Mechanistic Constraints Research Articles

Enhancer grammar in development, evolution, and disease: dependencies and interplay.

Each language has standard books describing that language's grammatical rules. Biologists have searched for similar, albeit more complex, principles relating enhancer sequence to gene expression. Here, we review the literature on enhancer grammar. We introduce dependency grammar, a model where enhancers encode information based on dependencies between enhancer features shaped by mechanistic, evolutionary, and biological constraints. Classifying enhancers based on the types of dependencies may identify unifying principles relating enhancer sequence to gene expression. Such rules would allow us to read the instructions for development within genomes and pinpoint causal enhancer variants underlying disease and evolutionary changes.

Corrigendum to: Mechanistic Causation and Constraints: Perspectival Parts and Powers, Non-perspectival Modal Patterns

Corrigendum to: Mechanistic Causation and Constraints: Perspectival Parts and Powers, Non-perspectival Modal Patterns

Osteohistological analyses reveal diverse strategies of theropod dinosaur body-size evolution.

The independent evolution of gigantism among dinosaurs has been a topic of long-standing interest, but it remains unclear if gigantic theropods, the largest bipeds in the fossil record, all achieved massive sizes in the same manner, or through different strategies. We perform multi-element histological analyses on a phylogenetically broad dataset sampled from eight theropod families, with a focus on gigantic tyrannosaurids and carcharodontosaurids, to reconstruct the growth strategies of these lineages and test if particular bones consistently preserve the most complete growth record. We find that in skeletally mature gigantic theropods, weight-bearing bones consistently preserve extensive growth records, whereas non-weight-bearing bones are remodelled and less useful for growth reconstruction, contrary to the pattern observed in smaller theropods and some other dinosaur clades. We find a heterochronic pattern of growth fitting an acceleration model in tyrannosaurids, with allosauroid carcharodontosaurids better fitting a model of hypermorphosis. These divergent growth patterns appear phylogenetically constrained, representing extreme versions of the growth patterns present in smaller coelurosaurs and allosauroids, respectively. This provides the first evidence of a lack of strong mechanistic or physiological constraints on size evolution in the largest bipeds in the fossil record and evidence of one of the longest-living individual dinosaurs ever documented.

Robust valence-induced biases on motor response and confidence in human reinforcement learning

In simple instrumental-learning tasks, humans learn to seek gains and to avoid losses equally well. Yet, two effects of valence are observed. First, decisions in loss-contexts are slower. Second, loss contexts decrease individuals’ confidence in their choices. Whether these two effects are two manifestations of a single mechanism or whether they can be partially dissociated is unknown. Across six experiments, we attempted to disrupt the valence-induced motor bias effects by manipulating the mapping between decisions and actions and imposing constraints on response times (RTs). Our goal was to assess the presence of the valence-induced confidence bias in the absence of the RT bias. We observed both motor and confidence biases despite our disruption attempts, establishing that the effects of valence on motor and metacognitive responses are very robust and replicable. Nonetheless, within- and between-individual inferences reveal that the confidence bias resists the disruption of the RT bias. Therefore, although concomitant in most cases, valence-induced motor and confidence biases seem to be partly dissociable. These results highlight new important mechanistic constraints that should be incorporated in learning models to jointly explain choice, reaction times and confidence.

Using Biophysical Models to Improve Survey Efficiency for Cryptic Ectotherms

ABSTRACTInefficiencies in monitoring programs waste resources. Ideally, we would predict when and where target species are most detectable and place our effort accordingly. Statistical models can generate predictor functions relating survey conditions to detectability but are phenomenological; they do not incorporate biological constraints and so using them to predict into unsampled time and space is risky. Biophysical ecology allows us to place constraints on detection by identifying abiotic conditions in which the target species cannot be present. We show how such constraint can be incorporated into standard detection models. We use the striped legless lizard (Delma impar), a threatened cryptic species, in southeastern Australia, as a case study, using fortnightly monitoring data collected between June 2016 to May 2017. These lizards are monitored by searching under tiles placed in arrays; we used a biophysical model to simulate the thermal microclimate under tiles and combined this with the striped legless lizard's thermal physiology to predict when tiles could be used. When compared against a large monitoring dataset, lizards were rarely observed at times the model predicted they should not be present, but the model also over‐predicted presences. A statistical occupancy model showed that much of this over‐prediction is explained by a generally low detection probability, and a seasonal trend in detection beyond that captured in the biophysical model. We then replaced the temperature covariates of detection in the statistical model with our biophysical prediction (a categorical variable). The resulting model explained almost the same amount of variance in detections as the original model but using a single variable that captured biological constraints. The biophysical model allowed us to place mechanistic constraints on detection, but it still needed to be informed by observed aspects of the species' behavior that were not influenced by temperature. Hybrid statistical‐biophysical models such as ours offer a powerful tool for forecasting optimal survey conditions for a wide array of species. © 2020 The Wildlife Society.

Ecology and allometry predict the evolution of avian developmental durations

The duration of the developmental period represents a fundamental axis of life-history variation, yet broad insights regarding the drivers of this diversity are currently lacking. Here, we test mechanistic and ecological explanations for the evolution of developmental duration using embryological data and information on incubation and fledging for 3096 avian species. Developmental phases associated primarily with growth are the longest and most variable, consistent with a role for allometric constraint in determining the duration of development. In addition, developmental durations retain a strong imprint of deep evolutionary history and body size differences among species explain less variation than previously thought. Finally, we reveal ecological correlates of developmental durations, including variables associated with the relative safety of the developmental environment and pressures of breeding phenology. Overall, our results provide broad-scale insight into the relative importance of mechanistic, ecological and evolutionary constraints in shaping the diversification of this key life-history trait.

Speech rhythms and their neural foundations.

The recognition of spoken language has typically been studied by focusing on either words or their constituent elements (for example, low-level features or phonemes). More recently, the 'temporal mesoscale' of speech has been explored, specifically regularities in the envelope of the acoustic signal that correlate with syllabic information and that play a central role in production and perception processes. The temporal structure of speech at this scale is remarkably stable across languages, with a preferred range of rhythmicity of 2- 8 Hz. Importantly, this rhythmicity is required by the processes underlying the construction of intelligible speech. A lot of current work focuses on audio-motor interactions in speech, highlighting behavioural and neural evidence that demonstrates how properties of perceptual and motor systems, and their relation, can underlie the mesoscale speech rhythms. The data invite the hypothesis that the speech motor cortex is best modelled as a neural oscillator, a conjecture that aligns well with current proposals highlighting the fundamental role of neural oscillations in perception and cognition. The findings also show motor theories (of speech) in a different light, placing new mechanistic constraints on accounts of the action-perception interface.

Sex Differences in the Recombination Landscape.

Sex differences in overall recombination rates are well known, but little theoretical or empirical attention has been given to how and why sexes differ in their recombination landscapes: the patterns of recombination along chromosomes. In the first scientific review of this phenomenon, we find that recombination is biased toward telomeres in males and more uniformly distributed in females in most vertebrates and many other eukaryotes. Notable exceptions to this pattern exist, however. Fine-scale recombination patterns also frequently differ between males and females. The molecular mechanisms responsible for sex differences remain unclear, but chromatin landscapes play a role. Why these sex differences evolve also is unclear. Hypotheses suggest that they may result from sexually antagonistic selection acting on coding genes and their regulatory elements, meiotic drive in females, selection during the haploid phase of the life cycle, selection against aneuploidy, or mechanistic constraints. No single hypothesis, however, can adequately explain the evolution of sex differences in all cases. Sex-specific recombination landscapes have important consequences for population differentiation and sex chromosome evolution.

Provitamin D3 modulation through prebiotics supplementation: simulation based assessment

Vitamin D is important in multiple health conditions. Vitamin D deficiency is prevalent globally even with exposure to adequate sunlight. Reduction in provitamin D3 (7-dehydrocholesterol, 7-DHC) is an important cause of vitamin D3 deficiency. Vitamin supplementation, food fortification, and use of probiotics are some approaches to reduce vitamin D3 deficiency. This study investigates plausibility of 7-DHC biosynthesis through dietary prebiotics supplementation. Furthermore, it reports mechanistic details and constraints for the biosynthesis using flux balance analysis (FBA) simulations. The FBA simulations using co-metabolism models comprising human host and a resident bacterium (Faecalibacterium prausnitzii or Bacteroides thetaiotamicron) indicated increased flux of 7-DHC with short-chain fructooligosaccharide (scFOS) or inulin supplementation. We observed around 2-fold increase in flux compared to the baseline. Biosynthesis of 7-DHC was primarily modulated through acetate, pyruvate and lactate secreted by the bacterium. We observed diverse mechanisms and dose dependent responses. We extended this assessment to 119 resident bacteria and investigated the metabolites profiles with prebiotics supplementation. In summary, the current study suggests the potential use of applying prebiotics in enhancing 7-DHC biosynthesis. Furthermore, performance of the different gut bacteria with prebiotic supplementation for secreted metabolites profile is reported. These results may be useful to design future clinical studies.

Intermolecular 2 + 2 Carbonyl–Olefin Photocycloadditions Enabled by Cu(I)–Norbornene MLCT

Photocycloadditions are often typified by the oxetane-forming Paternò-Büchi reaction. However, the mechanistic constraints of carbonyl excitation and olefin interception have limited this attractive oxetane-forming pathway. Here we describe the use of a Cu(I) precatalyst that achieves selective olefin activation via coordination to the metal center. Significantly, this intermolecular 2 + 2 carbonyl-olefin photocycloaddition engages alkyl ketones, which are more challenging to accommodate via direct irradiation pathways. Mechanistic investigations support the in situ formation of a Cu-norbornene resting state that undergoes a MLCT leading to oxetane formation.

Analysis of human acetylation stoichiometry defines mechanistic constraints on protein regulation

Lysine acetylation is a reversible posttranslational modification that occurs at thousands of sites on human proteins. However, the stoichiometry of acetylation remains poorly characterized, and is important for understanding acetylation-dependent mechanisms of protein regulation. Here we provide accurate, validated measurements of acetylation stoichiometry at 6829 sites on 2535 proteins in human cervical cancer (HeLa) cells. Most acetylation occurs at very low stoichiometry (median 0.02%), whereas high stoichiometry acetylation (>1%) occurs on nuclear proteins involved in gene transcription and on acetyltransferases. Analysis of acetylation copy numbers show that histones harbor the majority of acetylated lysine residues in human cells. Class I deacetylases target a greater proportion of high stoichiometry acetylation compared to SIRT1 and HDAC6. The acetyltransferases CBP and p300 catalyze a majority (65%) of high stoichiometry acetylation. This resource dataset provides valuable information for evaluating the impact of individual acetylation sites on protein function and for building accurate mechanistic models.

Nonequilibrium correlations in minimal dynamical models of polymer copying

Living systems produce "persistent" copies of information-carrying polymers, in which template and copy sequences remain correlated after physically decoupling. We identify a general measure of the thermodynamic efficiency with which these nonequilibrium states are created and analyze the accuracy and efficiency of a family of dynamical models that produce persistent copies. For the weakest chemical driving, when polymer growth occurs in equilibrium, both the copy accuracy and, more surprisingly, the efficiency vanish. At higher driving strengths, accuracy and efficiency both increase, with efficiency showing one or more peaks at moderate driving. Correlations generated within the copy sequence, as well as between template and copy, store additional free energy in the copied polymer and limit the single-site accuracy for a given chemical work input. Our results provide insight into the design of natural self-replicating systems and can aid the design of synthetic replicators.

Mechanistic Causation and Constraints: Perspectival Parts and Powers, Non-perspectival Modal Patterns

Abstract Any successful account of the metaphysics of mechanistic causation must satisfy at least five key desiderata. In this article, I lay out these five desiderata and explain why existing accounts of the metaphysics of mechanistic causation fail to satisfy them. I then present an alternative account that does satisfy the five desiderata. According to this alternative account, we must resort to a type of ontological entity that is new to metaphysics, but not to science: constraints. In this article, I explain how a constraints-based metaphysics fits best with the emerging consensus on the nature of mechanistic explanation. 1Introduction2Renormalizability2.1The first two desiderata: Intrinsicness and productivity2.2The third desideratum: Scientific validity or non-mysteriousness2.3The fourth desideratum: Directionality2.4The fifth desideratum: Perspectival nature of mechanisms3Constraints and Causation3.1Multi-perspectival realism and causal structure3.2Causal structure as laws3.3Causal structures in analytical mechanics: Constraints3.4A metaphysics inspired by analytical mechanics: Constraints as ontologically primitive modal structures4Constraints and Mechanistic Causal Powers 4.1Inter- versus intra-perspectival categories4.2Mechanistic causal powers are grounded by constraints4.3Intrinsicness and constraints4.4Constraints and productiveness4.5Constraints and directionality5Conclusion

Evolution and Manipulation of Vector Host Choice.

The transmission of many animal and plant diseases relies on the behavior of arthropod vectors. In particular, the specific preference for infected or uninfected hosts observed in many vector species is expected to affect the circulation of vector-borne diseases. Here I develop a theoretical framework to study the epidemiology and evolution of the manipulation of host choice behavior of vectors. I show that vector preference strategies have dramatic epidemiological consequences. I also explore the evolution of vector host choice under different scenarios regarding control of the vector behavior by the pathogen. This analysis yields multiple evolutionary outcomes and explains the diversity of host choice behaviors observed in a broad range of vector-borne diseases. In particular, this analysis helps us understand why several pathogens have evolved manipulation strategies that vary with the infectious status of their vector species while other pathogens seem unable to evolve such complex conditional strategies. I argue that contrasting the behavior of infected and uninfected vectors is key to revealing the mechanistic constraints acting on the evolution of the manipulation of vector behavior.

Testing the predictions of sex allocation hypotheses in dimorphic, cooperatively breeding riflemen.

Evolutionary theory predicts that parents should invest equally in the two sexes. If one sex is more costly, a production bias is predicted in favour of the other. Two well‐studied causes of differential costs are size dimorphism, in which the larger sex should be more costly, and sex‐biased helping in cooperative breeders, in which the more helpful sex should be less costly because future helping “repays” some of its parents’ investment. We studied a bird species in which both processes should favor production of males. Female riflemen Acanthisitta chloris are larger than males, and we documented greater provisioning effort in more female‐biased broods indicating they are likely costlier to raise. Riflemen are also cooperative breeders, and males provide more help than females. Contrary to expectations, we observed no male bias in brood sex ratios, which did not differ significantly from parity. We tested whether the lack of a population‐wide pattern was a result of facultative sex allocation by individual females, but this hypothesis was not supported either. Our results show an absence of adaptive patterns despite a clear directional hypothesis derived from theory. This appears to be associated with a suboptimal female‐biased investment ratio. We conclude that predictions of adaptive sex allocation may falter because of mechanistic constraint, unrecognized costs and benefits, or weak selection.

Charge and Polarity Preferences for N-Glycosylation: A Genome-Wide In Silico Study and Its Implications Regarding Constitutive Proliferation and Adhesion of Carcinoma Cells.

The structural and functional diversity of the human proteome is mediated by N- and O-linked glycosylations that define the individual properties of extracellular and membrane-associated proteins. In this study, we utilized different computational tools to perform in silico based genome-wide mapping of 1,117 human proteins and unravel the contribution of both penultimate and vicinal amino acids for the asparagine-based, site-specific N-glycosylation. Our results correlate the non-canonical involvement of charge and polarity environment of classified amino acids (designated as L, O, A, P, and N groups) in the N-glycosylation process, as validated by NetNGlyc predictions, and 130 literature-reported human proteins. From our results, particular charge and polarity combinations of non-polar aliphatic, acidic, basic, and aromatic polar side chain environment of both penultimate and vicinal amino acids were found to promote the N-glycosylation process. However, the alteration in side-chain charge and polarity environment of genetic variants, particularly in the vicinity of Asn-containing epitope, may induce constitutive glycosylation (e.g., aberrant glycosylation at preferred and non-preferred sites) of membrane proteins causing constitutive proliferation and triggering epithelial-to-mesenchymal transition. The current genome-wide mapping of 1,117 proteins (2,909 asparagine residues) was used to explore charge- and polarity-based mechanistic constraints in N-glycosylation, and discuss alterations of the neoplastic phenotype that can be ascribed to N-glycosylation at preferred and non-preferred sites.

Uncertain soil moisture feedbacks in model projections of Sahel precipitation

AbstractGiven the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long‐term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment‐Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land‐atmosphere feedbacks, even at the large spatial scales considered here.

Modelling the evolution of how vector-borne parasites manipulate the vector's host choice

The transmission of many animal and plant diseases relies on the behavior of arthropod vectors. In particular, the choice to feed on either infected or uninfected hosts can dramatically affect the epidemiology of vector-borne diseases. I develop an epidemiological model to explore the impact of host choice behavior on the dynamics of these diseases and to examine selection acting on vector behavior, but also on pathogen manipulation of this behavior. This model identifies multiple evolutionary conflicts over the control of this behavior and generates testable predictions under different scenarios. In general, the vector should evolve the ability to avoid infected hosts. However, if the vector behavior is under the control of the pathogen, uninfected vectors should prefer infected hosts while infected vectors should seek uninfected hosts. But some mechanistic constraints on pathogen manipulation ability may alter these predictions. These theoretical results are discussed in the light of observed behavioral patterns obtained on a diverse range of vector-borne diseases. These patterns confirm that several pathogens have evolved conditional behavioral manipulation strategies of their vector species. Other pathogens, however, seem unable to evolve such complex conditional strategies. Contrasting the behavior of infected and uninfected vectors may thus help reveal mechanistic constraints acting on the evolution of the manipulation of vector behavior.

The Role of Multiple Neuromodulators in Reinforcement Learning That Is Based on Competition between Eligibility Traces

The ability to maximize reward and avoid punishment is essential for animal survival. Reinforcement learning (RL) refers to the algorithms used by biological or artificial systems to learn how to maximize reward or avoid negative outcomes based on past experiences. While RL is also important in machine learning, the types of mechanistic constraints encountered by biological machinery might be different than those for artificial systems. Two major problems encountered by RL are how to relate a stimulus with a reinforcing signal that is delayed in time (temporal credit assignment), and how to stop learning once the target behaviors are attained (stopping rule). To address the first problem synaptic eligibility traces were introduced, bridging the temporal gap between a stimulus and its reward. Although, these were mere theoretical constructs, recent experiments have provided evidence of their existence. These experiments also reveal that the presence of specific neuromodulators converts the traces into changes in synaptic efficacy. A mechanistic implementation of the stopping rule usually assumes the inhibition of the reward nucleus; however, recent experimental results have shown that learning terminates at the appropriate network state even in setups where the reward nucleus cannot be inhibited. In an effort to describe a learning rule that solves the temporal credit assignment problem and implements a biologically plausible stopping rule, we proposed a model based on two separate synaptic eligibility traces, one for long-term potentiation (LTP) and one for long-term depression (LTD), each obeying different dynamics and having different effective magnitudes. The model has been shown to successfully generate stable learning in recurrent networks. Although, the model assumes the presence of a single neuromodulator, evidence indicates that there are different neuromodulators for expressing the different traces. What could be the role of different neuromodulators for expressing the LTP and LTD traces? Here we expand on our previous model to include several neuromodulators, and illustrate through various examples how different these contribute to learning reward-timing within a wide set of training paradigms and propose further roles that multiple neuromodulators can play in encoding additional information of the rewarding signal.

Enzyme level N and O isotope effects of assimilatory and dissimilatory nitrate reduction

AbstractTo provide mechanistic constraints to interpret nitrogen (N) and oxygen (O) isotope ratios of nitrate ( ), 15N/14N and 18O/16O, in the environment, we measured the enzymatic N and O isotope effects (15ε and 18ε) during its reduction by reductase enzymes, including (1) a prokaryotic respiratory reductase, Nar, from the heterotrophic denitrifier Paracoccus denitrificans, (2) eukaryotic assimilatory reductases, eukNR, from Pichia angusta and from Arabidopsis thaliana, and (3) a prokaryotic periplasmic reductase, Nap, from the photoheterotroph Rhodobacter sphaeroides. Enzymatic Nar and eukNR assays with artificial viologen electron donors yielded identical 18ε and 15ε of ∼28‰, regardless of [ ] or assay temperature, suggesting analogous kinetic mechanisms with viologen reductants. Nar assays fuelled with the physiological reductant hydroquinone (HQ) also yielded 18ε ≈ 15ε, but variable amplitudes from 21‰ to 33.0‰ in association with [ ], suggesting analogous substrate sensitivity in vivo. Nap assays fuelled by viologen revealed 18ε:15ε of 0.50, where 18ε ≈ 19‰ and 15ε ≈ 38‰, indicating a distinct catalytic mechanism than Nar and eukNR. Nap isotope effects measured in vivo showed a similar 18ε:15ε of 0.57, but reduced 18ε ≈ 11‰ and 15ε ≈ 19‰. Together, the results confirm identical enzymatic 18ε and 15ε during assimilation and denitrification, reinforcing the reliability of this benchmark to identify consumption in the environment. However, the amplitude of enzymatic isotope effects is apt to vary in vivo. The distinctive signature of Nap is of interest for deciphering catalytic mechanisms but may be negligible in most environments given its physiological role.