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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Structural basis for differential recognition of phosphohistidine-containing peptides by 1-pHis and 3-pHis monoclonal antibodies

In 2015, monoclonal antibodies (mAbs) that selectively recognize the 1-pHis or 3-pHis isoforms of phosphohistidine were developed by immunizing rabbits with degenerate Ala/Gly peptides containing the nonhydrolyzable phosphohistidine (pHis) analog- phosphotriazolylalanine (pTza). Here, we report structures of five rabbit mAbs bound to cognate pTza peptides: SC1-1 and SC50-3 that recognize 1-pHis, and their 3-pHis–specific counterparts, SC39-4, SC44-8, and SC56-2. These cocrystal structures provide insights into the binding modes of the pTza phosphate group that are distinct for the 1- and 3-pHis mAbs with the selectivity arising from specific contacts with the phosphate group and triazolyl ring. The mode of phosphate recognition in the 3-pHis mAbs recapitulates the Walker A motif, as present in kinases. The complementarity-determining regions (CDRs) of four of the Fabs interact with the peptide backbone rather than peptide side chains, thus conferring sequence independence, whereas SC44-8 shows a proclivity for binding a GpHAGA motif mediated by a sterically complementary CDRL3 loop. Specific hydrogen bonding with the triazolyl ring precludes recognition of pTyr and other phosphoamino acids by these mAbs. Kinetic binding experiments reveal that the affinity of pHis mAbs for pHis and pTza peptides is submicromolar. Bound pHis mAbs also shield the pHis peptides from rapid dephosphorylation. The epitope–paratope interactions illustrate how these anti-pHis antibodies are useful for a wide range of research techniques and this structural information can be utilized to improve the specificity and affinity of these antibodies toward a variety of pHis substrates to understand the role of histidine phosphorylation in healthy and diseased states.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structurally silent peptide anchor modifications allosterically modulate T cell recognition in a receptor-dependent manner

Presentation of peptides by class I MHC proteins underlies T cell immune responses to pathogens and cancer. The association between peptide binding affinity and immunogenicity has led to the engineering of modified peptides with improved MHC binding, with the hope that these peptides would be useful for eliciting cross-reactive immune responses directed toward their weak binding, unmodified counterparts. Increasing evidence, however, indicates that T cell receptors (TCRs) can perceive such anchor-modified peptides differently than wild-type (WT) peptides, although the scope of discrimination is unclear. We show here that even modifications at primary anchors that have no discernible structural impact can lead to substantially stronger or weaker T cell recognition depending on the TCR. Surprisingly, the effect of peptide anchor modification can be sensed by a TCR at regions distant from the site of modification, indicating a through-protein mechanism in which the anchor residue serves as an allosteric modulator for TCR binding. Our findings emphasize caution in the use and interpretation of results from anchor-modified peptides and have implications for how anchor modifications are accounted for in other circumstances, such as predicting the immunogenicity of tumor neoantigens. Our data also highlight an important need to better understand the highly tunable dynamic nature of class I MHC proteins and the impact this has on various forms of immune recognition.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Structural Basis for Ligand Recognition and Discrimination of a Quorum-quenching Antibody

In the postantibiotic era, available treatment options for severe bacterial infections caused by methicillin-resistant Staphylococcus aureus have become limited. Therefore, new and innovative approaches are needed to combat such life-threatening infections. Virulence factor expression in S. aureus is regulated in a cell density-dependent manner using 'quorum sensing,' which involves generation and secretion of autoinducing peptides (AIPs) into the surrounding environment to activate a bacterial sensor kinase at a particular threshold concentration. Mouse monoclonal antibody AP4-24H11 was shown previously to blunt quorum sensing-mediated changes in gene expression in vitro and protect mice from a lethal dose of S. aureus by sequestering the AIP signal. We have elucidated the crystal structure of the AP4-24H11 Fab in complex with AIP-4 at 2.5 {angstrom} resolution to determine its mechanism of ligand recognition. A key GluH95 provides much of the binding specificity through formation of hydrogen bonds with each of the four amide nitrogens in the AIP-4 macrocyclic ring. Importantly, these structural data give clues as to the interactions between the cognate staphylococcal AIP receptors AgrC and the AIPs, as AP4-24H11 {center_dot} AIP-4 binding recapitulates features that have been proposed for AgrC-AIP recognition. Additionally, these structural insights may enable the engineering of AIP cross-reactive antibodies or quorum quenching vaccines for use in active or passive immunotherapy for prevention or treatment of S. aureus infections.

08 HYDROGEN↗
DOE OSTI2012

Unique Ganglioside Recognition Strategies for Clostridial Neurotoxins

Botulinum neurotoxins (BoNTs) and tetanus neurotoxin are the causative agents of the paralytic diseases botulism and tetanus, respectively. The potency of the clostridial neurotoxins (CNTs) relies primarily on their highly specific binding to nerve terminals and cleavage of SNARE proteins. Although individual CNTs utilize distinct proteins for entry, they share common ganglioside co-receptors. Here, we report the crystal structure of the BoNT/F receptor-binding domain in complex with the sugar moiety of ganglioside GD1a. GD1a binds in a shallow groove formed by the conserved peptide motif E ... H ... SXWY ... G, with additional stabilizing interactions provided by two arginine residues. Comparative analysis of BoNT/F with other CNTs revealed several differences in the interactions of each toxin with ganglioside. Notably, exchange of BoNT/F His-1241 with the corresponding lysine residue of BoNT/E resulted in increased affinity for GD1a and conferred the ability to bind ganglioside GM1a. Conversely, BoNT/E was not able to bind GM1a, demonstrating a discrete mechanism of ganglioside recognition. These findings provide a structural basis for ganglioside binding among the CNTs and show that individual toxins utilize unique ganglioside recognition strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Design and testing of the first 2D Prototype Vertically Integrated Pattern Recognition Associative Memory

An associative memory-based track finding approach has been proposed for a Level 1 tracking trigger to cope with increasing luminosities at the LHC. The associative memory uses a massively parallel architecture to tackle the intrinsically complex combinatorics of track finding algorithms, thus avoiding the typical power law dependence of execution time on occupancy and solving the pattern recognition in times roughly proportional to the number of hits. This is of crucial importance given the large occupancies typical of hadronic collisions. The design of an associative memory system capable of dealing with the complexity of HL-LHC collisions and with the short latency required by Level 1 triggering poses significant, as yet unsolved, technical challenges. For this reason, an aggressive R&D program has been launched at Fermilab to advance state of-the-art associative memory technology, the so called VIPRAM (Vertically Integrated Pattern Recognition Associative Memory) project. The VIPRAM leverages emerging 3D vertical integration technology to build faster and denser Associative Memory devices. The first step is to implement in conventional VLSI the associative memory building blocks that can be used in 3D stacking, in other words, the building blocks are laid out as if it is a 3D design. In this paper, we report on the first successful implementation of a 2D VIPRAM demonstrator chip (protoVIPRAM00). The results show that these building blocks are ready for 3D stacking.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Evolution of CRISPR RNA recognition and processing by Cas6 endonucleases

In many bacteria and archaea, small RNAs derived from clustered regularly interspaced short palindromic repeats (CRISPRs) associate with CRISPRassociated (Cas) proteins to target foreign DNA for destruction. In Type I and III CRISPR/Cas systems, the Cas6 family of endoribonucleases generates functional CRISPR-derived RNAs by site-specific cleavage of repeat sequences in precursor transcripts. CRISPR repeats differ widely in both sequence and structure, with varying propensity to form hairpin folds immediately preceding the cleavage site. To investigate the evolution of distinct mechanisms for the recognition of diverse CRISPR repeats by Cas6 enzymes, we determined crystal structures of two Thermus thermophilus Cas6 enzymes both alone and bound to substrate and product RNAs. These structures show how the scaffold common to all Cas6 endonucleases has evolved two binding sites with distinct modes of RNA recognition: one specific for a hairpin fold and the other for a single-stranded 5' -terminal segment preceding the hairpin. These findings explain how divergent Cas6 enzymes have emerged to mediate highly selective pre-CRISPR-derived RNA processing across diverse CRISPR systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Face Recognition Oak Ridge (FaRO): A Framework for Distributed and Scalable Biometrics Applications

The facial biometrics community has seen a recent abundance of high-accuracy facial analytic models become freely available. Although these models' capabilities in facial detection, landmark detection, attribute analysis, and recognition are ever-increasing, they aren't always straightforward to deploy in a real-world environment. In reality, the use of the field's ever growing collection of models is becoming exceedingly difficult as library dependencies update and deprecate. Researchers often encounter headaches when attempting to utilize multiple models requiring different or conflicting software packages. Face Recognition Oak Ridge (FaRO) is an open-source project designed to provide a highly modular, flexible framework for unifying facial analytic models through a compartmentalized plug-and-play paradigm built on top of the gRPC (Google Remote Procedure Call) protocol. FaRO's server-client architecture and flexible portability allows easy construction of modularized and heterogeneous face analysis pipelines, distributed over many machines with differing hardware and software resources. This paper outlines FaRO's architecture and current capabilities, along with some experiments in model testing and distributed scaling through FaRO.

Bolme, David↗
DOE OSTI2017

Applying Pattern Recognition to High-Resolution Images to Determine Cellular Signaling Status

Two frequently used tools to acquire high-resolution images of cells are scanning electron microscopy (SEM) and atomic force microscopy (AFM). The former provides a nanometer resolution view of cellular features rapidly and with high throughput, while the latter enables visualizing hydrated and living cells. In current practice, these images are viewed by eye to determine cellular status, e.g. activated versus resting. Automatic and quantitative data analysis is lacking. This work develops an algorithm of pattern recognition that works very effectively for AFM and SEM images. Using rat basophilic leukemia (RBL) cells, our approach creates a support vector machine (SVM) to automatically classify resting and activated cells. 10-fold cross-validation with cells that are known to be activated or resting gives a good estimate of the generalized classification results. The pattern recognition of AFM images achieves 100% accuracy, while SEM reaches 95.4% for our images as well as images published in prior literature. This outcome suggests that our methodology could become an important and frequently used tool for researchers utilizing AFM and SEM for structural characterization as well as determining cellular signaling status and function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The Mertens Unrolled Network (MU-Net): A High Dynamic Range Fusion Neural Network for Through the Windshield Driver Recognition

Face recognition of vehicle occupants through windshields in unconstrained environments poses a number of unique challenges ranging from glare, poor illumination, driver pose and motion blur. In this paper, we further develop the hardware and software components of a custom vehicle imaging system to better overcome these challenges. After the build out of a physical prototype system that performs High Dynamic Range (HDR) imaging, we collect a small dataset of through-windshield image captures of known drivers. We then reformulate the classical Mertens-Kautz-Van Reeth HDR fusion algorithm as a pre-initialized neural network, which we name the Mertens Unrolled Network (MU-Net), for the purpose of fine-tuning the HDR output of through-windshield images. Reconstructed faces from this novel HDR method are then evaluated and compared against other traditional and experimental HDR methods in a pre-trained state-of-the-art (SOTA) facial recognition pipeline, verifying the efficacy of our approach.

Ruby, Max↗
DOE OSTI2015

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was used to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Antibody Recognition of CD4-Induced Open HIV-1 Env Trimers

Human immunodeficiency virus type 1 (HIV-1) envelope (Env), a heterotrimer of gp120-gp41 subunits, mediates fusion of the viral and host cell membranes after interactions with the host receptor CD4 and a coreceptor. CD4 binding induces rearrangements in Env trimer, resulting in a CD4-induced (CD4i) open Env conformation. Structural studies of antibodies isolated from infected donors have defined antibody-Env interactions, with one class of antibodies specifically recognizing the CD4i open Env conformation. In this study, we characterized a group of monoclonal antibodies isolated from HIV-1 infected donors (V2i MAbs) that displayed characteristics of CD4i antibodies. Binding experiments demonstrated that the V2i MAbs preferentially recognize CD4-bound open Env trimers. Structural characterizations of V2i MAb-Env-CD4 trimer complexes using single-particle cryo-electron microscopy showed recognition by V2i MAbs using different angles of approach to the gp120 V1V2 domain and the β2/β3 strands on a CD4i open conformation Env with no direct interactions of the MAbs with CD4. We also characterized CG10, a CD4i antibody that was raised in mice immunized with a gp120-CD4 complex, bound to an Env trimer plus CD4. CG10 exhibited characteristics similar to those of the V2i antibodies, i.e., recognition of the open Env conformation, but showed direct contacts to both CD4 and gp120. Structural comparisons of these and previously characterized CD4i antibody interactions with Env provide a suggested mechanism for how these antibodies are elicited during HIV-1 infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Structural Insights into the Recognition of Phosphopeptide by the FHA Domain of Kanadaptin

Kanadaptin is a nuclear protein of unknown function that is widely expressed in mammalian tissues. The crystal structure of the forkhead-associated (FHA) domain of human kanadaptin was determined to 1.6 Å resolution. The structure reveals an asymmetric dimer in which one monomer is complexed with a phosphopeptide mimic derived from a peptide segment from the N-terminus of a symmetry-related molecule as well as a sulfate bound to the structurally conserved phosphothreonine recognition cleft. This structure provides insights into the molecular recognition features utilized by this family of proteins and represents the first evidence that kanadaptin is likely involved in a phosphorylation-mediated signaling pathway. These results will be of use for designing experiments to further probe the function of kanadaptin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

DNA recognition by an RNA-guided bacterial Argonaute

Argonaute (Ago) proteins are widespread in prokaryotes and eukaryotes and share a four domain architecture capable of RNA- or DNA-guided nucleic acid recognition. Previous studies identified a prokaryotic Argonaute protein from the eubacterium Marinitoga piezophila (MpAgo), which binds preferentially to 50 -hydroxylated guide RNAs and cleaves single-stranded RNA (ssRNA) and DNA (ssDNA) targets. Here we present a 3.2 Å resolution crystal structure of MpAgo bound to a 21-nucleotide RNA guide and a complementary 21-nucleotide ssDNA substrate. Comparison of this ternary complex to other target-bound Argonaute structures reveals a unique orientation of the N-terminal domain, resulting in a straight helical axis of the entire RNA-DNA heteroduplex through the central cleft of the protein. Additionally, mismatches introduced into the heteroduplex reduce MpAgo cleavage efficiency with a symmetric profile centered around the middle of the helix. This pattern differs from the canonical mismatch tolerance of other Argonautes, which display decreased cleavage efficiency for substrates bearing sequence mismatches to the 50 region of the guide strand. This structural analysis of MpAgo bound to a hybrid helix advances our understanding of the diversity of target recognition mechanisms by Argonaute proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Development of a pattern recognition algorithm for reconstructing multi-particle events in the Mu2e detector

Mu2e is an upcoming experiment at Fermilab and its main goal is to search for the Charged Lepton Flavor Violation (CLFV) in the coherent transition of a muon into an electron on an Al target. In Mu2e, multi-particle events can occur simultaneously within the same time region and it is crucial to accurately identify each particle track, including signals, to improve the robustness of track finding methods and enhance reconstruction efficiency. ¯p annihilation is one of the background events and produces multiple particles that can mimic signal events. Additionally, photons from radiative pion captures can produce a γ → $e+e−$ pair, which can be used to calibrate the Mu2e momentum scale and the resolution. The Mu2e track reconstruction sequence begins by grouping hits produced in the tracker based on time and z coordinate information, called TimeCluster, and selected hits are processed to reconstruct helices and determine their momentum. The current pattern recognition algorithms identify a single helix per TimeCluster for single track events. A new pattern recognition algorithm is being developed to reconstruct multi-particle events and its features for finding multiple tracks and the current evaluation results are reported.

Kitagawa, H. [Pisa U.]↗
DOE OSTI2023

Recognition of centromere‐specific histone Cse4 by the inner kinetochore Okp1‐Ame1 complex

Abstract Successful mitosis depends on the timely establishment of correct chromosomal attachments to microtubules. The kinetochore, a modular multiprotein complex, mediates this connection by recognizing specialized chromatin containing a histone H3 variant called Cse4 in budding yeast and CENP‐A in vertebrates. Structural features of the kinetochore that enable discrimination between Cse4/CENP‐A and H3 have been identified in several species. How and when these contribute to centromere recognition and how they relate to the overall structure of the inner kinetochore are unsettled questions. More generally, this molecular recognition ensures that only one kinetochore is built on each chromatid and that this happens at the right place on the chromatin fiber. We have determined the crystal structure of a Cse4 peptide bound to the essential inner kinetochore Okp1‐Ame1 heterodimer from budding yeast. The structure and related experiments show in detail an essential point of Cse4 contact and provide information about the arrangement of the inner kinetochore.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Through the Windshield Driver Recognition

Biometric recognition of vehicle occupants in unconstrained environments is rife with a host of challenges. In particular, the complications arising from imaging through vehicle windshields provide a significant hurdle. Distance to target, glare, poor lighting, head pose of occupants, and speed of vehicle are some of the challenges. We explore the construction of a multi-unit computational camera system to mitigate these challenges in order to obtain accurate and consistent face recognition results. This paper documents the hardware components and software design of the computational imaging system. Also, we document the use of RCNN for face detection and GAN for machine learning-inspired High Dynamic Range Imaging, artifact removal, and image fusion.

Cornett, David↗
DOE OSTI2019

Broad substrate-specific phosphorylation events are associated with the initial stage of plant cell wall recognition in Neurospora crassa

Fungal plant cell wall degradation processes are governed by complex regulatory mechanisms, allowing the organisms to adapt their metabolic program with high specificity to the substrate at hand. While the uptake of representative plant cell wall mono- and disaccharides is known to induce specific transcriptional and translational responses, the processes related to early signal reception and transduction are still enigmatic. A fast and reversible way of transmitting extracellular signals throughout the cell are protein phosphorylations, which could initiate adaptations of the fungal metabolism on a post-translational level. In an effort to elucidate how changes in the initial substrate recognition phase of Neurospora crassa affect the global phosphorylation pattern, phosphoproteomics was performed after a short (2 minute) induction period with several plant cell wall-related mono- and disaccharides. The MS/MS-based peptide analysis revealed a large number of proteins that are phosphorylated or de-phosphorylated in a substrate-specific manner. A protein-protein-interaction network was constructed based on the proteins identified by MS/MS. Using this network, putative interaction partners of several phosphorylated proteins of interest were determined. This led to the discovery of substrate-specific protein-interactions that might be involved in mediating the substrate recognition of N. crassa. Besides a high number of kinases, phosphatases and transcription factors to be affected by differential phosphorylation, our data demonstrate, for example, that the cAMP signaling pathway is heavily modified by substrate-specific phosphorylations, including the key component adenylate cyclase CR-1 as well as several G-protein-coupled receptors. In addition, four differentially phosphorylated F-Box proteins were identified in the phospho-proteome. When physiologically characterized using the respective gene deletion strains, Fbx-19 and Fbx-22 were found to be involved in carbon catabolite repression responses. Overall, these results improve our understanding of how fungi respond to environmental cues and provide novel insights into the mechanisms of sensory perception and signal transduction during lignocellulose degradation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Mechanism of DNA Lesion Homing and Recognition by the Uvr Nucleotide Excision Repair System

Nucleotide excision repair (NER) is an essential DNA repair system distinguished from other such systems by its extraordinary versatility. NER removes a wide variety of structurally dissimilar lesions having only their bulkiness in common. NER can also repair several less bulky nucleobase lesions, such as 8-oxoguanine. Thus, how a single DNA repair system distinguishes such a diverse array of structurally divergent lesions from undamaged DNA has been one of the great unsolved mysteries in the field of genome maintenance. Here we employ a synthetic crystallography approach to obtain crystal structures of the pivotal NER enzyme UvrB in complex with duplex DNA, trapped at the stage of lesion-recognition. These structures coupled with biochemical studies suggest that UvrB integrates the ATPase-dependent helicase/translocase and lesion-recognition activities. Our work also conclusively establishes the identity of the lesion-containing strand and provides a compelling insight to how UvrB recognizes a diverse array of DNA lesions.

59 BASIC BIOLOGICAL SCIENCES↗