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.

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.

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.

On TCR binding predictors failing to generalize to unseen peptides.

Several recent studies investigate TCR-peptide/-pMHC binding prediction using machine learning or deep learning approaches. Many of these methods achieve impressive results on test sets, which include peptide sequences that are also included in the training set. In this work, we investigate how state-of-the-art deep learning models for TCR-peptide/-pMHC binding prediction generalize to unseen peptides. We create a dataset including positive samples from IEDB, VDJdb, McPAS-TCR, and the MIRA set, as well as negative samples from both randomization and 10X Genomics assays. We name this collection of samples TChard. We propose the hard split, a simple heuristic for training/test split, which ensures that test samples exclusively present peptides that do not belong to the training set. We investigate the effect of different training/test splitting techniques on the models' test performance, as well as the effect of training and testing the models using mismatched negative samples generated randomly, in addition to the negative samples derived from assays. Our results show that modern deep learning methods fail to generalize to unseen peptides. We provide an explanation why this happens and verify our hypothesis on the TChard dataset. We then conclude that robust prediction of TCR recognition is still far for being solved.

NKG2A and HLA-E define an alternative immune checkpoint axis in bladder cancer.

Programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1)-blockade immunotherapies have limited efficacy in the treatment of bladder cancer. Here, we show that NKG2A associates with improved survival and responsiveness to PD-L1 blockade immunotherapy in bladder tumors that have high abundance of CD8+ T cells. In bladder tumors, NKG2A is acquired on CD8+ T cells later than PD-1 as well as other well-established immune checkpoints. NKG2A+ PD-1+ CD8+ T cells diverge from classically defined exhausted T cells through their ability to react to human leukocyte antigen (HLA) class I-deficient tumors using T cell receptor (TCR)-independent innate-like mechanisms. HLA-ABC expression by bladder tumors is progressively diminished as disease progresses, framing the importance of targeting TCR-independent anti-tumor functions. Notably, NKG2A+ CD8+ T cells are inhibited when HLA-E is expressed by tumors and partly restored upon NKG2A blockade in an HLA-E-dependent manner. Overall, our study provides a framework for subsequent clinical trials combining NKG2A blockade with other T cell-targeted immunotherapies, where tumors express higher levels of HLA-E.

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.

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).

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.

Low-coverage whole-genome sequencing reveals molecular markers for spawning season and sex identification in Gulf of Maine Atlantic cod (Gadus morhua, Linnaeus 1758).

Atlantic cod (Gadus morhua, Linnaeus 1758) in the western Gulf of Maine are managed as a single stock despite several lines of evidence supporting two spawning groups (spring and winter) that overlap spatially, while exhibiting seasonal spawning isolation. Low-coverage whole-genome sequencing was used to evaluate the genomic population structure of Atlantic cod spawning groups in the western Gulf of Maine and Georges Bank using 222 individuals collected over multiple years. Results indicated low total genomic differentiation, while also showing strong differentiation between spring and winter-spawning groups at specific regions of the genome. Guided regularized random forest and ranked F ST methods were used to select panels of single nucleotide polymorphisms (SNPs) that could reliably distinguish spring and winter-spawning Atlantic cod (88.5% assignment rate), as well as males and females (95.0% assignment rate) collected in the western Gulf of Maine. These SNP panels represent a valuable tool for fisheries research and management of Atlantic cod in the western Gulf of Maine that will aid investigations of stock production and support accuracy of future assessments.

TGM4: an immunogenic prostate-restricted antigen.

BACKGROUND: Prostate cancer is the second leading cause of cancer-related death in men in the USA; death occurs when patients progress to metastatic castration-resistant prostate cancer (CRPC). Although immunotherapy with the Food and Drug Administration-approved vaccine sipuleucel-T, which targets prostatic acid phosphatase (PAP), extends survival for 2-4 months, the identification of new immunogenic tumor-associated antigens (TAAs) continues to be an unmet need. METHODS: We evaluated the differential expression profile of castration-resistant prostate epithelial cells that give rise to CRPC from mice following an androgen deprivation/repletion cycle. The expression levels of a set of androgen-responsive genes were further evaluated in prostate, brain, colon, liver, lung, skin, kidney, and salivary gland from murine and human databases. The expression of a novel prostate-restricted TAA was then validated by immunostaining of mouse tissues and analyzed in primary tumors across all human cancer types in The Cancer Genome Atlas. Finally, the immunogenicity of this TAA was evaluated in vitro and in vivo using autologous coculture assays with cells from healthy donors as well as by measuring antigen-specific antibodies in sera from patients with prostate cancer (PCa) from a neoadjuvant clinical trial. RESULTS: We identified a set of androgen-responsive genes that could serve as potential TAAs for PCa. In particular, we found transglutaminase 4 (Tgm4) to be highly expressed in prostate tumors that originate from luminal epithelial cells and only expressed at low levels in most extraprostatic tissues evaluated. Furthermore, elevated levels of TGM4 expression in primary PCa tumors correlated with unfavorable prognosis in patients. In vitro and in vivo assays confirmed the immunogenicity of TGM4. We found that activated proinflammatory effector memory CD8 and CD4 T cells were expanded by monocyte-derived dendritic cell (moDCs) pulsed with TGM4 to a greater extent than moDCs pulsed with either PAP or prostate-specific antigen (PSA), and T cells primed with TGM4-pulsed moDCs produce functional cytokines following a prime/boost regiment or in vitro stimulation. An IgG antibody response to TGM4 was detected in 30% of vaccinated patients, while fewer than 8% of vaccinated patients developed antibody responses to PSA or prostate-specific membrane antigen (PSMA). CONCLUSIONS: These results suggest that TGM4 is an immunogenic, prostate-restricted antigen with the potential for further development as an immunotherapy target.

Landscape and selection of vaccine epitopes in SARS-CoV-2.

BACKGROUND: Early in the pandemic, we designed a SARS-CoV-2 peptide vaccine containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation. The rationale for this design was to drive both humoral and cellular immunity with high specificity while avoiding undesired effects such as antibody-dependent enhancement (ADE). METHODS: We explored the set of computationally predicted SARS-CoV-2 HLA-I and HLA-II ligands, examining protein source, concurrent human/murine coverage, and population coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, sequence conservation, source protein abundance, and coverage of high frequency HLA alleles. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering for surface accessibility, sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. RESULTS: From 58 initial candidates, three B cell epitope regions were identified. From 3730 (MHC-I) and 5045 (MHC-II) candidate ligands, 292 CD8+ and 284 CD4+ T cell epitopes were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we proposed a set of 22 SARS-CoV-2 vaccine peptides for use in subsequent murine studies. We curated a dataset of ~ 1000 observed T cell epitopes from convalescent COVID-19 patients across eight studies, showing 8/15 recurrent epitope regions to overlap with at least one of our candidate peptides. Of the 22 candidate vaccine peptides, 16 (n = 10 T cell epitope optimized; n = 6 B cell epitope optimized) were manually selected to decrease their degree of sequence overlap and then synthesized. The immunogenicity of the synthesized vaccine peptides was validated using ELISpot and ELISA following murine vaccination. Strong T cell responses were observed in 7/10 T cell epitope optimized peptides following vaccination. Humoral responses were deficient, likely due to the unrestricted conformational space inhabited by linear vaccine peptides. CONCLUSIONS: Overall, we find our selection process and vaccine formulation to be appropriate for identifying T cell epitopes and eliciting T cell responses against those epitopes. Further studies are needed to optimize prediction and induction of B cell responses, as well as study the protective capacity of predicted T and B cell epitopes.

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.

P-Alkynyl functionalized benzazaphospholes as transmetalating agents.

Exposure of 10π-electron benzazaphosphole 1 to HCl, followed by nucleophilic substitution with the Grignard reagent BrMgCCPh afforded alkynyl functionalized 3 featuring an exocyclic -C[triple bond, length as m-dash]C-Ph group with an elongated P-C bond (1.7932(19) Å). Stoichiometric experiments revealed that treatment of trans-Pd(PEt3)2(Ar)(i) (Ar = p-Me (C) or p-F (D)) with 3 generated trans-Pd(PEt3)2(Ar)(CCPh) (Ar = p-Me (E) or p-F (F)), 5, which is the result of ligand exchange between P-I byproduct 4 and C/D, and the reductively eliminated product (Ar-C[triple bond, length as m-dash]C-Ph). Cyclic voltammetry studies showed and independent investigations confirmed 4 is also susceptible to redox processes including bimetallic oxidative addition to Pd(0) to give Pd(i) dimer 6-Pd2-(P(t-Bu)3)2 and reduction to diphosphine 7. During catalysis, we hypothesized that this unwanted reactivity could be circumvented by employing a source of fluoride as an additive. This was demonstrated by conducting a Sonogashira-type reaction between 1-iodotoluene and 3 in the presence of 10 mol% Na2PdCl4, 20 mol% P(t-Bu)Cy2, and 5 equiv. of tetramethylammonium fluoride (TMAF), resulting in turnover and the isolation of Ph-C[triple bond, length as m-dash]C-(o-Tol) as the major product.

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.

A Comprehensive Phenotypic and Functional Immune Analysis Unravels Circulating Anti-Phospholipase A2 Receptor Antibody Secreting Cells in Membranous Nephropathy Patients.

INTRODUCTION: Primary membranous nephropathy (MN) is characterized by the presence of antipodocyte antibodies, but studies describing phenotypic and functional abnormalities in circulating lymphocytes are limited. METHODS: We analyzed 68 different B- and T-cell subsets using flow cytometry in 30 MN patients (before initiating immunosuppression) compared with 31 patients with non-immune-mediated chronic kidney disease (CKD) and 12 healthy individuals. We also measured 19 serum cytokines in MN patients and in healthy controls. Lastly, we quantified the ex vivo production of phospholipase A2 receptor (PLA2R)-specific IgG by plasmablasts (measuring antibodies in culture supernatants and by the newly developed FluoroSpot assay [AutoImmun Diagnostika, Strasberg, Germany]) and assessed the circulating antibody repertoire by phage immunoprecipitation sequencing (PhIP-Seq). RESULTS: After adjusting for multiple testing, plasma cells and regulatory B cells (BREG) were significantly higher (P < 0.05) in MN patients compared with both control groups. The percentages of circulating plasma cells correlated with serum anti-PLA2R antibody levels (P = 0.042) and were associated with disease activity. Ex vivo-expanded PLA2R-specific IgG-producing plasmablasts generated from circulating PLA2R-specific memory B cells (mBCs) correlated with serum anti-PLA2R IgG antibodies (P < 0.001) in MN patients. Tumor necrosis factor-α (TNF-α) was the only significantly increased cytokine in MN patients (P < 0.05), whereas there was no significant difference across study groups in the autoantibody and antiviral antibody repertoire. CONCLUSION: This extensive phenotypic and functional immune characterization shows that autoreactive plasma cells are present in the circulation of MN patients, providing a new therapeutic target and a candidate biomarker of disease activity.

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.