Delocalized, asynchronous, closed-loop discovery of organic laser emitters.

Contemporary materials discovery requires intricate sequences of synthesis, formulation, and characterization that often span multiple locations with specialized expertise or instrumentation. To accelerate these workflows, we present a cloud-based strategy that enabled delocalized and asynchronous design-make-test-analyze cycles. We showcased this approach through the exploration of molecular gain materials for organic solid-state lasers as a frontier application in molecular optoelectronics. Distributed robotic synthesis and in-line property characterization, orchestrated by a cloud-based artificial intelligence experiment planner, resulted in the discovery of 21 new state-of-the-art materials. Gram-scale synthesis ultimately allowed for the verification of best-in-class stimulated emission in a thin-film device. Demonstrating the asynchronous integration of five laboratories across the globe, this workflow provides a blueprint for delocalizing-and democratizing-scientific discovery.

Metabolic trade-offs in Neonatal sepsis triggered by TLR4 and TLR1/2 ligands result in unique dysfunctions in neural breathing circuits.

Neonatal sepsis remains one of the leading causes of mortality in newborns. Several brainstem-regulated physiological processes undergo disruption during neonatal sepsis. Mechanistic knowledge gaps exist at the interplay between metabolism and immune activation to brainstem neural circuits and pertinent physiological functions in neonates. To delineate this association, we induced systemic inflammation either by TLR4 (LPS) or TLR1/2 (PAM3CSK4) ligand administration in postnatal day 5 mice (PD5). Our findings show that LPS and PAM3CSK4 evoke substantial changes in respiration and metabolism. Physiological trade-offs led to hypometabolic-hypothermic responses due to LPS, but not PAM3CSK4, whereas to both TLR ligands blunted respiratory chemoreflexes. Neuroinflammatory pathways modulation in brainstem showed more robust effects in LPS than PAM3CSK4. Brainstem neurons, microglia, and astrocyte gene expression analyses showed unique responses to TLR ligands. PAM3CSK4 did not significantly modulate gene expression changes in GLAST-1 positive brainstem astrocytes. PD5 pups receiving PAM3CSK4 failed to maintain a prolonged metabolic state repression, which correlated to enhanced gasping latency and impaired autoresuscitation during anoxic chemoreflex challenges. In contrast, LPS administered pups showed no significant changes in anoxic chemoreflex. Electrophysiological studies from brainstem slices prepared from pups exposed to either TLR4 or PAM3CSK4 showed compromised transmission between preBötzinger complex and Hypoglossal as an exclusive response to the TLR1/2 ligand. Spatial gene expression analysis demonstrated a region-specific modulation of PAM3CSK4 within the raphe nucleus relative to other anatomical sites evaluated. Our findings suggest that metabolic changes due to inflammation might be a crucial tolerance mechanism for neonatal sepsis preserving neural control of breathing.

Unsupervised machine learning models reveal predictive clinical markers of glioblastoma patient survival using white blood cell counts prior to initiating chemoradiation.

Background: Glioblastoma is a malignant brain tumor requiring careful clinical monitoring even after primary management. Personalized medicine has suggested the use of various molecular biomarkers as predictors of patient prognosis or factors utilized for clinical decision-making. However, the accessibility of such molecular testing poses a constraint for various institutes requiring identification of low-cost predictive biomarkers to ensure equitable care. Methods: We collected retrospective data from patients seen at Ohio State University, University of Mississippi, Barretos Cancer Hospital (Brazil), and FLENI (Argentina) who were managed for glioblastoma-amounting to 581 patient records documented using REDCap. Patients were evaluated using an unsupervised machine learning approach comprised of dimensionality reduction and eigenvector analysis to visualize the inter-relationship of collected clinical features. Results: We discovered that the serum white blood cell (WBC) count of a patient during baseline planning for treatment was predictive of overall survival with an over 6-month median survival difference between the upper and lower quartiles of WBC count. By utilizing an objective PD-L1 immunohistochemistry quantification algorithm, we were further able to identify an increase in PD-L1 expression in glioblastoma patients with high serum WBC counts. Conclusions: These findings suggest that in a subset of glioblastoma patients the incorporation of WBC count and PD-L1 expression in the brain tumor biopsy as simple biomarkers predicting glioblastoma patient survival. Moreover, machine learning models allow the distillation of complex clinical data sets to uncover novel and meaningful clinical relationships.

Chemoproteomic development of SLC15A4 inhibitors with anti-inflammatory activity.

SLC15A4 is an endolysosome-resident transporter linked with autoinflammation and autoimmunity. Specifically, SLC15A4 is critical for Toll-like receptors (TLRs) 7-9 as well as nucleotide-binding oligomerization domain-containing protein (NOD) signaling in several immune cell subsets. Notably, SLC15A4 is essential for the development of systemic lupus erythematosus in murine models and is associated with autoimmune conditions in humans. Despite its therapeutic potential, the availability of quality chemical probes targeting SLC15A4 functions is limited. In this study, we used an integrated chemical proteomics approach to develop a suite of chemical tools, including first-in-class functional inhibitors, for SLC15A4. We demonstrate that these inhibitors suppress SLC15A4-mediated endolysosomal TLR and NOD functions in a variety of human and mouse immune cells; we provide evidence of their ability to suppress inflammation in vivo and in clinical settings; and we provide insights into their mechanism of action. Our findings establish SLC15A4 as a druggable target for the treatment of autoimmune and autoinflammatory conditions.

Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences.

Post-resection radiologic monitoring to identify areas of new or progressive enhancement concerning for cancer recurrence is critical during patients with glioblastoma follow-up. However, treatment-related pseudoprogression presents with similar imaging features but requires different clinical management. While pathologic diagnosis is the gold standard to differentiate true progression and pseudoprogression, the lack of objective clinical standards and admixed histologic presentation creates the needs to (1) validate the accuracy of current approaches and (2) characterize differences between these entities to objectively differentiate true disease. We demonstrated using an online RNAseq repository of recurrent glioblastoma samples that cancer-immune cell activity levels correlate with heterogenous clinical outcomes in patients. Furthermore, nCounter RNA expression analysis of 48 clinical samples taken from second neurosurgical resection supports that pseudoprogression gene expression pathways are dominated with immune activation, whereas progression is predominated with cell cycle activity. Automated image processing and spatial expression analysis however highlight a failure to apply these broad expressional differences in a subset of cases with clinically challenging admixed histology. Encouragingly, applying unsupervised clustering approaches over our segmented histologic images provides novel understanding of morphologically derived differences between progression and pseudoprogression. Spatially derived data further highlighted polarization of myeloid populations that may underscore the tumorgenicity of novel lesions. These findings not only help provide further clarity of potential targets for pathologists to better assist stratification of progression and pseudoprogression, but also highlight the evolution of tumor-immune microenvironment changes which promote tumor recurrence.

The MIF promoter SNP rs755622 is associated with immune activation in glioblastoma.

Intratumoral heterogeneity is a defining hallmark of glioblastoma, driving drug resistance and ultimately recurrence. Many somatic drivers of microenvironmental change have been shown to affect this heterogeneity and, ultimately, the treatment response. However, little is known about how germline mutations affect the tumoral microenvironment. Here, we find that the single-nucleotide polymorphism (SNP) rs755622 in the promoter of the cytokine macrophage migration inhibitory factor (MIF) is associated with increased leukocyte infiltration in glioblastoma. Furthermore, we identified an association between rs755622 and lactotransferrin expression, which could also be used as a biomarker for immune-infiltrated tumors. These findings demonstrate that a germline SNP in the promoter region of MIF may affect the immune microenvironment and further reveal a link between lactotransferrin and immune activation.

Unsupervised machine learning models reveal predictive markers of glioblastoma patient survival using white blood cell counts prior to initiating chemoradiation.

Purpose: Glioblastoma is a malignant brain tumor requiring careful clinical monitoring even after primary management. Personalized medicine has suggested use of various molecular biomarkers as predictors of patient prognosis or factors utilized for clinical decision making. However, the accessibility of such molecular testing poses a constraint for various institutes requiring identification of low-cost predictive biomarkers to ensure equitable care. Methods: We collected retrospective data from patients seen at Ohio State University, University of Mississippi, Barretos Cancer Hospital (Brazil), and FLENI (Argentina) who were managed for glioblastoma-amounting to nearly 600 patient records documented using REDCap. Patients were evaluated using an unsupervised machine learning approach comprised of dimensionality reduction and eigenvector analysis to visualize the inter-relationship of collected clinical features. Results: We discovered that white blood cell count of a patient during baseline planning for treatment was predictive of overall survival with an over 6-month median survival difference between the upper and lower quartiles of white blood cell count. By utilizing an objective PDL-1 immunohistochemistry quantification algorithm, we were further able to identify an increase in PDL-1 expression in glioblastoma patients with high white blood cell counts. Conclusion: These findings suggest that in a subset of glioblastoma patients the incorporation of white blood cell count and PDL-1 expression in the brain tumor biopsy as simple biomarkers predicting glioblastoma patient survival. Moreover, use of machine learning models allows us to visualize complex clinical datasets to uncover novel clinical relationships.

Single-cell RNA sequencing reveals immunosuppressive myeloid cell diversity during malignant progression in a murine model of glioma.

Recent studies have shown the importance of the dynamic tumor microenvironment (TME) in high-grade gliomas (HGGs). In particular, myeloid cells are known to mediate immunosuppression in glioma; however, it is still unclear if myeloid cells play a role in low-grade glioma (LGG) malignant progression. Here, we investigate the cellular heterogeneity of the TME using single-cell RNA sequencing in a murine glioma model that recapitulates the malignant progression of LGG to HGG. LGGs show increased infiltrating CD4+ and CD8+ T cells and natural killer (NK) cells in the TME, whereas HGGs abrogate this infiltration. Our study identifies distinct macrophage clusters in the TME that show an immune-activated phenotype in LGG but then evolve to an immunosuppressive state in HGG. We identify CD74 and macrophage migration inhibition factor (MIF) as potential targets for these distinct macrophage populations. Targeting these intra-tumoral macrophages in the LGG stage may attenuate their immunosuppressive properties and impair malignant progression.

A heterobifunctional molecule system for targeted protein acetylation in cells.

Protein acetylation is a vital biological process that regulates myriad cellular events. Despite its profound effects on protein function, there are limited research tools to dynamically and selectively regulate protein acetylation. To address this, we developed an acetylation tagging system, called AceTAG, to target proteins for chemically induced acetylation directly in live cells. AceTAG uses heterobifunctional molecules composed of a ligand for the lysine acetyltransferase p300/CBP and a FKBP12F36V ligand. Target proteins are genetically tagged with FKBP12F36V and brought in proximity with p300/CBP by AceTAG molecules to subsequently undergo protein-specific acetylation. Targeted acetylation of proteins in cells using AceTAG is selective, rapid, and can be modulated in a dose-dependent fashion, enabling controlled investigations of acetylated protein targets directly in cells. In this protocol, we focus on (1) generation of AceTAG constructs and cell lines, (2) in vitro characterization of AceTAG mediated ternary complex formation and cellular target engagement studies; and (3) in situ characterization of AceTAG induced acetylation of targeted proteins by immunoblotting and quantitative proteomics. The robust procedures described herein should enable the use of AceTAG to explore the roles of acetylation for a variety of protein targets.

Taf2 mediates DNA binding of Taf14.

The assembly and function of the yeast general transcription factor TFIID complex requires specific contacts between its Taf14 and Taf2 subunits, however, the mechanism underlying these contacts remains unclear. Here, we determined the molecular and structural basis by which the YEATS and ET domains of Taf14 bind to the C-terminal tail of Taf2 and identified a unique DNA-binding activity of the linker region connecting the two domains. We show that in the absence of ligands the linker region of Taf14 is occluded by the surrounding domains, and therefore the DNA binding function of Taf14 is autoinhibited. Binding of Taf2 promotes a conformational rearrangement in Taf14, resulting in a release of the linker for the engagement with DNA and the nucleosome. Genetic in vivo data indicate that the association of Taf14 with both Taf2 and DNA is essential for transcriptional regulation. Our findings provide a basis for deciphering the role of individual TFIID subunits in mediating gene transcription.

Automated iterative Csp3-C bond formation.

Fully automated synthetic chemistry would substantially change the field by providing broad on-demand access to small molecules. However, the reactions that can be run autonomously are still limited. Automating the stereospecific assembly of Csp3-C bonds would expand access to many important types of functional organic molecules1. Previously, methyliminodiacetic acid (MIDA) boronates were used to orchestrate the formation of Csp2-Csp2 bonds and were effective building blocks for automating the synthesis of many small molecules2, but they are incompatible with stereospecific Csp3-Csp2 and Csp3-Csp3 bond-forming reactions3-10. Here we report that hyperconjugative and steric tuning provide a new class of tetramethyl N-methyliminodiacetic acid (TIDA) boronates that are stable to these conditions. Charge density analysis11-13 revealed that redistribution of electron density increases covalency of the N-B bond and thereby attenuates its hydrolysis. Complementary steric shielding of carbonyl π-faces decreases reactivity towards nucleophilic reagents. The unique features of the iminodiacetic acid cage2, which are essential for generalized automated synthesis, are retained by TIDA boronates. This enabled Csp3 boronate building blocks to be assembled using automated synthesis, including the preparation of natural products through automated stereospecific Csp3-Csp2 and Csp3-Csp3 bond formation. These findings will enable increasingly complex Csp3-rich small molecules to be accessed via automated assembly.

Information theory approaches to improve glioma diagnostic workflows in surgical neuropathology.

AIMS: Resource-strained healthcare ecosystems often struggle with the adoption of the World Health Organization (WHO) recommendations for the classification of central nervous system (CNS) tumors. The generation of robust clinical diagnostic aids and the advancement of simple solutions to inform investment strategies in surgical neuropathology would improve patient care in these settings. METHODS: We used simple information theory calculations on a brain cancer simulation model and real-world data sets to compare contributions of clinical, histologic, immunohistochemical, and molecular information. An image noise assay was generated to compare the efficiencies of different image segmentation methods in H&E and Olig2 stained images obtained from digital slides. An auto-adjustable image analysis workflow was generated and compared with neuropathologists for p53 positivity quantification. Finally, the density of extracted features of the nuclei, p53 positivity quantification, and combined ATRX/age feature was used to generate a predictive model for 1p/19q codeletion in IDH-mutant tumors. RESULTS: Information theory calculations can be performed on open access platforms and provide significant insight into linear and nonlinear associations between diagnostic biomarkers. Age, p53, and ATRX status have significant information for the diagnosis of IDH-mutant tumors. The predictive models may facilitate the reduction of false-positive 1p/19q codeletion by fluorescence in situ hybridization (FISH) testing. CONCLUSIONS: We posit that this approach provides an improvement on the cIMPACT-NOW workflow recommendations for IDH-mutant tumors and a framework for future resource and testing allocation.

Intracranial mesenchymal tumors with FET-CREB fusion are composed of at least two epigenetic subgroups distinct from meningioma and extracranial sarcomas.

'Intracranial mesenchymal tumor, FET-CREB fusion-positive' occurs primarily in children and young adults and has previously been termed intracranial angiomatoid fibrous histiocytoma (AFH) or intracranial myxoid mesenchymal tumor (IMMT). Here we performed genome-wide DNA methylation array profiling of 20 primary intracranial mesenchymal tumors with FET-CREB fusion to further study their ontology. These tumors resolved into two distinct epigenetic subgroups that were both divergent from all other analyzed intracranial neoplasms and soft tissue sarcomas, including meningioma, clear cell sarcoma of soft tissue (CCS), and AFH of extracranial soft tissue. The first subgroup (Group A, 16 tumors) clustered nearest to but independent of solitary fibrous tumor and AFH of extracranial soft tissue, whereas the second epigenetic subgroup (Group B, 4 tumors) clustered nearest to but independent of CCS and also lacked expression of melanocytic markers (HMB45, Melan A, or MITF) characteristic of CCS. Group A tumors most often occurred in adolescence or early adulthood, arose throughout the neuroaxis, and contained mostly EWSR1-ATF1 and EWSR1-CREB1 fusions. Group B tumors arose most often in early childhood, were located along the cerebral convexities or spinal cord, and demonstrated an enrichment for tumors with CREM as the fusion partner (either EWSR1-CREM or FUS-CREM). Group A tumors more often demonstrated stellate/spindle cell morphology and hemangioma-like vasculature, whereas Group B tumors more often demonstrated round cell or epithelioid/rhabdoid morphology without hemangioma-like vasculature, although robust comparison of these clinical and histologic features requires future study. Patients with Group B tumors had inferior progression-free survival relative to Group A tumors (median 4.5 vs. 49 months, p = 0.001). Together, these findings confirm that intracranial AFH-like neoplasms and IMMT represent histologic variants of a single tumor type ('intracranial mesenchymal tumor, FET-CREB fusion-positive') that is distinct from meningioma and extracranial sarcomas. Additionally, epigenomic evaluation may provide important prognostic subtyping for this unique tumor entity.

Targeted Protein Acetylation in Cells Using Heterobifunctional Molecules.

Protein acetylation is a central event in orchestrating diverse cellular processes. However, current strategies to investigate protein acetylation in cells are often nonspecific or lack temporal and magnitude control. Here, we developed an acetylation tagging system, AceTAG, to induce acetylation of targeted proteins. The AceTAG system utilizes bifunctional molecules to direct the lysine acetyltransferase p300/CBP to proteins fused with the small protein tag FKBP12F36V, resulting in their induced acetylation. Using AceTAG, we induced targeted acetylation of a diverse array of proteins in cells, specifically histone H3.3, the NF-κB subunit p65/RelA, and the tumor suppressor p53. We demonstrate that targeted acetylation with the AceTAG system is rapid, selective, reversible and can be controlled in a dose-dependent fashion. AceTAG represents a useful strategy to modulate protein acetylation and should enable the exploration of targeted acetylation in basic biological and therapeutic contexts.

ACAA2 is a ligand-dependent coactivator for thyroid hormone receptor ß1.

Thyroid hormones (THs) play a critical role in the metabolic phenotype of the heart; and most of the effects involve transcriptional regulation via thyroid hormone receptors (TRs). TRs ability to form combinatorial complexes with an array of partners accounts for TRs physiological flexibility in modulating gene expression. To identify proteins that associate with TRß1 in the heart we performed a pull-down assay on cardiac tissue using GST-TRß1 as bait and identified the bound proteins by LC MS/MS. ACAA2, a mitochondrial thiolase enzyme, was identified as a novel interacting protein. We confirmed ACAA2 localized to the nucleus and using a luciferase reporter assay showed ACAA2 acted as a TH-dependent coactivator for TRß1. ACAA2 showed an ability to bind to TR recognition sequences but did not alter TRß1 DNA binding ability. Thus, ACAA2 as a novel TRß1 associating protein opens a new paradigm to understanding how TH/TRs may be manipulated by energetic pathway molecules.

Machine learning-based data analytic approaches for evaluating post-natal mouse respiratory physiological evolution.

Respiratory parameters change during post-natal development, but the nature of their changes have not been well-described. The advent of commercially available plethysmographic instruments provided improved repeatability of measurements and standardization of measured breathing in mice across laboratories. These technologies thus allowed for exploration of more precise respiratory pattern changes during the post-natal developmental epoch. Current methods to analyze respiratory behavior utilize plethysmography to acquire standing values of frequency, volume and flow at specific time points in murine maturation. These metrics have historically been independently analyzed as a function of time with no further analysis examining the interplay these variables have with each other and in the context of postnatal maturation or during blood gas homeostasis. We posit that machine learning workflows can provide deeper physiological understanding into the postnatal development of respiration. In this manuscript, we delineate a machine learning workflow based on the R-statistical programming language to examine how variation and relationships of frequency (f) and tidal volume (TV) change with respect to inspiratory and expiratory parameters. Our analytical workflows could successfully predict age and found that the variation and relationships between respiratory metrics are dynamically shifting with age and during hypercapnic breathing. Thus, our work demonstrates the utility of high dimensional analyses to provide reliable class label predictions using non-invasive respiratory metrics. These approaches may be useful in large-scale phenotyping across development and in disease.

Intracranial mesenchymal tumor with FET-CREB fusion-A unifying diagnosis for the spectrum of intracranial myxoid mesenchymal tumors and angiomatoid fibrous histiocytoma-like neoplasms.

Intracranial mesenchymal tumors with FET-CREB fusions are a recently described group of neoplasms in children and young adults characterized by fusion of a FET family gene (usually EWSR1, but rarely FUS) to a CREB family transcription factor (ATF1, CREB1, or CREM), and have been variously termed intracranial angiomatoid fibrous histiocytoma or intracranial myxoid mesenchymal tumor. The clinical outcomes, histologic features, and genomic landscape are not well defined. Here, we studied 20 patients with intracranial mesenchymal tumors proven to harbor FET-CREB fusion by next-generation sequencing (NGS). The 16 female and four male patients had a median age of 14 years (range 4-70). Tumors were uniformly extra-axial or intraventricular and located at the cerebral convexities (n = 7), falx (2), lateral ventricles (4), tentorium (2), cerebellopontine angle (4), and spinal cord (1). NGS demonstrated that eight tumors harbored EWSR1-ATF1 fusion, seven had EWSR1-CREB1, four had EWSR1-CREM, and one had FUS-CREM. Tumors were uniformly well circumscribed and typically contrast enhancing with solid and cystic growth. Tumors with EWSR1-CREB1 fusions more often featured stellate/spindle cell morphology, mucin-rich stroma, and hemangioma-like vasculature compared to tumors with EWSR1-ATF1 fusions that most often featured sheets of epithelioid cells with mucin-poor collagenous stroma. These tumors demonstrated polyphenotypic immunoprofiles with frequent positivity for desmin, EMA, CD99, MUC4, and synaptophysin, but absence of SSTR2A, myogenin, and HMB45 expression. There was a propensity for local recurrence with a median progression-free survival of 12 months and a median overall survival of greater than 60 months, with three patients succumbing to disease (all with EWSR1-ATF1 fusions). In combination with prior case series, this study provides further insight into intracranial mesenchymal tumors with FET-CREB fusion, which represent a distinct group of CNS tumors encompassing both intracranial myxoid mesenchymal tumor and angiomatoid fibrous histiocytoma-like neoplasms.

Expressed Protein Ligation without Intein.

Proteins with a functionalized C-terminus such as a C-terminal thioester are key to the synthesis of larger proteins via expressed protein ligation. They are usually made by recombinant fusion to intein. Although powerful, the intein fusion approach suffers from premature hydrolysis and low compatibility with denatured conditions. To totally bypass the involvement of an enzyme for expressed protein ligation, here we showed that a cysteine in a recombinant protein was chemically activated by a small molecule cyanylating reagent at its N-side amide for undergoing nucleophilic acyl substitution with amines including a number of l- and d-amino acids and hydrazine. The afforded protein hydrazides could be used further for expressed protein ligation. We demonstrated the versatility of this activated cysteine-directed protein ligation (ACPL) approach with the successful synthesis of ubiquitin conjugates, ubiquitin-like protein conjugates, histone H2A with a C-terminal posttranslational modification, RNase H that actively hydrolyzed RNA, and exenatide that is a commercial therapeutic peptide. The technique, which is exceedingly simple but highly useful, expands to a great extent the synthetic capacity of protein chemistry and will therefore make a large avenue of new research possible.

The Druggability of Solute Carriers.

The transport of materials across membranes is a vital process for all aspects of cellular function, including growth, metabolism, and communication. Protein transporters are the molecular gates that control this movement and serve as key points of regulation for these processes, thus representing an attractive class of therapeutic targets. With more than 400 members, the solute carrier (SLC) membrane transport proteins are the largest family of transporters, yet, they are pharmacologically underexploited relative to other protein families and many of the available chemical tools possess suboptimal selectivity and efficacy. Fortuitously, there is increased interest in elucidating the physiological roles of SLCs as well as growing recognition of their therapeutic potential. This Perspective provides an overview of the SLC superfamily, including their biochemical and functional features, as well as their roles in various human diseases. In particular, we explore efforts and associated challenges toward drugging SLCs, as well as highlight opportunities for future drug discovery.