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Parker, D.

Publications and source records attributed to Parker, D..

At least 19 recordsLinked to original sources
bioRxiv2026

Synaptic microRNA dysregulation orchestrates aberrant glutamatergic transmission in a human neuronal model of 22q11.2 deletion syndrome

22q11.2 Deletion Syndrome (22q11DS), the most prevalent chromosomal microdeletion disorder in humans (incidence ~1 in 4,000 live births), arises from hemizygous deletions of a 1.5-3.0 Mb region on chromosome 22. Notably, 20-30% of individuals with 22q11DS develop schizophrenia (SCZ) by early adulthood, making 22q11DS one of the strongest genetic risk factors for SCZ. However, the mechanisms by which the 22q11.2 deletion perturbs neuronal function and drive psychotic manifestations in 22q11DS remain poorly defined. In this study, we generated human 2D cortical neurons and 3D cortical organoids from induced pluripotent stem cells (iPSCs) derived from clinically well-characterized individuals with 22q11DS. Cellular and electrophysiological analyses revealed that 22q11DS neurons exhibit hyperexcitability, reduced glutamatergic synaptic transmission, and impaired homeostatic synaptic plasticity, which are pathophysiological hallmarks that may be relevant to the clinical, cognitive, and psychophysiological profiles of patients. Transcriptomic profiling of neurons and synaptosomes from 22q11DS cortical organoids uncovered dysregulated immune pathways and synaptic gene networks. Integrative mRNA-microRNA network analysis identified synergistic downregulation of hsa-miR-185-5p and hsa-miR-128-3p at synapses, driving aberrant regulation of immune and synaptic transcripts. Experimental knockdown of these microRNAs in control neurons recapitulated the molecular and functional phenotypes of 22q11DS neurons, thereby establishing a mechanistic link to synaptic dysfunction and impaired plasticity. Collectively, these findings delineate a multimodal mechanistic framework that bridges genetic vulnerability, synaptic pathology, and psychosis penetrance in 22q11DS, positioning dysregulated synaptic microRNAs as nodal regulators of neurodevelopmental networks and potential therapeutic targets.

neuroscience↗
bioRxiv2026

PIGMENT: A deep learning framework for Porcine Immunohistochemistry seGMENTation

Traumatic brain injury produces widespread axonal damage can be assessed histologically using amyloid precursor protein (APP) immunohistochemistry, which labels injured axonal profiles at cellular resolution [1, 2]. However, quantification of APP pathology remains a major bottleneck: annotation is manual, time-consuming, spatially localized, and variable across raters, limiting scalability and reproducibility. This limitation is particularly important in studies that use histology as a reference for neuroimaging or other tissue-level measurements, where cellular APP pathology must be quantified in a spatial form that can be aligned with imaging abnormalities. Here, we introduce PIGMENT, an annotation-efficient deep-learning framework for automated segmentation and quantification of APP-positive pathology in porcine white matter histology. PIGMENT uses a compact SegFormer-B0 architecture trained on 525 expert-annotated 512 x 512-pixel tiles from four APP-stained sections across three pigs. Because APP-positive profiles are sparse, fragmented, stain-variable, and morphologically diverse, PIGMENT combines limited expert labels with APP-specific augmentation designed to model variation in APP-positive intensity, size, continuity, fragmentation, and local tissue context. We evaluated PIGMENT using an instance-level detection rate that measures whether discrete APP-positive components are localized. Across held-out APP-stained data, PIGMENT achieved a mean instance-level detection rate of 0.86. Across the configurations tested, the highest mean detection rate was achieved by a training set that included sections from different animals, suggesting that annotation diversity may be an important factor under limited-label conditions. By extending limited high-confidence expert annotations into whole-section APP burden maps, PIGMENT provides a scalable framework for characterizing the extent and spatial distribution of traumatic axonal injury. These maps may support future studies that align histological injury burden with imaging-derived measures.

neuroscience↗
bioRxiv2025

Methicillin-Resistant Staphylococcus aureus has Phenotypic Variation in mecA Expression that Alters Antibiotic Sensitivity

Methicillin resistant Staphylococcus aureus (MRSA) sepsis has a high rate of morbidity and mortality. Multiple clinical studies have demonstrated improved outcomes when MRSA sepsis is treated with dual antibiotic therapy that includes a {beta}-lactam antibiotic such as cefazolin. This is a paradox as MRSA should be inherently resistant to this class of antibiotics. We report a serendipitous observation revealed a phenotype where MRSA became sensitive to cefazolin when cultured in a physiologic relevant media of fetal bovine serum as well as in synovial fluid. This could be observed across multiple clinical isolates. Expected resistance was maintained when cultured in Muller Hinton Broth (MHB). MRSA {beta}-lactam antibiotic resistance is mediated by PBP2a, a penicillin-binding protein encoded by mecA. We hypothesized that this phenotype of antibiotic sensitivity in physiologic medium was based, in part, on levels of PBP2a expression and post-translational modifications of peptidoglycan wall teichoic acid (WTA). We therefore conducted quantitative RT-PCR analysis and Western blotting which demonstrated limited mecA expression in the mRNA level and limited PBP2a protein level when cultured in FBS or synovial fluid as compared to the clinical microbiology standard MHB, respectively. Whole genome sequencing of loss of function mutants generated through serial passaging in FBS revealed that the clp family of proteins and rpo genes were involved in {beta}-lactam resistance. Cell wall peptidoglycan analysis suggested that WTA glycosylation was altered between {beta}-lactam resistant and sensitive MRSA phenotypes. Together, this suggests pathways for clpP, rpoB, and WTA glycosylation can be new potential targets for MRSA treatment. IMPORTANCEThis study demonstrates that MRSA has phenotypic variation in mecA expression, PBP2a protein levels, and patterns of wall teichoic acid glycosylation based on environmental conditions which can result in a phenotype of {beta}-lactam antibiotic sensitivity. The presence of an antibiotic resistance gene does not necessarily result in antibiotic resistance. This provides a possible explanation for the clinical observations of potential therapeutic benefit of {beta}-lactam antibiotics in dual therapy treatment of MRSA sepsis and suggests new therapeutic strategies to combat multidrug resistant bacteria. More importantly, identifying genes potentially responsible for this phenotype offers new potential therapeutic targets for the treatment of multidrug resistant infection.

microbiology↗
bioRxiv2025

Malaria parasite population genomics during an elimination program in Eastern Myanmar

BackgroundWe investigated parasite population genomics during an intensive malaria elimination program in Kayin State (Myanmar), in which malaria posts were used for rapid detection and treatment of malaria cases, while mass drug administration (MDA) was used in villages with high submicroscopic reservoirs. MethodsWe collected 5014 dried blood spots from Plasmodium falciparum infected patients from 413 malaria posts, over 58-months (November 2015 - August 2020), and sequenced 2270 parasite genomes, each with geographic references (latitude and longitude). We used identity-by-descent (IBD) relationships to examine how control efforts impact parasite population structure. FindingsParasites were genetically depauperate: 1726 single-genotype infections comprised 166 unique genomes ([≥]90% IBD), while nine families ([≥]45% IBD) accounted for 62{middle dot}5% of parasites sampled. We observed localized, temporally stable transmission of unique parasite genotypes, identifying transmission chains. Parasite relatedness was positively correlated up to approximately 20 km revealing the scale of parasite subpopulations. Kelch13 diversity was stable from 2016-2019, but only one predominant clonal genotype (kelch13-R561H) remained in 2020. MDA resulted in parasite founder effects, providing genomic evidence for the efficacy of this malaria control tool. InterpretationOur genomic data show that parasite population size decreased over the study period, and we observed regional distribution of parasite genotypes, which can define operational units for parasite control. One parasite genotype (kelch13-R561H) from the north rose to high frequency in 2020, because transmission was halted elsewhere in the control area. Future surveillance will reveal whether this genotype spreads to neighboring regions. Genetic drift may have a stronger impact on parasite population structure than selection in low-transmission elimination settings. FundingNational Institutes of Health; Wellcome Trust; Global Fund to Fight against AIDS, Tuberculosis and Malaria; The Bill and Melinda Gates Foundation. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThis study describes the genomic analysis of malaria parasites collected during a malaria elimination program targeting four townships (Myawaddy, Kawkareik, Hlaingbwe, and Hpapun) in Kayin State, eastern Myanmar. We searched PubMed on May 10, 2025, using the terms: "malaria", "transmission", "drug resistance", "southeast Asia" and "genetic surveillance" without any date or language restrictions. Our search yielded 58 publications, including reports on declined immunity to malaria and increased drug resistance in southeast Asia; genetic diversity and population structure shaped by mass drug administration, transmission intensity, human movement and mosquito ecology; and the spread of kelch13 and pfcrt mutations conferring dihydroartemimsinin-piperaquine resistance in east southeast Asia countries. Added value of this studyWe sequenced and analyzed 2270 Plasmodium falciparum whole genomes (each with geographic location) collected between November 2015 and August 2020 in Kayin State. We described fine-scale molecular epidemiology changes during intense malaria elimination interventions. We observed localized, temporally stable transmission of parasite genotypes, with different parasite families and kelch13 haplotypes predominating in different subregions over the 5-year period. We found kelch13 haplotypes with local or regional origin, but none originating from eastern southeast Asia. The genomic data indicated decreasing parasite population size, but we observed no selection towards drug-resistance parasites. In 2020, only one predominant lineage (kelch13-R561H) remained in our studying region, consistent with genetic drift in a pre-elimination setting. Implications of all the available evidenceThe parasite population was genetically depauperate, with a spatially localized and temporally stable distribution of parasite lineages, and declining population size. In this situation genetic drift may play a heightened role in parasite epidemiology. Consistent with this, parasites carrying kelch13-R561H rose to high frequency in 2020, because transmission was eliminated in all regions except the north of Kayin State, where parasites bearing this kelch13 genotype have predominated since 2017. Future surveillance will determine whether this parasite genotype is transmitted to neighboring regions, and thus related to changes in P. falciparum drug resistance dynamics on the Thailand Myanmar border. These data illustrate how genetic drift in small populations can result in instantaneous changes in the resistance status of parasite populations in near elimination settings.

genomics↗
bioRxiv2025

Helminth infection favors reprogramming and proliferation of lung neutrophils

Neutrophils are a granulocytic population of myeloid cells that have critical effector functions during infectious disease but are generally thought to be short-lived and nonproliferative with markedly limited activation states. In these studies, we directly compared lung neutrophil activation following infection with different groups of pathogens including bacteria, fungi, and helminths. Our results demonstrate considerable heterogeneity depending on the type of infectious agent. In contrast to bacterial and fungal infection, after helminth infection neutrophils expressed markers associated with characteristic type 2 responses and unexpectedly upregulated genes associated with cell cycling and protein synthesis. Further studies showed reduced neutrophil cell death following helminth infection and increased proliferation, which was dependent on IL-4R signaling. This distinct subset of proliferating neutrophils expanded following helminth infection and was released from the endothelial niche to colocalize with invading parasites in the airways. These studies demonstrate a novel long-lived cycling phenotype for neutrophils following helminth infection.

immunology↗
bioRxiv2025

An effective response to respiratory inhibition by a Pseudomonas aeruginosa excreted quinoline promotes Staphylococcus aureus fitness and survival in co-culture

Pseudomonas aeruginosa and Staphylococcus aureus are primary bacterial pathogens isolated from the airways of cystic fibrosis patients. P. aeruginosa produces secondary metabolites that negatively impact the fitness of S. aureus, allowing P. aeruginosa to become the most prominent bacterium when the species are co-cultured. Some of these metabolites inhibit S. aureus respiration. SrrAB is a staphylococcal two-component regulatory system (TCRS) that responds to alterations in respiratory status and helps S. aureus transition between fermentative and respiratory metabolisms. We used P. aeruginosa mutant strains and chemical genetics to demonstrate that P. aeruginosa secondary metabolites, HQNO in particular, inhibit S. aureus respiration, resulting in modified SrrAB stimulation. Metabolomic analyses found that the ratio of NAD+ to NADH increased upon prolonged culture with HQNO. Consistent with this, the activity of the Rex transcriptional regulator, which senses and responds to alterations in the NAD+ / NADH ratio, had altered activity upon HQNO treatment. The presence of SrrAB increased fitness when cultured with HQNO and increased survival when challenged with P. aeruginosa. S. aureus strains with a decreased ability to maintain redox homeostasis via fermentation had decreased fitness when challenged with HQNO and decreased survival when challenged with P. aeruginosa. These findings led to a model wherein P. aeruginosa secreted HQNO inhibits S. aureus respiration, stimulating SrrAB, which promotes fitness and survival by increasing carbon flux through fermentative pathways to maintain redox homeostasis. ImportanceCystic fibrosis (CF) is a hereditary respiratory disease that predisposes patients to bacterial infections, primarily caused by Staphylococcus aureus and Pseudomonas aeruginosa. P. aeruginosa excreted secondary metabolites decrease S. aureus fitness during co-infection, ultimately eliminating it. The genetic mechanisms that S. aureus uses to detect and respond to these metabolites are unknown. The S. aureus SrrAB two-component regulatory system senses flux through respiratory pathways and increases transcription of genes utilized for adaption to low-respiration environments. This study demonstrates that SrrAB responds to the P. aeruginosa-produced respiratory toxin HQNO and responds by increasing fermentation increasing competition. This study describes interactions between these two bacterial pathogens, which could be exploited to decrease pathogen burden in individuals living with cystic fibrosis.

microbiology↗
bioRxiv2024

Quantitative analyses of structure-function heterogeneity of individual mitochondrial components reveal an early role of small-mitochondrial-networks in priming neoplastic transformation

Lack of quantitative understanding of the marked heterogeneity of multifaceted mitochondria poses challenges in unraveling their translatable role. Here, we hierarchically untangled multilevel heterogeneity of mitochondrial networks and non-networks by simultaneously analysing their structure-function within single components and their units, in cells and tissues. Such mito-SinComp quantitative analyses revealed that redox levels of mitochondrial networks and their dramatic intra-network heterogeneity can be predicted by structural features through a translatable machine-learning approach. Mito-SinComp identified and quantitatively characterized a redox-tuned subpopulation of Small-Mitochondrial-Networks(SMNs) that specifies stemness. These SMNs are generated by severing of nodes of oxidized Hyperfused-Mitochondrial-Networks(HMNs), are ten-folds smaller with specific network complexity and elevated mt-DNA nucleoid abundance. Thus, HMN to SMN conversion supports elevated expression of mtDNA genes in establishing MT-ND1(redox)-KRT15(stemness) transcriptomic interaction, as revealed by coupled scRNA-seq. This stemness priming of non-transformed cells is sustained after neoplastic transformation and is detected in patient transcriptome, demonstrating translational relevance of SMNs.

cell biology↗
bioRxiv2024

β-Amyloid impairs Proteasome structure and function. Proteasome activation mitigates amyloid induced toxicity and cognitive deficits

BackgroundImpaired proteasome activity is a robust and reproducible feature in Alzheimers disease (AD) patients and animal models. Although amyloid beta (A{beta}) may inhibit proteasomes, it is unclear if this reflects direct structural interference or indirect toxicity. The proteasome controls a myriad of critical neuronal processes with its disruption potentially driving downstream AD pathology. MethodsWe examined the direct impact of distinct A{beta} forms on proteasome structure, dynamics, and function by evaluating enzyme activity and morphology by atomic force microscopy (AFM) and native-gel electrophoresis. To prevent A{beta}-induced impairments in vitro and in AD animal models, we used allosteric proteasome activating peptidomimetics. We characterized their interactions with proteasome by AI enhanced in silico docking. ResultsToxic soluble A{beta}42 oligomers selectively inhibit 20S and 26S proteasome activity, while monomeric and fibrillar forms and A{beta}40 show minimal inhibitory effects. Morphometric analysis of AFM images suggests A{beta}42 oligomers bind laterally to the 20S proteasomes, and impair proteasome dynamics by disabling gate opening, critical for catalytic activity. Oligomer-decorated proteasomes are locked in catalytically inert cycling between closed and intermediate gate conformations. Oligomeric A{beta}42 also induces disassembly of the 26S complex, increasing content of free 20S cores. Importantly, we show proteasome dysfunction induced by oligomeric A{beta}42 is both preventable and reversible by employing an allosteric proteasome activator TAT-DEN, promoting gate opening and restoring enzymatic activity with the full-cycle of conformational transitions in oligomers-treated proteasomes. In cellular and animal models, restoring proteasome function via TAT-DEN mitigated A{beta}-induced cell death, spatial learning/memory deficits, and survival impairments, even under conditions of pre-established A{beta} deficits. ConclusionsOligomeric A{beta}42 decorates the lateral sides of the 20S proteasome restricting cycling between conformations and blocking gate opening. It also reduces the pool of 26S proteasomes necessary for the ubiquitin-dependent protein degradation. We demonstrate proteasome dysfunction can be prevented and reversed by proteasome agonist that lowers 20S affinity to oligomers and promotes allosteric gate opening. We show that proteasome activation with TAT-DEN prevents cognitive deficits in AD animal models. This suggests proteasome dysfunction is a key downstream target in AD pathology and supports proteasome activation as a therapeutic strategy to restore neuronal function in AD.

molecular biology↗
bioRxiv2024

Harmonization of Structural Brain Networks for Multi-site Studies

Diffusion MRI-based structural connectomes are increasingly used to investigate brain connectivity changes associated with various disorders. However, small sample sizes in individual studies, along with highly heterogeneous disorder-related manifestations, underscore the need to pool datasets across multiple studies to be able to identify coherent and generalizable connectivity patterns linked to these disorders. Yet, combining datasets introduces site-related differences due to variations in scanner hardware or acquisition protocols. These differences highlight the necessity for statistical data harmonization to mitigate site-related effects on structural connectomes while preserving the biological information associated with participant demographics and the disorders. While several paradigms exist for harmonizing normally distributed neuroimaging measures, this paper represents the first effort to establish a harmonization framework specifically tailored for the structural connectome. We conduct a thorough investigation of various statistical harmonization methods, adapting them to accommodate the unique distributional characteristics and graph-based properties of structural connectomes. Through rigorous evaluation, we demonstrate that the generalized linear model with a log-linked gamma model (gamma-GLM) outperforms other approaches in modeling structural connectomes, enabling the effective removal of site-related biases in both edge-based and downstream graph analyses while preserving biological variability. Two real-world applications further highlight the utility of our harmonization framework in addressing challenges in multi-site structural connectome analysis. Specifically, harmonization with gamma-GLM enhances the generalizability of connectome-based machine learning predictors to new datasets and increases statistical power for detecting group-level differences. Our work provides essential guidelines for harmonizing multi-site structural connectomes, paving the way for more robust discoveries through collaborative research in the era of team science and big data.

neuroscience↗
bioRxiv2024

Three-dimensional analysis of mitochondria in a patient-derived xenograft model of triple negative breast cancer reveals mitochondrial network remodeling following chemotherapy treatments

Mitochondria are hubs of metabolism and signaling, playing crucial roles in tumorigenesis, therapeutic resistance, and metastasis in many types of cancer. Various laboratory models of cancer demonstrate the extraordinary dynamics of mitochondrial structure, but little is known about the full extent of the complexity of the mitochondrial network, nor its regulation upon exposure to therapeutic stressors. We previously demonstrated the importance of mitochondrial structure and oxidative phosphorylation in the survival of chemotherapy-refractory triple negative breast cancer (TNBC) cells. As TNBC is a highly aggressive breast cancer subtype with few targeted therapy options, conventional chemotherapies remain the backbone of TNBC treatment. Unfortunately, approximately 45% of TNBC patients retain substantial residual tumor burden following chemotherapy, associated with abysmal prognoses. Herein we present the first three-dimensional analysis of mitochondrial networks in human tumor tissues. Use of two experimentally tractable orthotopic patient-derived xenograft (PDX) models TNBC enabled us to conduct longitudinal analyses to construct mitochondrial networks in treatment-naive and residual tumors persisting after exposure to a variety of conventional chemotherapies. Further, we modeled lipid droplet (LD) structures and their physical contacts with mitochondria. In total, we reconstructed 3,750 mitochondria and 800 LDs in three dimensions using serial block-face scanning electron microscopy (SBF-SEM), providing unprecedented insights into the complexity and intra-tumoral heterogeneity of mitochondria in TNBC. Both carboplatin (CRB) and docetaxel (DTX) chemotherapies produced residual tumors that harbored mitochondria with significantly increased areas, volumes, and perimeters in both PDX models. Additionally, treatment with the conventional combinations DTX plus CRB or Adriamycin plus cyclophosphamide (AC), led to reduced mitochondrial branching and elongation. In contrast, DTX or CRB alone elicited model-specific changes in mitochondrial complexity. Further, the extensive intra-tumoral heterogeneity of mitochondrial structure in untreated PDX tumors significantly decreased in residual tumors. Analyses of LDs revealed significant and consistent elevation of the number and physical proximity of MLCs in residual tumors, congruent with our previous studies providing evidence for transcriptomic and proteomic rewiring of lipid metabolism in residual TNBC. These results highlight the potential for structure-based monitoring of chemotherapeutic metabolic reprogramming and suggest unique molecular mechanisms that may underlie chemoresistance in TNBC. Furthermore, our findings provide novel insights into a new type of intratumoral heterogeneity, that of mitochondrial intratumoral heterogeneity, which complements our understanding of the genomic, epigenomic, transcriptomic, and proteomic complexity of TNBC.

cancer biology↗
bioRxiv2024

The Staphylococcus aureus small non-coding RNA IsrR regulates TCA cycle activity and virulence

Staphylococcus aureus has evolved mechanisms to cope with low iron (Fe) availability in host tissues. S. aureus uses the ferric uptake transcriptional regulator (Fur) to sense titers of cytosolic Fe. Upon Fe depletion, apo-Fur relieves transcriptional repression of genes utilized for Fe uptake. We demonstrate that an S. aureus {Delta}fur mutant has decreased expression of acnA, which codes for the Fe-dependent enzyme aconitase. Decreased acnA expression prevented the {Delta}fur mutant from growing with amino acids as sole carbon and energy sources. Suppressor analysis determined that a mutation in isrR, which produces a regulatory RNA, permitted growth by decreasing isrR transcription. The decreased AcnA activity of the {Delta}fur mutant was partially relieved by an {Delta}isrR mutation. Directed mutation of bases predicted to facilitate the interaction between the acnA transcript and IsrR, decreased the ability of IsrR to control acnA expression in vivo and IsrR bound to the acnA transcript in vitro. IsrR also bound to the transcripts coding the alternate TCA cycle proteins sdhC, mqo, citZ, and citM. Whole cell metal analyses suggest that IsrR promotes Fe uptake and increases intracellular Fe not ligated by macromolecules. Lastly, we determined that Fur and IsrR promote infection using murine skin and acute pneumonia models. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/601953v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1ec27b2org.highwire.dtl.DTLVardef@1224b64org.highwire.dtl.DTLVardef@83cd49org.highwire.dtl.DTLVardef@11a9cea_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗
bioRxiv2023

Digital twinning of cardiac electrophysiology for congenital heart disease

In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in pediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools. We generate a dataset of electrophysiology simulations covering cell-to-organ level model parameters and utilizing rigorous mathematical models based on differential equations. We previously proposed Branched Latent Neural Maps (BLNMs) as an accurate and efficient means to recapitulate complex physical processes in a neural network. Here, we employ BLNMs to encode the parametrized temporal dynamics of in silico 12-lead electrocardiograms (ECGs). BLNMs act as a geometry-specific surrogate model of cardiac function for fast and robust parameter estimation to match clinical ECGs in pediatric patients. Identifiability and trustworthiness of calibrated model parameters are assessed by sensitivity analysis and uncertainty quantification.

bioengineering↗
bioRxiv2023

Genome assembly of the dyeing poison frog provides insights into the dynamics of transposable element and genome-size evolution

Genome size varies greatly across the tree of life and transposable elements are an important contributor to this variation. Among vertebrates, amphibians display the greatest variation in genome size, making them ideal models to explore the causes and consequences of genome size variation. However, high-quality genome assemblies for amphibians have, until recently, been rare. Here, we generate a high-quality genome assembly for the dyeing poison frog, Dendrobates tinctorius. We compare this assembly to publicly-available frog genomes and find evidence for both large-scale conserved synteny and widespread rearrangements between frog lineages. Comparing conserved orthologs annotated in these genomes revealed a strong correlation between genome size and gene size. To explore the cause of gene-size variation, we quantified the location of transposable elements relative to gene features and find that the accumulation of transposable elements in introns has played an important role in the evolution of gene size in D. tinctorius, while estimates of insertion times suggest that many insertion events are recent and species-specific. Finally, we show that the diversity and abundance of transposable elements in poison frog genomes can complicate genotyping efforts that rely on repetitive elements as sequence anchors. Our results show that transposable elements have clearly played an important role in the evolution of large genome size in D. tinctorius. Future studies are needed to fully understand the dynamics of transposable element evolution and to optimise primer or bait design for cost-effective population-level genotyping in species with large, repetitive genomes. SignificanceAmphibians display more variation in genome size than any other vertebrate lineage. Complexities associated with large genomes frequently hamper genome assembly and population genetic studies. Here we use long-read HiFi sequences to generate a high-quality 6.3 Gbp genome assembly of the poison frog Dendrobates tinctorius. We use this genome and leverage comparative genomics and de novo annotations to quantify aspects of genome evolution driven by repetitive transposable genetic elements. Our results provide support for the dynamic role that transposable elements play in driving the evolution of "genomic gigantism" in amphibians. We also show how transposable elements can be leveraged for cost-efficient population genetic studies using limited input material.

genetics↗
bioRxiv2023

Development of an MR-guided focused ultrasound (MRgFUS) lesioning approach for small and deep structures in the rat brain

ObjectiveHigh-intensity magnetic resonance-guided focused ultrasound (MRgFUS) is a noninvasive therapy to lesion brain tissue, used clinically in patients and preclinically in several animal models. Challenges with focused ablation in rodent brains can include skull and near-field heating and accurately targeting small and deep brain structures. We overcame these challenges by creating a novel method consisting of a craniectomy skull preparation, a high-frequency transducer (3 MHz) with a small ultrasound focal spot, a transducer positioning system with an added manual adjustment of [~]0.1 mm targeting accuracy, and MR acoustic radiation force imaging for confirmation of focal spot placement. MethodsThe study consisted of two main parts. First, two skull preparation approaches were compared. A skull thinning approach (n=7 lesions) was compared to a craniectomy approach (n=22 lesions), which confirmed a craniectomy was necessary to decrease skull and near-field heating. Second, the two transducer positioning systems were compared with the fornix chosen as a subcortical ablation target. We evaluated the accuracy of targeting using a high-frequency transducer with a small ultrasound focal spot and MR acoustic radiation force imaging. ResultsComparing a motorized adjustment system ([~]1 mm precision, n=17 lesions) to the motorized system with an added micromanipulator ([~]0.1 mm precision, n=14 lesions), we saw an increase in the accuracy of targeting the fornix by 133%. The described work allows for repeatable and accurate targeting of small and deep structures in the rodent brain, such as the fornix, enabling the investigation of neurological disorders in chronic disease models.

bioengineering↗
bioRxiv2023

YlaN is an iron(II) binding protein that functions to relieve Fur-mediated repression of gene expression in Staphylococcus aureus

Iron (Fe) is a trace nutrient required by nearly all organisms. As a result of the demand for Fe and the toxicity of non-chelated cytosolic ionic Fe, regulatory systems have evolved to tightly balance Fe acquisition and usage while limiting overload. In most bacteria, including the mammalian pathogen Staphylococcus aureus, the ferric uptake regulator (Fur) is the primary transcriptional regulator that controls the transcription of genes that code for Fe uptake and utilization proteins. YlaN was demonstrated to be essential in Bacillus subtilis unless excess Fe is added to the growth medium, suggesting a role in Fe homeostasis. Here, we demonstrate that YlaN is expendable in S. aureus; however, YlaN became essential upon Fe deprivation. A null fur allele bypassed the essentiality of YlaN. The transcriptional response of Fur derepression resulted in a reprogramming of metabolism to prioritize fermentative growth over respiratory growth. The absence of YlaN diminished the derepression of Fur-dependent transcription during Fe limitation. Bioinformatic analyses suggest that ylaN was recruited to Gram positive bacteria and once acquired was maintained in the genome as it co-evolved with Fur. Consistent with a role for YlaN in influencing Fur-dependent regulation, YlaN and Fur interacted in vivo. YlaN bound Fe(II) in vitro using oxygen or nitrogen ligands with an association constant that is consistent with a physiological role in Fe sensing and/or buffering. These findings have led to a model wherein YlaN is an Fe(II) binding protein that influences Fur-dependent regulation through direct interaction. ImportanceIron (Fe) is an essential nutrient for nearly all organisms. If Fe homeostasis is not maintained, Fe can accumulate in the cytosol where it is toxic. Questions remain about how cells efficiently balance Fe uptake and usage to prevent imbalance. Iron uptake and proper metalation of proteins are essential processes in the mammalian bacterial pathogen Staphylococcus aureus. Understanding the gene products involved in Fe ion regulation, uptake, and usage, as well as the physiological adaptations that S. aureus uses to survive in Fe-depleted conditions, will provide insight into the role that Fe has in pathogenesis. These data will also provide insight into the selective pressures imparted by the mammalian host.

microbiology↗
bioRxiv2023

Quorum-sensing agr system of Staphylococcus aureus primes gene expression for protection from lethal oxidative stress

The agr quorum-sensing system links Staphylococcus aureus metabolism to virulence, in part by increasing bacterial survival during exposure to lethal concentrations of H2O2, a crucial host defense against S. aureus. We now report that protection by agr surprisingly extends beyond post-exponential growth to the exit from stationary phase when the agr system is no longer turned on. Thus, agr can be considered a constitutive protective factor. Deletion of agr increased both respiration and fermentation but decreased ATP levels and growth, suggesting that {Delta}agr cells assume a hyperactive metabolic state in response to reduced metabolic efficiency. As expected from increased respiratory gene expression, reactive oxygen species (ROS) accumulated more in the agr mutant than in wild-type cells, thereby explaining elevated susceptibility of {Delta}agr strains to lethal H2O2 doses. Increased survival of wild-type agr cells during H2O2 exposure required sodA, which detoxifies superoxide. Additionally, pretreatment of S. aureus with respiration-reducing menadione protected {Delta}agr cells from killing by H2O2. Thus, genetic deletion and pharmacologic experiments indicate that agr helps control endogenous ROS, thereby providing resilience against exogenous ROS. The long-lived "memory" of agr-mediated protection, which is uncoupled from agr activation kinetics, increased hematogenous dissemination to certain tissues during sepsis in ROS-producing, wild-type mice but not ROS-deficient (Nox2-/-) mice. These results demonstrate the importance of protection that anticipates impending ROS-mediated immune attack. The ubiquity of quorum sensing suggests that it protects many bacterial species from oxidative damage.

microbiology↗
bioRxiv2023

CrOssing fiber Modeling in the Peritumoral Area using dMRI (COMPARI)

Visualization of fiber tracts around the tumor is critical for neurosurgical planning and preservation of crucial structural connectivity during tumor resection. Biophysical modeling approaches estimate fiber tract orientations from differential water diffusivity information of diffusion MRI. However, the presence of edema and tumor infiltration presents a challenge to visualize crossing fiber tracts in the peritumoral region. Previous approaches proposed free water modeling to compensate for the effect of water diffusivity in edema, but those methods were limited in estimating complex crossing fiber tracts. We propose a new cascaded multi-compartment model to estimate tissue microstructure in the presence of edema and pathological contaminants in the area surrounding brain tumors. In our model (COMPARI), the isotropic components of diffusion signal, including free water and hindered water, were eliminated, and the fiber orientation distribution (FOD) of the remaining signal was estimated. In simulated data, COMPARI accurately recovered fiber orientations in the presence of extracellular water. In a dataset of 23 patients with highly edematous brain tumors, the amplitudes of FOD and anisotropic index distribution within the peritumoral region were higher with COMPARI than with a recently proposed multi-compartment constrained deconvolution model. In a selected patient with metastatic brain tumor, we demonstrated COMPARIs ability to effectively model and eliminate water from the peritumoral region. The white matter bundles reconstructed with our model were qualitatively improved compared to those of other models, and allowed the identification of crossing fibers. In conclusion, the removal of isotropic components as proposed with COMPARI improved the bio-physical modeling of dMRI in edema, thus providing information on crossing fibers, thereby enabling improved tractography in a highly edematous brain tumor. This model may improve surgical planning tools to help achieve maximal safe resection of brain tumors.

bioengineering↗
bioRxiv2022

Choice of parcellation atlas might not be too critical for connectomic analysis

Connectomics has been a rapidly growing discipline in neuroimaging and neuroscience that evolved our understanding of the brain. Connectomics involves representing the brain as a network of regions, where the parcellation of the brain into regions using a template atlas is an integral part of the analysis. Over developmental and young adult cohorts of healthy individuals, we investigated how choosing parcellation atlases at certain resolutions affect sex classification and age prediction tasks performed using deep learning on structural connectomes. Datasets were processed on a total of 35 parcellations, where the only significant difference was observed for age prediction on the developmental cohort with a slight improvement on higher resolutions. This indicates that choice of parcellation scheme is generally not critical for deep learningbased age prediction and sex classification. Therefore, results between studies using different parcellation schemes could be comparable and repeating analyses on multiple atlases might be unnecessary.

neuroscience↗