Biology subjects
Publications and source records attributed to Allen, A..
Withdrawal StatementThe authors discovered an error in the primary analysis and have withdrawn the results from this version of the investigation.
Excessive alcohol use is thought to increase the risk of respiratory infections by impairing mucociliary clearance (MCC). In this study, we investigate the hypothesis that alcohol reduces the function of CFTR, the protein that is defective in individuals with cystic fibrosis, thus altering mucus properties to impair MCC and the airways defense against inhaled pathogens. MethodsSprague Dawley rats with wild type CFTR (+/+), matched for age and sex, were administered either a Lieber-DeCarli alcohol diet or a control diet with the same number of calories for eight weeks. CFTR activity was measured using nasal potential difference (NPD) assay and Ussing chamber electrophysiology of tracheal tissue samples. In vivo MCC was determined by measuring the radiographic clearance of inhaled Tc99 particles and the depth of the airway periciliary liquid (PCL) and mucus transport rate in excised trachea using micro-optical coherence tomography ({micro}OCT). The levels of rat lung MUC5b and CFTR were estimated by protein and mRNA analysis. ResultsAlcohol diet was found to decrease CFTR ion transport in the nasal and tracheal epithelium in vivo and ex vivo. This decrease in activity was also reflected in partially reduced full-length CFTR protein levels but not, in mRNA copies, in the lungs of rats. Furthermore, alcohol-fed rats showed a significant decrease in MCC after 8 weeks of alcohol consumption. The trachea from these rats also showed reduced PCL depth, indicating a decrease in mucosal surface hydration that was reflected in delayed mucus transport. Diminished MCC rate was also likely due to the elevated MUC5b expression in alcohol-fed rat lungs. ConclusionsExcessive alcohol use can decrease the expression and activity of CFTR channels, leading to reduced airway surface hydration and impaired mucus clearance. This suggests that CFTR dysfunction plays a role in the compromised lung defense against respiratory pathogens in individuals who drink alcohol excessively. What is the current scientific knowledge on this subject?Excessive alcohol is associated with delayed mucociliary clearance (MCC) and an increased risk of respiratory infections among heavy drinkers. What does this study add to the field?Chronic alcohol use reduces CFTR activity and airway surface hydration explaining the mechanisms underlying mucociliary dysfunction. Acquired CFTR dysfunction may be a suitable target to improve host immunity in those affected by prolonged alcohol use.
CRISPR-associated proteins such as Cas9 and Cas12a are programable RNA-guided nucleases that have emerged as powerful tools for genome manipulation and molecular diagnostics. However, these enzymes are prone to cleaving off-target sequences that contain mismatches between the RNA guide and DNA protospacer. In comparison to Cas9, Cas12a has demonstrated distinct sensitivity to protospacer-adjacent-motif (PAM) distal mismatches, and the molecular basis of Cas12as enhanced target discrimination is of great interest. In this study, we investigated the mechanism of Cas12a target recognition using a combination of site-directed spin labeling, fluorescent spectroscopy, and enzyme kinetics. With a fully matched RNA guide, the data revealed an inherent equilibrium between a DNA unwound state and a DNA-paired duplex-like state. Experiments with off-target RNA guides and pre-nicked DNA substrates identified the PAM-distal DNA unwinding equilibrium as a mismatch sensing checkpoint prior to the first step of DNA cleavage. The data sheds light on the distinct targeting mechanism of Cas12a and may better inform CRISPR based biotechnology developments.
Rare variants (RVs) genetic association studies enable researchers to uncover the variation in phenotypic traits left unexplained by common variation. Traditional single-variant analysis lacks power; thus, researchers have developed various methods to aggregate the effects of RVs across genomic regions to study their collective impact. Some existing methods utilize a static delineation of genomic regions, often resulting in suboptimal effect aggregation, as neutral subregions within the test region will result in an attenuation of signal. Other methods use varying windows to search for signals but often result in long regions containing many neutral RVs. To pinpoint short genomic regions enriched for disease-associated RVs, we developed a novel method, DYNATE (DYNamic Aggregation TEsting). DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones and performs multiple testing for disease associations with controlled weighted false discovery rate. Extensive numerical simulations demonstrate the superior performance of DYNATE under various scenarios compared to existing methods. Importantly, DYNATE-identified regions have higher enrichment levels of disease-associated RVs. We applied DYNATE to an amyotrophic lateral sclerosis (ALS) study and identified a new gene, EPG5, harboringpossibly pathogenic mutations.
The small molecule erastin inhibits the cystine-glutamate antiporter, system xc-, which leads to intracellular cysteine and glutathione depletion. This can cause ferroptosis, which is an oxidative cell death process characterized by uncontrolled lipid peroxidation. Erastin and other ferroptosis inducers have been shown to affect metabolism but the metabolic effects of these drugs have not been systematically studied. To this end, we investigated how erastin impacts global metabolism in cultured cells and compared this metabolic profile to that caused by the ferroptosis inducer RSL3 or in-vivo cysteine deprivation. Common among the metabolic profiles were alterations in nucleotide and central carbon metabolism. Supplementing nucleosides to cysteine-deprived cells rescued cell proliferation in certain contexts, showing that these alterations to nucleotide metabolism can affect cellular fitness. While GPX4 inhibition caused a similar metabolic profile as cysteine deprivation, nucleoside treatment did not rescue cell viability or proliferation under RSL3 treatment, suggesting that these metabolic changes have varying importance in different scenarios of ferroptosis. Together, our study shows how global metabolism is affected during ferroptosis, and points to nucleotide metabolism as an important target of cysteine deprivation.
We explore the improvement of energy-based protein binder design using deep learning. We find that using AlphaFold2 or RoseTTAFold to assess the probability that a designed sequence adopts the designed monomer structure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. We find further that sequence design using ProteinMPNN rather than Rosetta considerably increases computational efficiency.
HIV integrase (IN) inserts viral DNA into the host genome and is the target of the strand transfer inhibitors (STIs), a class of small molecules currently in clinical use. Another potent class of antivirals is the allosteric inhibitors of integrase, or ALLINIs. ALLINIs promote IN aggregation by stabilizing an interaction between the catalytic core domain (CCD) and carboxy -terminal domain (CTD) that undermines viral particle formation in late replication. Ongoing challenges with inhibitor potency, toxicity, and viral resistance motivate research to understand their mechanism. Here, we report a 2.93 [A] X-ray crystal structure of the minimal ternary complex between CCD, CTD, and the ALLINI BI-224436. This structure reveals an asymmetric ternary complex with a prominent network of {pi}-mediated interactions that suggest specific avenues for future ALLINI development and optimization.
The ability to obtain single cell transcriptomes for stable cell types and dynamic cell states is ushering in a new era for biology. We created the Tabula Drosophilae, a single cell atlas of the adult fruit fly which includes 580k cells from 15 individually dissected sexed tissues as well as the entire head and body. Over 100 researchers from the fly community contributed annotations to >250 distinct cell types across all tissues. We provide an in-depth analysis of cell type-related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types that are shared between tissues, such as blood and muscle cells, allowed the discovery of rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the entire Drosophila community and serves as a comprehensive reference to study genetic perturbations and disease models at single cell resolution.
Predation is a fundamental ecological process that shapes communities and drives long-term evolutionary dynamics. As the world rapidly urbanizes, it is critical to understand how the built environment and other human perturbations alter predation across taxa. We conducted a meta-analysis to quantify the effects of urban environments on three components of trophic ecology in predators: dietary species richness (DSR), dietary evenness (DEV), and stable isotopic ratios ({delta}13C and {delta}15N IR). We then evaluated whether intensity of anthropogenic pressure, using the human footprint index (HFI), explained variation in the effect sizes of dietary attributes using a meta-regression. We calculated Hedges g effect sizes from 44 studies including 11,986 samples across 40 predatory species in 39 cities globally. The direction and magnitude of effect sizes varied between predator taxonomic groups with reptile diets exhibiting the most sensitivity to urbanization. Effect sizes revealed that predators in cities had comparable DSR, DEV, and nitrogen ratios, though carbon consumption was significantly higher. We found that HFI did not explain variation in effect sizes, a result consistent between the 1993 and 2009 editions of this metric. Our study provides the first assessment of how urbanization has perturbed predator-prey interactions for multiple taxa at a global scale, revealing that the functional role of predators is conserved in cities and urbanization does not inherently relax predation.
Understanding how an emergent pathogen successfully establishes itself and persists in a previously unaffected population is a crucial problem in disease ecology. In multi-host pathogen systems this problem is particularly difficult, as the importance of each host species to transmission is often poorly characterised, and the epidemiology of the disease is complex. Opportunities to observe and analyse such emergent scenarios are few. Here, we exploit a unique dataset combining densely-collected data on the epidemiological and evolutionary characteristics of an outbreak of Mycobacterium bovis (M. bovis, the causative agent of bovine tuberculosis, bTB) in a population of cattle and badgers in an area considered low-risk for bTB, that has no previous record of either persistent infection in cattle, or of any infection in wildlife. We analyse the outbreak dynamics using a combination of mathematical modelling, machine learning and Bayesian evolutionary analyses. Comparison to M. bovis whole-genome sequences from Northern Ireland confirmed this to be a single introduction of the pathogen from the latter region, with evolutionary analysis supporting an introduction directly into the local cattle population at least six years prior to its first discovery in badgers. Once introduced, the evidence supports M. bovis epidemiological dynamics passing through two phases, the first dominated by cattle-to-cattle transmission before becoming established in the local badger population. These findings emphasise the importance of disease surveillance for early containment of outbreaks, in particular for pathogens not causing immediately evident symptoms in the infected host, and highlight the utility of combining dynamic modelling and phylogenetic analyses for understanding the often complex infection dynamics associated with emergent outbreaks.
In every liter of seawater there are between 10 and 100 billion life forms, mostly invisible, called plankton, which form the largest and most dynamic ecosystem on our planet, at the heart of global ecological and economic processes. While physical and chemical parameters of planktonic ecosystems are fairly well measured and modelled at the planetary scale, but biological data are still scarce due to the extreme cost and relative inflexibility of the classical vessels and instruments used to explore marine biodiversity. Here we introduce Plankton Planet, an initiative whose goal is to merge the creativity of researchers, makers, and mariners to (i) develop frugal scientific instrumentation and protocols to assess the genetic and morphological diversity of plankton life, and (ii) organize their systematic deployment through fleets of volunteer sailors, fishermen, or cargo-ships to generate comparable and open-access plankton data across global and long-term spatio-temporal scales. As proof-of-concept, we show how 20 crews of sailors ("planktonauts") were abl to sample plankton biomass from the world surface ocean in a single year, generating the first citizen-based, planetary dataset of plankton biodiversity based on DNA barcodes. The quality of this dataset is comparable to that generated by Tara Oceans and is not biased by the multiplication of samplers. This dataset has unveiled significant genetic novelty and can be used to explore the taxonomic and ecological diversity of plankton at both regional and global scales. This pilot project paves the way for construction of a miniaturized, modular, evolvable, affordable and open-source citizen field-platform that will allow systematic assessment of the eco/morpho/genetic variation of aquatic ecosystems across the dimensions of the Earth system.
The Global Strategy for Plant Conservation (GSPC) ambitiously calls for an assessment of extinction risk for all recognised plant taxa by 20201. It is now clear that this target will not be met in the short-term; only 21-26% of known plant species have been assessed2 - a monumental shortfall in anticipated knowledge. Yet the need for risk assessments has never been more urgent. Plants are rapidly going extinct3,4 and face threats such as climate change5 and permanent deforestation6. Extinction risk assessments continue to provide the critical foundation to inform protection, management and recovery of plant species7,8, the loss of which will have clear consequences for maintaining planetary systems and human well-being9. Here, we rank countries of the world based on progress towards assessing the extinction risk to their endemic flora. Overall, 67% of country-based endemic species do not have an extinction risk assessment completed (143,294 species). We show that some of the worlds wealthiest nations, which also have relatively strong species protections, are failing to protect their unique flora by not systematically assessing risks to their endemic species.
NRGN is a schizophrenia risk gene identified in recent genetic studies, encoding a small neuronal protein, neurogranin (Ng). Individuals carrying a risk variant of NRGN showed decreased hippocampal activation during contextual fear conditioning. Furthermore, the expression of Ng was reduced in the post-mortem brains of schizophrenic patients. Using the mouse model, we found that the translation of Ng in hippocampus is rapidly increased in response to novel context exposure, and this up-regulation is required for encoding contextual memory. The extent and degree of the effect that altered Ng expression has on neuronal cellular functions are largely unknown. Here, we found that Ng bidirectionally regulates synaptic plasticity in the hippocampus. Elevated Ng levels facilitated long-term potentiation (LTP), whereas decreased Ng levels impaired LTP. Quantitative phosphoproteomic analysis revealed that decreasing Ng caused a significant shift in the phosphorylation status of postsynaptic density proteins, highlighting clusters of schizophrenia- and autism-related genes. In particular, decreasing Ng led to the hypo-phosphorylation of NMDAR subunit Grin2A at newly identified sites, resulting in accelerated decay of NMDAR-mediated channel currents. blocking protein phosphatase PP2B activity rescued the accelerated synaptic NMDAR current decay and the impairment of LTP caused by decreased Ng levels, suggesting that enhanced synaptic PP2B activity led to the deficits. Taken together, our work suggests that altered Ng levels under pathological conditions affect the phosphorylation status of neuronal proteins by tuning PP2B activity and thus the induction of synaptic plasticity, revealing a novel mechanistic link of a schizophrenia risk gene to cognitive deficits.
Under typical daytime light levels, the human pupillary light response (PLR) is driven by the activity of the L, M, and S cones, and melanopsin expressed in the so-called intrinsically photosensitive retinal ganglion cells (ipRGCs). However, the importance of each of these photoreceptive mechanisms in defining pupil size under real-world viewing conditions remains to be established. To address this question, we embedded photoreceptor-specific modulations in a movie displayed using a novel projector-based five-primary spatial stimulation system, which allowed for the precise control of photoreceptor activations in time and space. We measured the pupillary light response in eleven observers, who viewed short cartoon movies which contained hidden low-frequency (0.25 Hz) silent-substitution modulations of the L, M and S cones (no stimulation of melanopsin), melanopsin (no stimulation of L, M and S cones), both L, M, and S cones and melanopsin or no modulation at all. We find that all photoreceptors active at photopic light levels regulate pupil size under this condition. Our data imply that embedding modulations in photoreceptor contrast could provide a method to manipulate key adaptive aspects of the human visual system in everyday, real-world activities such as watching a movie.
Different parts of a gene can be of differential importance to development and health. This regional heterogeneity is also apparent in the distribution of disease mutations which often cluster in particular regions of disease genes. The ability to precisely estimate functionally important sub-regions of genes will be key in correctly deciphering relationships between genetic variation and disease. Previous methods have had some success using standing human variation to characterize this variability in importance by measuring sub-regional intolerance, i.e., the depletion in functional variation from expectation within a given region of a gene. However, the ability to precisely estimate local intolerance was restricted by the fact that only information within a given sub-region is used, leading to instability in local estimates, especially for small regions. We show that borrowing information across regions using a Bayesian hierarchical model, stabilizes estimates, leading to lower variability and improved predictive utility. Specifically, our approach more effectively identifies regions enriched for ClinVar pathogenic variants. We also identify significant correlations between sub-region intolerance and the distribution of pathogenic variation in disease genes, with AUCs for classifying de novo missense variants in Online Mendelian Inheritance in Man (OMIM) genes of up to 0.86 using exonic sub-regions and 0.91 using sub-regions defined by protein domains. This result immediately suggests that considering the intolerance of regions in which variants are found may improve diagnostic interpretation. We also illustrate the utility of integrating regional intolerance into gene-level disease association tests with a study of known disease genes for epileptic encephalopathy.
Large-scale sequencing efforts in amyotrophic lateral sclerosis (ALS) have implicated novel genes using gene-based collapsing methods. However, pathogenic mutations may be concentrated in specific genic regions. To address this, we developed two collapsing strategies, one focuses rare variation collapsing on homology-based protein domains as the unit for collapsing and another gene-level approach that, unlike standard methods, leverages existing evidence of purifying selection against missense variation on said domains. The application of these two collapsing methods to 3,093 ALS cases and 8,186 controls of European ancestry, and also 3,239 cases and 11,808 controls of diversified populations, pinpoints risk regions of ALS genes including SOD1, NEK1, TARDBP and FUS. While not clearly implicating novel ALS genes, the new analyses not only pinpoint risk regions in known genes but also highlight candidate genes as well.