Unconventional human CD61 pairing with CD103 promotes TCR signaling and antigen-specific T cell cytotoxicity.

Cancer remains one of the leading causes of mortality worldwide, leading to increased interest in utilizing immunotherapy strategies for better cancer treatments. In the past decade, CD103+ T cells have been associated with better clinical prognosis in patients with cancer. However, the specific immune mechanisms contributing toward CD103-mediated protective immunity remain unclear. Here, we show an unexpected and transient CD61 expression, which is paired with CD103 at the synaptic microclusters of T cells. CD61 colocalization with the T cell antigen receptor further modulates downstream T cell antigen receptor signaling, improving antitumor cytotoxicity and promoting physiological control of tumor growth. Clinically, the presence of CD61+ tumor-infiltrating T lymphocytes is associated with improved clinical outcomes, mediated through enhanced effector functions and phenotype with limited evidence of cellular exhaustion. In conclusion, this study identified an unconventional and transient CD61 expression and pairing with CD103 on human immune cells, which potentiates a new target for immune-based cellular therapies.

Differential effects of inosine monophosphate dehydrogenase (IMPDH/GuaB) inhibition in Acinetobacter baumannii and Escherichia coli.

Inosine 5'-monophosphate dehydrogenase (IMPDH), known as GuaB in bacteria, catalyzes the rate-limiting step in de novo guanine biosynthesis and is conserved from humans to bacteria. We developed a series of potent inhibitors that selectively target GuaB over its human homolog. Here, we show that these GuaB inhibitors are bactericidal, generate phenotypic signatures that are distinct from other antibiotics, and elicit different time-kill kinetics and regulatory responses in two important Gram-negative pathogens: Acinetobacter baumannii and Escherichia coli. Specifically, the GuaB inhibitor G6 rapidly kills A. baumannii but only kills E. coli after 24 h. After exposure to G6, the expression of genes involved in purine biosynthesis and stress responses change in opposite directions while siderophore biosynthesis is downregulated in both species. Our results suggest that different species respond to GuaB inhibition using distinct regulatory programs and possibly explain the different bactericidal kinetics upon GuaB inhibition. The comparison highlights opportunities for developing GuaB inhibitors as novel antibiotics.IMPORTANCEA. baumannii is a priority bacterial pathogen for which development of new antibiotics is urgently needed due to the emergence of multidrug resistance. We recently developed a series of specific inhibitors against GuaB, a bacterial inosine 5'-monophosphate dehydrogenase, and achieved sub-micromolar minimum inhibitory concentrations against A. baumannii. GuaB catalyzes the rate-limiting step of de novo guanine biosynthesis and is highly conserved across bacterial pathogens. This study shows that inhibition of GuaB induced a bacterial morphological profile distinct from that of other classes of antibiotics, highlighting a novel mechanism of action. Moreover, our transcriptomic analysis showed that regulation of de novo purine biosynthesis and stress responses of A. baumannii upon GuaB inhibition differed significantly from that of E. coli.

Biochemical Characterization of Rice Xylan Biosynthetic Enzymes in Determining Xylan Chain Elongation and Substitutions.

Grass xylan consists of a linear chain of ß-1,4-linked xylosyl residues that often form domains substituted only with either arabinofuranose (Araf) or glucuronic acid (GlcA)/methylglucuronic acid (MeGlcA) residues, and it lacks the unique reducing end tetrasaccharide sequence found in dicot xylan. The mechanism of how grass xylan backbone elongation is initiated and how its distinctive substitution pattern is determined remains elusive. Here, we performed biochemical characterization of rice xylan biosynthetic enzymes, including xylan synthases, glucuronyltransferases and methyltransferases. Activity assays of rice xylan synthases demonstrated that they required short xylooligomers as acceptors for their activities. While rice xylan glucuronyltransferases effectively glucuronidated unsubstituted xylohexaose acceptors, they transferred little GlcA residues onto (Araf)-substituted xylohexaoses and rice xylan 3-O-arabinosyltransferase could not arabinosylate GlcA-substituted xylohexaoses, indicating that their intrinsic biochemical properties may contribute to the distinctive substitution patterns of rice xylan. In addition, we found that rice xylan methyltransferase exhibited a low substrate binding affinity, which may explain the partial GlcA methylation in rice xylan. Furthermore, immunolocalization of xylan in xylem cells of both rice and Arabidopsis showed that it was deposited together with cellulose in secondary walls without forming xylan-rich nanodomains. Together, our findings provide new insights into the biochemical mechanisms underlying xylan backbone elongation and substitutions in grass species.

Structural basis for dual-mode inhibition of the ABC transporter MsbA.

The movement of core-lipopolysaccharide across the inner membrane of Gram-negative bacteria is catalysed by an essential ATP-binding cassette transporter, MsbA. Recent structures of MsbA and related transporters have provided insights into the molecular basis of active lipid transport; however, structural information about their pharmacological modulation remains limited. Here we report the 2.9 Å resolution structure of MsbA in complex with G907, a selective small-molecule antagonist with bactericidal activity, revealing an unprecedented mechanism of ABC transporter inhibition. G907 traps MsbA in an inward-facing, lipopolysaccharide-bound conformation by wedging into an architecturally conserved transmembrane pocket. A second allosteric mechanism of antagonism occurs through structural and functional uncoupling of the nucleotide-binding domains. This study establishes a framework for the selective modulation of ABC transporters and provides rational avenues for the design of new antibiotics and other therapeutics targeting this protein family.

Quantum Markov blankets for meta-learned classical inferential paradoxes with suboptimal free energy.

Quantum active Bayesian inference and quantum Markov blankets enable robust modeling and simulation of difficult-to-render natural agent-based classical inferential paradoxes interfaced with task-specific environments. Within a non-realist cognitive completeness regime, quantum Markov blankets ensure meta-learned irrational decision making is fitted to explainable manifolds at optimal free energy, where acceptable incompatible observations or temporal Bell-inequality violations represent important verifiable real-world outcomes.

Characterizing RNA modifications in the central nervous system and single cells by RNA sequencing and liquid chromatography-tandem mass spectrometry techniques.

Post-transcriptional modifications to RNA constitute a newly appreciated layer of translation regulation in the central nervous system (CNS). The identity, stoichiometric quantity, and sequence position of these unusual epitranscriptomic marks are central to their function, making analytical methods that are capable of accurate and reproducible measurements paramount to the characterization of the neuro-epitranscriptome. RNA sequencing-based methods and liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have been leveraged to provide an early glimpse of the landscape of RNA modifications in bulk CNS tissues. However, recent advances in sample preparation, separations, and detection methods have revealed that individual cells display remarkable heterogeneity in their RNA modification profiles, raising questions about the prevalence and function of cell-specific distributions of post-transcriptionally modified nucleosides in the brain. In this Trends article, we present an overview of RNA sequencing and LC-MS/MS methodologies for the analysis of RNA modifications in the CNS with special emphasis on recent advancements in techniques that facilitate single-cell and subcellular detection.

USP7 small-molecule inhibitors interfere with ubiquitin binding.

The ubiquitin system regulates essential cellular processes in eukaryotes. Ubiquitin is ligated to substrate proteins as monomers or chains and the topology of ubiquitin modifications regulates substrate interactions with specific proteins. Thus ubiquitination directs a variety of substrate fates including proteasomal degradation. Deubiquitinase enzymes cleave ubiquitin from substrates and are implicated in disease; for example, ubiquitin-specific protease-7 (USP7) regulates stability of the p53 tumour suppressor and other proteins critical for tumour cell survival. However, developing selective deubiquitinase inhibitors has been challenging and no co-crystal structures have been solved with small-molecule inhibitors. Here, using nuclear magnetic resonance-based screening and structure-based design, we describe the development of selective USP7 inhibitors GNE-6640 and GNE-6776. These compounds induce tumour cell death and enhance cytotoxicity with chemotherapeutic agents and targeted compounds, including PIM kinase inhibitors. Structural studies reveal that GNE-6640 and GNE-6776 non-covalently target USP7 12 Å distant from the catalytic cysteine. The compounds attenuate ubiquitin binding and thus inhibit USP7 deubiquitinase activity. GNE-6640 and GNE-6776 interact with acidic residues that mediate hydrogen-bond interactions with the ubiquitin Lys48 side chain, suggesting that USP7 preferentially interacts with and cleaves ubiquitin moieties that have free Lys48 side chains. We investigated this idea by engineering di-ubiquitin chains containing differential proximal and distal isotopic labels and measuring USP7 binding by nuclear magnetic resonance. This preferential binding protracted the depolymerization kinetics of Lys48-linked ubiquitin chains relative to Lys63-linked chains. In summary, engineering compounds that inhibit USP7 activity by attenuating ubiquitin binding suggests opportunities for developing other deubiquitinase inhibitors and may be a strategy more broadly applicable to inhibiting proteins that require ubiquitin binding for full functional activity.

High rates of observed face mask use at Colorado universities align with students' opinions about masking and support the safety and viability of in-person higher education during the COVID-19 pandemic.

BACKGROUND: Over the course of the COVID-19 pandemic, colleges and universities have focused on creating policies, such as mask mandates, to minimize COVID-19 transmission both on their campuses and in the surrounding community. Adherence to and opinions about these policies remain largely unknown. METHODS: The Centers for Disease Control and Prevention (CDC) developed a cross-sectional study, the Mask Adherence and Surveillance at Colleges and Universities Project (MASCUP!), to objectively and inconspicuously measure rates of mask use at institutes of higher education via direct observation. From February 15 through April 11, 2021 the University of Colorado Boulder (CU, n = 2,808 observations) and Colorado State University Fort Collins (CSU, n = 3,225 observations) participated in MASCUP! along with 52 other institutes of higher education (n = 100,353 observations) spanning 21 states and the District of Columbia. Mask use was mandatory at both Colorado universities and student surveys were administered to assess student beliefs and attitudes. RESULTS: We found that 91.7%, 93.4%, and 90.8% of persons observed at indoor locations on campus wore a mask correctly at University of Colorado, Colorado State University, and across the 52 other schools, respectively. Student responses to questions about masking were in line with these observed rates of mask use where 92.9% of respondents at CU and 89.8% at CSU believe that wearing masks can protect the health of others. Both Colorado universities saw their largest surges in COVID-19 cases in the fall of 2020, with markedly lower case counts during the mask observation window in the spring of 2021. CONCLUSION: High levels of mask use at Colorado's two largest campuses aligned with rates observed at other institutes across the country. These high rates of use, coupled with positive student attitudes about mask use, demonstrate that masks were widely accepted and may have contributed to reduced COVID-19 case counts. This study supports an emerging body of literature substantiating masks as an effective, low-cost measure to reduce disease transmission and establishes masking (with proper education and promotion) as a viable tactic to reduce respiratory disease transmission on college campuses.

Emergent linguistic structure in artificial neural networks trained by self-supervision.

This paper explores the knowledge of linguistic structure learned by large artificial neural networks, trained via self-supervision, whereby the model simply tries to predict a masked word in a given context. Human language communication is via sequences of words, but language understanding requires constructing rich hierarchical structures that are never observed explicitly. The mechanisms for this have been a prime mystery of human language acquisition, while engineering work has mainly proceeded by supervised learning on treebanks of sentences hand labeled for this latent structure. However, we demonstrate that modern deep contextual language models learn major aspects of this structure, without any explicit supervision. We develop methods for identifying linguistic hierarchical structure emergent in artificial neural networks and demonstrate that components in these models focus on syntactic grammatical relationships and anaphoric coreference. Indeed, we show that a linear transformation of learned embeddings in these models captures parse tree distances to a surprising degree, allowing approximate reconstruction of the sentence tree structures normally assumed by linguists. These results help explain why these models have brought such large improvements across many language-understanding tasks.

Ownership psychology as a "cognitive cell" adaptation: A minimalist model of microbial goods theory.

Microbes perfect social interactions with intuitive logics and goal-directed reciprocity. These multilevel, cognition-resembling adaptations in Dictyostelid cellular molds enable individual-to-group viability through public/private bacterial farming and dynamic marketspaces. Like humans and animals, Dictyostelid livestock-ownership depends on environmental sensing, cooperation, and competition. Moreover, social-norm policing of cosmopolitan colonies coordinates farmer decisions, phenotypes, and ownership identities with bacteria herding, privatization, and consumption.

Communication consistency, completeness, and complexity of digital ideography in trustworthy mobile extended reality.

Communication barriers long-associated with ideographs, including combinatorial grapholinguistic complexity, computational encoding-decoding complexity, and technological rendering and deployment, become trivialized through advancements in interoperable smart mobile digital devices. Such technologies impart unprecedented extended-reality user hazards only mitigated by unprecedented colloquial and bureaucratic societal norms. Digital age norms thus influence natural ideographic language origins and evolution in ways novel to human history.

Disruption of IRE1α through its kinase domain attenuates multiple myeloma.

Multiple myeloma (MM) arises from malignant immunoglobulin (Ig)-secreting plasma cells and remains an incurable, often lethal disease despite therapeutic advances. The unfolded-protein response sensor IRE1α supports protein secretion by deploying a kinase-endoribonuclease module to activate the transcription factor XBP1s. MM cells may co-opt the IRE1α-XBP1s pathway; however, the validity of IRE1α as a potential MM therapeutic target is controversial. Genetic disruption of IRE1α or XBP1s, or pharmacologic IRE1α kinase inhibition, attenuated subcutaneous or orthometastatic growth of MM tumors in mice and augmented efficacy of two established frontline antimyeloma agents, bortezomib and lenalidomide. Mechanistically, IRE1α perturbation inhibited expression of key components of the endoplasmic reticulum-associated degradation machinery, as well as secretion of Ig light chains and of cytokines and chemokines known to promote MM growth. Selective IRE1α kinase inhibition reduced viability of CD138+ plasma cells while sparing CD138- cells derived from bone marrows of newly diagnosed or posttreatment-relapsed MM patients, in both US- and European Union-based cohorts. Effective IRE1α inhibition preserved glucose-induced insulin secretion by pancreatic microislets and viability of primary hepatocytes in vitro, as well as normal tissue homeostasis in mice. These results establish a strong rationale for developing kinase-directed inhibitors of IRE1α for MM therapy.

Single-Neuron RNA Modification Analysis by Mass Spectrometry: Characterizing RNA Modification Patterns and Dynamics with Single-Cell Resolution.

The entire collection of post-transcriptional modifications to RNA, known as the epitranscriptome, has been increasingly recognized as a critical regulatory layer in the cellular translation machinery. However, contemporary methods for the analysis of RNA modifications are limited to the detection of highly abundant modifications in bulk tissue samples, potentially obscuring unique epitranscriptomes of individual cells with population averages. We developed an approach, single-neuron RNA modification analysis by mass spectrometry (SNRMA-MS), that enables the detection and quantification of numerous post-transcriptionally modified nucleosides in single cells. When compared to a conventional RNA extraction approach that does not allow detection of RNA modifications in single cells, SNRMA-MS leverages an optimized sample preparation approach to detect up to 16 RNA modifications in individual neurons from the central nervous system of Aplysia californica. SNRMA-MS revealed that the RNA modification profiles of identified A. californica neurons with different physiological functions were mostly cell specific. However, functionally homologous neurons tended to demonstrate similar modification patterns. Stable isotope labeling with CD3-Met showed significant differences in RNA methylation rates that were dependent on the identity of the modification and the cell, with metacerebral cells (MCCs) displaying the fastest incorporation of CD3 groups into endogenous RNAs. Quantitative SNRMA-MS showed higher intracellular concentrations for 2'-O-methyladenosine and 2'-O-methylcytidine in homologous R2/LPl1 cell pairs than in MCCs. Overall, SNRMA-MS is the first analytical approach capable of simultaneously quantifying numerous RNA modifications in single neurons and revealing cell-specific modification profiles.

Automated Solid-Phase Microextraction and Negative Chemical Ionization GC-MS for the Measurement of Synthetic Pyrethroids.

Synthetic pyrethroids are frequently detected as trace contaminants in sediment and natural waters. Because of the importance of measuring both total and freely available concentrations for ecotoxicity evaluations, solid-phase microextraction (SPME) combined with gas chromatography-mass spectrometry using negative chemical ionization (NCI-GC-MS) was investigated as an analytical technique. Automated SPME-NCI-GC-MS quantification of freely dissolved (and thus potentially bioavailable) pyrethroids in aqueous samples containing dissolved organic matter (DOM) was successfully applied. The introduction of stable isotope-labeled pyrethroid calibration standards into the water sample allows for the simultaneous determination of total concentrations. Because pyrethroids adsorb rapidly to container walls (especially in calibration standard solutions without DOM) it was necessary to develop a technique to minimize the resulting time-dependent losses from calibration standard solutions in autosampler vials as they await analysis. A staggered preparation of these analytical calibration standards immediately prior to analysis was shown to ameliorate this problem. The developed method provides accurate and reproducible results for aqueous samples containing a range of dissolved organic matter concentrations (e.g., sediment pore water or sediment/water mixtures) and yields practical benefits in comparison to conventional analysis methods, such as reduced sample volume requirements, reduced solvent consumption, and fewer sample manipulations, and makes simultaneous measurements of freely dissolved/bioavailable pyrethroids and total pyrethroids possible.

Insect Hemolymph Immune Complexes.

Insects possess powerful immune systems that have evolved to defend against wounding and environmental pathogens such as bacteria, fungi, protozoans, and parasitoids. This surprising sophistication is accomplished through the activation of multiple immune pathways comprised of a large array of components, many of which have been identified and studied in detail using both genetic manipulations and traditional biochemical techniques. Recent advances indicate that certain pathways activate arrays of proteins that interact to form large functional complexes. Here we discuss three examples from multiple insects that exemplify such processes, including pathogen recognition, melanization, and coagulation. The functionality of each depends on integrating recognition with the recruitment of immune effectors capable of healing wounds and destroying pathogens. In both melanization and coagulation, protein interactions also appear to be essential for enzymatic activities tied to the formation of melanin and for the recruitment of hemocytes. The importance of these immune complexes is highlighted by the evolution of mechanisms in pathogens to disrupt their formation, an example of which is provided. While technically difficult to study, and not always readily amenable to dissection through genetics, modern mass spectrometry has become an indispensable tool in the study of these higher-order protein interactions. The formation of immune complexes should be viewed as an essential and emerging frontier in the study of insect immunity.

Spectral Features of Canthaxanthin in HCP2. A QM/MM Approach.

The increased interest in sequencing cyanobacterial genomes has allowed the identification of new homologs to both the N-terminal domain (NTD) and C-terminal domain (CTD) of the Orange Carotenoid Protein (OCP). The N-terminal domain homologs are known as Helical Carotenoid Proteins (HCPs). Although some of these paralogs have been reported to act as singlet oxygen quenchers, their distinct functional roles remain unclear. One of these paralogs (HCP2) exclusively binds canthaxanthin (CAN) and its crystal structure has been recently characterized. Its absorption spectrum is significantly red-shifted, in comparison to the protein in solution, due to a dimerization where the two carotenoids are closely placed, favoring an electronic coupling interaction. Both the crystal and solution spectra are red-shifted by more than 50 nm when compared to canthaxanthin in solution. Using molecular dynamics (MD) and quantum mechanical/molecular mechanical (QM/MM) studies of HCP2, we aim to simulate these shifts as well as obtain insight into the environmental and coupling effects of carotenoid-protein interactions.

Quantum decision corrections for the neuroeconomics of irrational movement control and goal attainment.

Quantum decision theory corrects categorical and propositional logic pathologies common to classic statistical goal-oriented reasoning, such as rational neuroeconomics-based optimal foraging. Within this ecosalient framework, motivation, perception, learning, deliberation, brain computation, and conjunctive risk-order errors may be understood for subjective utility judgments underlying either rational or irrational canonical decisions-actions used to choose, procure, and consume rewarding nutrition with variable fitness.

Biphasic Liquid Microjunction Extraction for Profiling Neuronal RNA Modifications by Liquid Chromatography-Tandem Mass Spectrometry.

RNA modifications are emerging as critical players in the spatiotemporal regulation of gene expression. Although liquid chromatography-tandem mass spectrometry (LC-MS/MS) enables the simultaneous quantification of numerous enzymatically modified RNAs in a biological sample, conventional RNA extraction and enzymatic digestion protocols that are employed prior to analysis have precluded the application of this technique for small-volume samples. In this study, a biphasic liquid microjunction (LMJ) extraction system using coaxial capillaries that direct and aspirate extraction solvents onto a ∼350 µm diameter sample spot was developed and applied for the extraction of RNA from individual cell clusters in the central nervous system of the marine mollusk Aplysia californica. To maximize RNA recoveries, optimized extraction solvents consisting of 10% methanol and chloroform were evaluated under dynamic and static extraction conditions. An MS-compatible RNA digestion buffer was developed to minimize the number of sample-transfer steps and facilitate the direct enzymatic digestion of extracted RNA within the sample collection tube. Compared to RNA extraction using a conventional phenol-chloroform method, the LMJ-based method provided a 3-fold greater coverage of the neuronal epitranscriptome for similar amounts of tissues and also produced mRNA of sufficient purity for reverse transcription polymerase chain reaction amplification. Using this approach, the expression of RNA-modifying enzymes in a given neuronal cell cluster can be characterized and simultaneously correlated with the LC-MS/MS analysis of RNA modifications within the same subset of neurons.

Reduced scale model qualification of 5-L and 250-ml bioreactors using multivariant visualization and Bayesian inferential methods.

A novel method for the qualification of reduced scale models (RSMs) was illustrated using data from both a 250-ml advanced microscale bioreactor (ambr) and a 5-L bioreactor RSM for a 2,000-L manufacturing scale process using a CHO cell line to produce a recombinant monoclonal antibody. The example study showed how the method was used to identify process performance attributes and product quality attributes that capture important aspects of the RSM qualification process. The method uses two novel statistical approaches: multivariate dimension reduction and data visualization techniques, via partial least squares discriminant analysis (PLS-DA), and Bayesian multivariate linear modeling for inferential analysis. Bayesian multivariate linear modeling allows for individual probability distributions of the differences of the mean of each attribute for each scale, as well as joint probability statements on the differences of the means for multiple attributes. Depending on the results of this inferential procedure, PLS-DA is used to identify the process performance outputs at the different scales which have the greatest negative impact on the multivariate Bayesian joint probabilities. Experience with that particular process can then be leveraged to adjust operating conditions to minimize these differences, and then equivalence can be reassessed using the multivariate linear model.

Digital life, a theory of minds, and mapping human and machine cultural universals.

Emerging cybertechnologies, such as social digibots, bend epistemological conventions of life and culture already complicated by human and animal relationships. Virtually-augmented niches of machines and organic life promise new free-energy-governed selection of intelligent digital life. These provocative eco-evolutionary contexts demand a theory of (natural and artificial) minds to characterize and validate the immersive social phenomena universally-shaping cultural affordances.