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Manning, K.

Publications and source records attributed to Manning, K..

8 recordsLinked to original sources
bioRxiv2026

Phycosphere-associated bacteria differentially impact accessibility of dust-bound iron to model diatom Phaeodactylum tricornutum

In marine ecosystems, phytoplankton growth is frequently limited by iron, a micronutrient, due to its poor solubility from major sources such as atmospheric dust. Many phytoplankton cannot access dust-bound iron independently, and processes that solubilize this iron remain poorly understood. Here, we investigated whether bacterial partners can enhance phytoplankton growth under iron-limited conditions by facilitating utilization of dust-bound iron. Our study focused on Phaeodactylum tricornutum, a model diatom that is adapted to low iron growth conditions, grown in co-culture with bacteria isolated from its phycosphere. In iron-limited experiments using mineral dust as the sole iron source, the addition of Marinobacter significantly enhanced diatom growth compared to axenic controls, whereas Stappia significantly suppressed it. However, under iron-replete conditions, neither bacterium affected growth. These results indicated that under low-iron conditions, Marinobacter actively alleviates iron deficiency. Co-cultured bacterial cell abundances remained at least an order of magnitude lower than diatom cells. Marinobacter also enhanced algal growth within days of dust addition to established Fe-limited co-cultures, indicating its beneficial effect on P. tricornutum was not unique to a system in which it was newly introduced. Exometabolomic profiling comparing the axenic diatom and co-cultures revealed a suite of condensed aromatic organosulfur and peptide-like compounds associated with bacterial presence, as well as compounds that appeared to be unique to each co-culture, hinting at a molecular underpinning of each strains impact. Our findings demonstrate that low-abundance members of the phycosphere community can have a significant impact on host growth by modulating the accessibility of dust-bound Fe.

microbiology↗
bioRxiv2025

Extracellular Vesicle Gene Expression Enables Sensitive Detection of Colorectal Neoplasia

BACKGROUND & AIMSExtracellular vesicles (EVs), including exosomes, are emerging as promising carriers of disease-specific biomarkers due to their molecular cargo reflective of cellular origin. While cell-free DNA (cfDNA) methylation assays have recently been developed for colorectal cancer (CRC) screening and perform well for cancer detection, they show limited sensitivity for advanced adenomas (AA), a key precursor in the CRC pathway. To address this gap, we sought to determine whether other blood-based analytes, specifically EV-derived long and small RNA transcriptomes and EV proteomes, could improve detection of AA and early-stage CRC. In a prospective cohort, we performed a head-to-head comparison of EV transcriptomics, EV proteomics, and their combinations against cfDNA methylation, all measured from the same patient cohort, enabling a direct performance benchmark and identification of the most promising modality for larger-scale CRC screening studies. METHODSWe prospectively collected pre-colonoscopy plasma samples from 220 participants across three clinical sites. EVs were isolated and profiled using long RNA-seq, small RNA-seq, and Olink-based proteomics. cfDNA was analyzed for methylation patterns. Analyses were conducted according to a statistical analysis plan pre-specified before unblinding. Machine learning models were developed under nested cross-validation to evaluate sensitivity for detecting AA and CRC at a fixed specificity of 91%, consistent with clinical screening benchmarks. RESULTSEV-derived gene expression on long RNA demonstrated the highest sensitivity for detecting AA as well as CRC: 54.8% (95% CI, 26.4%-75.6%) for AA and 94.1% (95% CI, 79.2%-100%) for CRC. This outperformed cfDNA methylation (33.6% [95% CI, 9.7%-60.3%] for AA, 81.3% [95% CI, 64.6%- 93.9%] for CRC) and other EV-based modalities. In addition, for small RNA the sensitivities were 42.6% (95% CI, 35.9%-47.4%) for AA, and 78.9% (95% CI, 69.2%-83.0%) for CRC, while for proteomics the sensitivities were 30.0% (95% CI, 13.9%-40.0%) for AA, and 64.2% (95% CI, 43.6%-87.2%) for CRC. Transcriptomic profiles revealed progressive enrichment of hallmarks of cancer pathways, including apoptosis and epithelial-mesenchymal transition, across disease stages. Multiomic integration did not improve performance beyond EV transcriptomics alone. CONCLUSIONSBy directly comparing multiple EV-based and cfDNA analytes within the same patient cohort, we found that EV transcriptomics delivers the strongest diagnostic performance for both AA and CRC. This rigorous benchmarking approach allows clear prioritization of the most promising modality guiding the design of larger validation studies and accelerating development of next-generation, blood-based CRC screening tools.

genomics↗
bioRxiv2025

Deep Profiling of EV Long RNAs Reveals Biofluid-Specific Transcriptomes and Splicing Landscapes

RNA profiling of extracellular vesicles (EVs) from human biofluids has historically been limited to small RNA species, with long RNAs--such as mRNA exons and long non-coding RNAs--remaining largely underexplored. Moreover, the dominance of hematopoietic-derived EVs in complex fluids like plasma has posed significant challenges for detecting low-abundance, tissue-specific transcripts. Here, we establish foundational transcriptomic maps of long RNAs in EVs from plasma, urine, and cerebrospinal fluid (CSF) using ultra-deep whole transcriptome sequencing (WTS), revealing both fluid-specific and shared expression and splicing signatures. We then introduce a targeted RNA capture method that enriches for all protein-coding and long non-coding transcripts, dramatically enhancing sensitivity for gene and splice variant detection. Applying this approach to brain-specific transcripts, we achieve >85-fold enrichment of target gene expression and, on average, 3.1-fold increase in detected splice junctions per gene compared to untargeted WTS. As a proof of concept, we apply this brain-targeted RNA panel to EVs from plasma in a Parkinsons disease cohort of 40 plasma samples and compare its performance to exome sequencing as well as untargeted WTS. This work advances EV transcriptomics into the long RNA domain and establishes a framework for high-sensitivity, noninvasive biomarker profiling across tissues and diseases.

genomics↗
bioRxiv2024

Annotation of DOM Metabolomes with an Ultrahigh Resolution Mass Spectrometry Molecular Formula Library

Increased accessibility of liquid chromatography mass spectrometry (LC-MS) metabolomics instrumentation and software have expanded their use in studies of dissolved organic matter (DOM) and exometabolites released by microbes. Current strategies to annotate metabolomes generally rely on matching tandem MS/MS spectra to databases of authentic standards. However, spectral matching approaches typically have low annotation rates for DOM. An alternative approach is to annotate molecular formula based on accurate mass and isotopic fine structure measurements that can be obtained from state-of-the-art ultrahigh resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FT-ICR-MS), but instrument accessibility for large metabolomic studies is generally limited. Here, we describe a strategy to annotate exometabolomes obtained from lower resolution LC-MS systems by matching metabolomic features to a molecular formula library generated for a representative sample analyzed by LC-21T FT-ICR MS. The molecular formula library approach successfully annotated 53% of exometabolome features of the marine diatom Phaeodactylum tricornutum - a nearly ten-fold increase over the 6% annotation rate achieved using a conventional MS/MS approach. There was 94% agreement between assigned formula that were annotated with both approaches, and mass error analysis of the discrepancies suggested that the FT-ICR MS formula assignments were more reliable. Differences in the exometabolome of P. tricornutum grown under iron replete and iron limited conditions revealed 668 significant metabolites, including a suite of peptide-like molecules released by P. tricornutum in response to iron deficiency. These findings demonstrate the utility of FT-ICR MS formula libraries for extending the accuracy and comprehensiveness of metabolome annotations.

molecular biology↗
bioRxiv2023

Myofascial Trigger Point (MTrP) Size and Elasticity Properties Can Be Used to Differentiate Active and Latent MTrPs in Lower Back Skeletal Muscle

Myofascial Trigger Points (MTrPs) are localized contraction knots that develop after muscle overuse or an acute trauma. Significant work has been done to understand, diagnose, and treat MTrPs in order to improve patients suffering from their effects. However, effective non-invasive diagnostic tools are still a missing gap in both understanding and treating MTrPs. Effective treatments for patients suffering from MTrP mediated pain require a means to measure MTrP properties quantitatively and diagnostically both prior to and during intervention. Further, quantitative measurements of MTrPs are often limited by the availability of equipment and training. Here we develop ultrasound (US) based diagnostic metrics that clinicians can use during patient diagnosis and treatment. We highlight the advantages and limitations of previous US-based approaches that utilize elasticity theory. We show how US-based measurements can distinguish Active from Latent MTrPs. We demonstrate that Active MTrPs tend to be smaller, stiffer, and deeper in the muscle tissue. We provide evidence that more than one MTrP within a single US-image field increases the stiffness of neighboring MTrPs. Finally, we highlight a combination of metrics (depth, thickness, and stiffness) that can be used to assess individual MTrPs in combination with standard clinical assessments.

biophysics↗
bioRxiv2021

Durability of immune responses to the BNT162b2 mRNA vaccine

The development of the highly efficacious mRNA vaccines in less than a year since the emergence of SARS-CoV-2 represents a landmark in vaccinology. However, reports of waning vaccine efficacy, coupled with the emergence of variants of concern that are resistant to antibody neutralization, have raised concerns about the potential lack of durability of immunity to vaccination. We recently reported findings from a comprehensive analysis of innate and adaptive immune responses in 56 healthy volunteers who received two doses of the BNT162b2 vaccination. Here, we analyzed antibody responses to the homologous Wu strain as well as several variants of concern, including the emerging Mu (B.1.621) variant, and T cell responses in a subset of these volunteers at six months (day 210 post-primary vaccination) after the second dose. Our data demonstrate a substantial waning of antibody responses and T cell immunity to SARS-CoV-2 and its variants, at 6 months following the second immunization with the BNT162b2 vaccine. Notably, a significant proportion of vaccinees have neutralizing titers below the detection limit, and suggest a 3rd booster immunization might be warranted to enhance the antibody titers and T cell responses.

immunology↗
bioRxiv2017

Evidence that loss of consciousness under anesthesia is not associated with impaired stimulus representation in auditory cortex

The mechanism whereby anesthetics cause loss of consciousness (LOC) is poorly understood. Current theories suggest that impaired representation of information in cortico-thalamic networks contributes to LOC under anesthesia. We sought to determine whether such changes are present in auditory cortex using information theoretic analysis of multiunit responses in rats. We tested the effects of three agents with different molecular targets: isoflurane, which acts at multiple pre- and postsynaptic loci, propofol, which acts primarily on GABAA receptors, and dexmedetomidine, an 2 adrenergic agonist. We reasoned that changes in the representation of sensory stimuli causative for LOC would be present regardless of the molecular target of the anesthetic. All three agents caused LOC, as assayed by the loss of righting reflex (LORR). We presented acoustic stimuli that varied across a wide range of temporal and spectral dynamics under control, sub-hypnotic (i.e. dose too low to cause LORR), just-hypnotic (a dose just sufficient to cause LORR) and recovery conditions. Changes in mutual information (MI) between the stimulus and spike responses under anesthesia diverged in two ways from predictions of a model in which stimulus representation is impaired upon LOC. First, the sign of changes in MI was agent-specific: MI increased under dexmedetomidine, while it decreased under isoflurane and propofol. Second, there was no consistent change in MI when transitioning from sub-hyptnotic to just-hypnotic doses: for none of the agents did MI decrease at the higher dose, and in some cases MI actually increased relative to the sub-hypnotic dose. Changes in MI under anesthesia were strongly correlated with changes in precision and reliability of spike timing, consistent with the importance of temporal stimulus features in driving auditory cortical activity. These data indicate that primary sensory cortex is not the locus for changes in information representation causative for LOC under anesthesia.

neuroscience↗