Collective behavior from surprise minimization.

Collective motion is ubiquitous in nature; groups of animals, such as fish, birds, and ungulates appear to move as a whole, exhibiting a rich behavioral repertoire that ranges from directed movement to milling to disordered swarming. Typically, such macroscopic patterns arise from decentralized, local interactions among constituent components (e.g., individual fish in a school). Preeminent models of this process describe individuals as self-propelled particles, subject to self-generated motion and "social forces" such as short-range repulsion and long-range attraction or alignment. However, organisms are not particles; they are probabilistic decision-makers. Here, we introduce an approach to modeling collective behavior based on active inference. This cognitive framework casts behavior as the consequence of a single imperative: to minimize surprise. We demonstrate that many empirically observed collective phenomena, including cohesion, milling, and directed motion, emerge naturally when considering behavior as driven by active Bayesian inference-without explicitly building behavioral rules or goals into individual agents. Furthermore, we show that active inference can recover and generalize the classical notion of social forces as agents attempt to suppress prediction errors that conflict with their expectations. By exploring the parameter space of the belief-based model, we reveal nontrivial relationships between the individual beliefs and group properties like polarization and the tendency to visit different collective states. We also explore how individual beliefs about uncertainty determine collective decision-making accuracy. Finally, we show how agents can update their generative model over time, resulting in groups that are collectively more sensitive to external fluctuations and encode information more robustly.

Predicting the DNA binding specificity of mutated transcription factors using family-level biophysically interpretable machine learning.

Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughput in vitro binding assays coupled with computational analysis have made it possible to accurately define such sequence recognition in a biophysically interpretable yet mechanism-agonistic way for individual TFs. The fact that such sequence-to-affinity models are now available for hundreds of TFs provides new avenues for predicting how the DNA binding specificity of a TF changes when its protein sequence is mutated. To this end, we developed an analytical framework based on a tetrahedron embedding that can be applied at the level of a given structural TF family. Using bHLH as a test case, we demonstrate that we can systematically map dependencies between the protein sequence of a TF and base preference within the DNA binding site. We also develop a regression approach to predict the quantitative energetic impact of mutations in the DNA binding domain of a TF on its DNA binding specificity, and perform SELEX-seq assays on mutated TFs to experimentally validate our results. Our results point to the feasibility of predicting the functional impact of disease mutations and allelic variation in the cell-wide TF repertoire by leveraging high-quality functional information across sets of homologous wild-type proteins.

Fine-grained descending control of steering in walking Drosophila.

Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream from distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Notably, a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from brain cells that drive specific, coordinated modulations of low-level patterns.

Two Notorious Nodes: a Critical Examination of Relaxed Molecular Clock Age Estimates of the Bilaterian Animals and Placental Mammals.

The popularity of relaxed clock Bayesian inference of clade origin timings has generated several recent publications with focal results considerably older than the fossils of the clades in question. Here we critically examine two such clades: the animals (with focus on the bilaterians); and the mammals (with focus on the placentals). Each example displays a set of characteristic pathologies which, although much commented on, are rarely corrected for. We conclude that in neither case does the molecular clock analysis provide any evidence for an origin of the clade deeper than what is suggested by the fossil record. In addition, both these clades have other features (including, in the case of the placental mammals, proximity to a large mass extinction) that allow us to generate precise expectations of the timings of their origins. Thus, in these instances the fossil record can provide a powerful test of molecular clock methodology, and why it goes astray; and we have every reason to think these problems are general.

Scarless Modification of the Drosophila Genome Near Any Mapped attP Sites.

Here we describe a Drosophila genome engineering technique that can scarlessly modify genomic sequences near any mapped attP attachment site previously integrated by transposon mobilization or gene targeting. This technique combines two highly efficient and robust procedures: phiC31 integrase-mediated site-specific integration and homing endonuclease-mediated resolution of local duplications. In this technique, a donor fragment containing the desired mutation(s) is first integrated into a selected attP site near the target locus by phiC31 integrase-mediated site-specific integration, which creates local duplications consisting of the mutant-containing donor fragment and the wild-type target locus. Next, homing endonuclease-induced double-stranded DNA breaks trigger recombination between the duplications and resolve the target locus to generate scarless mutant alleles. In every step, the desired flies can be easily identified by patterns of dominant markers, so no large-scale screens are needed. This technique is highly efficient and can be used to generate scarless point mutations, insertions, and deletions. The availability of large libraries of mapped attP site-containing transposon/CRISPR insertions in Drosophila allows the modification of more than half of the euchromatic Drosophila genome at a high efficiency. As more and more attP-containing insertions are generated and mapped, this technique will be able to modify larger portions of the Drosophila genome. The principles of this technique are applicable to other organisms where modifications to the genome are feasible. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Verifying attP-containing insertions Support Protocol: Extracting genomic DNA Basic Protocol 2: Generating the donor plasmid Basic Protocol 3: Injecting the donor plasmid and establishing transformant stocks Basic Protocol 4: Verifying the transformants Basic Protocol 5: Generating the final scarless alleles Basic Protocol 6: Verifying the final alleles.

Smart self-propelled particles: a framework to investigate the cognitive bases of movement.

Decision-making and movement of single animals or group of animals are often treated and investigated as separate processes. However, many decisions are taken while moving in a given space. In other words, both processes are optimized at the same time, and optimal decision-making processes are only understood in the light of movement constraints. To fully understand the rationale of decisions embedded in an environment (and therefore the underlying evolutionary processes), it is instrumental to develop theories of spatial decision-making. Here, we present a framework specifically developed to address this issue by the means of artificial neural networks and genetic algorithms. Specifically, we investigate a simple task in which single agents need to learn to explore their square arena without leaving its boundaries. We show that agents evolve by developing increasingly optimal strategies to solve a spatially embedded learning task while not having an initial arbitrary model of movements. The process allows the agents to learn how to move (i.e. by avoiding the arena walls) in order to make increasingly optimal decisions (improving their exploration of the arena). Ultimately, this framework makes predictions of possibly optimal behavioural strategies for tasks combining learning and movement.

Impaired Thiamine Metabolism in Amyotrophic Lateral Sclerosis and Its Potential Treatment With Benfotiamine: A Case Report and a Review of the Literature.

Homogenates of brain tissue from the frontal cortex at autopsy in patients with amyotrophic lateral sclerosis (ALS) showed dramatically reduced levels of the enzyme thiamine pyrophosphatase (TPPase), the enzyme responsible for the conversion of thiamine pyrophosphate (TPP) to thiamine monophosphate (TMP). Additionally, free thiamine (vitamin B1) and TMP levels have been shown to be significantly reduced in the plasma and cerebral spinal fluid (CSF) of patients with ALS. These findings suggest that there is impaired thiamine metabolism in patients with ALS. Impaired thiamine metabolism decreases adenosine triphosphate (ATP) production and is a well-established cause of neurodegeneration. Decreased levels of TPPase, resulting in decreased levels of TMP in the cells of the frontal cortex, might account for the focal neurodegenerative changes observed in motor neurons in ALS. Benfotiamine, a safe, lipid-soluble, highly absorbable thiamine analogue, significantly raises free thiamine, TMP, and TPP levels in the blood. A case in which benfotiamine may have positively impacted the symptoms of a patient with ALS is presented. The use of benfotiamine in patients with ALS appears to be a promising therapeutic option. Considering the severity and the lack of satisfactory treatment options associated with this disease, more research on the effects of benfotiamine on the course of ALS is urgently needed.

Evolutionary stability of social interaction rules in collective decision-making.

Social animals can use the choices made by other members of their groups as cues in decision making. Individuals must balance the private information they receive from their own sensory cues with the social information provided by observing what others have chosen. These two cues can be integrated using decision making rules, which specify the probability to select one or other options based on the quality and quantity of social and non-social information. Previous empirical work has investigated which decision making rules can replicate the observable features of collective decision making, while other theoretical research has derived forms for decision making rules based on normative assumptions about how rational agents should respond to the available information. Here we explore the performance of one commonly used decision making rule in terms of the expected decision accuracy of individuals employing it. We show that parameters of this model which have typically been treated as independent variables in empirical model-fitting studies obey necessary relationships under the assumption that animals are evolutionarily optimised to their environment. We further investigate whether this decision making model is appropriate to all animal groups by testing its evolutionary stability to invasion by alternative strategies that use social information differently, and show that the likely evolutionary equilibrium of these strategies depends sensitively on the precise nature of group identity among the wider population of animals it is embedded within.

Police-led real-time surveillance system for suspected suicides in Great Britain.

It has become increasingly apparent that rapidly available information about the occurrence of suicides is needed, particularly to support suicide prevention efforts. Concerns about the potential impact of the COVID-19 pandemic on vulnerability to suicide highlighted the need for such early data internationally. Here, we set out the nature, current status and content of a real-time suicide monitoring system in Great Britain (England, Scotland and Wales), and explore its potential to contribute to timely and targeted suicide prevention initiatives. We also discuss the challenges to successful implementation.

Empirical test of the many-wrongs hypothesis reveals weighted averaging of individual routes in pigeon flocks.

The 'many-wrongs hypothesis' predicts that groups improve their decision-making performance by aggregating members' diverse opinions. Although this has been considered one of the major benefits of collective movement and migration, whether and how multiple inputs are in fact aggregated for superior directional accuracy has not been empirically verified in non-human animals. Here we showed that larger homing pigeon flocks had significantly more efficient (i.e. shorter) homing routes than smaller flocks, consistent with previous findings and with the predictions of the many-wrongs hypothesis. However, detailed analysis showed that flock routes were not simply averages of individual routes, but instead that pigeons that more faithfully recapitulated their routes during individual flights had a proportionally greater influence on their flocks' routes. We discuss the implications of our results for possible mechanisms of collective learning as well as for the definition of leadership in animals solving navigational tasks collectively.

Divergent expression of paralogous genes by modification of shared enhancer activity through a promoter-proximal silencer.

The duplication of genes and their associated cis-regulatory elements, or enhancers, is a key contributor to genome evolution and biological complexity. Moreover, many paralogs, particularly tandem duplicates, are fixed for long periods of time under the control of shared enhancers. However, in most cases, the mechanism by which gene expression and function diverge following duplication is not known. Here, we dissect the regulation and function of the paralogous nubbin/pdm2 genes during wing development in Drosophila melanogaster. We show that these paralogs play a redundant role in the wing and that their expression relies on a single shared wing enhancer. However, the two genes differ in their ability to respond to this enhancer, with nub responding in all wing progenitor cells and pdm2 only in a small subset. This divergence is a result of a pdm2-specific silencer element at the pdm2 promoter that receives repressive input from the transcription factor Rotund. Repression through this silencer also depends on nub, allowing pdm2 to fully respond to the wing enhancer when nub expression is perturbed and functional compensation to occur. Thus, expression divergence downstream of a shared enhancer arises as a consequence of silencing the promoter of one paralog.

Transcription factor paralogs orchestrate alternative gene regulatory networks by context-dependent cooperation with multiple cofactors.

In eukaryotes, members of transcription factor families often exhibit similar DNA binding properties in vitro, yet orchestrate paralog-specific gene regulatory networks in vivo. The serially homologous first (T1) and third (T3) thoracic legs of Drosophila, which are specified by the Hox proteins Scr and Ubx, respectively, offer a unique opportunity to address this paradox in vivo. Genome-wide analyses using epitope-tagged alleles of both Hox loci in the T1 and T3 leg imaginal discs, the precursors to the adult legs and ventral body regions, show that ~8% of Hox binding is paralog-specific. Binding specificity is mediated by interactions with distinct cofactors in different domains: the Hox cofactor Exd acts in the proximal domain and is necessary for Scr to bind many of its paralog-specific targets, while in the distal leg domain, the homeodomain protein Distal-less (Dll) enhances Scr binding to a different subset of loci. These findings reveal how Hox paralogs, and perhaps paralogs of other transcription factor families, orchestrate alternative downstream gene regulatory networks with the help of multiple, context-specific cofactors.

Post-transcriptional regulation of transcription factor codes in immature neurons drives neuronal diversity.

How the vast array of neuronal diversity is generated remains an unsolved problem. Here, we investigate how 29 morphologically distinct leg motoneurons are generated from a single stem cell in Drosophila. We identify 19 transcription factor (TF) codes expressed in immature motoneurons just before their morphological differentiation. Using genetic manipulations and a computational tool, we demonstrate that the TF codes are progressively established in immature motoneurons according to their birth order. Comparing RNA and protein expression patterns of multiple TFs reveals that post-transcriptional regulation plays an essential role in shaping these TF codes. Two RNA-binding proteins, Imp and Syp, expressed in opposing gradients in immature motoneurons, control the translation of multiple TFs. The varying sensitivity of TF mRNAs to the opposing gradients of Imp and Syp in immature motoneurons decrypts these gradients into distinct TF codes, establishing the connectome between motoneuron axons and their target muscles.

SpyChIP identifies cell type-specific transcription factor occupancy from complex tissues.

Chromatin immunoprecipitation (ChIP) is an important technique for characterizing protein-DNA binding in vivo. One drawback of ChIP-based techniques is the lack of cell type-specificity when profiling complex tissues. To overcome this limitation, we developed SpyChIP to identify cell type-specific transcription factor (TF) binding sites in native physiological contexts without tissue dissociation or nuclei sorting. SpyChIP takes advantage of a specific covalent isopeptide bond that rapidly forms between the 15-amino acid SpyTag and the 17-kDa protein SpyCatcher. In SpyChIP, the target TF is fused with SpyTag by genome engineering, and an epitope tagged SpyCatcher is expressed in cell populations of interest, where it covalently binds to SpyTag-TF. Cell type-specific ChIP is obtained by immunoprecipitating chromatin prepared from whole tissues using antibodies directed against the epitope-tagged SpyCatcher. Using SpyChIP, we identified the genome-wide binding profiles of the Hox protein Ultrabithorax (Ubx) in two distinct cell types of the Drosophila haltere imaginal disc. Our results revealed extensive region-specific Ubx-DNA binding events, highlighting the significance of cell type-specific ChIP and the limitations of whole-tissue ChIP approaches. Analysis of Ubx::SpyChIP results provided insights into the relationship between chromatin accessibility and Ubx-DNA binding, as well as different mechanisms Ubx employs to regulate its downstream cis-regulatory modules. In addition to SpyChIP, we suggest that SpyTag-SpyCatcher technology, as well as other protein pairs that form covalent isopeptide bonds, will facilitate many additional in vivo applications that were previously impractical.

Prediction of protein-ligand binding affinity from sequencing data with interpretable machine learning.

Protein-ligand interactions are increasingly profiled at high throughput using affinity selection and massively parallel sequencing. However, these assays do not provide the biophysical parameters that most rigorously quantify molecular interactions. Here we describe a flexible machine learning method, called ProBound, that accurately defines sequence recognition in terms of equilibrium binding constants or kinetic rates. This is achieved using a multi-layered maximum-likelihood framework that models both the molecular interactions and the data generation process. We show that ProBound quantifies transcription factor (TF) behavior with models that predict binding affinity over a range exceeding that of previous resources; captures the impact of DNA modifications and conformational flexibility of multi-TF complexes; and infers specificity directly from in vivo data such as ChIP-seq without peak calling. When coupled with an assay called KD-seq, it determines the absolute affinity of protein-ligand interactions. We also apply ProBound to profile the kinetics of kinase-substrate interactions. ProBound opens new avenues for decoding biological networks and rationally engineering protein-ligand interactions.

Modeling the effects of environmental and perceptual uncertainty using deterministic reinforcement learning dynamics with partial observability.

Assessing the systemic effects of uncertainty that arises from agents' partial observation of the true states of the world is critical for understanding a wide range of scenarios, from navigation and foraging behavior to the provision of renewable resources and public infrastructures. Yet previous modeling work on agent learning and decision-making either lacks a systematic way to describe this source of uncertainty or puts the focus on obtaining optimal policies using complex models of the world that would impose an unrealistically high cognitive demand on real agents. In this work we aim to efficiently describe the emergent behavior of biologically plausible and parsimonious learning agents faced with partially observable worlds. Therefore we derive and present deterministic reinforcement learning dynamics where the agents observe the true state of the environment only partially. We showcase the broad applicability of our dynamics across different classes of partially observable agent-environment systems. We find that partial observability creates unintuitive benefits in several specific contexts, pointing the way to further research on a general understanding of such effects. For instance, partially observant agents can learn better outcomes faster, in a more stable way, and even overcome social dilemmas. Furthermore, our method allows the application of dynamical systems theory to partially observable multiagent leaning. In this regard we find the emergence of catastrophic limit cycles, a critical slowing down of the learning processes between reward regimes, and the separation of the learning dynamics into fast and slow directions, all caused by partial observability. Therefore, the presented dynamics have the potential to become a formal, yet practical, lightweight and robust tool for researchers in biology, social science, and machine learning to systematically investigate the effects of interacting partially observant agents.

Fluorescent labeling of genomic loci in Drosophila imaginal discs with heterologous DNA-binding proteins.

Using the Drosophila melanogaster Hox gene Ultrabithorax (Ubx) as an example, we demonstrate the use of three heterologous DNA-binding protein systems-LacI/LacO, ParB1/ParS1, and ParB2/ParS2-to label genomic loci in imaginal discs with the insertion of a small DNA tag. We compare each system, considering the impact of labeling in genomic regions (1) inside versus outside of a transcribed gene body and (2) with varying chromatin accessibility. We demonstrate the value of this system by interrogating the relationship between gene expression level and enhancer-promoter distance, as well as inter-allelic distance at the Ubx locus. We find that the distance between an essential intronic cis-regulatory element, anterobithorax (abx), and the promoter does not vary with expression level. In contrast, inter-allelic distance correlates with Ubx expression level.

Cell-type-specific Hox regulatory strategies orchestrate tissue identity.

Hox proteins are homeodomain transcription factors that diversify serially homologous segments along the animal body axis, as revealed by the classic bithorax phenotype of Drosophila melanogaster, in which mutations in Ultrabithorax (Ubx) transform the third thoracic segment into the likeness of the second thoracic segment. To specify segment identity, we show that Ubx both increases and decreases chromatin accessibility, coinciding with its dual role as both an activator and repressor of transcription. However, the choice of transcriptional activity executed by Ubx is spatially regulated and depends on the availability of cofactors, with Ubx acting as a repressor in some populations and as an activator in others. Ubx-mediated changes to chromatin accessibility positively and negatively affect the binding of Scalloped (Sd), a transcription factor that is required for appendage development in both segments. These findings illustrate how a single Hox protein can modify complex gene regulatory networks to transform the identity of an entire tissue.

Homothorax controls a binary Rhodopsin switch in Drosophila ocelli.

Visual perception of the environment is mediated by specialized photoreceptor (PR) neurons of the eye. Each PR expresses photosensitive opsins, which are activated by a particular wavelength of light. In most insects, the visual system comprises a pair of compound eyes that are mainly associated with motion, color or polarized light detection, and a triplet of ocelli that are thought to be critical during flight to detect horizon and movements. It is widely believed that the evolutionary diversification of compound eye and ocelli in insects occurred from an ancestral visual organ around 500 million years ago. Concurrently, opsin genes were also duplicated to provide distinct spectral sensitivities to different PRs of compound eye and ocelli. In the fruit fly Drosophila melanogaster, Rhodopsin1 (Rh1) and Rh2 are closely related opsins that originated from the duplication of a single ancestral gene. However, in the visual organs, Rh2 is uniquely expressed in ocelli whereas Rh1 is uniquely expressed in outer PRs of the compound eye. It is currently unknown how this differential expression of Rh1 and Rh2 in the two visual organs is controlled to provide unique spectral sensitivities to ocelli and compound eyes. Here, we show that Homothorax (Hth) is expressed in ocelli and confers proper rhodopsin expression. We find that Hth controls a binary Rhodopsin switch in ocelli to promote Rh2 expression and repress Rh1 expression. Genetic and molecular analysis of rh1 and rh2 supports that Hth acts through their promoters to regulate Rhodopsin expression in the ocelli. Finally, we also show that when ectopically expressed in the retina, hth is sufficient to induce Rh2 expression only at the outer PRs in a cell autonomous manner. We therefore propose that the diversification of rhodpsins in the ocelli and retinal outer PRs occurred by duplication of an ancestral gene, which is under the control of Homothorax.