SASH1 S519N Variant Links Skin Hyperpigmentation and Premature Hair Graying to Dysfunction of Melanocyte Lineage.

A better understanding of human melanocyte (MC) and MC stem cell biology is essential for treating MC-related diseases. This study employed an inherited pigmentation disorder carrying the SASH1S519N variant in a Hispanic family to investigate SASH1 function in the MC lineage and the underlying mechanism for this disorder. We used a multidisciplinary approach, including clinical examinations, human cell assays, yeast 2-hybrid screening, and biochemical techniques. Results linked early hair graying to the SASH1S519N variant, a previously unrecognized clinical phenotype in hyperpigmentation disorders. In vitro, we identified SASH1 as a regulator in MC stem cell maintenance and discovered that TNKS2 is crucial for SASH1's role. In addition, the S519N variant is located in one of multiple tankyrase-binding motifs and alters the binding kinetics and affinity of the interaction. In summary, this disorder links both gain and loss of pigmentation in the same individual, hinting to accelerated aging in human MC stem cells. The findings offer insights into the roles of SASH1 and TNKS2 in MC stem cell maintenance and the molecular mechanisms of pigmentation disorders. We propose that a comprehensive clinical evaluation of patients with MC-related disorders should include an assessment and history of hair pigmentation loss.

Restoring spatiotemporal variability to enhance the capacity for dispersal-limited species to track climate change.

Climate refugia are areas where species can persist through climate change with little to no movement. Among the factors associated with climate refugia are high spatial heterogeneity, such that there is only a short distance between current and future optimal climates, as well as biotic or abiotic environmental factors that buffer against variability in time. However, these types of climate refugia may be declining due to anthropogenic homogenization of environments and degradation of environmental buffers. To quantify the potential for restoration of refugia-like environmental conditions to increase population persistence under climate change, we simulated a population's capacity to track their temperature over space and time given different levels of spatial and temporal variability in temperature. To determine how species traits affected the efficacy of restoring heterogeneity, we explored an array of values for species' dispersal ability, thermal tolerance, and fecundity. We found that species were more likely to persist in environments with higher spatial heterogeneity and lower environmental stochasticity. When simulating a management action that increased the spatial heterogeneity of a previously homogenized environment, species were more likely to persist through climate change, and population sizes were generally higher, but there was little effect with mild temperature change. The benefits of heterogeneity restoration were greatest for species with limited dispersal ability. In contrast, species with longer dispersal but lower fecundity were more likely to benefit from a reduction in environmental stochasticity than an increase in spatial heterogeneity. Our results suggest that restoring environments to refugia-like conditions could promote species' persistence under the influence of climate change in addition to conservation strategies such as assisted migration, corridors, and increased protection.

TBM Hunter: Identify and Score Canonical, Extended, and Unconventional Tankyrase-Binding Motifs in Any Protein.

Tankyrases, a versatile protein group within the poly(ADP-ribose) polymerase family, are essential for post-translational poly(ADP-ribosyl)ation, influencing various cellular functions and contributing to diseases, particularly cancer. Consequently, tankyrases have become important targets for anti-cancer drug development. Emerging approaches in drug discovery aim to disrupt interactions between tankyrases and their binding partners, which hinge on tankyrase-binding motifs (TBMs) within partner proteins and ankyrin repeat cluster domains within tankyrases. Our study addresses the challenge of identifying and ranking TBMs. We have conducted a comprehensive review of the existing literature, classifying TBMs into three distinct groups, each with its own scoring system. To facilitate this process, we introduce TBM Hunter-an accessible, web-based tool. This user-friendly platform provides a cost-free and efficient means to screen and assess potential TBMs within any given protein. TBM Hunter can handle individual proteins or lists of proteins simultaneously. Notably, our results demonstrate that TBM Hunter not only identifies known TBMs but also uncovers novel ones. In summary, our study offers an all-encompassing perspective on TBMs and presents an easy-to-use, precise, and free tool for identifying and evaluating potential TBMs in any protein, thereby enhancing research and drug development efforts focused on tankyrases.

Early warning signals have limited applicability to empirical lake data.

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.

SASH1 interacts with TNKS2 and promotes human melanocyte stem cell maintenance.

Both aging spots (hyperpigmentation) and hair graying (lack of pigmentation) are associated with aging, two seemingly opposite pigmentation phenotypes. It is not clear how they are mechanistically connected. This study investigated the underlying mechanism in a family with an inherited pigmentation disorder. Clinical examinations identified accelerated hair graying and skin dyspigmentation (intermixed hyper and hypopigmentation) in the family members carrying the SASH1 S519N variant. Cell assays indicated that SASH1 promoted stem-like characteristics in human melanocytes, and SASH1 S519N was defective in this function. Multiple assays showed that SASH1 binds to tankyrase 2 (TNKS2), which is required for SASH1's promotion of stem-like function. Further, the SASH1 S519N variant is in a bona fide Tankyrase-binding motif, and SASH1 S519N alters the binding kinetics and affinity. Results here indicate SASH1 as a novel protein regulating the appropriate balance between melanocyte stem cells (McSC) and mature melanocytes (MCs), with S519N variant causing defects. We propose that dysfunction of McSC maintenance connects multiple aging-associated pigmentation phenotypes in the general population.

Phenotypic response to different predator strategies can be mediated by temperature.

Temperature change affects biological systems in multifaceted ways, including the alteration of species interaction strengths, with implications for the stability of populations and communities. Temperature-dependent changes to antipredatory responses are an emerging mechanism of destabilization and thus there is a need to understand how prey species respond to predation pressures in the face of changing temperatures. Here, using ciliate protozoans, we assess whether temperature can alter the strength of phenotypic antipredator responses in a prey species and whether this relationship depends on the predator's hunting behavior. We exposed populations of the ciliate Paramecium caudatum to either (i) a sit-and-wait generalist predator (Homalozoon vermiculare) or (ii) a specialized active swimmer predator (Didinium nasutum) across two different temperature regimes (15 and 25°C) to quantify the temperature dependence of antipredator responses over a 24-h period. We utilized a novel high-throughput automated robotic monitoring system to track changes in the behavior (swimming speed) and morphology (cell size) of P. caudatum at frequencies and resolutions previously unachievable by manual sampling. The change in swimming speed through the 24 h differed between the two temperatures but was not altered by the presence of the predators. In contrast, P. caudatum showed a substantial temperature-dependent morphological response to the presence of D. nasutum (but not H. vermiculare), changing cell shape toward a more elongated morph at 15°C (but not at 25°C). Our findings suggest that temperature can have strong effects on prey morphological responses to predator presence, but that this response is potentially dependent on the predator's feeding strategy. This suggests that greater consideration of synergistic antipredator behavioral and physiological responses is required in species and communities subject to environmental changes.

The Structural Dynamics, Complexity of Interactions, and Functions in Cancer of Multi-SAM Containing Proteins.

SAM domains are crucial mediators of diverse interactions, including those important for tumorigenesis or metastasis of cancers, and thus SAM domains can be attractive targets for developing cancer therapies. This review aims to explore the literature, especially on the recent findings of the structural dynamics, regulation, and functions of SAM domains in proteins containing more than one SAM (multi-SAM containing proteins, MSCPs). The topics here include how intrinsic disorder of some SAMs and an additional SAM domain in MSCPs increase the complexity of their interactions and oligomerization arrangements. Many similarities exist among these MSCPs, including their effects on cancer cell adhesion, migration, and metastasis. In addition, they are all involved in some types of receptor-mediated signaling and neurology-related functions or diseases, although the specific receptors and functions vary. This review also provides a simple outline of methods for studying protein domains, which may help non-structural biologists to reach out and build new collaborations to study their favorite protein domains/regions. Overall, this review aims to provide representative examples of various scenarios that may provide clues to better understand the roles of SAM domains and MSCPs in cancer in general.

Corridor quality buffers extinction under extreme droughts in experimental metapopulations.

Corridors with good-quality habitats maintain the spatial dynamics of metapopulations by promoting dispersal between habitat patches, potentially buffering populations, and communities against continued global change. However, this function is threatened by habitats becoming increasingly fragmented, and habitat matrices becoming increasingly inhospitable, potentially reducing the resilience and persistence of populations. Yet, we lack a clear understanding of how reduced corridor quality interacts with rates of environmental change to destabilize populations. Using laboratory microcosms containing metapopulations of the Collembola Folsomia candida, we investigate the impact of corridor quality on metapopulation persistence under a range of simulated droughts, a key stressor for this species. We manipulated both drought severity and the number of patches affected by drought across landscapes connected by either good- or poor-quality corridors. We measured the time of metapopulation extinction, the maximum rate of metapopulation decline, and the variability of abundance among patches as criteria to evaluate the persistence ability of metapopulations. We show that while drought severity negatively influenced the time of metapopulation extinction and the increase in drought patches caused metapopulation decline, these results were mitigated by good-quality corridors, which increased metapopulation persistence time and decreased both how fast metapopulations declined and the interpatch variability in abundances. Our results suggest that enhancing corridor quality can increase the persistence of metapopulations, increasing the time available for conservation actions to take effect, and/or for species to adapt or move in the face of continued stress. Given that fragmentation increases the isolation of habitats, improving the quality of habitat corridors may provide a useful strategy to enhance the resistance of spatially structured populations.

Solution NMR backbone assignment of the SASH1 SLy proteins associated disordered region (SPIDER).

SASH1 is a scaffold protein with context-dependent biological functions in cell adhesion, tumor metastasis, lung development, and pigmentation. As a member of the SLy protein family, it contains the conserved SLY, SH3, and SAM domains. The 19 kDa SLY domain harbors over 70% of the SASH1 variants associated with pigmentation disorders. However, its solution structure or dynamics have not been investigated yet, and its exact position in the sequence is not clearly defined. Based on the bioinformatic and experimental evidence, we propose renaming this region to the SLy Proteins Associated Disordered Region (SPIDER) and defining the exact position to be amino acids 400-554 of SASH1. We have previously identified a variant in this region linked to a pigmentation disorder, S519N. Here, we used a novel deuteration technique, a suite of TROSY-based 3D NMR experiments, and a high-quality HNN to obtain near complete solution backbone assignment of SASH1's SPIDER. A comparison with the chemical shifts of non-variant (S519) SPIDER shows that the S519N substitution does not alter the free form solution structural propensities of SPIDER. This assignment is the first step to characterize the role of SPIDER in SASH1-mediated cellular functions and provides a model for the future study of sister SPIDER domains in the SLy protein family.

A predictive timeline of wildlife population collapse.

Contemporary rates of biodiversity decline emphasize the need for reliable ecological forecasting, but current methods vary in their ability to predict the declines of real-world populations. Acknowledging that stressor effects start at the individual level, and that it is the sum of these individual-level effects that drives populations to collapse, shifts the focus of predictive ecology away from using predominantly abundance data. Doing so opens new opportunities to develop predictive frameworks that utilize increasingly available multi-dimensional data, which have previously been overlooked for ecological forecasting. Here, we propose that stressed populations will exhibit a predictable sequence of observable changes through time: changes in individuals' behaviour will occur as the first sign of increasing stress, followed by changes in fitness-related morphological traits, shifts in the dynamics (for example, birth rates) of populations and finally abundance declines. We discuss how monitoring the sequential appearance of these signals may allow us to discern whether a population is increasingly at risk of collapse, or is adapting in the face of environmental change, providing a conceptual framework to develop new forecasting methods that combine multi-dimensional (for example, behaviour, morphology, life history and abundance) data.

Planktonic functional diversity changes in synchrony with lake ecosystem state.

Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional diversity (FD) appears as a sensitive and viable monitoring metric stemming from suggestions that FD is a universally important measure of biodiversity and has a mechanistic influence on ecological processes. It is however unclear whether changes in FD consistently occur prior to state responses or vice versa, with no current work on the temporal relationship between FD and state to support a transition towards trait-based indicators. There is consequently a knowledge gap regarding when functioning changes relative to biodiversity change and where FD change falls in that sequence. We therefore examine the lagged relationship between planktonic FD and abundance-based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and cutting edge non-linear empirical dynamic modelling approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. These results highlight the power of empirical dynamic modelling in disentangling time lagged relationships in complex multivariate ecosystems, but suggest that FD cannot be generically viable as an early indicator. Individual lakes therefore require consideration of their specific context and any interpretation of FD across systems requires caution. However, FD still retains value as an alternative state measure or a trait representation of biodiversity when considered at the system level.

Spatiotemporal thermal variation drives diversity trends in experimental landscapes.

Temperature is a fundamental driver of species' vital rates and thus coexistence, extinctions and community composition. While temperature is neither static in space nor in time, little work has incorporated spatiotemporal dynamics into community-level investigations of thermal variation. We conducted a microcosm experiment using ciliate protozoa to test the effects of temperatures fluctuating synchronously or asynchronously on communities in two-patch landscapes connected by short or long corridors. We monitored the abundance of each species for 4 weeks-equivalent to ~28 generations-measuring the effects of four temperature regimes and two corridor lengths on community diversity and composition. While corridor length significantly altered the trajectory of diversity change in the communities, this did not result in different community structures at the end of the experiment. The type of thermal variation significantly affected both the temporal dynamics of diversity change and final community composition, with synchronous fluctuation causing deterministic extinctions that were consistent across replicates and spatial variation causing the greatest diversity declines. Our results suggest that the presence and type of thermal variation can play an important role in structuring ecological communities, especially when it interacts with dispersal between habitat patches.

SAM1 domain of SASH1 harbors distinctive structural heterogeneity.

The sterile alpha motif (SAM) domains are among the most versatile protein domains in biology, and the variety of the oligomerization states contribute to their diverse roles in many diseases. A better understanding of the structure and dynamics of various SAM domains will provide a scientific basis for drug development targeting them. Here, we used SEC-MALS, HPLC, NMR, and other biophysical techniques to characterize the structural features and dynamics of the SAM1 domain in SASH1. SASH1 is a scaffold protein belonging to the same family as SASH3. Unlike the dimerization seen in SASH3's SAM domain, our SEC-MALS and SE-HPLC showed that SAM1 exists primarily as a less compact monomer with a minor oligomer. NMR assignment, relaxation, and exchange experiments revealed the presence of both a disordered monomer and a more structured oligomer with multiple timescale exchange regimes in solution. Mutagenesis and SE-HPLC showed that D663A/T664K substitutions in SAM1 increased its oligomerization. In sum, this study is the first to characterize a disordered structure for a SAM domain, provides additional evidence and framework for the diversity of SAM domains, and identifies a region in SAM1 as a potential starting point to further characterize the structural mechanism of oligomerization of the domain.

Towards the fully automated monitoring of ecological communities.

High-resolution monitoring is fundamental to understand ecosystems dynamics in an era of global change and biodiversity declines. While real-time and automated monitoring of abiotic components has been possible for some time, monitoring biotic components-for example, individual behaviours and traits, and species abundance and distribution-is far more challenging. Recent technological advancements offer potential solutions to achieve this through: (i) increasingly affordable high-throughput recording hardware, which can collect rich multidimensional data, and (ii) increasingly accessible artificial intelligence approaches, which can extract ecological knowledge from large datasets. However, automating the monitoring of facets of ecological communities via such technologies has primarily been achieved at low spatiotemporal resolutions within limited steps of the monitoring workflow. Here, we review existing technologies for data recording and processing that enable automated monitoring of ecological communities. We then present novel frameworks that combine such technologies, forming fully automated pipelines to detect, track, classify and count multiple species, and record behavioural and morphological traits, at resolutions which have previously been impossible to achieve. Based on these rapidly developing technologies, we illustrate a solution to one of the greatest challenges in ecology: the ability to rapidly generate high-resolution, multidimensional and standardised data across complex ecologies.

Community structure determines the predictability of population collapse.

Early warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Although a growing body of work has shown the utility of EWS based on either statistics derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations. However, to predict reliably the future state of ecological systems, which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical. Here, reconciling quantitative trait evolution and Lotka-Volterra equations, which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi-trophic predator-prey communities. Using these simulations and warning signals derived from both population- and community-level data, we showed the utility of abundance-based EWS, as well as metrics derived from stability-landscape theory (e.g. width and depth of the basin of attraction), were fundamentally linked. Thus, the depth and width of such stability-landscape curves could be used to identify which species should exhibit the strongest EWS of collapse. The probability a species displays both trait and abundance-based EWS was dependent on its position in a community, with some species able to act as indicator species. In addition, our results also demonstrated that in general trait-based EWS were less reliable in comparison with abundance-based EWS in forecasting species collapses in our simulated communities. Furthermore, community-level abundance-based EWS were fairly reliable in comparison with their species-level counterparts in forecasting species-level collapses. Our study suggests a holistic framework that combines abundance-based EWS and metrics derived from stability-landscape theory that may help in forecasting species loss in a community context.

Landscape configuration affects probability of apex predator presence and community structure in experimental metacommunities.

Biodiversity is declining at an unprecedented rate, highlighting the urgent requirement for well-designed protected areas. Design tactics previously proposed to promote biodiversity include enhancing the number, connectivity, and heterogeneity of reserve patches. However, how the importance of these features changes depending on what the conservation objective is remains poorly understood. Here we use experimental landscapes containing ciliate protozoa to investigate how the number and heterogeneity in size of habitat patches, rates of dispersal between neighbouring patches, and mortality risk of dispersal across the non-habitat 'matrix' interact to affect a number of diversity measures. We show that increasing the number of patches significantly increases γ diversity and reduces the overall number of extinctions, whilst landscapes with heterogeneous patch sizes have significantly higher γ diversity than those with homogeneous patch sizes. Furthermore, the responses of predators depended on their feeding specialism, with generalist predator presence being highest in a single large patch, whilst specialist predator presence was highest in several-small patches with matrix dispersal. Our evidence emphasises the importance of considering multiple diversity measures to disentangle community responses to patch configuration.

Machine learning methods trained on simple models can predict critical transitions in complex natural systems.

Forecasting sudden changes in complex systems is a critical but challenging task, with previously developed methods varying widely in their reliability. Here we develop a novel detection method, using simple theoretical models to train a deep neural network to detect critical transitions-the Early Warning Signal Network (EWSNet). We then demonstrate that this network, trained on simulated data, can reliably predict observed real-world transitions in systems ranging from rapid climatic change to the collapse of ecological populations. Importantly, our model appears to capture latent properties in time series missed by previous warning signals approaches, allowing us to not only detect if a transition is approaching, but critically whether the collapse will be catastrophic or non-catastrophic. These novel properties mean EWSNet has the potential to serve as an indicator of transitions across a broad spectrum of complex systems, without requiring information on the structure of the system being monitored. Our work highlights the practicality of deep learning for addressing further questions pertaining to ecosystem collapse and has much broader management implications.

Global patterns of resilience decline in vertebrate populations.

Maintaining the resilience of natural populations, their ability to resist and recover from disturbance, is crucial to prevent biodiversity loss. However, the lack of appropriate data and quantitative tools has hampered our understanding of the factors determining resilience on a global scale. Here, we quantified the temporal trends of two key components of resilience-resistance and recovery-in >2000 population time-series of >1000 vertebrate species globally. We show that the number of threats to which a population is exposed is the main driver of resilience decline in vertebrate populations. Such declines are driven by a non-uniform loss of different components of resilience (i.e. resistance and recovery). Increased anthropogenic threats accelerating resilience loss through a decline in the recovery ability-but not resistance-of vertebrate populations. These findings suggest we may be underestimating the impacts of global change, highlighting the need to account for the multiple components of resilience in global biodiversity assessments.

Early warning signal reliability varies with COVID-19 waves.

Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the emergence of disease outbreaks, offering hope that policymakers can make predictive rather than reactive management decisions. Here, using a novel, sequential analysis in combination with daily COVID-19 case data across 24 countries, we suggest that composite EWSs consisting of variance, autocorrelation and skewness can predict nonlinear case increases, but that the predictive ability of these tools varies between waves based upon the degree of critical slowing down present. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policymakers to improve the accuracy of urgent intervention decisions but best characterize hypothesized critical transitions.

Scaling the extinction vortex: Body size as a predictor of population dynamics close to extinction events.

Mutual reinforcement between abiotic and biotic factors can drive small populations into a catastrophic downward spiral to extinction-a process known as the "extinction vortex." However, empirical studies investigating extinction dynamics in relation to species' traits have been lacking.We assembled a database of 35 vertebrate populations monitored to extirpation over a period of at least ten years, represented by 32 different species, including 25 birds, five mammals, and two reptiles. We supplemented these population time series with species-specific mean adult body size to investigate whether this key intrinsic trait affects the dynamics of populations declining toward extinction.We performed three analyses to quantify the effects of adult body size on three characteristics of population dynamics: time to extinction, population growth rate, and residual variability in population growth rate.Our results provide support for the existence of extinction vortex dynamics in extirpated populations. We show that populations typically decline nonlinearly to extinction, while both the rate of population decline and variability in population growth rate increase as extinction is approached. Our results also suggest that smaller-bodied species are particularly prone to the extinction vortex, with larger increases in rates of population decline and population growth rate variability when compared to larger-bodied species.Our results reaffirm and extend our understanding of extinction dynamics in real-life extirpated populations. In particular, we suggest that smaller-bodied species may be at greater risk of rapid collapse to extinction than larger-bodied species, and thus, management of smaller-bodied species should focus on maintaining higher population abundances as a priority.