVS-based coal gangue classification and recognition, namely, channel signal data PVS (SDPVS), algorithm PVS (APVS), and algorithm and channel signal data combination double PVS (algorithm-data double parallel, A&SDPVS), were respectively investigated herein. The influence of signals combination mode, algorithms matching mode as well as combined mode of signals and algorithms on coal gangue “category” voting recognition accuracy was studied. The research results show that for the SDPVS when a single algorithm with higher recognition accuracy and its corresponding multiple channel signal data with higher recognition accuracy were selected and for the A&SDPVS when the multiple “Recognition combination of single algorithm and single channel signal data” with higher recognition accuracy was selected, coal gangue classification and recognition effect could be improved. PVS-based coal gangue “category” recognition accuracy could reach up to 97.5%, which effectively improved coal gangue classification and recognition ability; moreover, the effectiveness of the multi-information fusion method proposed in this study was proven.

Atg12-Interacting Motif Is Crucial for E2-E3 Interaction in Plant Atg8 System.

Autophagy is an intracellular degradation system regulating cellular homeostasis. The two ubiquitin-like modification systems named the Atg8 system and the Atg12 system are essential for autophagy. Atg8 and Atg12 are ubiquitin-like proteins covalently conjugated with a phosphatidylethanolamine (PE) and Atg5, respectively, via enzymatic reactions. The Atg8-PE conjugate binds to autophagic membranes and recruits various proteins through direct interaction, whereas the Atg12-Atg5 conjugate recognizes Atg3, the E2 enzyme for Atg8, and facilitates Atg8-PE conjugation by functioning as the E3 enzyme. Although structural and biochemical analyses have well established the Atg8-family interacting motif (AIM), studies on the interacting sequence for Atg12 are rare (only one example for human ATG12-ATG3), thereby making it challenging to define a binding motif. Here we determined the crystal structure of the plant ATG12b as a complex with the ATG12b-binding region of ATG3 and revealed that ATG12b recognizes the aspartic acid (Asp)-methionine (Met) motif in ATG3 via a hydrophobic pocket and a basic residue, which we confirmed critical for the complex formation by mutational analysis. This recognition mode is similar to that reported between human ATG12 and ATG3, suggesting that the Asp-Met sequence is a conserved Atg12-interacting motif (AIM12). These data suggest that AIM12 mediates E2-E3 interaction during Atg8 lipidation and provide structural basis for developing chemicals that regulate autophagy by targeting Atg12-family proteins.

Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics.

Macrocycles are attractive structures for drug development due to their favorable structural features, potential in binding to targets with flat featureless surfaces, and their ability to disrupt protein–protein interactions. Moreover, large novel highly diverse libraries of low-molecular-weight macrocycles with therapeutically favorable characteristics have been recently established. Considering the mentioned facts, having a validated, fast, and accurate computational protocol for studying the molecular recognition and binding mode of this interesting new class of macrocyclic peptides deemed to be helpful as well as insightful in the quest of accelerating drug discovery. To that end, the ability of the in-house supervised molecular dynamics protocol called SuMD in the reproduction of the X-ray crystallography final binding state of a macrocyclic non-canonical tetrapeptide—from a novel library of 8,988 sub-kilodalton macrocyclic peptides—in the thrombin active site was successfully validated. A comparable binding mode with the minimum root-mean-square deviation (RMSD) of 1.4 Å at simulation time point 71.6 ns was achieved. This method validation study extended the application domain of the SuMD sampling method for computationally cheap, fast but accurate, and insightful macrocycle–protein molecular recognition studies.

Accurate and Nonpurified Identification of Extracellular Vesicles Using Dual-Binding Recognition Mode.

Circulating extracellular vesicles (EVs) are promising biomarkers for the early diagnosis and prognosis of cancer in a non-invasive manner. However, the rapid and accurate identification of EVs in complex biological samples is technically challenging, which is attributed to the requirement of extensive sample purification and unsatisfactory detection accuracy due to the disturbance of interfering proteins. Herein, a simultaneous binding of double-positive EV membrane protein-based recognition mode (DRM) is proposed. By the combination of DRM-mediated toehold activation and G-quadruplex DNAZyme-catalyzed etching of Au@Ag nanorods (Au@Ag NRs), we have developed an accurate, non-purified, low-cost, and visual strategy for EV identification. The synchronous binding of double-positive proteins on EV membranes is validated by confocal laser scanning microscopy analysis. This approach exhibits excellent specificity and sensitivity toward EVs ranging from 1.0 × 105 to 1.0 × 109 particles/mL with a detection limit of 6.31 × 104 particles/mL. Moreover, we have successfully realized non-purified EV quantification in complex biological media. In addition, target-initiated catalyzed hairpin assembly (CHA) is integrated with G-quadruplex DNAZyme-catalyzed color variation of Au@Ag NRs; thus, low-background EV detection can be achieved by the naked eye. Furthermore, our strategy is easy to adapt to high-throughput formats by using an automatic microplate reader, which could be expected to meet the requirements for high-throughput detection of clinical samples. With its capacities of rapidness, portability, affordability, high throughput, non-purification, and visual detection, this strategy could provide a practical tool for accurate identification of EVs and early diagnosis of cancer.

A 28 nm, 397 [formula omitted]W real-time dynamic gesture recognition chip based on RISC-V processor

This paper presents a low-power programmable dynamic gesture recognition chip based on a RISC-V processor using RGB images. The chip uses two gesture recognition algorithms to recognize the most commonly used dynamic gestures (up, down, left, and right) with any shape of a hand at the distance of 10 cm ∼ 90 cm and speed of 10 cm/s ∼ 150 cm/s. The chip is fabricated in a 28 nm process and occupies an area of 640μm x 640μm. The accuracy reaches 93% ∼ 99% at complex backgrounds with 320x240 RGB image. It operates either in the recognition mode or in the standby mode that can be automatically switched to the other. The power consumption of the recognition mode is 397 μW at 0.584 V supply voltage, 25 MHz clock, and 30 FPS. And the power consumption of the standby mode at room temperature is 78.3 μW.

Crystal structure of the PDZ4 domain of MAGI2 in complex with PBM of ARMS reveals a canonical PDZ recognition mode

Membrane-associated guanylate kinase, WW and PDZ domain-containing protein 2 (MAGI2) is a neuronal scaffold protein that plays critical roles at synaptic junctions by assembling neurotransmitter receptors and cell adhesion proteins through its multiple protein-protein interaction domains, including six PDZ domains, two phosphoserine-phosphothreonine binding WW domains, and a guanylate kinase GK domain. Previous studies showed that MAGI2 participates in formation of tetrameric complexes with PDZ-GEF1, TrkA receptor, and ankyrin repeat-rich membrane spanning (ARMS) protein at late endosomes and is crucial for neurite outgrowth. However, the molecular mechanism governing the assembly of these complexes remains unknown. Here, we characterize the direct interaction between MAGI2 and ARMS through multiple biochemical assays. Moreover, our solved crystal structure of the truncated PDZ4/PBM (PDZ binding motifs) complex of MAGI2 and ARMS proteins (MAGI2-PDZ4/ARMS-PBM) reveals that the binding interface lies between the αB/βB groove from the PDZ4 of MAGI2 and the C-terminal PBM from ARMS. The structure reveals high similarity to others in this protein family where canonical PDZ/PBM interactions are observed. However, the conserved “GLGF” motif in the PSD-95-PDZ3 changes to “GFGF” in the MAGI2-PDZ4/ARMS-PBM complex. We further validated our crystal structure through serial mutagenesis assays. Taken together, our study provides the biochemical details and binding mechanisms that underpin the stabilization of the MAGI2-PDZ4/ARMS-PBM complex, thereby offering a biochemical and structural basis for further understanding of the functional roles of MAGI2, ARMS, PDZ-GEF1, and TrkA in forming the tetrameric receptor complex in neuronal signaling.

Recognizing fractional orbital angular momentum using feed forward neural network

Fractional vortex beam (FVB) possessing helical phase can be applied in the shift-keying communication due to its fractional orbital angular momentum (FOAM) mode, which theoretically allows an infinite increase of the transmitted capacity. However, the discontinuity of spiral phase makes FVB more likely to be disturbed in turbulence environment, and the precise measurement of distorted FOAM modes is crucial for practical FOAM-based communication application. Here, we proposed a FOAM mode recognition method with feedforward neural network (FNN). Employing the diffraction preprocessing of a two-dimensional fork grating, the original optical features of FVBs can be extended along the far-field diffraction order, endowing FNN more feature information and saving calculation time, and enlarging the detection range to conjugate FOAM modes. The simulation results show that the 9-layer FNN can identify FOAM mode with interval of 0.1 with an accuracy of 99.1% under the turbulences of Cn2=1×10-14m-2/3 and Δz=10m. Furthermore, we experimentally constructed a 102-ary FOAM shift-keying communication link to transmit gray image, and the signals are successfully demodulated by the FNN model with the pixel-error-rate of 0.07160. It is anticipated that the proposed FNN-based FOAM recognition method will break the limitation of precision measurement under turbulence environment in practical FOAM applications.

Bdellovibrio bacteriovorus phosphoglucose isomerase structures reveal novel rigidity in the active site of a selected subset of enzymes upon substrate binding.

Glycolysis and gluconeogenesis are central pathways of metabolism across all domains of life. A prominent enzyme in these pathways is phosphoglucose isomerase (PGI), which mediates the interconversion of glucose-6-phosphate and fructose-6-phosphate. The predatory bacterium Bdellovibrio bacteriovorus leads a complex life cycle, switching between intraperiplasmic replicative and extracellular 'hunter' attack-phase stages. Passage through this complex life cycle involves different metabolic states. Here we present the unliganded and substrate-bound structures of the B. bacteriovorus PGI, solved to 1.74 Å and 1.67 Å, respectively. These structures reveal that an induced-fit conformational change within the active site is not a prerequisite for the binding of substrates in some PGIs. Crucially, we suggest a phenylalanine residue, conserved across most PGI enzymes but substituted for glycine in B. bacteriovorus and other select organisms, is central to the induced-fit mode of substrate recognition for PGIs. This enzyme also represents the smallest conventional PGI characterized to date and probably represents the minimal requirements for a functional PGI.

Dual-site recognition of Pseudomonas aeruginosa using polymyxin B and bacteriophage tail fiber protein

As one of the top three opportunistic pathogens, Pseudomonas aeruginosa (P. aeruginosa) has long accounted for hospital-acquired infections with high risk of death. In this work, a fluorescent method based on a dual-site recognition mode was developed for rapid assay of P. aeruginosa. Employing its strong binding capability towards lipid A on the outer membrane of Gram-negative bacteria, polymyxin B acted as one recognition element for P. aeruginosa. To overcome the poor binding specificity of polymyxin B, a recombinant bacteriophage tail fiber protein was expressed and employed as a species-specific recognition element for the target pathogen. Thus a dual-site recognition mode was developed for specific assay of P. aeruginosa species by using fluorescein isothiocyanate as a fluorescent probe. The target pathogen can be assayed within a broad dynamic range from 2.0 × 103 CFU mL−1 to 2.0 × 107 CFU mL−1. Due to the ideal specificity of tail fiber protein, the method is capable of excluding the interference from other Gram-negative bacteria and all Gram-positive bacteria. It has been employed for assaying P. aeruginosa in various types of sample matrixes inclusive of lake water, physiological saline injection, human urine and milk. The acceptable assay results demonstrate its promising prospect for practical application in various areas such as environmental hygiene, medical diagnosis, as well as drug and food safety.

Exploring molecular determinants of polysaccharide lyase family 6-1 enzyme activity.

The polysaccharide lyase family 6 (PL6) represents one of the 41 polysaccharide lyase families classified in the CAZy database with the vast majority of its members being alginate lyases grouped into three subfamilies, PL6_1-3. To decipher the mode of recognition and action of the enzymes belonging to subfamily PL6_1, we solved the crystal structures of Pedsa0632, Patl3640, Pedsa3628 and Pedsa3807, which all show different substrate specificities and mode of action (endo-/exolyase). Thorough exploration of the structures of Pedsa0632 and Patl3640 in complex with their substrates as well as docking experiments confirms that the conserved residues in subsites -1 to +3 of the catalytic site form a common platform that can accommodate various types of alginate in a very similar manner but with a series of original adaptations bringing them their specificities of action. From comparative studies with existing structures of PL6_1 alginate lyases, we observe that in the right-handed parallel β-helix fold shared by all these enzymes, the substrate-binding site harbors the same overall conserved structures and organization. Despite this apparent similarity, it appears that members of the PL6_1 subfamily specifically accommodate and catalyze the degradation of different alginates suggesting that this common platform is actually a highly adaptable and specific tool.

Human and viral membrane–associated E3 ubiquitin ligases MARCH1 and MIR2 recognize different features of CD86 to downregulate surface expression

Immune-stimulatory ligands, such as major histocompatibility complex molecules and the T-cell costimulatory ligand CD86, are central to productive immunity. Endogenous mammalian membrane-associated RING-CHs (MARCH) act on these and other targets to regulate antigen presentation and activation of adaptive immunity, whereas virus-encoded homologs target the same molecules to evade immune responses. Substrate specificity is encoded in or near the membrane-embedded domains of MARCHs and the proteins they regulate, but the exact sequences that distinguish substrates from nonsubstrates are poorly understood. Here, we examined the requirements for recognition of the costimulatory ligand CD86 by two different MARCH-family proteins, human MARCH1 and Kaposi's sarcoma herpesvirus modulator of immune recognition 2 (MIR2), using deep mutational scanning. We identified a highly specific recognition surface in the hydrophobic core of the CD86 transmembrane (TM) domain (TMD) that is required for recognition by MARCH1 and prominently features a proline at position 254. In contrast, MIR2 requires no specific sequences in the CD86 TMD but relies primarily on an aspartic acid at position 244 in the CD86 extracellular juxtamembrane region. Surprisingly, MIR2 recognized CD86 with a TMD composed entirely of valine, whereas many different single amino acid substitutions in the context of the native TM sequence conferred MIR2 resistance. These results show that the human and viral proteins evolved completely different recognition modes for the same substrate. That some TM sequences are incompatible with MIR2 activity, even when no specific recognition motif is required, suggests a more complicated mechanism of immune modulation via CD86 than was previously appreciated.

A Data-Driven Scheme for Fault Detection of Discrete-Time Switched Systems.

This paper is concerned with the fault detection issue for a class of discrete-time switched systems via the data-driven approach. For the fault detection of switched systems, it is inevitable to consider the mode matching problem between the activated subsystem and the executed residual generator since the mode mismatching may cause a false fault alarm in all probability. Frequently, studies assume that the switching laws are available to the residual generator, by which the residual generator keeps the same mode as the system plant and then the mode mismatching is excluded. However, this assumption is conservative and impractical because many switching laws are hard to acquire in practical applications. This work focuses on the case of switched systems with unavailable switching laws. In view of the unavailability of switching information, the mode recognition is considered for the fault detection process and meanwhile, sufficient conditions are presented for the mode distinguishability. Moreover, a novel decision logic for the fault detection is proposed, based on which new algorithms are established for the data-driven realization. Finally, a benchmark case on a three-tank system is used to illustrate the feasibility and usefulness of the obtained results.

Bitcoin in the economics and finance literature: a survey.

This paper provides a review of the literature on key matters related to the popular cryptocurrency Bitcoin. Another key motivation of this paper is to understand the underlying principle of this digital currency from the economic and financial point of view. For the survey to be comprehensive, the paper is categorized into varied themes: price dynamics, volatility, bubble dynamics, mode of recognition in the financial market, efficiency, economics, social media and investor sentiment, and lastly regulation and legality. We argue that Bitcoin is still in an embryonic phase and needs to evolve with time especially keeping in pace with technological advancements. It should be robust to get accepted as an alternative currency and be able to prevent any fraudulent exploitation.

An Environmental Perception Self‐Adaptive Discolorable Hydrogel Film toward Sensing and Display

AbstractVision perception, especially color change, is the most direct and convenient way of feedback among numerous information recognition modes. Because of unique discoloration property upon stimulation, photonic crystals have attracted wide attention. Herein, with a facile UV polymerization process under the magnetic field, a sensitive photonic hydrogel film with vivid structural color is made. The structural color comes from the 1D chain‐like structures assembled by the carbon‐encapsulated Fe3O4 colloidal nanocrystal clusters (Fe3O4@CNCs), which are embedded in the flexible hydrogel matrix. The hydrogel can adapt its size to the environment, resulting in the regulation of intergranular distance and apparent color variation. Thus, a hydrogel film with humidity, ion concentration, and stress responsivity can be obtained, showing high sensitivity, stability, and full reversibility in a wide range of visible spectrum. It can be designed as a reusable display board or applied to colorimetric measurements similar to pH test paper. Innovatively, the hydrogel film is integrated as back reflectors to improve the efficiency of semitransparent polymer solar cells while protecting devices. This structural color hydrogel film makes it easier to recognize environmental dynamic changes and provide a wider application prospect in optics devices, sensing, display, and diagnostics.

Teaching Chinese Sign Language with a Smartphone

BackgroundThere is a large group of deaf-mutes in the world, and sign language is their major communication tool. Therefore, it’s necessary for the deaf-mutes to communicate with hearing-speech people and the hearing-speech people also have needed to understand sign language, which produces a great demand for sign language teaching. Even though there have already been a large number of books for sign language, it is low efficient to learn sign language with books, even teaching videos. To solve this problem, we develop a smartphone-based interactive Chinese sign language teaching systemfor sign language learning. MethodsThe system provides a learner with some kinds of learning modes and captures the learner’s actions from its front camera of the smartphone. Right now the system provides a vocabulary set with 1000 frequently used words, and the learner can evaluate his/her sign action by subjective or objective comparison. In the mode of word recognition, the users can play any word within the vocabulary and the system will turn the top three retrieved candidates, so it can remind the learners what the sign is. ResultsThis system provides interactive learning for a user to learn sign language high efficiently. The systemadopts an algorithm based on point cloud recognition to evaluate a user’s sign and costs about 700ms inference time for each sample, which meets the real-time requirements. ConclusionThis interactive learning system decreases the communication barriers between the deaf-mutes and hearing-speechers.

The end of global pluralism?

The liberal international order is a fragmented institutional complex, comprising often disparate elements. One of these is a distinctive institutional approach to the global organization of cultural difference. This approach combines universal Westphalian sovereignty (and the pluralist interstate order it facilitates) with international human rights norms that seek to protect the cultural freedoms of individuals. I term this institutional amalgam “global pluralism”. Like many elements of the liberal order, such pluralism is now under challenge, confronted by resurgent ethno-nationalism, politicized religion, and civilizational chauvinism. The key question is whether global pluralism has the adaptive capacities to withstand such challenges. This article develops a theoretical framework for comprehending these institutional capacities. Conceiving global pluralism as a “diversity regime,” I argue that such regimes always rest on social “recognition contracts,” and that these give them certain structural characteristics: configurations of political authority and modes of cultural recognition. Focusing on these characteristics, I compare global pluralism with past Western and non-Western diversity regimes, and clarify the adaptive strengths and weaknesses of different institutional forms. This contractual-structural analysis exposes the historical uniqueness of global pluralism but also its structural vulnerabilities. While global pluralism has distinct advantages over past diversity regimes—principally, that it does not itself generate unstable cultural cleavages and hierarchies—it requires complex forms of social contracting to sustain, and its individualist mode of recognition struggles to accommodate collectivist cultural claims. Such contracting is essential, however, if global pluralism is to withstand current challenges, all of which involve collectivist claims.

Sequence-Signature Optimization Enables Improved Identification of Human HV6-1-Derived Class Antibodies That Neutralize Diverse Influenza A Viruses.

Sequence signatures of multidonor broadly neutralizing influenza antibodies can be used to quantify the prevalence of B cells with virus-neutralizing potential to accelerate development of broadly protective vaccine strategies. Antibodies of the same class share similar recognition modes and developmental pathways, and several antibody classes have been identified that neutralize diverse group 1- and group 2-influenza A viruses and have been observed in multiple human donors. One such multidonor antibody class, the HV6-1-derived class, targets the stem region of hemagglutinin with extraordinary neutralization breadth. Here, we use an iterative process to combine informatics, biochemical, and structural analyses to delineate an improved sequence signature for HV6-1-class antibodies. Based on sequence and structure analyses of known HV6-1 class antibodies, we derived a more inclusive signature (version 1), which we used to search for matching B-cell transcripts from published next-generation sequencing datasets of influenza vaccination studies. We expressed selected antibodies, evaluated their function, and identified amino acid-level requirements from which to refine the sequence signature (version 2). The cryo-electron microscopy structure for one of the signature-identified antibodies in complex with hemagglutinin confirmed motif recognition to be similar to known HV6-1-class members, MEDI8852 and 56.a.09, despite differences in recognition-loop length. Threading indicated the refined signature to have increased accuracy, and signature-identified heavy chains, when paired with the light chain of MEDI8852, showed neutralization comparable to the most potent members of the class. Incorporating sequences of additional class members thus enables an improved sequence signature for HV6-1-class antibodies, which can identify class members with increased accuracy.

Ultrasensitive detection by maxillary palp neurons allows non-host recognition without consumption of harmful allelochemicals

Most lepidopteran insect larvae exhibit stepwise feeding behaviors, such as palpation using the maxillary palps (MPs) followed by test biting and persistent biting. However, the purpose of palpation has been unclear. In particular, nothing is known about the neurons in the MP and their mode of recognition of undesired plants, although such neurons have been suggested to exist. In this study, we used larvae of the stenophagous insect Bombyx mori and compared the roles of palpation and test biting in the selection of feeding behavior. When the larvae were given non-host plant leaves, they did not initiate test biting, indicating that non-host plant leaves were recognized via palpation without biting, and that this behavior resulted in a lack of persistent biting, as the leaves were judged non-suitable for consumption. Surface extracts of inedible leaves significantly suppressed test biting of mulberry leaves, a host plant of B. mori, suggesting that secondary metabolites on the leaf surface of inedible leaves function as test biting suppressors, even when another conditions are suitable for test biting. The allelochemical coumarin, which is found in the inedible leaves of cherry, Cerasus speciosa, significantly suppressed test biting of mulberry leaves, suggesting that coumarin is a possible deterrent to the eating of cherry leaves. Using the electrophysiological method of tip recording and a leaf-surface extract as the test material, leaf-surface compound-responsive neurons were identified in the MP. In addition, several neurons that respond to coumarin in the attomolar range were identified, suggesting that the larvae use ultrasensitive neurons in the MP to recognize inedible leaves. In the HEK293T cell heterologous expression system, the B. mori gustatory receptors BmGr53 and BmGr19, which were previously found to be expressed in the MP and to respond to coumarin in the attomolar range, responded to a leaf-surface extract of C. speciosa, suggesting that these receptors may be present on the inedible-leaf-recognizing neurons of the MP. These findings suggest that ultrasensitive plant secondary metabolite-recognizing neurons in the MP allow for the recognition of non-host plants via palpation without risking damage caused by ingesting harmful allelochemicals.

3D Structural View of Pathogen Recognition by Mammalian Lectin Receptors.

Humans and other mammals resist exogenous pathogens by recognizing them as non-self. How do they do this? The answer lies in the recognition by mammalian lectin receptors of glycans usually found on the surface of pathogens and whose chemical structure is species-specific. Some glycan components, such as galactofuranose, only occur in microbes, and is the principal means by which mammalian lectin receptors recognize non-self. Several lectins may function together as pattern recognition receptors to survey the infecting pathogen before the adaptive immune system is invoked. Most lectins have primary and secondary monosaccharide-binding sites which together determine the specificity of a receptor toward microbial glycans. There may also be a hydrophobic groove alongside the sugar binding sites that increases specificity. Another elaboration is through oligomerization of lectin domains with defined spacing and arrangement that creates high-affinity binding towards multiply-presented glycans on microbes. Microbe-specific polysaccharides may arise through unique sugar linkages. Specificity can come from mammalian receptors possessing a shallow binding site and binding only internal disaccharide units, as in the recognition of mannan by Dectin-2. The accumulation of 3D structural information on lectins receptors has allowed the recognition modes of microbe glycans to be classified into several groupings. This review is an introduction to our current knowledge on the mechanisms of pathogen recognition by representative mammalian lectin receptors.