Deep mutational scanning of hepatitis B virus reveals a mechanism for cis-preferential reverse transcription.

Hepatitis B virus (HBV) is a small double-stranded DNA virus that chronically infects 296 million people. Over half of its compact genome encodes proteins in two overlapping reading frames, and during evolution, multiple selective pressures can act on shared nucleotides. This study combines an RNA-based HBV cell culture system with deep mutational scanning (DMS) to uncouple cis- and trans-acting sequence requirements in the HBV genome. The results support a leaky ribosome scanning model for polymerase translation, provide a fitness map of the HBV polymerase at single-nucleotide resolution, and identify conserved prolines adjacent to the HBV polymerase termination codon that stall ribosomes. Further experiments indicated that stalled ribosomes tether the nascent polymerase to its template RNA, ensuring cis-preferential RNA packaging and reverse transcription of the HBV genome.

Corticotropin-releasing hormone signaling from prefrontal cortex to lateral septum suppresses interaction with familiar mice.

Social preference, the decision to interact with one member of the same species over another, is critical to optimize social interactions. Thus, adult rodents favor interacting with novel conspecifics over familiar ones, but whether this social preference stems from neural circuits facilitating interactions with novel individuals or suppressing interactions with familiar ones remains unknown. Here, we identify neurons in the infra-limbic area (ILA) of the mouse prefrontal cortex that express the neuropeptide corticotropin-releasing hormone (CRH) and project to the dorsal region of the rostral lateral septum (rLS). We show how release of CRH during familiar encounters disinhibits rLS neurons, thereby suppressing social interactions with familiar mice and contributing to social novelty preference. We further demonstrate how the maturation of CRH expression in ILA during the first 2 post-natal weeks enables the developmental shift from a preference for littermates in juveniles to a preference for novel mice in adults.

Discovery of deaminase functions by structure-based protein clustering.

The elucidation of protein function and its exploitation in bioengineering have greatly advanced the life sciences. Protein mining efforts generally rely on amino acid sequences rather than protein structures. We describe here the use of AlphaFold2 to predict and subsequently cluster an entire protein family based on predicted structure similarities. We selected deaminase proteins to analyze and identified many previously unknown properties. We were surprised to find that most proteins in the DddA-like clade were not double-stranded DNA deaminases. We engineered the smallest single-strand-specific cytidine deaminase, enabling efficient cytosine base editor (CBE) to be packaged into a single adeno-associated virus (AAV). Importantly, we profiled a deaminase from this clade that edits robustly in soybean plants, which previously was inaccessible to CBEs. These discovered deaminases, based on AI-assisted structural predictions, greatly expand the utility of base editors for therapeutic and agricultural applications.

Widespread detoxifying NO reductases impart a distinct isotopic fingerprint on N2O under anoxia.

Nitrous oxide (N2O), a potent greenhouse gas, can be generated by multiple biological and abiotic processes in diverse contexts. Accurately tracking the dominant sources of N2O has the potential to improve our understanding of N2O fluxes from soils as well as inform the diagnosis of human infections. Isotopic "Site Preference" (SP) values have been used toward this end, as bacterial and fungal nitric oxide reductases (NORs) produce N2O with different isotopic fingerprints, spanning a large range. Here, we show that flavohemoglobin (Fhp), a hitherto biogeochemically neglected yet widely distributed detoxifying bacterial NO reductase, imparts a distinct SP value onto N2O under anoxic conditions (~+10‰) that correlates with typical environmental N2O SP measurements. Using Pseudomonas aeruginosa as a model organism, we generated strains that only contained Fhp or the dissimilatory NOR, finding that in vivo N2O SP values imparted by these enzymes differ by over 10‰. Depending on the cellular physiological state, the ratio of Fhp:NOR varies significantly in wild-type cells and controls the net N2O SP biosignature: When cells grow anaerobically under denitrifying conditions, NOR dominates; when cells experience rapid, increased nitric oxide concentrations under anoxic conditions but are not growing, Fhp dominates. Other bacteria that only make Fhp generate similar N2O SP biosignatures to those measured from our P. aeruginosa Fhp-only strain. Fhp homologs in sequenced bacterial genomes currently exceed NOR homologs by nearly a factor of four. Accordingly, we suggest a different framework to guide the attribution of N2O biological sources in nature and disease.

The evolution of social behaviors and risk preferences in settings with uncertainty.

Humans update their social behavior in response to past experiences and changing environments. Behavioral decisions are further complicated by uncertainty in the outcome of social interactions. Faced with uncertainty, some individuals exhibit risk aversion while others seek risk. Attitudes toward risk may depend on socioeconomic status; and individuals may update their risk preferences over time, which will feedback on their social behavior. Here, we study how uncertainty and risk preferences shape the evolution of social behaviors. We extend the game-theoretic framework for behavioral evolution to incorporate uncertainty about payoffs and variation in how individuals respond to this uncertainty. We find that different attitudes toward risk can substantially alter behavior and long-term outcomes, as individuals seek to optimize their rewards from social interactions. In a standard setting without risk, for example, defection always overtakes a well-mixed population engaged in the classic Prisoner's Dilemma, whereas risk aversion can reverse the direction of evolution, promoting cooperation over defection. When individuals update their risk preferences along with their strategic behaviors, a population can oscillate between periods dominated by risk-averse cooperators and periods of risk-seeking defectors. Our analysis provides a systematic account of how risk preferences modulate, and even coevolve with, behavior in an uncertain social world.

Perspectives on valuing water quality improvements using stated preference methods.

Improvements to the quality of freshwater rivers and lakes can generate a wide array of benefits, from "use values" such as recreational boating, fishing, and swimming to "nonuse values" such as improved outcomes for aquatic biodiversity. Bringing these nonmarket values into decision-making is crucial to determining appropriate levels of investment in water quality improvements. However, progress in the economic valuation of water quality benefits has lagged similar efforts to value air quality benefits, with implications for water policy. New data sources, modeling techniques, and innovation in stated preference survey methods offer notable improvements to estimates of use and nonuse benefits of improved water quality. Here, we provide a perspective on how recent applications of stated preference techniques to the valuation of the nonmarket benefits of water quality improvements have advanced the field of environmental valuation. This overview is structured around four key questions: i) What is it about water quality that we seek to value? ii) How should we design and implement the surveys which elicit individuals' stated preferences? iii) How do we assess the validity of the findings provided by such studies? and iv) What are the contributions of these valuation exercises to public policy? In answering these questions, we make reference to the contributions provided by the papers in this Symposium.

Estimating the benefits of stream water quality improvements in urbanizing watersheds: An ecological production function approach.

Streams in urbanizing watersheds are threatened by economic development that can lead to excessive sediment erosion and surface runoff. These anthropogenic stressors diminish valuable ecosystem services and result in pervasive degradation commonly referred to as "urban stream syndrome." Understanding how the public perceives and values improvements in stream conditions is necessary to support efforts to quantify the economic benefits of water quality improvements. We develop an ecological production framework that translates measurable indicators of stream water quality into ecological endpoints. Our interdisciplinary approach integrates a predictive hierarchical water quality model that is well suited for sparse data environments, an expert elicitation that translates measurable water quality indicators into ecological endpoints that focus group participants identified as most relevant, and a stated preference survey that elicits the public's willingness to pay for changes in these endpoints. To illustrate our methods, we develop an application to the Upper Neuse River Watershed located in the rapidly developing Triangle region of North Carolina (the United States). Our results suggest, for example, that residents are willing to pay roughly $127 per household and $54 million per year in aggregate (2021 US$) for water quality improvements resulting from a stylized intervention that increases stream bank canopy cover by 25% and decreases runoff from impervious surfaces, leading to improvements in water quality and ecological endpoints for local streams. Although the three components of our analysis are conducted with data from North Carolina, we discuss how our findings are generalizable to urban and urbanizing areas across the larger Piedmont ecoregion of the Eastern United States.

Estimating biotic integrity to capture existence value of freshwater ecosystems.

The US Environmental Protection Agency (EPA) uses a water quality index (WQI) to estimate benefits of proposed Clean Water Act regulations. The WQI is relevant to human use value, such as recreation, but may not fully capture aspects of nonuse value, such as existence value. Here, we identify an index of biological integrity to supplement the WQI in a forthcoming national stated preference survey that seeks to capture existence value of streams and lakes more accurately within the conterminous United States (CONUS). We used literature and focus group research to evaluate aquatic indices regularly reported by the EPA's National Aquatic Resource Surveys. We chose an index that quantifies loss in biodiversity as the observed-to-expected (O/E) ratio of taxonomic composition because focus group participants easily understood its meaning and the environmental changes that would result in incremental improvements. However, available datasets of this index do not provide the spatial coverage to account for how conditions near survey respondents affect their willingness to pay for its improvement. Therefore, we modeled and interpolated the values of this index from sampled sites to 1.1 million stream segments and 297,071 lakes across the CONUS to provide the required coverage. The models explained 13 to 36% of the variation in O/E scores and demonstrate how modeling can provide data at the required density for benefits estimation. We close by discussing future work to improve performance of the models and to link biological condition with water quality and habitat models that will allow us to forecast changes resulting from regulatory options.

A multifaceted poverty reduction program has economic and behavioral consequences.

This paper examines the causal impact of poverty reduction interventions on the social preferences of the poor. A multifaceted poverty reduction program in China provides a setting for the use of a fuzzy regression discontinuity design. The design compares households with base-year income just below a preset criterion, who were more likely to receive the program treatment, with households just above the criterion. Five years after the program's launch, we conducted a lab-in-the-field experiment to measure the distributional preferences of household heads. Combining quasi-random variation from program rules with administrative census and experimental data, we find both economic and behavioral consequences of the program: It increased household income by 50% 5 y later, increased consistency with utility maximization by household heads, and increased their efficiency preference while reducing selfishness and leaving equality preference unchanged. Our findings advance scientific understanding of social preferences formation and highlight a broad perspective in evaluating poverty reduction interventions.

How acidic amino acid residues facilitate DNA target site selection.

Despite the negative charge of the DNA backbone, acidic residues (Asp/Glu) commonly participate in the base readout, with a strong preference for cytosine. In fact, in the solved DNA/protein structures, cytosine is recognized almost exclusively by Asp/Glu through a direct hydrogen bond, while at the same time, adenine, regardless of its amino group, shows no propensity for Asp/Glu. Here, we analyzed the contribution of Asp/Glu to sequence-specific DNA binding using classical and ab initio simulations of selected transcription factors and found that it is governed by a fine balance between the repulsion from backbone phosphates and attractive interactions with cytosine. Specifically, Asp/Glu lower the affinity for noncytosine sites and thus act as negative selectors preventing off-target binding. At cytosine-containing sites, the favorable contribution does not merely rely on the formation of a single H-bond but usually requires the presence of positive potential generated by multiple cytosines, consistently with the observed excess of cytosine in the target sites. Finally, we show that the preference of Asp/Glu for cytosine over adenine is a result of the repulsion from the adenine imidazole ring and a tendency of purine-purine dinucleotides to adopt the BII conformation.

The emergence of economic rationality of GPT.

As large language models (LLMs) like GPT become increasingly prevalent, it is essential that we assess their capabilities beyond language processing. This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences. We measure economic rationality by assessing the consistency of GPT's decisions with utility maximization in classic revealed preference theory. We find that GPT's decisions are largely rational in each domain and demonstrate higher rationality score than those of human subjects in a parallel experiment and in the literature. Moreover, the estimated preference parameters of GPT are slightly different from human subjects and exhibit a lower degree of heterogeneity. We also find that the rationality scores are robust to the degree of randomness and demographic settings such as age and gender but are sensitive to contexts based on the language frames of the choice situations. These results suggest the potential of LLMs to make good decisions and the need to further understand their capabilities, limitations, and underlying mechanisms.

Activity of estrogen receptor ß expressing neurons in the medial amygdala regulates preference toward receptive females in male mice.

The processing of information regarding the sex and reproductive state of conspecific individuals is critical for successful reproduction and survival in males. Generally, male mice exhibit a preference toward the odor of sexually receptive (RF) over nonreceptive females (XF) or gonadally intact males (IM). Previous studies suggested the involvement of estrogen receptor beta (ERß) expressed in the medial amygdala (MeA) in male preference toward RF. To further delineate the role played by ERß in the MeA in the neuronal network regulating male preference, we developed a new ERß-iCre mouse line using the CRISPR-Cas9 system. Fiber photometry Ca2+ imaging revealed that ERß-expressing neurons in the postero-dorsal part of the MeA (MeApd-ERß+ neurons) were more active during social investigation toward RF compared to copresented XF or IM mice in a preference test. Chemogenetic inhibition of MeApd-ERß+ neuronal activity abolished a preference to RF in "RF vs. XF," but not "RF vs. IM," tests. Analysis with cre-dependent retrograde tracing viral vectors identified the principal part of the bed nucleus of stria terminalis (BNSTp) as a primary projection site of MeApd-ERß+ neurons. Fiber photometry recording in the BNSTp during a preference test revealed that chemogenetic inhibition of MeApd-ERß+ neurons abolished differential neuronal activity of BNSTp cells as well as a preference to RF against XF but not against IM mice. Collectively, these findings demonstrate for the first time that MeApd-ERß+ neuronal activity is required for expression of receptivity-based preference (i.e., RF vs. XF) but not sex-based preference (i.e., RF vs. IM) in male mice.

Calcitonin receptors are ancient modulators for rhythms of preferential temperature in insects and body temperature in mammals.

Daily body temperature rhythm (BTR) is essential for maintaining homeostasis. BTR is regulated separately from locomotor activity rhythms, but its molecular basis is largely unknown. While mammals internally regulate BTR, ectotherms, including Drosophila, exhibit temperature preference rhythm (TPR) behavior to regulate BTR. Here, we demonstrate that the diuretic hormone 31 receptor (DH31R) mediates TPR during the active phase in Drosophila DH31R is expressed in clock cells, and its ligand, DH31, acts on clock cells to regulate TPR during the active phase. Surprisingly, the mouse homolog of DH31R, calcitonin receptor (Calcr), is expressed in the suprachiasmatic nucleus (SCN) and mediates body temperature fluctuations during the active phase in mice. Importantly, DH31R and Calcr are not required for coordinating locomotor activity rhythms. Our results represent the first molecular evidence that BTR is regulated distinctly from locomotor activity rhythms and show that DH31R/Calcr is an ancient specific mediator of BTR during the active phase in organisms ranging from ectotherms to endotherms.

Activating Lobule VI PCTH+-Med Pathway in Cerebellum Blocks the Acquisition of Methamphetamine Conditioned Place Preference in Mice.

Cerebellum has been implicated in drug addiction; however, its underlying cellular populations and neuronal circuitry remain largely unknown. In the current study, we identified a neural pathway from tyrosine hydroxylase (TH)-positive Purkinje cells (PCTH+) in cerebellar lobule VI to calcium/calmodulin-dependent protein kinase II (CaMKII)-positive glutamatergic neurons in the medial cerebellar nucleus (MedCaMKII), forming the lobule VI PCTH+-MedCaMKII pathway in male mice. In naive male mice, inhibition of PCTH+ neurons activated Med neurons. During conditioned place preference (CPP) training, exposure to methamphetamine (METH) inhibited lobule VI PCTH+ neurons while excited MedCaMKII neurons in mice. Silencing MedCaMKII using a tetanus toxin light chain (tettox) suppressed the acquisition of METH CPP in mice but resulted in motor coordination deficits in naive mice. In contrast, activating lobule VI PCTH+ terminals within Med inhibited the activity of Med neurons and subsequently blocked the acquisition of METH CPP in mice without affecting motor coordination, locomotor activity, and sucrose reinforcements in naive mice. Our findings identified a novel lobule VI PCTH+-MedCaMKII pathway within the cerebellum and explored its role in mediating the acquisition of METH-preferred behaviors.

Tadpoles rely on mechanosensory stimuli for communication when visual capabilities are poor.

The ways in which animals sense the world changes throughout development. For example, young of many species have limited visual capabilities, but still make social decisions, likely based on information gathered through other sensory modalities. Poison frog tadpoles display complex social behaviors that have been suggested to rely on vision despite a century of research indicating tadpoles have poorly-developed visual systems relative to adults. Alternatively, other sensory modalities, such as the lateral line system, are functional at hatching in frogs and may guide social decisions while other sensory systems mature. Here, we examined development of the mechanosensory lateral line and visual systems in tadpoles of the mimic poison frog (Ranitomeya imitator) that use vibrational begging displays to stimulate egg feeding from their mothers. We found that tadpoles hatch with a fully developed lateral line system. While begging behavior increases with development, ablating the lateral line system inhibited begging in pre-metamorphic tadpoles, but not in metamorphic tadpoles. We also found that the increase in begging and decrease in reliance on the lateral line co-occurs with increased retinal neural activity and gene expression associated with eye development. Using the neural tracer neurobiotin, we found that axonal innervations from the eye to the brain proliferate during metamorphosis, with few retinotectal connections in recently-hatched tadpoles. We then tested visual function in a phototaxis assay and found tadpoles prefer darker environments. The strength of this preference increased with developmental stage, but eyes were not required for this behavior, possibly indicating a role for the pineal gland. Together, these data suggest that tadpoles rely on different sensory modalities for social interactions across development and that the development of sensory systems in socially complex poison frog tadpoles is similar to that of other frog species.

MtNPF6.5 mediates chloride uptake and nitrate preference in Medicago roots.

The preference for nitrate over chloride through regulation of transporters is a fundamental feature of plant ion homeostasis. We show that Medicago truncatula MtNPF6.5, an ortholog of Arabidopsis thaliana AtNPF6.3/NRT1.1, can mediate nitrate and chloride uptake in Xenopus oocytes but is chloride selective and that its close homologue, MtNPF6.7, can transport nitrate and chloride but is nitrate selective. The MtNPF6.5 mutant showed greatly reduced chloride content relative to wild type, and MtNPF6.5 expression was repressed by high chloride, indicating a primary role for MtNPF6.5 in root chloride uptake. MtNPF6.5 and MtNPF6.7 were repressed and induced by nitrate, respectively, and these responses required the transcription factor MtNLP1. Moreover, loss of MtNLP1 prevented the rapid switch from chloride to nitrate as the main anion in nitrate-starved plants after nitrate provision, providing insight into the underlying mechanism for nitrate preference. Sequence analysis revealed three sub-types of AtNPF6.3 orthologs based on their predicted substrate-binding residues: A (chloride selective), B (nitrate selective), and C (legume specific). The absence of B-type AtNPF6.3 homologues in early diverged plant lineages suggests that they evolved from a chloride-selective MtNPF6.5-like protein.

Stochastic Character Mapping, Bayesian Model Selection, and Biosynthetic Pathways Shed New Light on the Evolution of Habitat Preference in Cyanobacteria.

Cyanobacteria are the only prokaryotes to have evolved oxygenic photosynthesis paving the way for complex life. Studying the evolution and ecological niche of cyanobacteria and their ancestors is crucial for understanding the intricate dynamics of biosphere evolution. These organisms frequently deal with environmental stressors such as salinity and drought, and they employ compatible solutes as a mechanism to cope with these challenges. Compatible solutes are small molecules that help maintain cellular osmotic balance in high salinity environments, such as marine waters. Their production plays a crucial role in salt tolerance, which, in turn, influences habitat preference. Among the five known compatible solutes produced by cyanobacteria (sucrose, trehalose, glucosylglycerol, glucosylglycerate, and glycine betaine), their synthesis varies between individual strains. In this study, we work in a Bayesian stochastic mapping framework, integrating multiple sources of information about compatible solute biosynthesis in order to predict the ancestral habitat preference of Cyanobacteria. Through extensive model selection analyses and statistical tests for correlation, we identify glucosylglycerol and glucosylglycerate as the most significantly correlated with habitat preference, while trehalose exhibits the weakest correlation. Additionally, glucosylglycerol, glucosylglycerate, and glycine betaine show high loss/gain rate ratios, indicating their potential role in adaptability, while sucrose and trehalose are less likely to be lost due to their additional cellular functions. Contrary to previous findings, our analyses predict that the last common ancestor of Cyanobacteria (living at around 3180 Ma) had a 97% probability of a high salinity habitat preference and was likely able to synthesise glucosylglycerol and glucosylglycerate. Nevertheless, cyanobacteria likely colonized low-salinity environments shortly after their origin, with an 89% probability of the first cyanobacterium with low-salinity habitat preference arising prior to the Great Oxygenation Event (2460 Ma). Stochastic mapping analyses provide evidence of cyanobacteria inhabiting early marine habitats, aiding in the interpretation of the geological record. Our age estimate of ~2590 Ma for the divergence of two major cyanobacterial clades (Macro- and Microcyanobacteria) suggests that these were likely significant contributors to primary productivity in marine habitats in the lead-up to the Great Oxygenation Event, and thus played a pivotal role in triggering the sudden increase in atmospheric oxygen.

Preferences predict who commits crime among young men.

Understanding who commits crime and why is a key topic in social science and important for the design of crime prevention policy. In theory, people who commit crime face different social and economic incentives for criminal activity than other people, or they evaluate the costs and benefits of crime differently because they have different preferences. Empirical evidence on the role of preferences is scarce. Theoretically, risk-tolerant, impatient, and self-interested people are more prone to commit crime than risk-averse, patient, and altruistic people. We test these predictions with a unique combination of data where we use incentivized experiments to elicit the preferences of young men and link these experimental data to their criminal records. In addition, our data allow us to control extensively for other characteristics such as cognitive skills, socioeconomic background, and self-control problems. We find that preferences are strongly associated with actual criminal behavior. Impatience and, in particular, risk tolerance are still strong predictors when we include the full battery of controls. Crime propensities are 8 to 10 percentage points higher for the most risk-tolerant individuals compared to the most risk averse. This effect is half the size of the effect of cognitive skills, which is known to be a very strong predictor of criminal behavior. Looking into different types of crime, we find that preferences significantly predict property offenses, while self-control problems significantly predict violent, drug, and sexual offenses.

Worth the Work? Monkeys Discount Rewards by a Subjective Adapting Effort Cost.

All life must solve how to allocate limited energy resources to maximize benefits from scarce opportunities. Economic theory posits decision makers optimize choice by maximizing the subjective benefit (utility) of reward minus the subjective cost (disutility) of the required effort. While successful in many settings, this model does not fully account for how experience can alter reward-effort trade-offs. Here, we test how well the subtractive model of effort disutility explains the behavior of two male nonhuman primates (Macaca mulatta) in a binary choice task in which reward quantity and physical effort to obtain were varied. Applying random utility modeling to independently estimate reward utility and effort disutility, we show the subtractive effort model better explains out-of-sample choice behavior when compared with parabolic and exponential effort discounting. Furthermore, we demonstrate that effort disutility depends on previous experience of effort: in analogy to work from behavioral labor economics, we develop a model of reference-dependent effort disutility to explain the increased willingness to expend effort following previous experience of effortful options in a session. The result of this analysis suggests that monkeys discount reward by an effort cost that is measured relative to an expected effort learned from previous trials. When this subjective cost of effort, a function of context and experience, is accounted for, trial-by-trial choices can be explained by the subtractive cost model of effort. Therefore, in searching for net utility signals that may underpin effort-based decision-making in the brain, careful measurement of subjective effort costs is an essential first step.SIGNIFICANCE STATEMENT All decision-makers need to consider how much effort they need to expend when evaluating potential options. Economic theories suggest that the optimal way to choose is by cost-benefit analysis of reward against effort. To be able to do this efficiently over many decision contexts, this needs to be done flexibly, with appropriate adaptation to context and experience. Therefore, in aiming to understand how this might be achieved in the brain, it is important to first carefully measure the subjective cost of effort. Here, we show monkeys make reward-effort cost-benefit decisions, subtracting the subjective cost of effort from the subjective value of rewards. Moreover, the subjective cost of effort is dependent on the monkeys' experience of effort in previous trials.

Nutrient-Sensitive Reinforcement Learning in Monkeys.

In reinforcement learning (RL), animals choose by assigning values to options and learn by updating these values from reward outcomes. This framework has been instrumental in identifying fundamental learning variables and their neuronal implementations. However, canonical RL models do not explain how reward values are constructed from biologically critical intrinsic reward components, such as nutrients. From an ecological perspective, animals should adapt their foraging choices in dynamic environments to acquire nutrients that are essential for survival. Here, to advance the biological and ecological validity of RL models, we investigated how (male) monkeys adapt their choices to obtain preferred nutrient rewards under varying reward probabilities. We found that the nutrient composition of rewards strongly influenced learning and choices. Preferences of the animals for specific nutrients (sugar, fat) affected how they adapted to changing reward probabilities; the history of recent rewards influenced choices of the monkeys more strongly if these rewards contained the their preferred nutrients (nutrient-specific reward history). The monkeys also chose preferred nutrients even when they were associated with lower reward probability. A nutrient-sensitive RL model captured these processes; it updated the values of individual sugar and fat components of expected rewards based on experience and integrated them into subjective values that explained the choices of the monkeys. Nutrient-specific reward prediction errors guided this value-updating process. Our results identify nutrients as important reward components that guide learning and choice by influencing the subjective value of choice options. Extending RL models with nutrient-value functions may enhance their biological validity and uncover nutrient-specific learning and decision variables.SIGNIFICANCE STATEMENT RL is an influential framework that formalizes how animals learn from experienced rewards. Although reward is a foundational concept in RL theory, canonical RL models cannot explain how learning depends on specific reward properties, such as nutrients. Intuitively, learning should be sensitive to the nutrient components of the reward to benefit health and survival. Here, we show that the nutrient (fat, sugar) composition of rewards affects how the monkeys choose and learn in an RL paradigm and that key learning variables including reward history and reward prediction error should be modified with nutrient-specific components to account for the choice behavior observed in the monkeys. By incorporating biologically critical nutrient rewards into the RL framework, our findings help advance the ecological validity of RL models.