C. elegans as a model for inter-individual variation in metabolism.

Individuals can exhibit differences in metabolism that are caused by the interplay of genetic background, nutritional input, microbiota and other environmental factors1-4. It is difficult to connect differences in metabolism to genomic variation and derive underlying molecular mechanisms in humans, owing to differences in diet and lifestyle, among others. Here we use the nematode Caenorhabditis elegans as a model to study inter-individual variation in metabolism. By comparing three wild strains and the commonly used N2 laboratory strain, we find differences in the abundances of both known metabolites and those that have not to our knowledge been previously described. The latter metabolites include conjugates between 3-hydroxypropionate (3HP) and several amino acids (3HP-AAs), which are much higher in abundance in one of the wild strains. 3HP is an intermediate in the propionate shunt pathway, which is activated when flux through the canonical, vitamin-B12-dependent propionate breakdown pathway is perturbed5. We show that increased accumulation of 3HP-AAs is caused by genetic variation in HPHD-1, for which 3HP is a substrate. Our results suggest that the production of 3HP-AAs represents a 'shunt-within-a-shunt' pathway to accommodate a reduction-of-function allele in hphd-1. This study provides a step towards the development of metabolic network models that capture individual-specific differences of metabolism and more closely represent the diversity that is found in entire species.

Amino acid and protein specificity of protein fatty acylation in C. elegans.

Protein lipidation plays critical roles in regulating protein function and localization. However, the chemical diversity and specificity of fatty acyl group utilization have not been investigated using untargeted approaches, and it is unclear to what extent structures and biosynthetic origins of S-acyl moieties differ from N- and O-fatty acylation. Here, we show that fatty acylation patterns in Caenorhabditis elegans differ markedly between different amino acid residues. Hydroxylamine capture revealed predominant cysteine S-acylation with 15-methylhexadecanoic acid (isoC17:0), a monomethyl branched-chain fatty acid (mmBCFA) derived from endogenous leucine catabolism. In contrast, enzymatic protein hydrolysis showed that N-terminal glycine was acylated almost exclusively with straight-chain myristic acid, whereas lysine was acylated preferentially with two different mmBCFAs and serine was acylated promiscuously with a broad range of fatty acids, including eicosapentaenoic acid. Global profiling of fatty acylated proteins using a set of click chemistry-capable alkyne probes for branched- and straight-chain fatty acids uncovered 1,013 S-acylated proteins and 510 hydroxylamine-resistant N- or O-acylated proteins. Subsets of S-acylated proteins were labeled almost exclusively by either a branched-chain or a straight-chain probe, demonstrating acylation specificity at the protein level. Acylation specificity was confirmed for selected examples, including the S-acyltransferase DHHC-10. Last, homology searches for the identified acylated proteins revealed a high degree of conservation of acylation site patterns across metazoa. Our results show that protein fatty acylation patterns integrate distinct branches of lipid metabolism in a residue- and protein-specific manner, providing a basis for mechanistic studies at both the amino acid and protein levels.

A D-2-hydroxyglutarate dehydrogenase mutant reveals a critical role for ketone body metabolism in Caenorhabditis elegans development.

In humans, mutations in D-2-hydroxyglutarate (D-2HG) dehydrogenase (D2HGDH) result in D-2HG accumulation, delayed development, seizures, and ataxia. While the mechanisms of 2HG-associated diseases have been studied extensively, the endogenous metabolism of D-2HG remains unclear in any organism. Here, we find that, in Caenorhabditis elegans, D-2HG is produced in the propionate shunt, which is transcriptionally activated when flux through the canonical, vitamin B12-dependent propionate breakdown pathway is perturbed. Loss of the D2HGDH ortholog, dhgd-1, results in embryonic lethality, mitochondrial defects, and the up-regulation of ketone body metabolism genes. Viability can be rescued by RNAi of hphd-1, which encodes the enzyme that produces D-2HG or by supplementing either vitamin B12 or the ketone bodies 3-hydroxybutyrate (3HB) and acetoacetate (AA). Altogether, our findings support a model in which C. elegans relies on ketone bodies for energy when vitamin B12 levels are low and in which a loss of dhgd-1 causes lethality by limiting ketone body production.

A neurotransmitter produced by gut bacteria modulates host sensory behaviour.

Animals coexist in commensal, pathogenic or mutualistic relationships with complex communities of diverse organisms, including microorganisms1. Some bacteria produce bioactive neurotransmitters that have previously been proposed to modulate nervous system activity and behaviours of their hosts2,3. However, the mechanistic basis of this microbiota-brain signalling and its physiological relevance are largely unknown. Here we show that in Caenorhabditis elegans, the neuromodulator tyramine produced by commensal Providencia bacteria, which colonize the gut, bypasses the requirement for host tyramine biosynthesis and manipulates a host sensory decision. Bacterially produced tyramine is probably converted to octopamine by the host tyramine ß-hydroxylase enzyme. Octopamine, in turn, targets the OCTR-1 octopamine receptor on ASH nociceptive neurons to modulate an aversive olfactory response. We identify the genes that are required for tyramine biosynthesis in Providencia, and show that these genes are necessary for the modulation of host behaviour. We further find that C. elegans colonized by Providencia preferentially select these bacteria in food choice assays, and that this selection bias requires bacterially produced tyramine and host octopamine signalling. Our results demonstrate that a neurotransmitter produced by gut bacteria mimics the functions of the cognate host molecule to override host control of a sensory decision, and thereby promotes fitness of both the host and the microorganism.

Natural genetic variation in the pheromone production of C. elegans.

From bacterial quorum sensing to human language, communication is essential for social interactions. Nematodes produce and sense pheromones to communicate among individuals and respond to environmental changes. These signals are encoded by different types and mixtures of ascarosides, whose modular structures further enhance the diversity of this nematode pheromone language. Interspecific and intraspecific differences in this ascaroside pheromone language have been described previously, but the genetic basis and molecular mechanisms underlying the variation remain largely unknown. Here, we analyzed natural variation in the production of 44 ascarosides across 95 wild Caenorhabditis elegans strains using high-performance liquid chromatography coupled to high-resolution mass spectrometry. We discovered wild strains defective in the production of specific subsets of ascarosides (e.g., the aggregation pheromone icas#9) or short- and medium-chain ascarosides, as well as inversely correlated patterns between the production of two major classes of ascarosides. We investigated genetic variants that are significantly associated with the natural differences in the composition of the pheromone bouquet, including rare genetic variants in key enzymes participating in ascaroside biosynthesis, such as the peroxisomal 3-ketoacyl-CoA thiolase, daf-22, and the carboxylesterase cest-3. Genome-wide association mappings revealed genomic loci harboring common variants that affect ascaroside profiles. Our study yields a valuable dataset for investigating the genetic mechanisms underlying the evolution of chemical communication.

Parallel pathways for serotonin biosynthesis and metabolism in C. elegans.

The neurotransmitter serotonin plays a central role in animal behavior and physiology, and many of its functions are regulated via evolutionarily conserved biosynthesis and degradation pathways. Here we show that in Caenorhabditis elegans, serotonin is abundantly produced in nonneuronal tissues via phenylalanine hydroxylase, in addition to canonical biosynthesis via tryptophan hydroxylase in neurons. Combining CRISPR-Cas9 genome editing, comparative metabolomics and synthesis, we demonstrate that most serotonin in C. elegans is incorporated into N-acetylserotonin-derived glucosides, which are retained in the worm body and further modified via the carboxylesterase CEST-4. Expression patterns of CEST-4 suggest that serotonin or serotonin derivatives are transported between different tissues. Last, we show that bacterial indole production interacts with serotonin metabolism via CEST-4. Our results reveal a parallel pathway for serotonin biosynthesis in nonneuronal cell types and further indicate that serotonin-derived metabolites may serve distinct signaling functions and contribute to previously described serotonin-dependent phenotypes.

Oligonucleotide Catabolism-Derived Gluconucleosides in Caenorhabditis elegans.

Nucleosides are essential cornerstones of life, and nucleoside derivatives and synthetic analogues have important biomedical applications. Correspondingly, production of non-canonical nucleoside derivatives in animal model systems is of particular interest. Here, we report the discovery of diverse glucose-based nucleosides in Caenorhabditis elegans and related nematodes. Using a mass spectrometric screen based on all-ion fragmentation in combination with total synthesis, we show that C. elegans selectively glucosylates a series of modified purines but not the canonical purine and pyrimidine bases. Analogous to ribonucleosides, the resulting gluconucleosides exist as phosphorylated and non-phosphorylated forms. The phosphorylated gluconucleosides can be additionally decorated with diverse acyl moieties from amino acid catabolism. Syntheses of representative variants, facilitated by a novel 2'-O- to 3'-O-dibenzyl phosphoryl transesterification reaction, demonstrated selective incorporation of different nucleobases and acyl moieties. Using stable-isotope labeling, we further show that gluconucleosides incorporate modified nucleobases derived from RNA and possibly DNA breakdown, revealing extensive recycling of oligonucleotide catabolites. Gluconucleosides are conserved in other nematodes, and biosynthesis of specific subsets is increased in germline mutants and during aging. Bioassays indicate that gluconucleosides may function in stress response pathways.

Zinc protection of fertilized eggs is an ancient feature of sexual reproduction in animals.

One of the earliest and most prevalent barriers to successful reproduction is polyspermy, or fertilization of an egg by multiple sperm. To prevent these supernumerary fertilizations, eggs have evolved multiple mechanisms. It has recently been proposed that zinc released by mammalian eggs at fertilization may block additional sperm from entering. Here, we demonstrate that eggs from amphibia and teleost fish also release zinc. Using Xenopus laevis as a model, we document that zinc reversibly blocks fertilization. Finally, we demonstrate that extracellular zinc similarly disrupts early embryonic development in eggs from diverse phyla, including Cnidaria, Echinodermata, and Chordata. Our study reveals that a fundamental strategy protecting human eggs from fertilization by multiple sperm may have evolved more than 650 million years ago.

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method.

Protein-ligand interactions are essential to drug discovery and drug development efforts. Desirable on-target or multitarget interactions are the first step in finding an effective therapeutic, while undesirable off-target interactions are the first step in assessing safety. In this work, we introduce a novel ligand-based featurization and mapping of human protein pockets to identify closely related protein targets and to project novel drugs into a hybrid protein-ligand feature space to identify their likely protein interactions. Using structure-based template matches from PDB, protein pockets are featured by the ligands that bind to their best co-complex template matches. The simplicity and interpretability of this approach provide a granular characterization of the human proteome at the protein-pocket level instead of the traditional protein-level characterization by family, function, or pathway. We demonstrate the power of this featurization method by clustering a subset of the human proteome and evaluating the predicted cluster associations of over 7000 compounds.

Can Abnormal Spinopelvic Relationships be Identified by Anteroposterior Pelvic Radiographs?

BACKGROUND: Abnormal spinopelvic relationships may place patients at an increased risk for instability after primary total hip arthroplasty. The purpose of this study was to determine if radiographic markers on a standing anteroposterior (AP) pelvis radiograph could identify patients with sagittal spinopelvic imbalance or spinal stiffness. METHODS: Patients undergoing primary total hip arthroplasty at a single institution from 2017 to 2020 with standing AP pelvis radiographs and sitting/standing lateral radiographs were identified. AP pelvis radiographs were assessed for the following: lumbosacral hardware, spine osteophytes, disc space narrowing, scoliosis>5°, pelvic obliquity>5°, and overlap of the sacrococcygeal junction/pubic symphysis. Patients with spinopelvic imbalance and/or spinopelvic stiffness were identified. Univariate and multivariate analyses were performed. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. RESULTS: Four hundred eighty-six patients were included. Prevalence of isolated sagittal spinopelvic imbalance and isolated spinopelvic stiffness was 12% and 21%, respectively; 11% of patients had sagittal imbalance and stiffness. Overlap of the sacrococcygeal junction/pubic symphysis (OR = 10.2, 95% CI = 5.3-19.8) and presence of lumbosacral hardware (OR = 4.4, 95% CI = 2.0-9.4) were markers of an increased risk of combined sagittal imbalance and stiffness. Seventy-nine percent of patients with overlap of the sacrococcygeal junction and pubic symphysis and 82% of patients with lumbosacral hardware had an abnormal spinopelvic relationship. CONCLUSION: Isolated sagittal imbalance and stiffness were difficult to predict on standing AP pelvis radiographs. Overlap of the sacrococcygeal junction/pubic symphysis and presence of lumbosacral hardware associated with a higher risk of combined sagittal imbalance/stiffness and were present in ≥79% of patients with an abnormal spinopelvic relationship. LEVEL OF EVIDENCE: IV; retrospective cohort study.

Combinatorial Assembly of Modular Glucosides via Carboxylesterases Regulates C. elegans Starvation Survival.

The recently discovered modular glucosides (MOGLs) form a large metabolite library derived from combinatorial assembly of moieties from amino acid, neurotransmitter, and lipid metabolism in the model organism C. elegans. Combining CRISPR-Cas9 genome editing, comparative metabolomics, and synthesis, we show that the carboxylesterase homologue Cel-CEST-1.2 is responsible for specific 2-O-acylation of diverse glucose scaffolds with a wide variety of building blocks, resulting in more than 150 different MOGLs. We further show that this biosynthetic role is conserved for the closest homologue of Cel-CEST-1.2 in the related nematode species C. briggsae, Cbr-CEST-2. Expression of Cel-cest-1.2 and MOGL biosynthesis are strongly induced by starvation conditions in C. elegans, one of the premier model systems for mechanisms connecting nutrition and physiology. Cel-cest-1.2-deletion results in early death of adult animals under starvation conditions, providing first insights into the biological functions of MOGLs.

Hypoactivation in the precuneus and posterior cingulate cortex during ambiguous decision making in individuals with HIV.

People with human immunodeficiency virus (HIV) often have neurocognitive impairment. People with HIV make riskier decisions when the outcome probabilities are known, and have abnormal neural architecture underlying risky decision making. However, ambiguous decision making, when the outcome probabilities are unknown, is more common in daily life, but the neural architecture underlying ambiguous decision making in people with HIV is unknown. Eighteen people with HIV and 20 controls completed a decision making task while undergoing functional magnetic resonance imaging scanning. Participants chose between a certain reward and uncertain reward with a known (risky) or unknown (ambiguous) probability of winning. There were three levels of risk: high, medium, and low. Ambiguous > risky brain activity was compared between groups. Ambiguous > risky brain activity was correlated with emotional/psychiatric functioning in people with HIV. Both groups were similarly ambiguity-averse. People with HIV were more risk-averse than controls and chose the high-risk uncertain option less often. People with HIV had hypoactivity in the precuneus, posterior cingulate cortex (PCC), and fusiform gyrus during ambiguous > medium risk decision making. Ambiguous > medium risk brain activity was negatively correlated with emotional/psychiatric functioning in individuals with HIV. To make ambiguous decisions, people with HIV underrecruit key regions of the default mode network, which are thought to integrate internally and externally derived information to come to a decision. These regions and related cognitive processes may be candidates for interventions to improve decision-making outcomes in people with HIV.

Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference.

Predicting accurate protein-ligand binding affinities is an important task in drug discovery but remains a challenge even with computationally expensive biophysics-based energy scoring methods and state-of-the-art deep learning approaches. Despite the recent advances in the application of deep convolutional and graph neural network-based approaches, it remains unclear what the relative advantages of each approach are and how they compare with physics-based methodologies that have found more mainstream success in virtual screening pipelines. We present fusion models that combine features and inference from complementary representations to improve binding affinity prediction. This, to our knowledge, is the first comprehensive study that uses a common series of evaluations to directly compare the performance of three-dimensional (3D)-convolutional neural networks (3D-CNNs), spatial graph neural networks (SG-CNNs), and their fusion. We use temporal and structure-based splits to assess performance on novel protein targets. To test the practical applicability of our models, we examine their performance in cases that assume that the crystal structure is not available. In these cases, binding free energies are predicted using docking pose coordinates as the inputs to each model. In addition, we compare these deep learning approaches to predictions based on docking scores and molecular mechanic/generalized Born surface area (MM/GBSA) calculations. Our results show that the fusion models make more accurate predictions than their constituent neural network models as well as docking scoring and MM/GBSA rescoring, with the benefit of greater computational efficiency than the MM/GBSA method. Finally, we provide the code to reproduce our results and the parameter files of the trained models used in this work. The software is available as open source at https://github.com/llnl/fast. Model parameter files are available at ftp://gdo-bioinformatics.ucllnl.org/fast/pdbbind2016_model_checkpoints/.

Deep Interrogation of Metabolism Using a Pathway-Targeted Click-Chemistry Approach.

Untargeted metabolomics indicates that the number of unidentified small-molecule metabolites may exceed the number of protein-coding genes for many organisms, including humans, by orders of magnitude. Uncovering the underlying metabolic networks is essential for elucidating the physiological and ecological significance of these biogenic small molecules. Here we develop a click-chemistry-based enrichment strategy, DIMEN (deep interrogation of metabolism via enrichment), that we apply to investigate metabolism of the ascarosides, a family of signaling molecules in the model organism C. elegans. Using a single alkyne-modified metabolite and a solid-phase azide resin that installs a diagnostic moiety for MS/MS-based identification, DIMEN uncovered several hundred novel compounds originating from diverse biosynthetic transformations that reveal unexpected intersection with amino acid, carbohydrate, and energy metabolism. Many of the newly discovered transformations could not be identified or detected by conventional LC-MS analyses without enrichment, demonstrating the utility of DIMEN for deeply probing biochemical networks that generate extensive yet uncharacterized structure space.

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning.

Accurately predicting small molecule partitioning and hydrophobicity is critical in the drug discovery process. There are many heterogeneous chemical environments within a cell and entire human body. For example, drugs must be able to cross the hydrophobic cellular membrane to reach their intracellular targets, and hydrophobicity is an important driving force for drug-protein binding. Atomistic molecular dynamics (MD) simulations are routinely used to calculate free energies of small molecules binding to proteins, crossing lipid membranes, and solvation but are computationally expensive. Machine learning (ML) and empirical methods are also used throughout drug discovery but rely on experimental data, limiting the domain of applicability. We present atomistic MD simulations calculating 15,000 small molecule free energies of transfer from water to cyclohexane. This large data set is used to train ML models that predict the free energies of transfer. We show that a spatial graph neural network model achieves the highest accuracy, followed closely by a 3D-convolutional neural network, and shallow learning based on the chemical fingerprint is significantly less accurate. A mean absolute error of ∼4 kJ/mol compared to the MD calculations was achieved for our best ML model. We also show that including data from the MD simulation improves the predictions, tests the transferability of each model to a diverse set of molecules, and show multitask learning improves the predictions. This work provides insight into the hydrophobicity of small molecules and ML cheminformatics modeling, and our data set will be useful for designing and testing future ML cheminformatics methods.

Molecular Mechanism for Gramicidin Dimerization and Dissociation in Bilayers of Different Thickness.

Membrane protein functions can be altered by subtle changes in the host lipid bilayer physical properties. Gramicidin channels have emerged as a powerful system for elucidating the underlying mechanisms of membrane protein function regulation through changes in bilayer properties, which are reflected in the thermodynamic equilibrium distribution between nonconducting gramicidin monomers and conducting bilayer-spanning dimers. To improve our understanding of how subtle changes in bilayer thickness alter the gramicidin monomer and dimer distributions, we performed extensive atomistic molecular dynamics simulations and fluorescence-quenching experiments on gramicidin A (gA). The free-energy calculations predicted a nonlinear coupling between the bilayer thickness and channel formation. The energetic barrier inhibiting gA channel formation was sharply increased in the thickest bilayer (1,2-dierucoyl-sn-glycero-3-phosphocholine). This prediction was corroborated by experimental results on gramicidin channel activity in bilayers of different thickness. To further explore the mechanism of channel formation, we performed extensive unbiased molecular dynamics simulations, which allowed us to observe spontaneous gA dimer formation in lipid bilayers. The simulations revealed structural rearrangements in the gA subunits and changes in lipid packing, as well as water reorganization, that occur during the dimerization process. Together, the simulations and experiments provide new, to our knowledge, insights into the process and mechanism of gramicidin channel formation, as a prototypical example of the bilayer regulation of membrane protein function.

Phospholipid Chain Interactions with Cholesterol Drive Domain Formation in Lipid Membranes.

Cholesterol is a key component of eukaryotic membranes, but its role in cellular biology in general and in lipid rafts in particular remains controversial. Model membranes are used extensively to determine the phase behavior of ternary mixtures of cholesterol, a saturated lipid, and an unsaturated lipid with liquid-ordered and liquid-disordered phase coexistence. Despite many different experiments that determine lipid-phase diagrams, we lack an understanding of the molecular-level driving forces for liquid phase coexistence in bilayers with cholesterol. Here, we use atomistic molecular dynamics computer simulations to address the driving forces for phase coexistence in ternary lipid mixtures. Domain formation is directly observed in a long-timescale simulation of a mixture of 1,2-distearoyl-sn-glycero-3-phosphocholine, unsaturated 1,2-dilinoleoyl-sn-glycero-3-phosphocholine, and cholesterol. Free-energy calculations for the exchange of the saturated and unsaturated lipids between the ordered and disordered phases give insight into the mixing behavior. We show that a large energetic contribution to domain formation is favorable enthalpic interactions of the saturated lipid in the ordered phase. This favorable energy for forming an ordered, cholesterol-rich phase is opposed by a large unfavorable entropy. Martini coarse-grained simulations capture the unfavorable free energy of mixing but do not reproduce the entropic contribution because of the reduced representation of the phospholipid tails. Phospholipid tails and their degree of unsaturation are key energetic contributors to lipid phase separation.

Two Novel Urban Health Primary Care Residency Tracks That Focus On Community-Level Structural Vulnerabilities.

BACKGROUND: Although residency programs are well situated for developing a physician workforce with knowledge, skills, and attitudes that incorporate the strengths and reflect the priorities of community organizations, few curricula explicitly do so. AIM: To develop urban health primary care tracks for internal medicine and combined internal medicine-pediatrics residents. SETTING: Academic hospital, community health center, and community-based organizations. PARTICIPANTS: Internal medicine and combined internal medicine-pediatrics residents. PROGRAM DESCRIPTION: The program integrates community-based experiences with a focus on stakeholder engagement into its curriculum. A significant portion of the training (28 weeks out of 3 years for internal medicine and 34 weeks out of 4 years for medicine-pediatrics) occurs outside the hospital and continuity clinic to support residents' understanding of structural vulnerabilities. PROGRAM EVALUATION: Sixteen internal medicine and 14 medicine-pediatrics residents have graduated from our programs. Fifty-six percent of internal medicine graduates and 79% of medicine-pediatrics graduates are seeking primary care careers, and eight overall (27%) have been placed in community organizations. Seven (23%) hold leadership positions. DISCUSSION: We implemented two novel residency tracks that successfully placed graduates in community-based primary care settings. Integrating primary care training with experiences in community organizations can create primary care leaders and may foster collective efficacy among medical centers and community organizations.

Mechanism of action of the anti-inflammatory connexin43 mimetic peptide JM2.

Connexin-based therapeutics have shown the potential for therapeutic efficacy in improving wound healing. Our previous work demonstrated that the connexin43 (Cx43) mimetic peptide juxtamembrane 2 (JM2) reduced the acute inflammatory response to a submuscular implant model by inhibiting purinergic signaling. Given the prospective application in improving tissue-engineered construct tolerance that these results indicated, we sought to determine the mechanism of action for JM2 in the present study. Using confocal microscopy, a gap-FRAP cell communication assay, and an ethidium bromide uptake assay of hemichannel function we found that the peptide reduced cell surface Cx43 levels, Cx43 gap junction (GJ) size, GJ communication, and hemichannel activity. JM2 is based on the sequence of the Cx43 microtubule binding domain, and microtubules have a confirmed role in intracellular trafficking of Cx43 vesicles. Therefore, we tested the effect of JM2 on Cx43-microtubule interaction and microtubule polymerization. We found that JM2 enhanced Cx43-microtubule interaction and that microtubule polymerization was significantly enhanced. Taken together, these data suggest that JM2 inhibits trafficking of Cx43 to the cell surface by promoting irrelevant microtubule polymerization and thereby reduces the number of hemichannels in the plasma membrane available to participate in proinflammatory purinergic signaling. Importantly, this work indicates that JM2 may have therapeutic value in the treatment of proliferative diseases such as cancer. We conclude that the targeted action of JM2 on Cx43 channels may improve the tolerance of implanted tissue-engineered constructs against the innate inflammatory response.