Biology subjects

Hale, J.

Publications and source records attributed to Hale, J..

12 recordsLinked to original sources

bioRxiv2026

Scalable platform for cellular and biochemical screening of combinatorial small-molecule libraries in droplets

A new pattern of hit discovery is emerging with the rise of chemocentric modalities, such as chemical induced proximity (CIP). Synthesis and functional screening of dynamic, purpose-built libraries, such as E3 ligase biased libraries for targeted protein degradation (TPD), is redefining the druggable landscape. However, this new paradigm arguably lies beyond the remit of conventional screening methods which have been optimized for static, diversity-oriented libraries. To address this gap, we developed microfluidic compound screening in droplets (MicDrop), a scalable platform where purpose-built DNA-encoded one-bead one-compound library members are individually tested at high concentrations in pico-liter sized droplets for either biochemical or cellular function. A proof-of-concept CRBN library demonstrated the robustness of the workflow through an IKZF3 degradation screen which discovered an unexpected succinimide-based IKZF3 degrader, while reproducing the relative potency ranking of reference compounds. Screening of a prospective VHL library for CDO1 recruitment and degradation demonstrated that orthogonal assays gave an informative consensus hit list and an actionable machine-learning (ML) recruitment model. These findings establish a blueprint for intentional discovery of chemical inducers of proximity, while producing reliable data to accelerate ML-based design-make-test-analyze (DMTA) cycles in pursuit of new therapeutics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/730915v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@12de3cborg.highwire.dtl.DTLVardef@1c6618dorg.highwire.dtl.DTLVardef@12ea42eorg.highwire.dtl.DTLVardef@11cea77_HPS_FORMAT_FIGEXP M_FIG C_FIG

Cell Biology↗

bioRxiv2026

Temporal Dissociation of Syntactic Disambiguation and Memory Retrieval during Sentence Processing: Naturalistic MEG Evidence from Interpretable Models

Human sentence comprehension proceeds word-by-word, with prior research proposing two central sources of cognitive demand during incremental processing: forward-looking disambiguation of the incoming information stream, and backward-looking retrieval of information associated with previous words from working memory. Recent work has shown that Transformer-based language models successfully generate predictions about sentence processing load in human psycho- and neurolinguistic data by operationalizing disambiguation cost as next-token surprisal, and memory retrieval cost as normalized attention entropy (NAE). Such models, however, remain difficult to interpret as it is not well understood what factors play causally into the decision to assign a cost value to a given word in such artificial neural networks. Here, we present interpretable and cognitively grounded models of disambiguation and memory retrieval and evaluate their neural alignment and spatio-temporal correlates using human magnetoencephalography responses to naturalistic narrative speech. Multivariate temporal response function modeling demonstrates firstly that these human-bias-informed models fare equally well in accounting for observed human language processing data as their Transformer counterparts. This same modeling framework then suggests that surprisal and NAE temporally dissociate in the cortical language network -- surprisal being predictive of bilateral superior temporal gyrus and supramarginal gyrus activation [~]300-500 ms, and NAE being predictive of activity in the same regions, but later [~]750-850 ms. By demonstrating that interpretable neurocomputational models can achieve meaningful brain alignment while maintaining explanatory transparency, this work offers a methodological blueprint for bridging the gap between algorithmic theory and neural implementation.

neuroscience↗

bioRxiv2026

AAV-Delivered RNAi Targeting Mutant LDB3 Prevents and Reverses Myofibrillar Myopathy through Mechanosignaling Restoration

The autosomal dominant p.Ala165Val mutation in LIM Domain Binding Protein 3 (LDB3) causes myofibrillar myopathy marked by Z-disc disruption, accumulation of filamin-C (FLNc) and chaperone proteins, and progressive muscle weakness. We previously showed that this mutation interferes with the LDB3-protein kinase C alpha (PKC)-FLNc mechanosensing axis and impairs chaperone-assisted selective autophagy (CASA), establishing a gain-of-function mechanism. In this study, we examined whether mutant allele-specific knockdown could reverse the disease or mitigate disease progression in-vivo. A single intramuscular-injection of an AAV9-delivered microRNA-based shRNA produced substantial knockdown of mutant Ldb3 transcripts and protein in Ldb3Ala165Val/+ knock-in mice treated either before or after the onset of pathology. Treatment after disease onset reduced filamin-C and CASA protein aggregates and improved muscle strength, whereas early intervention prevented development of molecular and histological features of myopathy. Phosphoproteomic profiling further showed broad remodeling of dysregulated phosphorylation networks, including restoration of PKC-responsive sites and normalization of altered sarcomeric and cytoskeletal signaling observed in Ldb3Ala165Val/+ mice. These findings identify disruption of the LDB3-PKC-FLNc mechanosensing pathway as a central disease driver and suggest that restoring this signaling axis may complement mutant allelespecific RNA interference (RNAi). Overall, our results support RNAi as a promising therapeutic strategy for dominant LDB3-related myofibrillar myopathy.

neuroscience↗

bioRxiv2024

A genotype-first approach identifies variants for orofacial clefts and other phenotypes in dogs

Dog breeding promotes within-group homogeneity through conformation to strict breed standards, and also drives between-group heterogeneity in pursuit of characteristic breed traits. There are over 350 recognized dog breeds that provide the foundation for investigating the genetic basis of phenotypic diversity. Typically, breed standard phenotypes such as stature, fur length, and craniofacial structure are analyzed in genetic association studies. However, such analyses are limited to the assayed phenotypes, leaving difficult to measure phenotypic subtleties potentially overlooked. In this study, the genotype-first approach was adapted to the dog genome to investigate coding variation from over 2000 dogs, leading to discoveries of new mutations related to craniofacial morphology and stature. Breed-enriched variants were prioritized according to gene constraint, which was calculated using a mutation model derived from trinucleotide substitution probabilities in the dog. Among the discovered variants was a splice-acceptor mutation in PDGFRA associated with bifid nose, a characteristic trait of Catalburun dogs, implicating the genes role in midline closure, and a frameshift mutation in LCORL associated with large canine body size, thus highlighting the importance of allelic heterogeneity in selection for breed traits. Most priority variants were not associated with genomic signatures for breed differentiation, as these regions were enriched for constrained genes intolerant to nonsynonymous variation, suggesting a model of breed phenotype diversification based on regulatory changes to essential genes. Identification of trait-associated variants in dogs informs new biological roles for genes. Improved collection of breed disease risk data, along with increased breed representation, will drive further discoveries.

genomics↗

bioRxiv2024

Le Petit Prince Hong Kong (LPPHK): Naturalistic fMRI and EEG data from older Cantonese speakers

Currently, the field of neurobiology of language is based on data from only a few Indo-European languages. The majority of this data comes from younger adults neglecting other age groups. Here we present a multimodal database which consists of task-based and resting state fMRI, structural MRI, and EEG data while participants over 65 years old listened to sections of the story The Little Prince in Cantonese. We also provide data on participants language history, lifetime experiences, linguistic and cognitive skills. Audio and text annotations, including time- aligned speech segmentation and prosodic information, as well as word-by-word predictors such as frequency and part-of-speech tagging derived from natural language processing (NLP) tools are included in this database. Both MRI and EEG data diagnostics revealed that the data has good quality. This multimodal database could advance our understanding of spatiotemporal dynamics of language comprehension in the older population and help us study the effects of healthy aging on the relationship between brain and behaviour.

neuroscience↗

bioRxiv2021

The interplay of additivity, dominance, and epistasis in a diploid yeast cross

We used a double barcoding system to generate and phenotype a panel of ~200,000 diploid yeast segregants that can be partitioned into hundreds of interrelated families. This experimental design enabled the detection of thousands of genetic interactions and many loci whose effects vary across families. Traits were largely specified by a small number of hub loci with major additive and dominance effects, and pervasive epistasis. Genetic background commonly influenced both the additive and dominance effects of loci, with multiple modifiers typically involved. The most prominent dominance modifier was the mating locus, which had no effect on its own. Our findings show that the interplay between additivity, dominance, and epistasis underlies a complex genotype-to-phenotype map in diploids. One sentence summaryIn diploids, epistasis frequently modifies both additivity and dominance.

genetics↗

bioRxiv2021

Neural correlates of semantic number: A cross-linguistic investigation

One aspect of natural language comprehension is understanding how many of what or whom a speaker is referring to. While previous work has documented the neural correlates of general number comprehension and quantity comparison, we investigate semantic number from a cross-linguistic perspective with the goal of identifying cortical regions involved in distinguishing plural from singular nouns. We use three fMRI datasets in which Chinese, French, and English native speakers listen to an audiobook of a childrens story in their native language. We select these three languages because they differ in their number semantics. While Chinese lacks nominal pluralization, French and English nouns are overtly marked for number. We find a number of known semantic processing regions in common, including dorsomedial prefrontal cortex and the pars orbitalis, in which cortical activation is greater for plural than singular nouns and posit a cross-linguistic role for number in semantic comprehension.

neuroscience↗

bioRxiv2021

Decoding the silence: Neural bases of zero pronoun resolution in Chinese

Chinese is one of many languages that can drop subjects. We report an fMRI study of language comprehension processes in these "zero pronoun" cases. The fMRI data come from Chinese speakers who listened to an audiobook. We conducted both univariate GLM and multivariate pattern analysis (MVPA) on these data time-locked to each verb with a zero pronoun subject. We found increased left middle temporal gyrus activity for zero pronouns compared to overt subjects, suggesting additional effort searching for an antecedent during zero pronoun resolution. MVPA further revealed that the intended referent of a zero pronoun seems to be physically represented in the Precuneus and the Parahippocampal Gyrus shortly after its presentation. This highlights the role of memory and discourse-level processing in resolving referential expressions, including unspoken ones, in naturalistic language comprehension.

neuroscience↗

bioRxiv2020

Modeling pronoun resolution in the brain

Human language processing involves not only combining word meanings in accordance with semantic and syntactic constraints, but also figuring out who and what is being referred to. Here we present a first study towards a mechanistic understanding of the neural basis for referential processing. Using both functional MRI and magnetoencephalography (MEG), we identified a consistent increase of activity in a network spanning the anterior and posterior left middle temporal gyrus and the angular gyrus for pronoun processing during naturalistic listening for both English and Chinese speakers. We then adopted a "reverse-engineering" approach to examine the cognitive processes underlying pronoun resolution. We evaluated the neural fit of three symbolic models that each formalizes a different strand of explanation for pronoun resolution in the cognitive and linguistic literature, as well as two deep neural network models with an LSTM or a Transformer architecture. Our results favor the memory-based symbolic model, suggesting a domain-general mechanism of pronoun resolution that resembles memory retrieval.

neuroscience↗

bioRxiv2020

Altered lipid metabolism marks glioblastoma stem and non-stem cells in separate tumor niches

BackgroundGlioblastoma (GBM) is marked by cellular heterogeneity, including metabolic heterogeneity, that varies among cellular microenvironments in the same tumor. Altered cellular metabolism in cancer is well-established, but how lipid metabolism is altered to suit different microenvironmental conditions and cellular states within a tumor remains unexplored. MethodsWe assessed GBM organoid models that mimic the transition zone between nutrient-rich and nutrient-poor pseudopalisading/perinecrotic tumor zones and performed spatial RNA-sequencing of cells to interrogate lipid metabolism. Using targeted lipidomic analysis, we assessed differences in acutely enriched cancer stem cells (CSCs) and non-CSCs from multiple patient-derived models to explore the link between the stem cell state and lipid metabolism. ResultsSpatial analysis revealed a striking difference in lipid content between microenvironments, with lipid enrichment in the hypoxic organoid cores and the perinecrotic and pseudopalisading regions of primary patient tumors. This was accompanied by regionally restricted upregulation of hypoxia-inducible lipid droplet-associated (HILPDA) gene expression in organoid cores and in clinical GBM specimens, but not lower-grade brain tumors, that was specifically localized to pseudopalisading regions of patient tumors. CSCs have low lipid droplet accumulation compared to non-CSCs in organoid models and xenograft tumors, and prospectively sorted lipid-low GBM cells are functionally enriched for stem cell activity. Targeted lipidomic analysis revealed that CSCs had decreased levels of major classes of neutral lipids compared to non-CSCs but had significantly increased polyunsaturated fatty acid production due to high fatty acid desaturase (FADS1/2) expression. ConclusionsOur data demonstrate that lipid metabolism is differentially altered across GBM microenvironments and cellular hierarchies, providing guidance for targeting of these altered lipid metabolic pathways. Key pointsO_LIGBM cells in nutrient-poor tumor regions have increased accumulation of lipid droplets. C_LIO_LICSCs have reduced lipid content compared to non-CSCs. C_LIO_LIGBM CSCs and non-CSCs have disparate lipid metabolisms that may be uniquely targetable. C_LI Importance of the StudyMetabolic targeting has long been advocated as a therapy against many tumors including GBM, and it remains an outstanding question whether cancer stem cells (CSCs) have altered lipid metabolism. We demonstrated striking differences in lipid metabolism between diverse cell populations from the same patient. These spatially and phenotypically distinct lipid phenotypes occur clinically in the majority of patients and can be recapitulated in laboratory models. Lipidomic analysis of multiple patient-derived models shows a significant shift in lipid metabolism between GBM CSCs and non-CSCs, suggesting that lipid levels may not be simply a product of the microenvironment but also may be a reflection of cellular state. Our results suggest that therapeutic targeting of GBM lipid metabolism must consider multiple separate tumor cell populations to be effective, and we provide a methodologic framework for studying these metabolically diverse cellular populations.

cancer biology↗

bioRxiv2019

Glucocorticoids Induce the Expansion of an Immature Human CFU-E Population

Despite effective clinical use, the mechanistic bases for the regulation of human erythropoiesis by glucocorticoids remain poorly understood. Here, we employed an erythroid culture system to differentiate primary human CD34+ cells isolated from control peripheral blood, cord blood and patients with Diamond Blackfan anemia (DBA), as model of an erythropoietic disorder treated with glucocorticoids. We found that the response to Dexamethasone is dependent on the developmental origin of the source of CD34+ cells, specifically increasing the expansion of CD34+ cells from peripheral blood but not cord blood. We also demonstrated that Dex treatment leads to the expansion of a novel immature colony-forming unit-erythroid (CFU-E) population in peripheral blood which is uniquely responsible for the proliferative effects observed during human adult erythropoiesis. Dex treatment of peripheral blood CFU-E cells also induced p57Kip2 expression while patients with DBA resistant to steroids had altered p57Kip2 expression that did not increase with Dex. Furthermore, shRNA knockdown of p57Kip2 reduced proliferation and abrogated the effects of Dex. Finally, proteomics of Dex-treated CFU-E from peripheral blood and cord blood additionally revealed novel Dex targets in the erythroid system. Altogether, these results provide novel insights into the regulation of human erythropoiesis by glucocorticoids.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC=\"FIGDIR/small/722850v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@c5c076org.highwire.dtl.DTLVardef@dec2f9org.highwire.dtl.DTLVardef@d27737org.highwire.dtl.DTLVardef@190c795_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2019

The speciation and hybridization history of the genus Salmonella

Bacteria and archaea make up most of natural diversity but the mechanisms that underlie the origin and maintenance of prokaryotic species are poorly understood. We investigated the speciation history of the genus Salmonella, an ecologically diverse bacterial lineage, within which S. enterica subsp. enterica is responsible for important human food-borne infections. We performed a survey of diversity across a large reference collection using multilocus sequence typing, followed by genome sequencing of distinct lineages. We identified eleven distinct phylogroups, three of which were previously undescribed. Strains assigned to S. enterica subsp. salamae are polyphyletic, with two distinct lineages that we designate Salamae A and Salamae B. Strains of subspecies houtenae are subdivided into two groups, Houtenae A and B and are both related to Selanders group VII. A phylogroup we designate VIII was previously unknown. A simple binary fission model of speciation cannot explain observed patterns of sequence diversity. In the recent past, there have been large scale hybridization events involving an unsampled ancestral lineage and three distantly related lineages of the genus that have given rise to Houtenae A, Houtenae B and VII. We found no evidence for ongoing hybridization in the other eight lineages but detected more subtle signals of ancient recombination events. We are unable to fully resolve the speciation history of the genus, which might have involved additional speciation-by-hybridization or multi-way speciation events. Our results imply that traditional models of speciation by binary fission and divergence may not apply in Salmonella.\n\nData summaryIllumina sequence data were submitted to the European Nucleotide Archive under project number PRJEB2099 and are available from INSDC (NCBI/ENA/DDBJ) under accession numbers ERS011101 to ERS011146. The MLST sequence and profile data generated in this study have been publicly available on the Salmonella MLST web site between 2010 and the migration of the Salmonella MLST website to EnteroBase (https://enterobase.warwick.ac.uk/), and subsequently from there.

microbiology↗