Biology subjects

Nelson, A. R.

Publications and source records attributed to Nelson, A. R..

10 recordsLinked to original sources

bioRxiv2024

Chaparral wildfire shifts the functional potential for soil pyrogenic organic matter and nitrogen cycling

Wildfires reshape soil microbiomes and chemistry, enhancing nitrogen availability and leaving behind pyrogenic organic matter (PyOM), a difficult to degrade carbon substrate potentially used by pyrophilous or "fire-loving" microbes. Understanding whether pyrophilous bacteria can metabolize post-fire resources is critical for predicting the fate of both carbon and nitrogen. We explored how secondary succession of pyrophilous bacteria align with changes in functional gene composition, particularly genes related to PyOM degradation and microbial nitrogen metabolism using shotgun metagenomics on 30 burned and unburned soils collected at 17, 25, 34, 131, and 376 days after a high-severity wildfire in a fire-adapted chaparral in Southern California. In burned soils, genes for PyOM degradation increased over time by 167% and for inorganic nitrogen cycling by 117%, while unburned soils showed no significant changes. Genes encoding catechol and protocatechuate, intermediates in the PyOM degradation pathway, indicate that the easier-to-degrade ortho-cleavage pathways consistently dominated the burned plots. These pathways co-occurred with genes for nitrification and nitrogen retention, including assimilatory and dissimilatory nitrate reduction to ammonia (DNRA). We also identified 446 bacterial metagenome-assembled genomes (MAGs) and linked gene profiles to dominant taxa and found that increases in genes for PyOM and nitrogen cycling paralleled the dominance of pyrophilous Massilia and Noviherbaspirillum, which encoded distinct pathways for PyOM and inorganic nitrogen use over time. Together, these findings reveal previously unrecognized functional shifts in bacterial communities over a high-resolution successional timeline, providing insights into the long-term impact of fire on microbial-mediated ecosystem processes that shape soil carbon and nitrogen dynamics.

microbiology↗

bioRxiv2024

Structural characterization of antibody-responses from Zolgensma treatment provides the blueprint for the engineering of an AAV capsid suitable for redosing

Monoclonal antibodies (mAbs) are useful tools to dissect the neutralizing antibody response against the adeno-associated virus (AAV) capsids used as gene therapy delivery vectors. This study structurally characterizes the interactions of 21 human-derived antibodies from patients treated with the AAV9 vector, Zolgensma(R), utilizing high-resolution cryo-electron microscopy. The majority of the bound antibodies do not conform to the icosahedral symmetry of the capsid, thus requiring localized reconstructions. These complex structures provide unprecedented details of the mAbs binding interfaces, with some antibodies inducing structural perturbations of the capsid upon binding. Key surface capsid amino acid residues were identified facilitating the design of capsid variants with an antibody escape phenotype, with the potential to expand the patient cohort treatable with AAV9 vectors to include those that were previously excluded due to their pre-existing neutralizing antibodies, and possibly also to those requiring redosing.

immunology↗

bioRxiv2023

Molecular signature and functional properties of human pluripotent stem cell-derived brain pericytes

Brain pericytes maintain the blood-brain barrier (BBB), secrete neurotrophic factors and clear toxic proteins. Their loss in neurological disorders leads to BBB breakdown, neuronal dysfunction, and cognitive decline. Therefore, cell therapy to replace lost pericytes holds potential to restore impaired cerebrovascular and brain functions. However, the molecular composition and function of human iPSC-derived brain pericytes (iPSC-PC) remains poorly characterized. Here, we show by a quantitative analysis of 8,344 proteins and 20,572 phosphopeptides that iPSC-PC share 96% of total proteins and 98% of protein phosphorylation sites with primary human brain pericytes. This includes cell adhesion and tight junction proteins, transcription factors, and different protein kinase families of the human kinome. In pericyte-deficient mice, iPSC-PC home to host brain capillaries to form hybrid human-mouse microvessels with ligand-receptor associations. They repair BBB leaks and protect against neuron loss, which we show requires PDGRFB and pleiotrophin. They also clear Alzheimers amyloid-{beta} and tau neurotoxins in an ex vivo brain slice assay via lipoprotein receptor. Thus, iPSC-PC may have potential as a replacement therapy for pericyte-deficient neurological disorders.

neuroscience↗

bioRxiv2023

Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts

Fibroblasts are essential regulators of extracellular matrix deposition following cardiac injury. These cells exhibit highly plastic responses in phenotype during fibrosis in response to environmental stimuli. Here, we test whether and how candidate anti-fibrotic drugs differentially regulate measures of cardiac fibroblast phenotype, which may help identify treatments for cardiac fibrosis. We conducted a high content microscopy screen of human cardiac fibroblasts treated with 13 clinically relevant drugs in the context of TGF{beta} and/or IL-1{beta}, measuring phenotype across 137 single-cell features. We used the phenotypic data from our high content imaging to train a logic-based mechanistic machine learning model (LogiMML) for fibroblast signaling. The model predicted how pirfenidone and Src inhibitor WH-4-023 reduce actin filament assembly and actin-myosin stress fiber formation, respectively. Validating the LogiMML model prediction that PI3K partially mediates the effects of Src inhibition, we found that PI3K inhibition reduces actin-myosin stress fiber formation and procollagen I production in human cardiac fibroblasts. In this study, we establish a modeling approach combining the strengths of logic-based network models and regularized regression models, apply this approach to predict mechanisms that mediate the differential effects of drugs on fibroblasts, revealing Src inhibition acting via PI3K as a potential therapy for cardiac fibrosis. SignificanceCardiac fibrosis is a dysregulation of the normal wound healing response, resulting in excessive scarring and cardiac dysfunction. As cardiac fibroblasts primarily regulate this process, we explored how candidate anti-fibrotic drugs alter the fibroblast phenotype. We identify a set of 137 phenotypic features that change in response to drug treatments. Using a new computational modeling approach termed logic-based mechanistic machine learning, we predict how pirfenidone and Src inhibition affect the regulation of the phenotypic features actin filament assembly and actin-myosin stress fiber formation. We also show that inhibition of PI3K reduces actin-myosin stress fiber formation and procollagen I production in human cardiac fibroblasts, supporting a role for PI3K as a mechanism by which Src inhibition may suppress fibrosis.

systems biology↗

bioRxiv2021

Implications of sample treatment on characterization of the riverine environmental metabolome

High-resolution mass spectrometry techniques are widely used in the environmental sciences to characterize natural organic matter and, when utilizing these instruments, researchers must make multiple decisions regarding sample pre-treatment and the instrument ionization mode. To identify how these choices alter organic matter characterization and resulting conclusions, we analyzed a collection of 17 riverine samples from East River, CO (USA) under four PPL-based Solid Phase Extraction (SPE) treatment and electrospray ionization polarity (e.g., positive and negative) combinations: SPE (+), SPE (-), non-SPE (-), and non-SPE (+). The greatest number of formula assignments were achieved with SPE-treated samples due to the removal of compounds that could interfere with ionization. Furthermore, the SPE (-) treatment captured the most formulas across the widest chemical compound diversity. In addition to a reduced number of assigned formulas, the non-SPE datasets resulted in altered thermodynamic interpretations that could cascade into incomplete assumptions about the availability of organic matter pools for microbial heterotrophic respiration. Thus, we infer that the SPE (-) treatment is the best single method for characterizing environmental organic matter pools unless the focus is on lipid-like compounds, in which case we recommend a combination of SPE (-) and SPE (+) to adequately characterize these molecules. SynopsisWe provide data-driven sample treatment and ionization mode recommendations to researchers who aim to use high-resolution mass spectrometry to characterize environmental organic matter. Abstract Art O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

ecology↗

bioRxiv2021

Playing with FiRE: A genome resolved view of the soil microbiome responses to high severity forest wildfire

Warming climate has increased the frequency and size of high severity wildfires in the western United States, with deleterious impacts on forest ecosystem resilience. Although forest soil microbiomes provide a myriad of ecosystem functions, little is known regarding the impact of high severity fire on microbially-mediated processes. Here, we characterized functional shifts in the soil microbiome (bacterial, fungal, and viral) across wildfire burn severity gradients one year post-fire in coniferous forests (Colorado and Wyoming, USA). We generated the Fire Responding Ecogenomic database (FiRE-db), consisting of 637 metagenome-assembled bacterial genomes, 2490 viral populations, and 2 fungal genomes complemented by 12 metatranscriptomes from soils affected by low and high-severity, and complementary marker gene sequencing and metabolomics data. Actinobacteria dominated the fraction of enriched and active taxa across burned soils. Taxa within surficial soils impacted by high severity wildfire exhibited traits including heat resistance, sporulation and fast growth that enhanced post-fire survival. Carbon cycling within this system was predicted to be influenced by microbial processing of pyrogenic compounds and turnover of dominant bacterial community members by abundant viruses. These genome-resolved analyses across trophic levels reveal the complexity of post-fire soil microbiome activity and offer opportunities for restoration strategies that specifically target these communities.

microbiology↗

bioRxiv2019

Network analysis reveals a distinct axis of macrophage activation in response to conflicting inflammatory cues

Macrophages are subject to a wide range of cytokine and pathogen signals in vivo, which contribute to differential activation and modulation of inflammation. Understanding the response to multiple, often conflicting, cues that macrophages experience requires a network perspective. Here, we integrate data from literature curation and mRNA expression profiles to develop a large-scale computational model of the macrophage signaling network. In response to stimulation across all pairs of 9 cytokine inputs, the model predicted activation along the classic M1-M2 polarization axis but also a second axis of macrophage activation that distinguishes unstimulated macrophages from a mixed phenotype induced by conflicting cues. Along this second axis, combinations of conflicting stimuli, interleukin 4 (IL4) with lipopolysaccharide (LPS), interferon-{gamma} (IFN{gamma}), IFN{beta}, or tumor necrosis factor- (TNF), produced mutual inhibition of several signaling pathways, e.g. nuclear factor {kappa}B (NF{kappa}B) and signal transducer and activator of transcription 6 (STAT6), but also mutual activation of the phosphoinositide 3-kinases (PI3K) signaling module. In response to combined IFN{gamma} and IL4, the model predicted genes whose expression was mutually inhibited, e.g. inducible nitric oxide synthase (iNOS) and arginase 1 (Arg1), or mutually enhanced, e.g. IL4 receptor- (IL4R) and suppressor of cytokine signaling 1 (SOCS1), which was validated by independent experimental data. Knockdown simulations further predicted network mechanisms underlying functional crosstalk, such as mutual STAT3/STAT6-mediated enhancement of IL4R expression. In summary, the computational model predicts that network crosstalk mediates a broadened spectrum of macrophage activation in response to mixed pro- and anti-inflammatory cytokine cues, making it useful for modeling in vivo scenarios. Summary sentenceNetwork modeling of macrophage activation predicts responses to combinations of cytokines along both the M1-M2 polarization axis and a second axis associated with a mixed macrophage activation phenotype.

systems biology↗

bioRxiv2019

Computational Model Predicts Paracrine and Intracellular Drivers of Fibroblast Phenotype After Myocardial Infarction

The fibroblast is a key mediator of wound healing in the heart and other organs, yet how it integrates multiple time-dependent paracrine signals to control extracellular matrix synthesis has been difficult to study in vivo. Here, we extended a computational model to simulate the dynamics of fibroblast signaling and fibrosis after myocardial infarction in response to time-dependent data for nine paracrine stimuli. This computational model was validated against dynamic collagen expression and collagen area fraction data from post-infarction rat hearts. The model predicted that while many features of the fibroblast phenotype at inflammatory or maturation phases of healing could be recapitulated by single static paracrine stimuli (interleukin-1 and angiotensin-II, respectively), mimicking of the proliferative phase required paired stimuli (e.g. TGF{beta} and angiotensin-II). Virtual overexpression screens with static cytokine pairs and after myocardial infarction predicted phase-specific regulators of collagen expression. Several regulators increased (Smad3) or decreased (Smad7, protein kinase G) collagen expression specifically in the proliferative phase. NADPH oxidase overexpression sustained collagen expression from proliferative to maturation phases, driven by TGF{beta} and endothelin positive feedback loops. Interleukin-1 overexpression suppressed collagen via NF{kappa}B and BAMBI (BMP and activin membrane-bound inhibitor) incoherent feedforward loops, but it then later sustained collagen expression due to the TGF{beta} positive feedback loop. These model-based predictions reveal network mechanisms by which the dynamics of paracrine stimuli and interacting signaling pathways drive the progression of fibroblast phenotypes and fibrosis after myocardial infarction.

systems biology↗

bioRxiv2019

Multiple PLCβ signaling pathways in taste receptor cells contribute to the detection of bitter, sweet and umami stimuli

Taste receptor cells use multiple signaling pathways to detect chemicals in potential food items. These cells are functionally grouped into different types: Type I cells act as support cells and have glial-like properties; Type II cells detect bitter, sweet, and umami taste stimuli; and Type III cells detect sour and salty stimuli. We have identified a new population of taste cells that are broadly tuned to multiple taste stimuli including bitter, sweet, sour and umami. The goal of this study was to characterize these broadly responsive (BR) taste cells. We used an IP3R3-KO mouse (does not release calcium (Ca2+) from Type II cells when stimulated with bitter, sweet or umami stimuli) to characterize the BR cells without any potentially confounding input from Type II cells. Using live cell Ca2+ imaging in isolated taste cells from the IP3R3-KO mouse, we found that BR cells are a subset of Type III cells that respond to sour stimuli but also use a PLC{beta}3 signaling pathway to respond to bitter, sweet and umami stimuli. Unlike Type II cells, individual BR cells are broadly tuned and respond to multiple stimuli across different taste modalities. Live cell imaging in a PLC{beta}3-KO mouse confirmed that BR cells use a PLC{beta}3 signaling pathway to generate Ca2+ signals to bitter, sweet and umami stimuli. Analysis of c-Fos activity in the nucleus of the solitary tract (NTS) and short term behavioral assays revealed that BR cells make significant contributions to taste.

neuroscience↗

bioRxiv2019

Alpha1-Adrenergic Receptor Mediated Long-Term Depression at CA3-CA1 Synapses Can be Induced via Accumulation of Endogenous Norepinephrine and is Preserved Following Noradrenergic Denervation

Locus coeruleus (LC) provides the sole source of noradrenergic (NA) innervation to hippocampus, and it undergoes significant degeneration early in Alzheimers disease (AD). Norepinephrine (NE) modulates synaptic transmission and plasticity at hippocampal synapses which likely contributes to hippocampus dependent learning and memory. We previously reported that pharmacological activation of 1 adrenergic receptors (1ARs) induces long-term depression (LTD) at CA3-CA1 synapses. Here we investigated whether accumulation of endogenous NE via pharmacological blockade of NE transporters (NET) and the NE degradative enzyme, monoamine oxidase (MAO), can induce 1AR LTD, as these inhibitors are used clinically. Further, we sought to determine how degeneration of hippocampal NA innervation, as occurs in AD, impacts 1AR function and 1AR LTD. Bath application of NET and MAO inhibitors in slices from control rats reliably induced 1AR LTD when {beta} adrenergic receptors were inhibited. To induce degeneration of LC-NA innervation, rats were treated with the specific NA neurotoxin DSP-4 and recordings performed 1-3 weeks later when NA axon degeneration had stabilized. Even with 85% loss of hippocampal NA innervation, 1AR LTD was successfully induced using either the 1AR agonist phenylephrine or the combined NET and MAO inhibitors, and importantly, the LTD magnitude was not different from saline-treated control. These data suggest that despite significant decreases in NA input to hippocampus, the mechanisms necessary for the induction of 1AR LTD remain functional. Furthermore, we posit that 1AR activation could be a viable therapeutic target for pharmacological intervention in AD and other diseases involving malfunctions of NA neurotransmission.

neuroscience↗