Shared Immunogenic Poly-Epitope Frameshift Mutations in Microsatellite Unstable Tumors.

Microsatellite instability-high (MSI-H) tumors are characterized by high tumor mutation burden and responsiveness to checkpoint blockade. We identified tumor-specific frameshifts encoding multiple epitopes that originated from indel mutations shared among patients with MSI-H endometrial, colorectal, and stomach cancers. Epitopes derived from these shared frameshifts have high population occurrence rates, wide presence in many tumor subclones, and are predicted to bind to the most frequent MHC alleles in MSI-H patient cohorts. Neoantigens arising from these mutations are distinctly unlike self and viral antigens, signifying novel groups of potentially highly immunogenic tumor antigens. We further confirmed the immunogenicity of frameshift peptides in T cell stimulation experiments using blood mononuclear cells isolated from both healthy donors and MSI-H cancer patients. Our study uncovers the widespread occurrence and strong immunogenicity of tumor-specific antigens derived from shared frameshift mutations in MSI-H cancer and Lynch syndrome patients, suitable for the design of common "off-the-shelf" cancer vaccines.

Mapping Systemic Inflammation and Antibody Responses in Multisystem Inflammatory Syndrome in Children (MIS-C).

Initially, children were thought to be spared from disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, a month into the epidemic, a novel multisystem inflammatory syndrome in children (MIS-C) emerged. Herein, we report on the immune profiles of nine MIS-C cases. All MIS-C patients had evidence of prior SARS-CoV-2 exposure, mounting an antibody response with intact neutralization capability. Cytokine profiling identified elevated signatures of inflammation (IL-18 and IL-6), lymphocytic and myeloid chemotaxis and activation (CCL3, CCL4, and CDCP1), and mucosal immune dysregulation (IL-17A, CCL20, and CCL28). Immunophenotyping of peripheral blood revealed reductions of non-classical monocytes, and subsets of NK and T lymphocytes, suggesting extravasation to affected tissues. Finally, profiling the autoantigen reactivity of MIS-C plasma revealed both known disease-associated autoantibodies (anti-La) and novel candidates that recognize endothelial, gastrointestinal, and immune-cell antigens. All patients were treated with anti-IL-6R antibody and/or IVIG, which led to rapid disease resolution.

OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization.

AlphaFold2 revolutionized structural biology with the ability to predict protein structures with exceptionally high accuracy. Its implementation, however, lacks the code and data required to train new models. These are necessary to (1) tackle new tasks, like protein-ligand complex structure prediction, (2) investigate the process by which the model learns and (3) assess the model's capacity to generalize to unseen regions of fold space. Here we report OpenFold, a fast, memory efficient and trainable implementation of AlphaFold2. We train OpenFold from scratch, matching the accuracy of AlphaFold2. Having established parity, we find that OpenFold is remarkably robust at generalizing even when the size and diversity of its training set is deliberately limited, including near-complete elisions of classes of secondary structure elements. By analyzing intermediate structures produced during training, we also gain insights into the hierarchical manner in which OpenFold learns to fold. In sum, our studies demonstrate the power and utility of OpenFold, which we believe will prove to be a crucial resource for the protein modeling community.

Zinc limitation triggers anticipatory adaptations in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) has complex and dynamic interactions with the human host, and subpopulations of Mtb that emerge during infection can influence disease outcomes. This study implicates zinc ion (Zn2+) availability as a likely driver of bacterial phenotypic heterogeneity in vivo. Zn2+ sequestration is part of "nutritional immunity", where the immune system limits micronutrients to control pathogen growth, but this defense mechanism seems to be ineffective in controlling Mtb infection. Nonetheless, Zn2+-limitation is an environmental cue sensed by Mtb, as calprotectin triggers the zinc uptake regulator (Zur) regulon response in vitro and co-localizes with Zn2+-limited Mtb in vivo. Prolonged Zn2+ limitation leads to numerous physiological changes in vitro, including differential expression of certain antigens, alterations in lipid metabolism and distinct cell surface morphology. Furthermore, Mtb enduring limited Zn2+ employ defensive measures to fight oxidative stress, by increasing expression of proteins involved in DNA repair and antioxidant activity, including well described virulence factors KatG and AhpC, along with altered utilization of redox cofactors. Here, we propose a model in which prolonged Zn2+ limitation defines a population of Mtb with anticipatory adaptations against impending immune attack, based on the evidence that Zn2+-limited Mtb are more resistant to oxidative stress and exhibit increased survival and induce more severe pulmonary granulomas in mice. Considering that extracellular Mtb may transit through the Zn2+-limited caseum before infecting naïve immune cells or upon host-to-host transmission, the resulting phenotypic heterogeneity driven by varied Zn2+ availability likely plays a key role during early interactions with host cells.

Anti-inflammatory Quinoline Alkaloids from the Roots of Waltheria indica.

Sixteen new quinoline alkaloids (1a-7, 8a, 9, 10, 13-15, 17, and 21) and 10 known analogs (8b, 11, 12, 16, 18-20, and 22-24), along with three known cyclopeptide alkaloids (25-27), were isolated from the roots of Waltheria indica. The structures of the new compounds were elucidated by detailed NMR and circular dichroism with computational support and mass spectrometry data interpretation. Anti-inflammatory potential of isolates was evaluated based on inhibition of lipopolysaccharide (LPS)-induced nitric oxide (NO) production and tumor necrosis factor-alpha (TNF-α)-induced nuclear factor kappa B (NF-κB) activity with cell culture models. In the absence of cell growth inhibition, compounds 6, 8a, 9-11, 13, 21, and 24 reduced TNF-α-induced NF-κB activity with IC50 values ranging from 7.1 to 12.1 µM, comparable to the positive control (BAY 11-7082, IC50 = 9.7 µM). Compounds 6, 8a, 8b, and 11 showed significant NO-inhibitory activity with IC50 values ranging from 11.0 to 12.8 µM, being more active than the positive control (l-NMMA, IC50 = 22.7 µM). Structure-activity relationships indicated that NO inhibitory activity was significantly affected by C-8 substitution. Inhibition of LPS-induced nitric oxide synthase (iNOS) by 8b [(5S)-waltherione M, IC50 11.7 ± 0.8 µM] correlated with inhibition of iNOS mRNA expression. The biological potential of W. indica metabolites supports the traditional use of this plant for the treatment of inflammatory-related disorders.

Spirovetivane- and Eudesmane-Type Sesquiterpenoids Isolated from the Culture Media of Two Cyanobacterial Strains.

As part of a study examining polar metabolites produced by cyanobacterial strains, we examined media extracts of a Calothrix sp. (strain R-3-1) and a Scytonema sp. (strain U-3-3). The cell mass of each was separated from the media, and HP20 resin was added for adsorption of secreted metabolites, a relatively unexplored area of cyanobacterial chemistry. HPLC-UV-LCMS-guided isolation led to the discovery of seven sesquiterpenoid compounds with five new, one known, and one previously isolated as the methyl ester. Through a complement of 1D and 2D NMR spectroscopic techniques, the planar structures and relative configurations of the seven compounds were elucidated. Spironostoic acid (1), 11,12-didehydrospironostoic acid (2), and 12-hydroxy-2-oxo-11-epi-hinesol (4) are spirovetivane-type compounds from R-3-1, while stigolone (5), 11R,12-dihydroxystigolone (6), and 11S,12-dihydroxystigolone (7) are three eudesmane-type compounds from U-3-3. Circular dichroism was utilized to decipher the absolute configurations of new compounds 1, 2, 4, 5, 6, and 7. Due to the structural variety observed among the spirovetivane- and eudesmane-type compounds in the literature and often a lack of clarity in how determinations were made, computational spectra and model compounds were used to support the interpretation of ECD and NMR spectra. A straightforward process to determine the configuration of these systems is presented.

Coumarinolignans with Reactive Oxygen Species (ROS) and NF-κB Inhibitory Activities from the Roots of Waltheria indica.

Seven new coumarinolignans, walthindicins A-F (1a, 1b, 2-5, 7), along with five known analogs (6, 8-11), were isolated from the roots of Waltheria indica. The structures of the new compounds are determined by detailed nuclear magnetic resonance (NMR), circular dichroism (CD) with extensive computational support, and mass spectroscopic data interpretation. Compounds were tested for their antioxidant activity in Human Cervical Cancer cells (HeLa cells). Compounds 1a and 6 showed higher reactive oxygen species (ROS) inhibitory activity at 20 µg/mL when compared with other natural compound-based antioxidants such as ascorbic acid. Considering the role of ROS in nuclear-factor kappa B (NF-κB) activation, compounds 1a and 6 were evaluated for NF-κB inhibitory activity and showed a concentration-dependent inhibition in Human Embryonic Kidney 293 cells (Luc-HEK-293).

Tolyporphins L-R: Unusual Tetrapyrroles from a Brasilonema sp. of Cyanobacterium.

Tolyporphins L-R (2-8) have been isolated from a mixed cyanobacterium-microbial culture. The structures of tolyporphins L and M have been revised to four constitutional isomers, isolated as two mixtures of dioxobacteriochlorins (2/3 and 4/5). In contrast, tolyporphin P (6) is a fully oxidized tetrapyrrole, while tolyporphins Q and R (7 and 8) are oxochlorins. X-ray structures are reported for the first time for tolyporphins A (1), R (8), and E (9), revealing unexpected stereochemical variation within the series.

6-Deoxy- and 11-Hydroxytolypodiols: Meroterpenoids from the Cyanobacterium HT-58-2.

Chemical investigation of cyanobacterial strain HT-58-2, which most closely aligns with the genus Brasilomena, has led to the isolation of two compounds related to tolypodiol. The structures and absolute configuration of 6-deoxytolypodiol (1) and 11-hydroxytolypodiol (2) were elucidated by spectroscopic and spectrometric analysis. While tolypodiol previously showed anti-inflammatory activity in a mouse ear edema assay, only 2 reduced in vitro thromboxane B2 and superoxide anion (O2-) generation from Escherichia coli lipopolysaccharide-activated rat neonatal microglia to any appreciable degree.

Production and excretion of astaxanthin by engineered Yarrowia lipolytica using plant oil as both the carbon source and the biocompatible extractant.

This study aimed to develop a bioprocess using plant oil as the carbon source for lipid-assimilating yeast to produce high-value astaxanthin. Using high-oleic safflower oil as a model, efficient cell growth and astaxanthin production by the engineered Yarrowia lipolytica strain ST7403 was demonstrated, and a considerable portion of astaxanthin was found excreted into the spent oil. Astaxanthin was the predominant carotenoid in the extracellular oil phase that allowed facile in situ recovery of astaxanthin without cell lysis. Autoclaving the safflower oil medium elevated the peroxide level but it declined quickly during fermentation (reduced by 84% by day 3) and did not inhibit cell growth or astaxanthin production. In a 1.5-L fed-batch bioreactor culture with a YnB-based medium containing 20% safflower oil, and with the feeding of casamino acids, astaxanthin production reached 54 mg/L (53% excreted) in 28 days. Further improvement in astaxanthin titer and productivity was achieved by restoring leucine biosynthesis in the host, and running fed-batch fermentation using a high carbon-to-nitrogen ratio yeast extract/peptone medium containing 70% safflower oil, with feeding of additional yeast extract/peptone, to attain 167 mg/L astaxanthin (48% excreted) in 9.5 days of culture. These findings facilitate industrial microbial biorefinery development that utilizes renewable lipids as feedstocks to not only produce high-value products but also effectively extract and recover the products, including non-native ones.Key Points• Yarrowia lipolytica can use plant oil as a C-source for astaxanthin production.• Astaxanthin is excreted and accumulated in the extracellular oil phase.• Astaxanthin is the predominant carotenoid in the extracellular oil phase.• Plant oil serves as a biocompatible solvent for in situ astaxanthin extraction. Graphical abstract.

Predictive validity of NEDA in the 16- and 21-year follow-up from the pivotal trial of interferon beta-1b.

BACKGROUND: Long-term follow-up from the randomized trial of interferon beta-1b (IFNB-1b) permitted the assessment of different definitions of no evidence of disease activity (NEDA) for predicting long-term outcome in multiple sclerosis (MS). OBJECTIVE: To examine the predictive validity of different NEDA definitions. METHODS: Predictive validity for negative disability outcomes (NDOs) at 16 years and survival at 21 years post-randomization were assessed. NEDA in the first 2 years was defined as follows: clinical NEDA: no relapses or Expanded Disability Status Scale (EDSS) progression from baseline to Year 2; NEDA-3a: no relapses, no confirmed ⩾1-point EDSS progression, and no new T2-active lesions; NEDA-3b: no relapses, no EDSS progression, and no increase in T2 burden of disease (T2-BOD); and NEDA-4: no relapses, no EDSS progression, and no increase in T2-BOD or atrophy. NDOs were defined as death, need for wheelchair, EDSS ⩾6, or progressive MS. RESULTS: A total of 245 and 371 patients were evaluated at 16 and 21 years, respectively. Clinical NEDA predicted NDOs ( p = 0.0029), as did baseline EDSS ( p < 0.0001), baseline T2-BOD ( p < 0.0001), and change in T2-BOD ( p = 0.0033). IFNB-1b treatment ( p = 0.0251), relapse rate in the 2 years before study start ( p = 0.0260), T2-BOD at baseline ( p = 0.0014), and change in T2-BOD ( p = 0.0129) predicted survival at 21 years. CONCLUSION: Clinical NEDA predicted long-term disability outcome. By contrast, definitions of NEDA that included on-therapy changes in magnetic resonance imaging variables did not increase the predictive validity.

A thousand studies for the price of one: Accelerating psychological science with Pushkin.

Half of the world's population has internet access. In principle, researchers are no longer limited to subjects they can recruit into the laboratory. Any study that can be run on a computer or mobile device can be run with nearly any demographic anywhere in the world, and in large numbers. This has allowed scientists to effectively run hundreds of experiments at once. Despite their transformative power, such studies remain rare for practical reasons: the need for sophisticated software, the difficulty of recruiting so many subjects, and a lack of research paradigms that make effective use of their large amounts of data, due to such realities as that they require sophisticated software in order to run effectively. We present Pushkin: an open-source platform for designing and conducting massive experiments over the internet. Pushkin allows for a wide range of behavioral paradigms, through integration with the intuitive and flexible jsPsych experiment engine. It also addresses the basic technical challenges associated with massive, worldwide studies, including auto-scaling, extensibility, machine-assisted experimental design, multisession studies, and data security.

Chemotherapy weakly contributes to predicted neoantigen expression in ovarian cancer.

BACKGROUND: Patients with highly mutated tumors, such as melanoma or smoking-related lung cancer, have higher rates of response to immune checkpoint blockade therapy, perhaps due to increased neoantigen expression. Many chemotherapies including platinum compounds are known to be mutagenic, but the impact of standard treatment protocols on mutational burden and resulting neoantigen expression in most human cancers is unknown. METHODS: We sought to quantify the effect of chemotherapy treatment on computationally predicted neoantigen expression for high grade serous ovarian carcinoma patients enrolled in the Australian Ovarian Cancer Study. In this series, 35 of 114 samples were collected after exposure to chemotherapy; 14 are matched with an untreated sample from the same patient. Our approach integrates whole genome and RNA sequencing of bulk tumor samples with class I MHC binding prediction and mutational signatures extracted from studies of chemotherapy-exposed Caenorhabditis elegans and Gallus gallus cells. We additionally investigated the relationship between neoantigens, tumor infiltrating immune cells estimated from RNA-seq with CIBERSORT, and patient survival. RESULTS: Greater neoantigen burden and CD8+ T cell infiltration in primary, pre-treatment samples were independently associated with improved survival. Relapse samples collected after chemotherapy harbored a median of 78% more expressed neoantigens than untreated primary samples, a figure that combines the effects of chemotherapy and other processes operative during relapse. The contribution from chemotherapy-associated signatures was small, accounting for a mean of 5% (range 0-16) of the expressed neoantigen burden in relapse samples. In both treated and untreated samples, most neoantigens were attributed to COSMIC Signature (3), associated with BRCA disruption, Signature (1), associated with a slow mutagenic process active in healthy tissue, and Signature (8), of unknown etiology. CONCLUSION: Relapsed ovarian cancers harbor more predicted neoantigens than primary tumors, but the increase is due to pre-existing mutational processes, not mutagenesis from chemotherapy.

Grammatical morphology as a source of early number word meanings.

How does cross-linguistic variation in linguistic structure affect children's acquisition of early number word meanings? We tested this question by investigating number word learning in two unrelated languages that feature a tripartite singular-dual-plural distinction: Slovenian and Saudi Arabic. We found that learning dual morphology affects children's acquisition of the number word two in both languages, relative to English. Children who knew the meaning of two were surprisingly frequent in the dual languages, relative to English. Furthermore, Slovenian children were faster to learn two than children learning English, despite being less-competent counters. Finally, in both Slovenian and Saudi Arabic, comprehension of the dual was correlated with knowledge of two and higher number words.

Preconfiguration of the antigen-binding site during affinity maturation of a broadly neutralizing influenza virus antibody.

Affinity maturation refines a naive B-cell response by selecting mutations in antibody variable domains that enhance antigen binding. We describe a B-cell lineage expressing broadly neutralizing influenza virus antibodies derived from a subject immunized with the 2007 trivalent vaccine. The lineage comprises three mature antibodies, the unmutated common ancestor, and a common intermediate. Their heavy-chain complementarity determining region inserts into the conserved receptor-binding pocket of influenza HA. We show by analysis of structures, binding kinetics and long time-scale molecular dynamics simulations that antibody evolution in this lineage has rigidified the initially flexible heavy-chain complementarity determining region by two nearly independent pathways and that this preconfiguration accounts for most of the affinity gain. The results advance our understanding of strategies for developing more broadly effective influenza vaccines.

Key mutations stabilize antigen-binding conformation during affinity maturation of a broadly neutralizing influenza antibody lineage.

Affinity maturation, the process in which somatic hypermutation and positive selection generate antibodies with increasing affinity for an antigen, is pivotal in acquired humoral immunity. We have studied the mechanism of affinity gain in a human B-cell lineage in which two main maturation pathways, diverging from a common ancestor, lead to three mature antibodies that neutralize a broad range of H1 influenza viruses. Previous work showed that increased affinity in the mature antibodies derives primarily from stabilization of the CDR H3 loop in the antigen-binding conformation. We have now used molecular dynamics simulations and existing crystal structures to identify potentially key maturation mutations, and we have characterized their effects on the CDR H3 loop and on antigen binding using further simulations and experimental affinity measurements, respectively. In the two maturation pathways, different contacts between light and heavy chains stabilize the CDR H3 loop. As few as two single-site mutations in each pathway can confer substantial loop stability, but none of them confers experimentally detectable stability on its own. Our results support models of the germinal center reaction in which two or more mutations can occur without concomitant selection and show how divergent pathways have yielded functionally equivalent antibodies.

The Plausibility of Sampling as an Algorithmic Theory of Sentence Processing.

Words that are more surprising given context take longer to process. However, no incremental parsing algorithm has been shown to directly predict this phenomenon. In this work, we focus on a class of algorithms whose runtime does naturally scale in surprisal-those that involve repeatedly sampling from the prior. Our first contribution is to show that simple examples of such algorithms predict runtime to increase superlinearly with surprisal, and also predict variance in runtime to increase. These two predictions stand in contrast with literature on surprisal theory (Hale, 2001; Levy, 2008a) which assumes that the expected processing cost increases linearly with surprisal, and makes no prediction about variance. In the second part of this paper, we conduct an empirical study of the relationship between surprisal and reading time, using a collection of modern language models to estimate surprisal. We find that with better language models, reading time increases superlinearly in surprisal, and also that variance increases. These results are consistent with the predictions of sampling-based algorithms.

Identification, Heterologous Expression, and Characterization of the Tolypodiol Biosynthetic Gene Cluster through an Integrated Approach.

Cyanobacteria are tremendous producers of biologically active natural products, including the potent anti-inflammatory compound tolypodiol. However, linking biosynthetic gene clusters with compound production in cyanobacteria has lagged behind that in other bacterial genera. Tolypodiol is a meroterpenoid originally isolated from the cyanobacterium HT-58-2. Here we describe the identification of the tolypodiol biosynthetic gene cluster through heterologous expression in Anabaena and in vitro protein assays of a methyltransferase found in the tolypodiol biosynthetic gene cluster. We have also identified similar biosynthetic gene clusters in cyanobacterial and actinobacterial genomes, suggesting that meroterpenoids with structural similarity to the tolypodiols may be synthesized by other microbes. We also report the identification of two new analogs of tolypodiol that we have identified in both the original and heterologous producer. This work further illustrates the usefulness of Anabaena as a heterologous expression host for cyanobacterial compounds and how integrated approaches can help to link natural product compounds with their producing biosynthetic gene clusters.

Synthesizing theories of human language with Bayesian program induction.

Automated, data-driven construction and evaluation of scientific models and theories is a long-standing challenge in artificial intelligence. We present a framework for algorithmically synthesizing models of a basic part of human language: morpho-phonology, the system that builds word forms from sounds. We integrate Bayesian inference with program synthesis and representations inspired by linguistic theory and cognitive models of learning and discovery. Across 70 datasets from 58 diverse languages, our system synthesizes human-interpretable models for core aspects of each language's morpho-phonology, sometimes approaching models posited by human linguists. Joint inference across all 70 data sets automatically synthesizes a meta-model encoding interpretable cross-language typological tendencies. Finally, the same algorithm captures few-shot learning dynamics, acquiring new morphophonological rules from just one or a few examples. These results suggest routes to more powerful machine-enabled discovery of interpretable models in linguistics and other scientific domains.