Generative replay underlies compositional inference in the hippocampal-prefrontal circuit.

Human reasoning depends on reusing pieces of information by putting them together in new ways. However, very little is known about how compositional computation is implemented in the brain. Here, we ask participants to solve a series of problems that each require constructing a whole from a set of elements. With fMRI, we find that representations of novel constructed objects in the frontal cortex and hippocampus are relational and compositional. With MEG, we find that replay assembles elements into compounds, with each replay sequence constituting a hypothesis about a possible configuration of elements. The content of sequences evolves as participants solve each puzzle, progressing from predictable to uncertain elements and gradually converging on the correct configuration. Together, these results suggest a computational bridge between apparently distinct functions of hippocampal-prefrontal circuitry and a role for generative replay in compositional inference and hypothesis testing.

Incipient functional SARS-CoV-2 diversification identified through neural network haplotype maps.

Since its introduction in the human population, SARS-CoV-2 has evolved into multiple clades, but the events in its intrahost diversification are not well understood. Here, we compare three-dimensional (3D) self-organized neural haplotype maps (SOMs) of SARS-CoV-2 from thirty individual nasopharyngeal diagnostic samples obtained within a 19-day interval in Madrid (Spain), at the time of transition between clades 19 and 20. SOMs have been trained with the haplotype repertoire present in the mutant spectra of the nsp12- and spike (S)-coding regions. Each SOM consisted of a dominant neuron (displaying the maximum frequency), surrounded by a low-frequency neuron cloud. The sequence of the master (dominant) neuron was either identical to that of the reference Wuhan-Hu-1 genome or differed from it at one nucleotide position. Six different deviant haplotype sequences were identified among the master neurons. Some of the substitutions in the neural clouds affected critical sites of the nsp12-nsp8-nsp7 polymerase complex and resulted in altered kinetics of RNA synthesis in an in vitro primer extension assay. Thus, the analysis has identified mutations that are relevant to modification of viral RNA synthesis, present in the mutant clouds of SARS-CoV-2 quasispecies. These mutations most likely occurred during intrahost diversification in several COVID-19 patients, during an initial stage of the pandemic, and within a brief time period.

Localizing somatic symptoms associated with childhood maltreatment.

Childhood maltreatment has been linked to adult somatic symptoms, although this has rarely been examined in daily life. Furthermore, the localization of somatization associated with childhood maltreatment and its subtypes is unknown. This large-scale experience sampling study used body maps to examine the relationships between childhood maltreatment, its subtypes, and the intensity and location of negative somatic sensations in daily life. Participants (N = 2,234; 33% female and 67% male) were part of MyBPLab 2.0, a study conducted using a bespoke mobile phone application. Four categories of childhood maltreatment (emotional abuse, emotional neglect, physical abuse, and physical neglect) were measured using the Childhood Trauma Questionnaire. Using gender-matched human silhouettes, participants indicated the location and intensity of feelings of negative activation in the body. Childhood maltreatment generally and its four measured subtypes were all positively associated with heightened negative activation on both the front and back body maps. For females, total childhood maltreatment was associated with negative activation in the abdomen and lower back, while for males, the association was localized to the lower back. Similarly, each of the four subscales had localized associations with negative activation in the abdomen and lower back in females and lower back in males, except for emotional abuse, which was also associated with negative activation in the abdomen in males. These associations likely reflect increased somatization in individuals exposed to childhood maltreatment, suggesting a role for psychotherapeutic interventions in alleviating associated distress.

Abstract cognitive maps of social network structure aid adaptive inference.

Social navigation-such as anticipating where gossip may spread, or identifying which acquaintances can help land a job-relies on knowing how people are connected within their larger social communities. Problematically, for most social networks, the space of possible relationships is too vast to observe and memorize. Indeed, people's knowledge of these social relations is well known to be biased and error-prone. Here, we reveal that these biased representations reflect a fundamental computation that abstracts over individual relationships to enable principled inferences about unseen relationships. We propose a theory of network representation that explains how people learn inferential cognitive maps of social relations from direct observation, what kinds of knowledge structures emerge as a consequence, and why it can be beneficial to encode systematic biases into social cognitive maps. Leveraging simulations, laboratory experiments, and "field data" from a real-world network, we find that people abstract observations of direct relations (e.g., friends) into inferences of multistep relations (e.g., friends-of-friends). This multistep abstraction mechanism enables people to discover and represent complex social network structure, affording adaptive inferences across a variety of contexts, including friendship, trust, and advice-giving. Moreover, this multistep abstraction mechanism unifies a variety of otherwise puzzling empirical observations about social behavior. Our proposal generalizes the theory of cognitive maps to the fundamental computational problem of social inference, presenting a powerful framework for understanding the workings of a predictive mind operating within a complex social world.

Two differentially stable rDNA loci coexist on the same chromosome and form a single nucleolus.

The nucleolus is the most prominent membraneless compartment within the nucleus-dedicated to the metabolism of ribosomal RNA. Nucleoli are composed of hundreds of ribosomal DNA (rDNA) repeated genes that form large chromosomal clusters, whose high recombination rates can cause nucleolar dysfunction and promote genome instability. Intriguingly, the evolving architecture of eukaryotic genomes appears to have favored two strategic rDNA locations-where a single locus per chromosome is situated either near the centromere (CEN) or the telomere. Here, we deployed an innovative genome engineering approach to cut and paste to an ectopic chromosomal location-the ~1.5 mega-base rDNA locus in a single step using CRISPR technology. This "megablock" rDNA engineering was performed in a fused-karyotype strain of Saccharomyces cerevisiae. The strategic repositioning of this locus within the megachromosome allowed experimentally mimicking and monitoring the outcome of an rDNA migratory event, in which twin rDNA loci coexist on the same chromosomal arm. We showed that the twin-rDNA yeast readily adapts, exhibiting wild-type growth and maintaining rRNA homeostasis, and that the twin loci form a single nucleolus throughout the cell cycle. Unexpectedly, the size of each rDNA array appears to depend on its position relative to the CEN, in that the locus that is CEN-distal undergoes size reduction at a higher frequency compared to the CEN-proximal counterpart. Finally, we provided molecular evidence supporting a mechanism called paralogous cis-rDNA interference, which potentially explains why placing two identical repeated arrays on the same chromosome may negatively affect their function and structural stability.

Deriving the number of salience maps an observer has from the number and quality of concurrent centroid judgments.

[C. Koch, S. Ullman, Hum. Neurobiol.4, 219-227 (1985)] proposed a 2D topographical salience map that took feature-map outputs as its input and represented the importance "saliency" of the feature inputs at each location as a real number. The computation on the map, "winner-take-all," was used to predict action priority. We propose that the same or a similar map is used to compute centroid judgments, the center of a cloud of diverse items. [P. Sun, V. Chu, G. Sperling, Atten. Percept. Psychophys.83, 934-955 (2021)] demonstrated that following a 250-msec exposure of a 24-dot array of 3 intermixed colors, subjects could accurately report the centroid of each dot color, thereby indicating that these subjects had at least three salience maps. Here, we use a postcue, partial-report paradigm to determine how many more salience maps subjects might have. In 11 experiments, subjects viewed 0.3-s flashes of 28 to 32 item arrays composed of M, M = 3,...,8, different features followed by a cue to mouse-click the centroid of items of just the post-cued feature. Ideal detector response analyses show that subjects utilized at least 12 to 17 stimulus items. By determining whether a subject's performance in (M-1)-feature experiments could/could-not predict performance in M-feature experiments, we conclude that one subject has at least 7 and the other two have at least five salience maps. A computational model shows that the primary performance-limiting factors are channel capacity for representing so many concurrently presented groups of items and working-memory capacity for so many computed centroids.

BioID organelle mapping: you are the company you keep.

In a recent study, Go, Knight et al. combined a panel of protein markers with BioID proximity-dependent labeling to profile the composition of 20 distinct subcellular compartments. Comparison with similar global datasets acquired using imaging or fractionation-based approaches confirmed the consistency of the results while highlighting unique advantages.

Unravelling the origin of the reward positivity: a human intracranial event-related brain potential study.

The reward positivity (RewP) is an event-related brain potential (ERP) component that emerges approximately 250 to 350 milliseconds (ms) after receiving reward-related feedback stimuli and is believed to be important for reinforcement learning and reward processing. Although numerous localization studies have indicated that the anterior cingulate cortex (ACC) is the neural generator of this component, other studies have identified sources outside of the ACC, fuelling a debate about its origin. Because the results of EEG and MEG source localization studies are severely limited by the inverse problem, we addressed this question by leveraging the high spatial and temporal resolution of intracranial EEG. We predicted that we would identify a neural generator of the RewP in the caudal ACC. We recorded intracranial EEG in 19 refractory epilepsy patients who underwent invasive video-EEG monitoring at Ghent University Hospital, Belgium. Participants engaged in the virtual T-maze task (vTMT), a trial-and-error task known to elicit a canonical RewP, while scalp and intracranial EEG were simultaneously recorded. The RewP was identified using a difference wave approach for both scalp and intracranial EEG. The data were aggregated across participants to create a virtual "meta-participant" that contained all the recorded intracranial ERPs (iERPs) with respect to their intracranial contact locations. We used both a hypothesis-driven (focused on ACC) and exploratory (whole-brain analysis) approach to segment the brain into regions of interest (ROI). For each ROI, we evaluated the degree to which the time course of the absolute current density (ACD) activity mirrored the time course of the RewP, and confirmed the statistical significance of the results using permutation analysis. The grand average waveform of the scalp data revealed a RewP at 309 ms after reward feedback with a frontocentral scalp distribution, consistent with the identification of this component as the RewP. The meta-participant contained iERPs recorded from 582 intracranial contacts in total. The ACD activity of the aggregated iERPs were most similar to the RewP in left caudal ACC, left dorsolateral prefrontal cortex, left frontomedial cortex, and left white matter, with the highest score attributed to caudal ACC, as predicted. To our knowledge, this is the first study that uses intracranial EEG aggregated across multiple human epilepsy patients and current source density analysis to identify the neural generator(s) of the RewP. These results provide direct evidence that the ACC is a neural generator of the RewP.

Asynchronous behavioral and neurophysiological changes in word production in the adult lifespan.

Behavioral and brain-related changes in word production have been claimed to predominantly occur after 70 years of age. Most studies investigating age-related changes in adulthood only compared young to older adults, failing to determine whether neural processes underlying word production change at an earlier age than observed in behavior. This study aims to fill this gap by investigating whether changes in neurophysiological processes underlying word production are aligned with behavioral changes. Behavior and the electrophysiological event-related potential patterns of word production were assessed during a picture naming task in 95 participants across five adult lifespan age groups (ranging from 16 to 80 years old). While behavioral performance decreased starting from 70 years of age, significant neurophysiological changes were present at the age of 40 years old, in a time window (between 150 and 220 ms) likely associated with lexical-semantic processes underlying referential word production. These results show that neurophysiological modifications precede the behavioral changes in language production; they can be interpreted in line with the suggestion that the lexical-semantic reorganization in mid-adulthood influences the maintenance of language skills longer than for other cognitive functions.

Matrix Inversion and Subset Selection (MISS): A pipeline for mapping of diverse cell types across the murine brain.

The advent of increasingly sophisticated imaging platforms has allowed for the visualization of the murine nervous system at single-cell resolution. However, current experimental approaches have not yet produced whole-brain maps of a comprehensive set of neuronal and nonneuronal types that approaches the cellular diversity of the mammalian cortex. Here, we aim to fill in this gap in knowledge with an open-source computational pipeline, Matrix Inversion and Subset Selection (MISS), that can infer quantitatively validated distributions of diverse collections of neural cell types at 200-µm resolution using a combination of single-cell RNA sequencing (RNAseq) and in situ hybridization datasets. We rigorously demonstrate the accuracy of MISS against literature expectations. Importantly, we show that gene subset selection, a procedure by which we filter out low-information genes prior to performing deconvolution, is a critical preprocessing step that distinguishes MISS from its predecessors and facilitates the production of cell-type maps with significantly higher accuracy. We also show that MISS is generalizable by generating high-quality cell-type maps from a second independently curated single-cell RNAseq dataset. Together, our results illustrate the viability of computational approaches for determining the spatial distributions of a wide variety of cell types from genetic data alone.

Microestimates of wealth for all low- and middle-income countries.

Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty. Yet many poverty maps are out of date or exist only at very coarse levels of granularity. Here we develop microestimates of the relative wealth and poverty of the populated surface of all 135 low- and middle-income countries (LMICs) at 2.4 km resolution. The estimates are built by applying machine-learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, and topographic maps, as well as aggregated and deidentified connectivity data from Facebook. We train and calibrate the estimates using nationally representative household survey data from 56 LMICs and then validate their accuracy using four independent sources of household survey data from 18 countries. We also provide confidence intervals for each microestimate to facilitate responsible downstream use. These estimates are provided free for public use in the hope that they enable targeted policy response to the COVID-19 pandemic, provide the foundation for insights into the causes and consequences of economic development and growth, and promote responsible policymaking in support of sustainable development.

ISL1 is necessary for auditory neuron development and contributes toward tonotopic organization.

A cardinal feature of the auditory pathway is frequency selectivity, represented in a tonotopic map from the cochlea to the cortex. The molecular determinants of the auditory frequency map are unknown. Here, we discovered that the transcription factor ISL1 regulates the molecular and cellular features of auditory neurons, including the formation of the spiral ganglion and peripheral and central processes that shape the tonotopic representation of the auditory map. We selectively knocked out Isl1 in auditory neurons using Neurod1Cre strategies. In the absence of Isl1, spiral ganglion neurons migrate into the central cochlea and beyond, and the cochlear wiring is profoundly reduced and disrupted. The central axons of Isl1 mutants lose their topographic projections and segregation at the cochlear nucleus. Transcriptome analysis of spiral ganglion neurons shows that Isl1 regulates neurogenesis, axonogenesis, migration, neurotransmission-related machinery, and synaptic communication patterns. We show that peripheral disorganization in the cochlea affects the physiological properties of hearing in the midbrain and auditory behavior. Surprisingly, auditory processing features are preserved despite the significant hearing impairment, revealing central auditory pathway resilience and plasticity in Isl1 mutant mice. Mutant mice have a reduced acoustic startle reflex, altered prepulse inhibition, and characteristics of compensatory neural hyperactivity centrally. Our findings show that ISL1 is one of the obligatory factors required to sculpt auditory structural and functional tonotopic maps. Still, upon Isl1 deletion, the ensuing central plasticity of the auditory pathway does not suffice to overcome developmentally induced peripheral dysfunction of the cochlea.

Spared Premotor Areas Undergo Rapid Nonlinear Changes in Functional Organization Following a Focal Ischemic Infarct in Primary Motor Cortex of Squirrel Monkeys.

Recovery of motor function after stroke is accompanied by reorganization of movement representations in spared cortical motor regions. It is widely assumed that map reorganization parallels recovery, suggesting a causal relationship. We examined this assumption by measuring changes in motor representations in eight male and six female squirrel monkeys in the first few weeks after injury, a time when motor recovery is most rapid. Maps of movement representations were derived using intracortical microstimulation techniques in primary motor cortex (M1), ventral premotor cortex (PMv), and dorsal premotor cortex (PMd) in 14 adult squirrel monkeys before and after a focal infarct in the M1 distal forelimb area. Maps were derived at baseline and at either 2 (n = 7) or 3 weeks (n = 7) postinfarct. In PMv the forelimb maps remained unchanged at 2 weeks but contracted significantly (-42.4%) at 3 weeks. In PMd the forelimb maps expanded significantly (+110.6%) at 2 weeks but contracted significantly (-57.4%) at 3 weeks. Motor deficits were equivalent at both time points. These results highlight two features of plasticity after M1 lesions. First, significant contraction of distal forelimb motor maps in both PMv and PMd is evident by 3 weeks. Second, an unpredictable nonlinear pattern of reorganization occurs in the distal forelimb representation in PMd, first expanding at 2 weeks, and then contracting at 3 weeks postinjury. Together with previous results demonstrating reliable map expansions in PMv several weeks to months after M1 injury, the subacute time period may represent a critical window for the timing of therapeutic interventions.SIGNIFICANCE STATEMENT The relationship between motor recovery and motor map reorganization after cortical injury has rarely been examined in acute/subacute periods. In nonhuman primates, premotor maps were examined at 2 and 3 weeks after injury to primary motor cortex. Although maps are known to expand late after injury, the present study demonstrates early map expansion at 2 weeks (dorsal premotor cortex) followed by contraction at 3 weeks (dorsal and ventral premotor cortex). This nonlinear map reorganization during a time of gradual behavioral recovery suggests that the relationship between map plasticity and motor recovery is much more complex than previously thought. It also suggests that rehabilitative motor training may have its most potent effects during this early dynamic phase of map reorganization.

Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology.

The mammalian cell is a complex entity, with membrane-bound and membrane-less organelles playing vital roles in regulating cellular homeostasis. Organellar protein niches drive discrete biological processes and cell functions, thus maintaining cell equilibrium. Cellular processes such as signaling, growth, proliferation, motility, and programmed cell death require dynamic protein movements between cell compartments. Aberrant protein localization is associated with a wide range of diseases. Therefore, analyzing the subcellular proteome of the cell can provide a comprehensive overview of cellular biology. With recent advancements in mass spectrometry, imaging technology, computational tools, and deep machine learning algorithms, studies pertaining to subcellular protein localization and their dynamic distributions are gaining momentum. These studies reveal changing interaction networks because of "moonlighting proteins" and serve as a discovery tool for disease network mechanisms. Consequently, this review aims to provide a comprehensive repository for recent advancements in subcellular proteomics subcontexting methods, challenges, and future perspectives for method developers. In summary, subcellular proteomics is crucial to the understanding of the fundamental cellular mechanisms and the associated diseases.

An Ensemble Framework for Projecting the Impact of Lymphatic Filariasis Interventions Across Sub-Saharan Africa at a Fine Spatial Scale.

BACKGROUND: Lymphatic filariasis (LF) is a neglected tropical disease targeted for elimination as a public health problem by 2030. Although mass treatments have led to huge reductions in LF prevalence, some countries or regions may find it difficult to achieve elimination by 2030 owing to various factors, including local differences in transmission. Subnational projections of intervention impact are a useful tool in understanding these dynamics, but correctly characterizing their uncertainty is challenging. METHODS: We developed a computationally feasible framework for providing subnational projections for LF across 44 sub-Saharan African countries using ensemble models, guided by historical control data, to allow assessment of the role of subnational heterogeneities in global goal achievement. Projected scenarios include ongoing annual treatment from 2018 to 2030, enhanced coverage, and biannual treatment. RESULTS: Our projections suggest that progress is likely to continue well. However, highly endemic locations currently deploying strategies with the lower World Health Organization recommended coverage (65%) and frequency (annual) are expected to have slow decreases in prevalence. Increasing intervention frequency or coverage can accelerate progress by up to 5 or 6 years, respectively. CONCLUSIONS: While projections based on baseline data have limitations, our methodological advancements provide assessments of potential bottlenecks for the global goals for LF arising from subnational heterogeneities. In particular, areas with high baseline prevalence may face challenges in achieving the 2030 goals, extending the "tail" of interventions. Enhancing intervention frequency and/or coverage will accelerate progress. Our approach facilitates preimplementation assessments of the impact of local interventions and is applicable to other regions and neglected tropical diseases.

CT-guided spatial normalization of nuclear hybrid imaging adapted to enlarged ventricles: Impact on striatal uptake quantification.

INTRODUCTION: Spatial normalization is a prerequisite step for the quantitative analysis of SPECT or PET brain images using volume-of-interest (VOI) template or voxel-based analysis. MRI-guided spatial normalization is the gold standard, but the wide use of PET/CT or SPECT/CT in routine clinical practice makes CT-guided spatial normalization a necessary alternative. Ventricular enlargement is observed with aging, and it hampers the spatial normalization of the lateral ventricles and striatal regions, limiting their analysis. The aim of the present study was to propose a robust spatial normalization method based on CT scans that takes into account features of the aging brain to reduce bias in the CT-guided striatal analysis of SPECT images. METHODS: We propose an enhanced CT-guided spatial normalization pipeline based on SPM12. Performance of the proposed pipeline was assessed on visually normal [123I]-FP-CIT SPECT/CT images. SPM12 default CT-guided spatial normalization was used as reference method. The metrics assessed were the overlap between the spatially normalized lateral ventricles and caudate/putamen VOIs, and the computation of caudate and putamen specific binding ratios (SBR). RESULTS: In total 231 subjects (mean age ± SD = 61.9 ± 15.5 years) were included in the statistical analysis. The mean overlap between the spatially normalized lateral ventricles of subjects and the caudate VOI and the mean SBR of caudate were respectively 38.40 % (± SD = 19.48 %) of the VOI and 1.77 (± 0.79) when performing SPM12 default spatial normalization. The mean overlap decreased to 9.13 % (± SD = 1.41 %, P < 0.001) of the VOI and the SBR of caudate increased to 2.38 (± 0.51, P < 0.0001) when performing the proposed pipeline. Spatially normalized lateral ventricles did not overlap with putamen VOI using either method. The mean putamen SBR value derived from the proposed spatial normalization (2.75 ± 0.54) was not significantly different from that derived from the default SPM12 spatial normalization (2.83 ± 0.52, P > 0.05). CONCLUSION: The automatic CT-guided spatial normalization used herein led to a less biased spatial normalization of SPECT images, hence an improved semi-quantitative analysis. The proposed pipeline could be implemented in clinical routine to perform a more robust SBR computation using hybrid imaging.

Hue and orientation pinwheels in macaque area V4.

Area V4 is an intermediate-level area of the macaque visual cortical hierarchy that serves key functions in visual processing by integrating inputs from lower areas such as V1 and V2 and providing feedforward inputs to many higher cortical areas. Previous V4 imaging studies have focused on differential responses to color, orientation, disparity, and motion stimuli, but many details of the spatial organization of significant hue and orientation tuning have not been fully described. We used support vector machine (SVM) decoding of intrinsic cortical single-condition responses to generate high-resolution maps of hue and orientation tuning and to describe the organization of hue and orientation pinwheels in V4. Like V1 and V2, V4 contains maps of orientation that are organized as pinwheels. V4 also contains maps of hue that are organized as pinwheels, whose circular organization more closely represents the perception of hue than is observed in antecedent cortical areas. Unlike V1, where orientation is continuously mapped across the surface, V4 hue and orientation pinwheels are organized in limited numbers of pinwheel sequences. The organization of these sequences and the distance between pinwheels may provide insight into the functional organization of V4. Regions significantly tuned for hue occupy roughly four times that of the orientation, are largely separated from each other, and overlap by roughly 5%. This spatial organization is largely consistent with segregated inputs arising from V2 thin and interstripes. This modular organization of V4 suggests that further integration of color and shape might occur in higher areas in inferotemporal cortical.NEW & NOTEWORTHY The representation of hue and orientation in macaque monkey area V4 was determined by intrinsic cortical imaging of responses to isoluminant hues and achromatic grating stimuli. Vector summation of support vector machine (SVM) decoded single-condition responses was used to generate hue and orientation maps that, like V1 orientation maps, were both characterized by distinct pinwheel patterns. These data suggest that pinwheels are an important structure to represent different stimulus features across multiple visual cortical areas.

Predictive Mapping of Antimicrobial Resistance for Escherichia coli, Salmonella, and Campylobacter in Food-Producing Animals, Europe, 2000-2021.

In Europe, systematic national surveillance of antimicrobial resistance (AMR) in food-producing animals has been conducted for decades; however, geographic distribution within countries remains unknown. To determine distribution within Europe, we combined 33,802 country-level AMR prevalence estimates with 2,849 local AMR prevalence estimates from 209 point prevalence surveys across 31 countries. We produced geospatial models of AMR prevalence in Escherichia coli, nontyphoidal Salmonella, and Campylobacter for cattle, pigs, and poultry. We summarized AMR trends by using the proportion of tested antimicrobial compounds with resistance >50% and generated predictive maps at 10 × 10 km resolution that disaggregated AMR prevalence. For E. coli, predicted prevalence rates were highest in southern Romania and southern/eastern Italy; for Salmonella, southern Hungary and central Poland; and for Campylobacter, throughout Spain. Our findings suggest that AMR distribution is heterogeneous within countries and that surveillance data from below the country level could help with prioritizing resources to reduce AMR.

The Architecture of Metabolic Networks Constrains the Evolution of Microbial Resource Hierarchies.

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often use them sequentially according to a preference hierarchy, resulting in well-known patterns of diauxic growth. In theory, the evolutionary diversification of metabolic hierarchies could represent a mechanism supporting coexistence and biodiversity by enabling temporal segregation of niches. Despite this ecologically critical role, the extent to which substrate preference hierarchies can evolve and diversify remains largely unexplored. Here, we used genome-scale metabolic modeling to systematically explore the evolution of metabolic hierarchies across a vast space of metabolic network genotypes. We find that only a limited number of metabolic hierarchies can readily evolve, corresponding to the most commonly observed hierarchies in genome-derived models. We further show how the evolution of novel hierarchies is constrained by the architecture of central metabolism, which determines both the propensity to change ranks between pairs of substrates and the effect of specific reactions on hierarchy evolution. Our analysis sheds light on the genetic and mechanistic determinants of microbial metabolic hierarchies, opening new research avenues to understand their evolution, evolvability, and ecology.

Predicting Environmental and Ecological Drivers of Human Population Structure.

Landscape, climate, and culture can all structure human populations, but few existing methods are designed to simultaneously disentangle among a large number of variables in explaining genetic patterns. We developed a machine learning method for identifying the variables which best explain migration rates, as measured by the coalescent-based program MAPS that uses shared identical by descent tracts to infer spatial migration across a region of interest. We applied our method to 30 human populations in eastern Africa with high-density single nucleotide polymorphism array data. The remarkable diversity of ethnicities, languages, and environments in this region offers a unique opportunity to explore the variables that shape migration and genetic structure. We explored more than 20 spatial variables relating to landscape, climate, and presence of tsetse flies. The full model explained ∼40% of the variance in migration rate over the past 56 generations. Precipitation, minimum temperature of the coldest month, and elevation were the variables with the highest impact. Among the three groups of tsetse flies, the most impactful was fusca which transmits livestock trypanosomiasis. We also tested for adaptation to high elevation among Ethiopian populations. We did not identify well-known genes related to high elevation, but we did find signatures of positive selection related to metabolism and disease. We conclude that the environment has influenced the migration and adaptation of human populations in eastern Africa; the remaining variance in structure is likely due in part to cultural or other factors not captured in our model.