Biology subjects

Hanson, C.

Publications and source records attributed to Hanson, C..

12 recordsLinked to original sources

bioRxiv2025

Cell villages and Dirichlet modeling map human cell fitness genetics

The capacity of cells to proliferate and survive is central to development and disease. Assays that measure cell fitness are therefore a cornerstone of biology, but traditional techniques lack donor diversity and have high technical variability that impedes scale and reproducibility. To overcome these barriers, we designed and validated a "cell village"-based fitness screening approach using pooled cultures of 12-39 genetically distinct human neural progenitor cell (NPC) lines. We also developed Townlet to establish a foundational statistical framework based on Dirichlet regression for analyzing proportional data from cell villages. Applying these systems, we identified hyperproliferation in NPCs harboring the autism risk factor chromosome 16p11.2 deletion, mapped common genetic variants near ZFHX3 associated with NPC proliferation rate, and discovered genetic modifiers of lead (Pb) sensitivity implicating ARNT2. Together, these experimental and analytical tools advance a scalable, genetically diverse in vitro platform for dissecting human variation in cell fitness and gene-environment interactions.

genetics↗

bioRxiv2025

Polyclonal origins of human premalignant colorectal lesions

Cancer is generally thought to be caused by expansion of a single mutant cell1. However, analyses of early colorectal cancer lesions suggest that tumors may instead originate from multiple, genetically distinct cell populations2,3. Detecting polyclonal tumor initiation is challenging in patients, as it requires profiling early-stage lesions before clonal sweeps obscure diversity. To investigate this, we analyzed normal colorectal mucosa, benign and dysplastic premalignant polyps, and malignant adenocarcinomas (123 samples) from six individuals with familial adenomatous polyposis (FAP). Individuals with FAP have a germline heterozygous APC mutation, predisposing them to colorectal cancer and numerous premalignant polyps by early adulthood4. Whole-genome and/or whole-exome sequencing revealed that many premalignant polyps--40% with benign histology and 28% with dysplasia--were composed of multiple genetic lineages that diverged early, consistent with polyclonal origins. This conclusion was reinforced by whole-genome sequencing of single crypts from multiple polyps in additional patients which showed limited sharing of mutations among crypts within the same lesion. In some cases, multiple distinct APC mutations co-existed in different lineages of a single polyp, consistent with polyclonality. These findings reshape our understanding of early neoplastic events, demonstrating that tumor initiation can arise from the convergence of diverse mutant clones. They also suggest that cell-intrinsic growth advantages alone may not fully explain tumor initiation, highlighting the importance of microenvironmental and tissue-level factors in early cancer evolution.

cancer biology↗

bioRxiv2024

A tale of two tumors: differential, but detrimental, effects of glioblastoma extracellular vesicles (EVs) on normal human brain cells

Glioblastomas (GBMs) are dreadful brain tumors with abysmal survival outcomes. GBM EVs dramatically affect normal brain cells (largely astrocytes) constituting the tumor microenvironment (TME). EVs from different patient-derived GBM spheroids induced differential transcriptomic, secretomic, and proteomic effects on cultured astrocytes/brain tissue slices as GBM EV recipients. The net outcome of brain cell differential changes nonetheless converges on increased tumorigenicity. GBM spheroids and brain slices were derived from neurosurgical patient tissues following informed consent. Astrocytes were commercially obtained. EVs were isolated from conditioned culture media by ultrafiltration, ultraconcentration, and ultracentrifugation. EVs were characterized by nanoparticle tracking analysis, electron microscopy, biochemical markers, and proteomics. Astrocytes/brain tissues were treated with GBM EVs before downstream analyses. EVs from different GBMs induced brain cells to alter secretomes with pro-inflammatory or TME-modifying (proteolytic) effects. Astrocyte responses ranged from anti-viral gene/protein expression and cytokine release to altered extracellular signal-regulated protein kinase (ERK1/2) signaling pathways, and conditioned media from EV-treated cells increased GBM cell proliferation. Thus, astrocytes/brain slices treated with different GBM EVs underwent non-identical changes in various omics readouts and other assays, indicating "personalized" tumor-specific GBM EV effects on the TME. This raises concern regarding reliance on "model" systems as a sole basis for translational direction. Nonetheless, net downstream impacts from differential cellular and TME effects still led to increased tumorigenic capacities for the different GBMs.

cancer biology↗

bioRxiv2023

Decreased efficacy of a COVID-19 vaccine due to mutations present in early SARS-CoV-2 variants of concern

With the SARS-CoV-2 virus still circulating and evolving, there remains an outstanding question if variant-specific vaccines represent the optimal path forward, or if other strategies might be more efficacious towards providing broad protection against emerging variants. Here, we examine the efficacy of strain-specific variants of our previously reported, pan-sarbecovirus vaccine candidate, DCFHP-alum, a ferritin nanoparticle functionalized with an engineered form of the SARS-CoV-2 spike protein. In non-human primates, DCFHP-alum elicits neutralizing antibodies against all known VOCs that have emerged to date and SARS-CoV-1. During development of the DCFHP antigen, we investigated the incorporation of strain-specific mutations from the major VOCs that had emerged to date: D614G, Epsilon, Alpha, Beta, and Gamma. Here, we report the biochemical and immunological characterizations that led us to choose the ancestral Wuhan-1 sequence as the basis for the final DCFHP antigen design. Specifically, we show by size exclusion chromatography and differential scanning fluorimetry that mutations in the VOCs adversely alter the antigens structure and stability. More importantly, we determined that DCFHP without strain-specific mutations elicits the most robust, cross-reactive response in both pseudovirus and live virus neutralization assays. Our data suggest potential limitations to the variant-chasing approach in the development of protein nanoparticle vaccines, but also have implications for other approaches including mRNA-based vaccines.

biochemistry↗

bioRxiv2023

Temporal Dynamics of Activity in Default Mode Network Suggests a Role in Top-down processing

The default mode network (DMN) is a collection of brain regions including midline frontal and parietal structures, medial and lateral temporal lobes, and lateral parietal cortex. Although there is evidence that the network can be subdivided into at least two subcomponents, the network reliably exhibits highly correlated activity both at rest and during task performance. Current understanding regarding the function of the DMN rests on a large body of research indicating that activity in the network decreases during task epochs of experimental paradigms relative to inter-trial intervals. A seeming contradiction arises when the experimental paradigm includes tasks involving autobiographical memory, thinking about ones self, planning for the future, or social cognition. In such cases, the DMNs activity increases and is correlated with attentional networks. Some have therefore concluded that the DMN supports advanced human cognitive abilities such as interoceptive processing and theory of mind. This conclusion may be called into question by evidence of correlated activity in homologous brain regions in other, even non-primate, species. Thus, there are contradictory findings related to the function of the DMN that have been difficult to integrate into a coherent theory regarding its function. Using data from the Human Connectome Project, we explore the temporal dynamics of activity in different regions of the DMN in relation to stimulus presentation. We show that generally the dorsal portion of the network exhibits only a transient initial decrease in activity at the start of trials that increases over trial duration. The ventral component often has more similarity in its time course to that of task-activated areas. We propose that task-associated ramping dynamics in the network are incompatible with a task-negative view of the DMN and propose the dorsal and ventral sub-components of network may rather work together to support bottom-up salience detection and subsequent top-down voluntary action. In this context, we re-interpret the body of anatomical and neurophysiological experimental evidence, arguing that this interpretation can accommodate the seeming contradictions regarding DMN function in the extant literature.

neuroscience↗

bioRxiv2022

A ferritin-based COVID-19 nanoparticle vaccine that elicits robust, durable, broad-spectrum neutralizing antisera in non-human primates

While the rapid development of COVID-19 vaccines has been a scientific triumph, the need remains for a globally available vaccine that provides longer-lasting immunity against present and future SARS-CoV-2 variants of concern (VOCs). Here, we describe DCFHP, a ferritin-based, protein-nanoparticle vaccine candidate that, when formulated with aluminum hydroxide as the sole adjuvant (DCFHP-alum), elicits potent and durable neutralizing antisera in non-human primates against known VOCs, including Omicron BQ.1, as well as against SARS-CoV-1. Following a booster [~]one year after the initial immunization, DCFHP-alum elicits a robust anamnestic response. To enable global accessibility, we generated a cell line that can enable production of thousands of vaccine doses per liter of cell culture and show that DCFHP-alum maintains potency for at least 14 days at temperatures exceeding standard room temperature. DCFHP-alum has potential as a once-yearly booster vaccine, and as a primary vaccine for pediatric use including in infants.

immunology↗

bioRxiv2021

The B.1.427/1.429 (epsilon) SARS-CoV-2 variants are more virulent than ancestral B.1 (614G) in Syrian hamsters

As novel SARS-CoV-2 variants continue to emerge, it is critical that their potential to cause severe disease and evade vaccine-induced immunity is rapidly assessed in humans and studied in animal models. In early January 2021, a novel variant of concern (VOC) designated B.1.429 comprising 2 lineages, B.1.427 and B.1.429, was originally detected in California (CA) and shown to enhance infectivity in vitro and decrease antibody neutralization by plasma from convalescent patients and vaccine recipients. Here we examine the virulence, transmissibility, and susceptibility to pre-existing immunity for B 1.427 and B 1.429 in the Syrian hamster model. We find that both strains exhibit enhanced virulence as measured by increased body weight loss compared to hamsters infected with ancestral B.1 (614G), with B.1.429 causing the most body weight loss among all 3 lineages. Faster dissemination from airways to parenchyma and more severe lung pathology at both early and late stages were also observed with B.1.429 infections relative to B.1. (614G) and B.1.427 infections. In addition, subgenomic viral RNA (sgRNA) levels were highest in oral swabs of hamsters infected with B.1.429, however sgRNA levels in lungs were similar in all three strains. This demonstrates that B.1.429 replicates to higher levels than ancestral B.1 (614G) or B.1.427 in the upper respiratory tract (URT) but not in the lungs. In multi-virus in-vivo competition experiments, we found that epsilon (B.1.427/B.1.429) and gamma (P.1) dramatically outcompete alpha (B.1.1.7), beta (B.1.351) and zeta (P.2) in the lungs. In the URT gamma, and epsilon dominate, but the highly infectious alpha variant also maintains a moderate size niche. We did not observe significant differences in airborne transmission efficiency among the B.1.427, B.1.429 and ancestral B.1 (614G) variants in hamsters. These results demonstrate enhanced virulence and high relative fitness of the epsilon (B.1.427/B.1.429) variant in Syrian hamsters compared to an ancestral B.1 (614G) strain. Author SummaryIn the last 12 months new variants of SARS-CoV-2 have arisen in the UK, South Africa, Brazil, India, and California. New SARS-CoV-2 variants will continue to emerge for the foreseeable future in the human population and the potential for these new variants to produce severe disease and evade vaccines needs to be understood. In this study, we used the hamster model to determine the epsilon (B.1.427/429) SARS-CoV-2 strains that emerged in California in late 2020 cause more severe disease and infected hamsters have higher viral loads in the upper respiratory tract compared to the prior B.1 (614G) strain. These findings are consistent with human clinical data and help explain the emergence and rapid spread of this strain in early 2021.

microbiology↗

bioRxiv2021

A FOXN1 mutation competitively displaces wild-type FOXN1 from higher order nuclear condensates to cause immunodeficiency

The transcription factor FOXN1 is a master regulator of thymic epithelial cell development and function. Here we demonstrate that FOXN1 expression is differentially regulated during organogenesis and participates in multi-molecular nuclear condensates essential for the factors transcriptional activity. FOXN1s C-terminal sequence regulates the diffusion velocity within these aggregates and modulates the binding to proximal gene regulatory regions. These dynamics are significantly altered in a patient with a mutant FOXN1 which is modified in its C-terminal sequence. This mutant is transcriptionally inactive and acts as a dominant negative factor displacing wild-type FOXN1 from condensates and causing athymia and severe lymphopenia in heterozygotes. Expression of the mutated mouse ortholog, selectively impairs mouse thymic epithelial cell (TEC) differentiation revealing a gene dose dependency for individual TEC subtypes. We have therefore identified the cause for a primary immunodeficiency disease and determined the mechanism by which this FOXN1 gain-of-function mutant mediates its dominant negative effect.

immunology↗

bioRxiv2020

Evaluation of the Abbott ARCHITECT HIV Ag/Ab Combo Assay for Determining Recent HIV-1 Infection

BackgroundGiven the challenges and costs associated with implementing HIV-1 incidence assay testing, there is great interest in evaluating the use of commercial HIV diagnostic tests for determining recent HIV infection. A diagnostic test with the capability of providing reliable data for the determination of recent HIV infection without substantial modifications to the test protocol would have a significant impact on HIV surveillance. The Abbott ARCHITECT HIV Ag/Ab Combo Assay is an antigen/antibody immunoassay, which meets the criteria as the first screening test in the recommended HIV laboratory diagnostic algorithm for the United States. MethodsIn this study, we evaluated the performance characteristics of the ARCHITECT HIV Ag/Ab Combo signal-to-cutoff ratio (S/Co) for determining recent infection, including estimation of the mean duration of recent infection (MDRI) and false recent rate (FRR), and selection of recency cutoffs. ResultsThe MDRI estimates for the S/Co recency cutoff of 400 is within the 4 to 12 months range recommended for HIV incidence assays, and the FRR rate for this cutoff was 1.5%. Additionally, ARCHITECT Combo S/Co values were compared relative to diagnostic test results from two prior prospective HIV-1 diagnostic studies in order to validate the use of the S/Co for both diagnostic and recency determination. ConclusionDual-use of the ARCHITECT Combo assay data for diagnostic and incidence purposes would reduce the need for separate HIV incidence testing and allow for monitoring of recent infection for incidence estimation and other public health applications.

microbiology↗

bioRxiv2020

DECODING SECOND ORDER ISOMORPHISMS IN THE BRAIN: The case of colors and letters.

We introduce a new method for decoding neural data from fMRI. It is based on two assumptions, first that neural representation is distributed over networks of neurons embeded in voxel noise and second that the stimuli can be decoded as learned relations from sets of categorical stimuli. We illustrate these principles with two types of stimuli, color (wavelength) and letters (visual shape), both of which have early visual system response, but at the same time must be learned within a given function or category (color contrast, alphabet). Key to the decoding method is reducing the stimulus cross-correlation by a matched noise voxel sample by normalizing the stimulus voxel matrix thus unmasking a highly discriminative neural profile per stimulus. Projection of this new voxel space (ROI) to a smaller set of dimensions (with e.g., non-metric Multidimensional scaling), the relational information takes a unique geometric form revealing functional relationships between sets of stimuli, defined by R. Shepard, as second-order isomorphisms (SOI). In the case of colors the SOI appears as a nearly equally spaced set of wavelengths arranged in a color wheel, with a gap between the "purples" and "reds" (consistent with the gap in the original Ekmans color set). In the case of letters, a cluster space resulted from the decorrelated voxel neural profiles, which matched the phrase structure of the mnemonic used for more than 100 years to teach children the alphabet (across multiple languages), The Alphabet Song.

neuroscience↗

bioRxiv2018

Genome-wide non-coding variant interpretation improves discovery of transcriptional regulators of drug response

Identification of functional non-coding variants (polymorphisms) and their mechanistic interpretation is a major challenge of modern genomics, especially for precision medicine. Transcription factor (TF) binding profiles and epigenomic landscapes in reference samples can help us functionally annotate the genome, but do not provide ready answers regarding the effects of non-coding variants. A promising computational approach is to build models that predict TF-DNA binding from sequence, and use such models to score a variants impact on TF binding strength. Here, we asked if this mechanistic approach to variant interpretation can be combined with information on genotype-phenotype associations to discover important transcription factors regulating phenotypic variation among individuals. We developed a statistical approach that integrates phenotype, genotype, gene expression, TF ChIP-seq and Hi-C chromatin interaction data to answer this question. Using drug sensitivity measured in lymphoblastoid cell lines as the phenotype of interest, we tested if the non-coding variants statistically linked to the phenotype are enriched for strong predicted impact on DNA-binding strength of a TF, and used this test to identify TFs regulating individual differences in the phenotype. Our method relies on a new method for predicting variant impact on TF-DNA binding, that uses a combination of biophysical modelling and machine learning. We report statistical and literature-based support for many of the TFs discovered here as regulators of drug response variation. We show that the use of mechanistically driven variant impact predictors can identify TF-drug associations that would otherwise be missed. We examined in depth the evidence underlying one reported association - that of the transcription factor ELF1 with the drug doxorubicin - and identified several genes that may mediate this regulatory relationship.

bioinformatics↗

bioRxiv2017

Principled Multi-Omic Analysis Reveals Gene Regulatory Mechanisms Of Phenotype Variation

Recent studies have analyzed large scale data sets of gene expression to identify genes associated with inter-individual variation in phenotypes ranging from cancer sub-types to drug sensitivity, promising new avenues of research in personalized medicine. However, gene expression data alone is limited in its ability to reveal cis-regulatory mechanisms underlying phenotypic differences. In this study, we develop a new probabilistic model, called pGENMi, that integrates multi-omics data to investigate the transcriptional regulatory mechanisms underlying inter-individual variation of a specific phenotype - that of cell line response to cytotoxic treatment. In particular, pGENMi simultaneously analyzes genotype, DNA methylation, gene expression and transcription factor (TF)-DNA binding data, along with phenotypic measurements, to identify TFs regulating the phenotype. It does so by combining statistical information about expression quantitative trait loci (eQTLs) and expression-correlated methylation marks (eQTMs) located within TF binding sites, as well as observed correlations between gene expression and phenotype variation. Application of pGENMi to data from a panel of lymphoblastoid cell lines treated with 24 drugs, in conjunction with ENCODE TF ChIP data, yielded a number of known as well as novel TF-drug associations. Experimental validations by TF knock-down confirmed 41% of the predicted and tested associations, compared to a 12% confirmation rate of tested non-associations (controls). Extensive literature survey also corroborated 62% of the predicted associations above a stringent threshold. Moreover, associations predicted only when combining eQTL and eQTM data showed higher precision compared to an eQTL-only or eQTM-only analysis with the same method, further demonstrating the value of multi-omic integrative analysis.

genomics↗