Biology subjects

Fink, D.

Publications and source records attributed to Fink, D..

15 recordsLinked to original sources

bioRxiv2026

NLRP3 activators disrupt the endocytic AP2 complex and plasma membrane signaling

Organellar perturbations are linked to NLRP3 inflammasome activation, however, it remains unclear whether unrelated agonists converge on a common upstream pathway. Here, we traced intracellular organelle and protein movements by differential ultracentrifugation combined with mass spectrometry-based proteomics. We show that NLRP3 activators uniformly disrupt the endocytic Adaptor Protein 2 (AP2) complex, whereas other subcellular rearrangements are stimulus-specific. We discovered Dynasore as a K-efflux-independent NLRP3 activator that engages this signaling node irrespective of endocytosis inhibition. Pharmacological and genetic perturbation of AP2 renders cells unresponsive to extracellular cues, blunting GPCR signaling, cAMP production, and chemotaxis, thereby enforcing a frozen signaling state that propagates NLRP3 inflammasome activation. Collectively, our study reveals a common surveillance checkpoint linking impaired plasma membrane signaling to the execution of inflammation and cell death. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/707400v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@178eb1dorg.highwire.dtl.DTLVardef@193cb02org.highwire.dtl.DTLVardef@1f50080org.highwire.dtl.DTLVardef@1f3e3e4_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Population-level migration modeling of North American birds through data integration with BirdFlow

BackgroundAccurate information on population-level movements of migratory animals is essential for understanding migration and for designing effective conservation strategies in a changing world. Yet such information remains scarce for most migratory species due to the effort and expense needed to collect data across their full distribution ranges. BirdFlow is a probabilistic modeling framework that infers population-level movements from weekly species distribution maps produced by the participatory science project eBird. However, BirdFlow models have only been tuned for a handful of species using high-resolution individual tracking data, which is not available for most migratory species. MethodsHere, we introduce a general tuning and evaluation framework for BirdFlow that enables the first large-scale integration of distributional and individual-level data to infer animal movement across continents and hundreds of migratory species, eliminating reliance on any single individual-tracking data source. By generalizing the BirdFlow model parametrization, we enable tuning and validation using multiple complementary data sources, including GPS tracks, banding recoveries, and radio telemetry data from the Motus Wildlife Tracking System. We investigate the efficacy of this approach by (1) investigating predictive performance compared to null models; (2) validating the biological plausibility of BirdFlow models by comparing movement properties such as route straightness, number of stopovers, and migration speed between model-generated routes and real movement tracks; and (3) comparing the performance of models tuned on species-specific movement data to models tuned using hyperparameters transferred from other species. ResultsOur results show that BirdFlow models produced by the new tuning framework achieve biologically realistic performance, even for prediction horizons of thousands of kilometers and several months. When species-specific data are unavailable, models can still be tuned using data from other phylogenetically adjacent species to achieve improved performance. ConclusionsBy integrating eBird Status & Trends abundance surfaces with data from banding recaptures, radio telemetry, and GPS tracking, we scale BirdFlow model to 153 North American migratory species, representing the first collection of continental-scale population-level movement and forecasting models. Species-specific tuning improves population-level movement forecasts, while taxonomically informed hyperparameter transfer supports the modeling of data-limited species. Overall, our work offers a foundation for more accurate predictions across hundreds of species for research in ecology and conservation, disease surveillance, aviation, and public outreach.

ecology↗

bioRxiv2024

Elovl1 inhibition reduced very long chain fatty acids in a mouse model of adrenoleukodystrophy

Adrenoleukodystrophy (ALD) is a rare neurometabolic disease caused by mutations in the ABCD1 gene, which encodes for the peroxisomal very long chain fatty acid (VLCFAs) transporter. It is a debilitating disorder, which has a spectrum of clinical presentations. The most severe form is a rapidly progressing demyelinating disease called cerebral ALD or CALD. Patients with cALD have a life expectancy of 2-4 years after onset and symptoms often manifest in childhood. The other forms are adrenomyeloneuropathy or AMN, which is a slower progressing degeneration of the spinal cord, and adrenal insufficiency (Addison disease). Since the accumulation of VLCFAs are a common factor in all ALD pathologies, we identified therapeutic approach that could correct this metabolic defect. We developed a substrate reduction therapy (SRT) for ALD in the form of an inhibitor of the lipid elongase principally responsible for the generation of VLCFAs, Elovl1. This small molecule was able to successfully reduce the accumulation of VLCFA in the brain and spinal cord of ABCD1-/y mice. We used single nuclei RNA seq to identify the pathways altered in the ABCD1-/y mouse and corrected with Elovl1 inhibition. Though many lipid metabolism genes and pathways were indeed corrected, treatment with the Elovl1 inhibitor unexpectedly led to profound transcriptional changes beyond correction of pathways altered by loss of ABCD1. These data suggest that Elovl1 inhibition may have broader consequences in ABCD1-/y mice than correction of lipid homeostasis.

pharmacology and toxicology↗

bioRxiv2024

Preservation of memory B cell homeostasis in an individual producing broadly neutralising antibodies against HIV-1

Immunological determinants favouring emergence of broadly neutralising antibodies are crucial to the development of HIV-1 vaccination strategies. Here, we combined RNAseq and B cell cloning approaches to isolate a broadly neutralising antibody (bnAb) ELC07 from an individual living with untreated HIV-1. Using single particle cryogenic electron microscopy (cryo-EM), we show that the antibody recognises a conformational epitope at the gp120-gp41 interface. ELC07 binds the closed state of the viral glycoprotein causing considerable perturbations to the gp41 trimer core structure. Phenotypic analysis of memory B cell subsets from the ELC07 bnAb donor revealed a lack of expected HIV-1-associated dysfunction, specifically no increase in CD21-/CD27- cells was observed whilst the resting memory (CD21+/CD27+) population appeared preserved despite uncontrolled HIV-1 viraemia. Moreover, single cell transcriptomes of memory B cells from this bnAb donor showed a resting memory phenotype irrespective of the epitope they targeted or their ability to neutralise diverse strains of HIV-1. Strikingly, single memory B cells from the ELC07 bnAb donor were transcriptionally similar to memory B cells from HIV-negative individuals. Our results demonstrate that potent bnAbs can arise without the HIV-1-induced dysregulation of the memory B cell compartment and suggest that sufficient levels of antigenic stimulation with a strategically designed immunogen could be effective in HIV-negative vaccine recipients.

microbiology↗

bioRxiv2023

Spatial and seasonal variation in thermal sensitivity within North American bird species

Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity (non-stationarity) given adaptation to local and seasonal environments. Non-stationarity carries important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 20 bird species. Across their ranges, most birds demonstrated spatial and seasonal variation in both thermal optimum and breadth, or the temperature and range of temperatures of peak occurrence. Some birds demonstrated constant thermal optima or breadths (stationarity) while others varied according to local and current environmental conditions (non-stationarity). Across species, birds typically invested in either geographic or seasonal adaptation to climate. Intraspecific variation in thermal sensitivity is likely an important but neglected aspect of organismal responses to climate change.

ecology↗

bioRxiv2022

BirdFlow: Learning Seasonal Bird Movements from Citizen Science Data

Large-scale monitoring of seasonal animal movement is integral to science, conservation, and outreach. However, gathering representative movement data across entire species ranges is frequently intractable. Citizen science databases collect millions of animal observations throughout the year, but it is challenging to infer individual movement behavior solely from observational data. We present BO_SCPLOWIRDC_SCPLOWFO_SCPLOWLOWC_SCPLOW, a probabilistic modeling framework that draws on citizen science data from the eBird database to model the population flows of migratory birds. We apply the model to 11 species of North American birds, using GPS and satellite tracking data to tune and evaluate model performance. We show that BO_SCPLOWIRDC_SCPLOWFO_SCPLOWLOWC_SCPLOW models can accurately infer individual seasonal movement behavior directly from eBird relative abundance estimates. Supplementing the model with a sample of tracking data from wild birds improves performance. Researchers can extract a number of behavioral inferences from model results, including migration routes, timing, connectivity, and forecasts. The BO_SCPLOWIRDC_SCPLOWFO_SCPLOWLOWC_SCPLOW framework has the potential to advance migration ecology research, boost insights gained from direct tracking studies, and serve a number of applied functions in conservation, disease surveillance, aviation, and public outreach.

ecology↗

bioRxiv2021

The CIP2A-TOPBP1 complex safeguards chromosomal stability during mitosis

The accurate repair of DNA double-strand breaks (DSBs), highly toxic DNA lesions, is crucial for genome integrity and is tightly regulated during the cell cycle. In mitosis, cells inactivate DSB repair in favor of a tethering mechanism that stabilizes broken chromosomes until they are repaired in the subsequent cell cycle phases. How this is achieved mechanistically is not yet understood, but the adaptor protein TOPBP1 is critically implicated in this process. Here, we identify CIP2A as a TOPBP1-interacting protein that regulates TOPBP1 localization specifically in mitosis. Cells lacking CIP2A display increased micronuclei formation, DSB repair defects and chromosomal instability. CIP2A is actively exported from the cell nucleus in interphase but, upon nuclear envelope breakdown at the onset of mitosis, gains access to chromatin where it forms a complex with MDC1 and TOPBP1 to promote TOPBP1 recruitment to sites of mitotic DSBs. Collectively, our data uncover CIP2A-TOPBP1 as a mitosis-specific genome maintenance complex.

cell biology↗

bioRxiv2020

HIV-1 Vpr antagonizes cGAS sensing by targeting karyopherin-mediated NF-κB/IRF3 nuclear transport

HIV-1 must replicate in cells that are equipped to defend themselves from infection through intracellular innate immune systems. HIV-1 evades innate immune sensing through encapsidated DNA synthesis and encodes accessory genes that antagonize specific antiviral effectors. Here we show that both particle associated, and expressed HIV-1 Vpr, antagonize the stimulatory effect of a variety of pathogen associated molecular patterns by inhibiting IRF3 and NF-κB nuclear transport. Phosphorylation of IRF3 at S396, but not S386, was also inhibited. We propose that, rather than promoting HIV-1 nuclear import, Vpr interacts with karyopherins to disturb their import of IRF3 and NF-κB to promote replication in macrophages. Concordantly, we demonstrate Vpr dependent rescue of HIV-1 replication in human macrophages from inhibition by cGAMP, the product of activated cGAS. We propose a model that unifies Vpr manipulation of nuclear import and inhibition of innate immune activation to promote HIV-1 replication and transmission.Competing Interest StatementThe authors have declared no competing interest.View Full Text

microbiology↗

bioRxiv2019

Integrating citizen science data with expert surveys improves the accuracy and range of inference of species distribution models

Information on species habitat associations and distributions, across a wide range of spatial and temporal scales, are a fundamental source of ecological knowledge. However, collecting biological information at relevant scales if often cost prohibitive, although it is essential for framing the broader context of more focused research and conservation efforts. Citizen-science data has been signaled as an increasingly important source of biological information needed to fill in data gaps needed to make more comprehensive and robust inferences on species distributions. However, there are perceived trade-offs of combining highly structured, scientific survey data with largely unstructured, citizen-science data. As a result, the focus of most methodological advances to combine these sources of information has been on treating these sources as independent. The degree to which each source of information is allowed to directly inform a common underlying process (e.g. species distribution) depends on the perceived quality of the data. In this paper, we explore these trade-offs by applying a simplified approach of filtering citizen-science data to resemble structured survey data, and analyze both sources of data under a common framework. To accomplish this, we explored ways of integrating high-resolution survey data on shorebirds in the northern Central Valley of California with observations in eBird for the entire region that were filtered to improve their quality. The integration of survey data with the filtered citizen-science data in eBird resulted in improved inference and predictive ability, and increased the extent and accuracy of inferences on shorebirds for the Central Valley. The structured surveys were found to improve the overall accuracy of ecological inference based only on citizen-science data, by increasing the representation of data collected from high quality habitats for shorebirds (e.g. rice fields). The practical approach we have shown for data integration can be also be used to improve the efficiency of designing biological surveys in the context of larger, citizen-science monitoring efforts, ultimately reducing the financial and time expenditures typically required of monitoring programs and focused research. The simple processing and filtering method we present can be used to integrate other types of data (e.g. camera traps) with more localized efforts (e.g. research projects), ultimately improving our ecological knowledge on the distribution and habitat associations of species of conservation concern worldwide.

ecology↗

bioRxiv2019

Best practices for making reliable inferences from citizen science data: case study using eBird to estimate species distributions

Citizen science data are valuable for addressing a wide range of ecological research questions, and there has been a rapid increase in the scope and volume of data available. However, data from large-scale citizen science projects typically present a number of challenges that can inhibit robust ecological inferences. These challenges include: species bias, spatial bias, and variation in effort. To demonstrate addressing key challenges in analysing citizen science data, we use the example of estimating species distributions with data from eBird, a large semi-structured citizen science project. We estimate two widely applied metrics of species distributions: encounter rate and occupancy probability. For each metric, we assess the impact of data processing steps that either degrade or refine the data used in the analyses. We also test whether differences in model performance are maintained at different sample sizes. Model performance improved when data processing and analytical methods addressed the challenges arising from citizen science data. The largest gains in model performance were achieved with: 1) the use of complete checklists (where observers report all the species they detect and identify); and 2) the use of covariates describing variation in effort and detectability for each checklist. Occupancy models were more robust to a lack of complete checklists and effort variables. Improvements in model performance with data refinement were more evident with larger sample sizes. Here, we describe processes to refine semi-structured citizen science data to estimate species distributions. We demonstrate the value of complete checklists, which can inform the design and adaptation of citizen science projects. We also demonstrate the value of information on effort. The methods we have outlined are also likely to improve other forms of inference, and will enable researchers to conduct robust analyses and harness the vast ecological knowledge that exists within citizen science data.

ecology↗

bioRxiv2018

MRI-related anxiety in healthy individuals, intrinsic BOLD oscillations at 0.1 Hz and heart rate variability in low frequency bands

Participation in a MRI scan is associated with increased anxiety, thus possibly impacting baseline recording for functional MRI studies. We investigated in 23 healthy individuals without any former MRI experience (scanner-naive) the relations between anxiety, 0.1-Hz BOLD oscillations and heart rate variability (HRV) in two separate resting state sessions (R1, R2). BOLD signals were recorded from precentral gyrus (PCG) and insula in both hemispheres. Phase-locking and time delays were computed in the frequency band 0.07-0.13 Hz. Positive (pTD) and negative time delays (nTD) were found. The pTD characterize descending neural BOLD oscillations spreading from PCG to insula and nTD characterize ascending vascular BOLD oscillations related to blood flow in the middle cerebral artery. HRV power in two low frequency bands 0.06-0.1 Hz and 0.1-0.14 Hz was computed. Based on the drop rate of the anxiety level from R1 to R2, two groups could be identified: one with a strong anxiety decline (large drop group) and one with a moderate decline or even anxiety increase (small drop group). A significant correlation was found only between the left-hemispheric time delay (pTD, nTD) of BOLD oscillations and anxiety drop, with a dominance of nTD in the large drop group. The analysis of within-scanner HRV revealed a pronounced increase of low frequency power between both resting states, dominant in the band 0.06-0.1 Hz in the large drop group and in the band 0.1-0.14 Hz in the small drop group. These results suggest different mechanisms related to anxiety processing in healthy individuals. One mechanism (large drop group) could embrace an increase of blood circulation in the territory of the left middle cerebral artery (vascular BOLD) and another (small drop group) translates to rhythmic central commands (neural BOLD) in the frequency band 0.1-0.14 Hz.

neuroscience↗

bioRxiv2018

Finding the signal in the noise of Citizen Science Observations

While many observations of species are being collected by citizen science projects worldwide, it can be challenging to identify projects collecting data that effectively monitor biodiversity. Over the past several years the allure of taking a \"Big Data\" approach has provided the opportunity to gather massive quantities of observations via the Internet, too often with insufficient information to describe how the observations were made. Information about species populations -- where and when they occur and how many of them are there -- (i.e., the signal) can be lost because insufficient information is gathered to account for the inherent biases in data collection (i.e., the noise). Here we suggest that citizen science projects that have succeeded in motivating large numbers of participants, must consider factors that influence the ecological process that affect species populations as well as the observation process that determines how observations are made. Those citizen science projects that collect sufficient contextual information describing the observation process can be used to generate increasingly accurate information about the distribution and abundance of organisms. We illustrate this using eBird as a case study, describing how this citizen science platform is able to collect vital contextual information on the observation process while maintaining a broad global constituency of participants. We highlight how eBird provides information with which to generate biodiversity indicators -- specifically distribution, abundance, and habitat associations -- across the entire annual cycle, even for populations of long distance migratory birds, a highly challenging taxon.

ecology↗

bioRxiv2018

Using citizen science data in integrated population models to inform conservation decision-making

Analysis of animal population status and change are core elements of ecological research and critical for prioritizing conservation actions. Traditionally, count-based data from structured surveys have been the main source of information used to estimate trends and changes in populations. In the past decade, advances in integrated population models (IPMs) have allowed these data to be combined with other data sources (e.g., observations of marked individuals). IPMs have allowed researchers to determine the direction and magnitude of a species population trajectory and to test underlying mechanisms. For many species, life-history characteristics (e.g., low site-fidelity), low abundance and/or low detection probability make it difficult to collect sufficient data; thus, IPMs for these species are difficult to employ. We used count data from eBird to estimate population trends for one such species, the tricolored blackbird (Agelaius tricolor). We combined estimates of relative abundance with banding and nesting data. Our joint estimation of demographic rates allowed us to evaluate their individual contributions to the population growth rate. We suggest that investments in increasing reproductive success and recruitment are the most likely conservation strategies to increase the population. The extensive survey efforts of citizen scientists aided the employment of IPMs to inform conservation efforts.\n\nData AccessibilityShould the manuscript be accepted, the data supporting the results will be published along with the manuscript. The eBird data used for analyses in this manuscript may be downloaded from https://ebird.org/data/download.

ecology↗

bioRxiv2018

Optimizing conservation of migratory species over their full annual cycle in the Western Hemisphere

Limited knowledge of the distribution, abundance, and habitat associations of migratory species introduces uncertainty about the most effective conservation actions. We used Neotropical migratory birds as a model group to evaluate contrasting approaches to land prioritization to support [≥]30% of the global abundances of 117 species throughout the annual cycle in the Western hemisphere. Conservation targets were achieved in 43% less land area in plans based on annual vs. weekly optimizations. Plans agnostic to population structure required comparatively less land area to meet targets, but at the expense of representation. Less land area was also needed to meet conservation targets when human-dominated lands were included rather than excluded from solutions. Our results point to key trade-offs between efforts minimizing the opportunity costs of conservation vs. those ensuring spatiotemporal representation of populations, and demonstrate a novel approach to the conservation of migratory species based on leading-edge abundance models and linear programming to identify portfolios of priority landscapes and inform conservation planners.

ecology↗

bioRxiv2018

Modeling Avian Full Annual Cycle Distribution and Population Trends with Citizen Science Data

Information on species distributions and abundances, and how these change over time are central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at relevant scales across range-wide extents for two main reasons. First, local and regional processes that affect populations vary throughout the year and across species ranges, requiring fine-scale, year-round information across broad -- sometimes hemispheric -- spatial extents. Second, while citizen science projects can collect data at these scales, using these data requires appropriate analysis to address known sources of bias. Here we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long-distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and relative abundance with enough spatiotemporal resolution to support inference across a range of spatial scales throughout the annual cycle. Additionally, we generate intra-annual estimates of the range, intra-annual estimates of the associations between species and the local environment, and inter-annual trends in relative abundance. This is the first example of an analysis to capture intra- and inter-annual distributional dynamics across the entire range of a broadly distributed, highly mobile species.

ecology↗