Biology subjects

Huang, A.

Publications and source records attributed to Huang, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Insect wings arose with a genetic circuit that extends the useful range of a BMP morphogen

Morphogens are produced by a subset of cells to trigger a signalling gradient that provides positional information to surrounding tissues. At increasing distances from the source, the dwindling number of morphogen molecules is expected to constrain the useful range of morphogen gradients. We have identified a genetic circuit that counteracts this limitation in developing wings of Drosophila by boosting BMP signalling at the distal end of the gradient without amplifying the signal near the source. This circuit involves Brinker, a transcription factor that represses BMP target genes while itself being repressed by BMP signalling. We suggest that temporal averaging inherent to the production of the inverse Brk gradient contributes to the enhancement of the positional information far from the Dpp source. Despite being a core component of BMP signalling in flies, Brinker is exclusively found in insects, likely in all insect species. Genomic analysis across a wide range of insects and gene expression analysis in limb primordia of the apterygote Thermobia domestica suggests that Brinker is an insect-specific innovation that was subsequently wired into the BMP signalling network in pterygotes, perhaps to enable wing development.

developmental biology↗

bioRxiv2025

The mycotoxin Beauvericin is an uncompetitive inhibitor of Cathepsin B

Beauvericin (BEA), a cyclic depsipeptide, is a mycotoxin of the enniatin family and the secondary metabolite of various toxigenic fungi. Multiple biological functions of BEA have been well investigated, such as anti-cancer, anti-inflammatory, anti-microbial, and immune-activating functions. In a recent study, we showed that BEA can target Toll-like receptor 4 (TLR4) to induce dendritic cell (DC) activation. In an in silico screen, we identified Cathepsin B (CTSB) as a potential additional interaction partner for BEA, which has been verified recently in a study showing inhibition of CTSB activity by BEA in cell-free assays. The underlying molecular mechanism of BEA-mediated CTSB inhibition remains unknown as do the cellular entities where this inhibition takes place. In this study, we determine the effects of BEA on CTSB within granulocyte-macrophage colony-stimulating factor (GM-CSF)-cultured bone marrow-derived dendritic cells (BMDCs) and human leukemia monocytic cell line THP-1 induced dendritic cells (iDCs). BEA significantly suppresses CTSB activity in both mouse BMDCs and human iDCs. NMR analyses indicate that BEA directly interacts with CTSB. Enzyme kinetics show that BEA can directly inhibit CTSB activity and acts as an uncompetitive inhibitor. Molecular docking analysis revealed a putative binding site for BEA in human CTSB. Collectively, we describe the molecular mechanisms underlying the biological activity of BEA against human CTSB, suggesting that CTSB may be a candidate target for tumor therapy.

biochemistry↗

bioRxiv2024

Self-organizing human heart assembloids with autologous and developmentally relevant cardiac neural crest-derived tissues

Neural crest cells (NCCs) are a multipotent embryonic cell population of ectodermal origin that extensively migrate during early development and contribute to the formation of multiple tissues. Cardiac NCCs play a critical role in heart development by orchestrating outflow tract septation, valve formation, aortic arch artery patterning, parasympathetic innervation, and maturation of the cardiac conduction system. Abnormal migration, proliferation, or differentiation of cardiac NCCs can lead to severe congenital cardiovascular malformations. However, the complexity and timing of early embryonic heart development pose significant challenges to studying the molecular mechanisms underlying NCC-related cardiac pathologies. Here, we present a sophisticated functional model of human heart assembloids derived from induced pluripotent stem cells, which, for the first time, recapitulates cardiac NCC integration into the human embryonic heart in vitro. NCCs successfully integrated at developmentally relevant stages into heart organoids, and followed developmental trajectories known to occur in the human heart. They demonstrated extensive migration, differentiated into cholinergic neurons capable of generating nerve impulses, and formed mature glial cells. Additionally, they contributed to the mesenchymal populations of the developing outflow tract. Through transcriptomic analysis, we revealed that NCCs acquire molecular features of their cardiac derivatives as heart assembloids develop. NCC-derived parasympathetic neurons formed functional connections with cardiomyocytes, promoting the maturation of the cardiac conduction system. Leveraging this models cellular complexity and functional maturity, we uncovered that early exposure of NCCs to antidepressants harms the development of NCC derivatives in the context of the developing heart. The commonly prescribed antidepressant Paroxetine disrupted the expression of a critical early neuronal transcription factor, resulting in impaired parasympathetic innervation and functional deficits in cardiac tissue. This advanced heart assembloid model holds great promise for high-throughput drug screening and unraveling the molecular mechanisms underlying NCC-related cardiac formation and congenital heart defects. IN BRIEFHuman neural crest heart assembloids resembling the major directions of neural crest differentiation in the human embryonic heart, including parasympathetic innervation and the mesenchymal component of the outflow tract, provide a human-relevant embryonic platform for studying congenital heart defects and drug safety.

bioengineering↗

bioRxiv2024

Human heart assembloids with autologous tissue-resident macrophages recreate physiological immuno-cardiac interactions

Interactions between the developing heart and the embryonic immune system are essential for proper cardiac development and maintaining homeostasis, with disruptions linked to various diseases. While human pluripotent stem cell (hPSC)-derived organoids are valuable models for studying human organ function, they often lack critical tissue-resident immune cells. Here, we introduce an advanced human heart assembloid model, termed hHMA (human heart-macrophage assembloid), which fully integrates autologous cardiac tissue- resident macrophages (MPs) with pre-existing human heart organoids (hHOs). Through multi-omic analyses, we confirmed that these MPs are phenotypically similar to embryonic cardiac tissue-resident MPs and remain viable in the assembloids over time. The inclusion of MPs significantly impacts hHMA development, influencing cardiac cellular composition, boosting cellular communication, remodeling the extracellular matrix, promoting ventricular morphogenesis, and enhancing sarcomeric maturation. Our findings indicate that MPs contribute to homeostasis via efferocytosis, integrate into the cardiomyocyte electrical system, and support catabolic metabolism. To demonstrate the versatility of this model, we developed a platform to study cardiac arrhythmias by chronic exposure to pro-inflammatory factors linked to arrhythmogenesis in clinical settings, successfully replicating key features of inflammasome-mediated atrial fibrillation. Overall, this work introduces a robust platform for examining the role of immune cells in cardiac development, disease mechanisms, and drug discovery, bridging the gap between in vitro models and human physiology. These findings offer insights into cardiogenesis and inflammation-driven heart disease, positioning the hHMA system as an invaluable tool for future cardiovascular research and therapeutic development.

bioengineering↗

bioRxiv2024

Cerebellar-Prefrontal Connectivity Predicts Negative Symptom Severity Across the Psychosis Spectrum

BackgroundNegative symptom severity predicts functional outcome and quality life in people with psychosis. However, negative symptoms are poorly responsive to antipsychotic medication and existing literature has not converged on their neurobiological basis. Previous work in small schizophrenia samples has observed that lower cerebellar-prefrontal connectivity is associated with higher negative symptom severity and demonstrated in a separate neuromodulation experiment that increasing cerebellar-prefrontal connectivity reduced negative symptom severity. We sought to expand this finding to test associations between cerebellar-prefrontal connectivity with negative symptom severity and cognitive performance in a large, transdiagnostic sample of individuals with psychotic disorders. MethodsIn this study, 260 individuals with psychotic disorders underwent resting-state MRI and clinical characterization. Negative symptom severity was measured using the Positive and Negative Symptoms Scale, and cognitive performance was assessed with the Screen for Cognitive Impairment in Psychiatry. Using a previously identified cerebellar region as a seed, we performed seed to whole brain analyses and regressed connectivity against negative symptom severity, using age and sex as covariates. ResultsConsistent with prior work, we identified relationships between higher cerebellar-prefrontal connectivity and lower negative symptom severity (r=-0.17, p=.007). Higher cerebellar-prefrontal connectivity was also associated with better delayed verbal learning (r=.13, p=.034). ConclusionsOur results provide further evidence supporting the relationship between cerebellar-prefrontal connectivity and negative symptom severity and cognitive performance. Larger, randomized, sham-controlled neuromodulation studies should test if increasing cerebellar-prefrontal connectivity leads to reductions in negative symptoms in psychosis.

neuroscience↗

bioRxiv2024

Effects of Host-Tree Foliage on Polymorphism in an Insect Pathogen

The theory of host-pathogen interactions has successfully shown that persistent pathogen virulence may be explained through tradeoffs between different pathogen fitness components, but classical theory cannot explain pathogen coexistence. More recent theory invokes both tradeoffs and environmental heterogeneity, but resembles classical theory in focusing on a limited range of possible tradeoffs, and therefore has seen few applications. To better understand the usefulness of tradeoff theory for explaining pathogen coexistence in nature, we measured components of pathogen fitness in two distantly related morphotypes of a baculovirus that infects larvae of the Douglas-fir tussock moth (Orgyia pseudotsugata). We show that the two morphotypes vary in multiple components of fitness, including the probability of infection given exposure to the pathogen, the incubation time of the pathogen, variability in the incubation time of the pathogen, and the detectability of the pathogen. Moreover, because the baculovirus is transmitted when host larvae accidentally consume infectious virus particles while feeding on foliage of the insects host trees, the strength and direction of the differences in fitness components of the two morphotypes depends on the host-tree species on which host larvae consume the virus. Through simulations of a model parameterized using our experimental data, we demonstrate how several varying fitness components can work in concert to promote strain coexistence, particularly highlighting the role of variability in incubation time. Our results suggest that the two morphotypes may coexist because of variation in forest tree-species composition, providing important empirical evidence that tradeoffs and environmental heterogeneity can together modulate pathogen competition.

ecology↗

bioRxiv2024

Robotic Visible-Light Optical Coherence Tomography Visualizes Segmental Schlemms Canal Anatomy and Segmental Pilocarpine Response

PurposeTo use robotic visible-light OCT (vis-OCT) to study circumferential segmental Schlemms canal (SC) anatomy in mice after topical pilocarpine administration. MethodsAnterior segment imaging was performed using a vis-OCT sample arm attached to a 6-degree-of-freedom robotic arm to maintain normal (perpendicular) laser illumination aimed at SC around the limbus. Sixteen mice were studied for repeatability testing and to study aqueous humor outflow (AHO) pathway response to topical drug. Pharmaceutical-grade pilocarpine (1%; n = 5) or control artificial tears (n = 9) were given, and vis-OCT imaging was performed before and 15 minutes after drug application. After SC segmentation, SC areas and volumes were measured circumferentially in control- and drug-treated eyes. ResultsCircumferential vis-OCT provided high-resolution imaging of the anterior segment and AHO pathways, including SC. Segmental SC anatomy was visualized with the average cross-sectional area greatest temporal (3971 {+/-} 328 {micro}m2) and the least nasal (2727 {+/-} 218 {micro}m2; p = 0.018). After pilocarpine administration, the iris became flatter, and SC became larger (pilocarpine: 26.8 {+/-} 5.0% vs. control: 8.9 {+/-} 4.6% volume increase; p = 0.030). However, the pilocarpine alteration was segmental as well, with a greater increase observed superior (pilocarpine: 31.6 {+/-} 8.9% vs. control: 1.8 {+/-} 5.7% volume increase; p = 0.023) and nasal (pilocarpine: 41.1 {+/-} 15.3% vs. control: 13.9 {+/-} 4.5% volume increase; p = 0.045). ConclusionHigh-resolution circumferential non-invasive imaging using AS-OCT of AHO pathways is possible in living animals with robotic control. Segmental SC anatomy was seen at baseline and was consistent with the known segmental nature of trabecular AHO. Segmental SC anatomical response to a muscarinic agonist was seen as well. Segmental glaucoma drug response around the circumference of AHO pathways is a novel observation that may explain the variable patient response to glaucoma treatments.

bioengineering↗

bioRxiv2024

BRAIN-METASTATIC MELANOMA MODELS UNCOVER IMMUNE AND MOLECULAR CORRELATES OF RESPONSE TO IMMUNOTHERAPY

Despite the promising results of immune checkpoint blockade (ICB) therapy, outcomes for patients with brain metastasis (BrM) remain poor. Identifying resistance mechanisms has been hindered by limited access to patient samples and relevant preclinical models. Here, we developed two mouse melanoma BrM models that recapitulate the disparate responses to ICB seen in patients. We demonstrate that these models capture the cellular and molecular complexity of human disease and reveal key factors shaping the tumor microenvironment and influencing ICB response. BR1-responsive tumor cells express inflammatory programs that polarize microglia into reactive states, eliciting robust T cell recruitment. In contrast, BR3-resistant melanoma cells are enriched in neurological programs and exploit tolerance mechanisms to maintain microglia homeostasis and limit T cell infiltration. In humans, BR1 and BR3 expression signatures correlate positively or negatively with T cell infiltration and BrM patient outcomes, respectively. Our study provides clinically relevant models and uncovers mechanistic insights into BrM ICB responses, offering potential biomarkers and therapeutic targets to improve therapy efficacy.

immunology↗

bioRxiv2024

IRF5 mediates adaptive immunity via altered glutamine metabolism, mTORC1 signaling and post-transcriptional regulation following T cell receptor activation

Although dynamic alterations in transcriptional, translational, and metabolic programs have been described in T cells, the factors and pathways guiding these molecular shifts are poorly understood, with recent studies revealing a disassociation between transcriptional responses and protein expression following T cell receptor (TCR) stimulation. Previous studies identified interferon regulatory factor 5 (IRF5) in the transcriptional regulation of cytokines, chemotactic molecules and T effector transcription factors following TCR signaling. In this study, we identified T cell intrinsic IRF5 regulation of mTORC1 activity as a key modulator of CD40L protein expression. We further demonstrated a global shift in T cell metabolism, with alterations in glutamine metabolism accompanied by shifts in T cell populations at the single cell level due to loss of Irf5. T cell conditional Irf5 knockout mice in a murine model of experimental autoimmune encephalomyelitis (EAE) demonstrated protection from clinical disease with conserved defects in mTORC1 activity and glutamine regulation. Together, these findings expand our mechanistic understanding of IRF5 as an intrinsic regulator of T effector function(s) and support the therapeutic targeting of IRF5 in multiple sclerosis. Sentence SummaryFindings provide new insight into the mechanisms by which T cell intrinsic IRF5 regulates the adaptive immune response via modulation of mTORC1 signaling, glutamine metabolism, and protein translation.

immunology↗

bioRxiv2024

Chaotic dynamics for homeostatic hematopoiesis

Homeostatic hematopoiesis is a dynamical process, characterized by large variations (e.g., with coefficients of variation larger than 1) of cell quantities, cell proliferation rates, and extensive correlations/anticorrelations between cell types within the myeloid/lymphoid lineage, and between lineages. All cell types exhibit rare but synchronized bursts of proliferation in the bone marrow, blood and spleen. Through longitudinal study of the blood contents of healthy mice, we found that leukocyte fluctuations are ergodic yet subject to chaotic behaviors characterized by a broad spectrum of characteristic timescales. We then built a minimal mathematical model to capture these dynamical features of hematopoiesis (fluctuations, correlations, and chaos) and explain how the accumulation of B cells (e.g. during lymphoma development) would transition the blood cell dynamics from chaos to oscillations as observed clinically. Finally, we demonstrated the ubiquity of the correlated blood cell fluctuations by comparing mouse cohorts of different genetic backgrounds and ages.

immunology↗

bioRxiv2024

Stochastic Wiring of Cell Types Enhances Fitness by Generating Phenotypic Variability

The development of neural connectivity is a crucial biological process that gives rise to diverse brain circuits and behaviors. Neural development is a stochastic process, but this stochasticity is often treated as a nuisance to overcome rather than as a functional advantage. Here we use a computational model, in which connection probabilities between discrete cell types are genetically specified, to investigate the benefits of stochasticity in the development of neural wiring. We show that this model can be viewed as a generalization of a powerful class of artificial neural networks--Bayesian neural networks--where each network parameter is a sample from a distribution. Our results reveal that stochasticity confers a greater benefit in large networks and variable environments, which may explain its role in organisms with larger brains. Surprisingly, we find that the average fitness over a population of agents is higher than a single agent defined by the average connection probability. Our model reveals how developmental stochasticity, by inducing a form of non-heritable phenotypic variability, can increase the probability that at least some individuals will survive in rapidly changing, unpredictable environments. Our results suggest how stochasticity may be an important feature rather than a bug in neural development.

neuroscience↗

bioRxiv2024

Differentiation of Acute Disseminated Encephalomyelitis from Multiple Sclerosis Using a Novel Brain Lesion Segmentation and Classification Pipeline

Multiple Sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system, while Acute Disseminated Encephalomyelitis (ADEM) is a sudden, often monophasic inflammatory condition of the brain and spinal cord. Only 17% of ADEM cases are correctly diagnosed on the first visit due to overlapping clinical and radiological presentations with Multiple Sclerosis (MS) [1]. Both ADEM and MS are demyelinating diseases, meaning they cause brain lesions by damaging the myelin sheath, leading to scar tissue that disrupts nerve signals [2]. Previous machine learning pipelines have differentiated Neuromyelitis Optica Spectrum Disorder (NMOSD) (a different demyelinating disease) from MS and ADEM from NMOSD based on MRI imagery with varying accuracies [3, 4]. Our novel Classifier for Demyelinating Disease (CDD) pipeline is the first to differentiate ADEM from MS using MRI imagery. It does this in two stages: a segmentation stage which creates segmentation masks of the lesions and a classification stage to classify them as either ADEM or MS. Additionally, we introduce a novel ADEM dataset from open-access medical case reports. The CDD pipeline achieves an accuracy of 90.0% on our validation dataset, making it a potentially viable diagnostic tool in the future. All data and code is available here. 2

neuroscience↗

bioRxiv2024

Top-Down Proteomics Identifies Plasma Proteoform Signatures of Liver Cirrhosis Progression

Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2 years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery Top-down Proteomics (TDP) to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/599662v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@797e27org.highwire.dtl.DTLVardef@495bb7org.highwire.dtl.DTLVardef@2478a9org.highwire.dtl.DTLVardef@6dbc0a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIPerformed a pilot top-down LC-MS/MS analysis to identify proteoforms (PFRs) in the plasma of patients with 3 progressive stages of liver cirrhosis. C_LIO_LIIdentified 2867 proteoforms (PFRs) and 209 differentially regulated proteoforms (DRPs) in the different stages of the disease. C_LIO_LIIdentified DRP profiles able to potentially distinguish early from late stages of the disease, including 115 liver-derived DRPs. C_LIO_LIFibrinogen alpha chain, haptoglobin, and Apo A-I are the proteins with the highest number of DRPs and represent potential candidate biomarkers of liver cirrhosis progression. C_LI

molecular biology↗

bioRxiv2024

Freeform robotic optical coherence tomography beyond the optical field-of-view limit

Imaging complex, non-planar anatomies with optical coherence tomography (OCT) is limited by the optical field of view (FOV) in a single volumetric acquisition. Combining linear mechanical translation with OCT extends the FOV but suffers from inflexibility in imaging non-planar anatomies. We report the freeform robotic OCT to fill this gap. To address challenges in volumetric reconstruction associated with the robotic movement accuracy being two orders of magnitudes worse than OCT imaging resolution, we developed a volumetric registration algorithm based on simultaneous localization and mapping (SLAM) to overcome this limitation. We imaged the entire aqueous humor outflow pathway, whose imaging has the potential to customize glaucoma surgeries but is typically constrained by the FOV, circumferentially in mice as a test. We acquired volumetric OCT data at different robotic poses and reconstructed the entire anterior segment of the eye. The reconstructed volumes showed heterogeneous Schlemms canal (SC) morphology in the reconstructed anterior segment and revealed a segmental nature in the circumferential distribution of collector channels (CC) with spatial features as small as a few micrometers.

bioengineering↗

bioRxiv2024

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of "atlas" training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice. Successful integration of all three domains presents an opportunity for uncovering cell populations that are functionally stratified by their spatial contexts at cellular and tissue levels: the key motivation for employing spatial-omics technologies in the first place. In this work, we introduce Cell Spatio- and Neighborhood-informed Annotation and Patterning (CellSNAP), a self-supervised computational method that learns a representation vector for each cell in tissue samples measured by spatial-omics technologies at the single-cell or finer resolution. The learned representation vector fuses information about the corresponding cell across all three aforementioned domains. By applying CellSNAP to datasets spanning both spatial proteomic and spatial transcriptomic modalities, and across different tissue types and disease settings, we show that CellSNAP markedly enhances de novo discovery of biologically relevant cell populations at fine granularity, beyond current approaches, by fully integrating cells molecular profiles with cellular neighborhood and tissue image information.

bioinformatics↗

bioRxiv2024

Worldwide study of the taste of bitter medicines and their modifiers

The bitter taste of medicines hinders patient compliance, but not everyone experiences these difficulties because people worldwide differ in their bitterness perception. To better understand how people from diverse ancestries perceive medicines and taste modifiers, 338 adults, European and recent US and Canada immigrants from Asia, South Asia, and Africa, rated the bitterness intensity of taste solutions on a 100-point generalized visual analog scale and provided a saliva sample for genotyping. The taste solutions were five medicines, tenofovir alafenamide (TAF), moxifloxacin, praziquantel, amodiaquine, and propylthiouracil (PROP), and four other solutions, TAF mixed with sucralose (sweet, reduces bitterness) or 6-methylflavone (tasteless, reduces bitterness), sucralose alone, and sodium chloride alone. Bitterness ratings differed by ancestry for two of the five drugs (amodiaquine and PROP) and for TAF mixed with sucralose. Genetic analysis showed that people with variants in one bitter receptor variant gene (TAS2R38) reported PROP was more bitter than did those with a different variant (p= 7.6e-19) and that people with either an RIMS2 or a THSD4 genotype found sucralose more bitter than did others (p=2.6e-8, p=7.9e-11, resp.). Our findings may help guide the formulation of bad- tasting medicines to meet the needs of those most sensitive to them.

physiology↗

bioRxiv2024

A sequence- and structure-based characterization of microbial enzymes identifies P. stutzeri as a plastic-degrading species

Plastic waste has accumulated rapidly in the past century and is now found throughout every ecosystem on Earth. Its ubiquitous presence means that plastic is routinely ingested by countless organisms, with potential negative consequences for organismal health. New solutions are urgently needed to combat plastic pollution. Among the many strategies required to curb the plastic pollution crisis, the bioremediation of plastic via enzymatic activity of microbial species represents a promising approach. Diverse microbes harbor enzymes capable of degrading plastic polymers and utilizing the polymers as a carbon source. Herein, we characterize the landscape of microbial protein-coding sequences with potential plastic degrading capability. Using the two enzyme systems of PETase and MHETase as a guide, we combined sequence motif analysis, phylogenetic inference, and machine learning-guided 3D protein structure prediction to pinpoint potential plastic-degrading enzymes. Our analysis platform identified hundreds of enzymes from diverse microbial taxa with similarity to known PETases, and far fewer enzymes with similarity to known MHETases. Phylogenetic reconstruction revealed that the plastic degrading enzymes formed distinct clades from the sequences of ancestral enzymes. Among the potential candidate sequences, we pinpointed both a PETase-like and MHETase-like enzyme within the bacterium Pseudomonas stutzeri. Using plate clearing assays, we demonstrated that P. stutzeri is capable of degrading both polyurethane (Impranil(R)) and polycaprolactone (PCL). Pseudomonas stutzeri also grew on carbon-free agar supplemented with polystyrene, suggesting this organism can utilize synthetic polymers as a carbon source. Overall, our integrated bioinformatics and experimental approach provides a rapid and low-cost solution to identify and test novel polymer-degrading enzymes for use in the development of plastic bioremediation technologies.

microbiology↗

bioRxiv2024

Detection of clade 2.3.4.4b highly pathogenic H5N1 influenza virus in New York City

Highly pathogenic avian influenza viruses of the H5N1 clade 2.3.4.4b arrived in North America in the winter of 2021/2022. These viruses have spread across the Americas causing morbidity and mortality in both wild and domestic birds as well as some mammalian species, including cattle. Many surveillance programs in wildlife as well as commercial poultry operations have detected these viruses. Here we conducted surveillance of avian species in the urban environment in New York City. We detected highly pathogenic H5N1 viruses in six samples from four different bird species and performed full genome sequencing. Sequence analysis showed the presence of multiple different genotypes. Our work highlights that the interface between animals and humans that may give rise to zoonotic infections or even pandemics is not limited to rural environments and commercial poultry operations but extends into the heart of our urban centers. ImportanceWhile surveillance for avian influenza viruses is often focused on migratory routes and their associated stop-over locations, or commercial poultry operations, many bird species - including migratory birds - frequent or live in urban green spaces and wetlands. This brings them into contact with a highly dense population of humans and pets providing an extensive urban animal-human interface in which the general public may have little awareness of circulating infectious diseases. This study focuses on virus surveillance at this interface, combined with culturally responsive science education and community outreach.

microbiology↗