Biology subjects

Walsh, S.

Publications and source records attributed to Walsh, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Heterotypic interactions and sequence features modulate cellular reflectin condensate dynamics

Reflectin proteins drive dynamic structural coloration in cephalopods by organizing into dense intracellular lamellar structures that dictate local refractive index. While reconstituted reflectins readily undergo liquid-liquid phase separation in vitro, these assemblies frequently undergo dynamic arrest, vitrifying into non-dynamic condensates. Here, we investigate how primary sequence features, post-translational modifications, and heterotypic interactions regulate the material properties of reflectin condensates within the environment of mammalian HeLa cells. Using confocal microscopy and fluorescence recovery after photobleaching (FRAP), we demonstrate that canonical block copolymeric A-type reflectins readily form dynamically arrested condensates, with the linker blocks primarily responsible for the observed arrest. In contrast, non-canonical B/C reflectin variants exhibit significantly greater fluidity and rapid recovery kinetics. We show that phosphomimetic substitutions progressively fluidize some reflectin condensates. Lastly, we find that heterotypic condensates composed of canonical and non-canonical reflectins in combinations associated with reversible iridescence in squid substantially enhance canonical mobility. Our findings establish a biophysical framework in which phosphorylation and heterotypic mixing cooperatively suppress dynamic arrest, enabling the reversible material transitions required for active cephalopod camouflage and communication.

biophysics↗

bioRxiv2026

Astrocytes mediate the pro-cognitive value of α7nAChRs and of α7nAChR-targeting therapeutics

The 7-nicotinic acetylcholine receptor (7nAChR) has driven extensive research over the past three decades for its pro-cognitive potential. It is the leading druggable target for the cognitive deficits associated with schizophrenia and has motivated major pharmaceutical and clinical efforts to ameliorate similar impairments in other neurological disorders, such as Alzheimers disease (AD). Yet, a systematic evaluation of the role played by 7nAChR in cognition, and its mechanistic underpinnings, is still lacking. Here we report that 7nAChRs on principal and inhibitory forebrain neurons are largely inconsequential to mouse behavior, including in domains that are most sensitive to schizophrenia-related cognitive impairments. By contrast, loss of 7nAChR from astrocytes produces profound behavioral alterations that are cognitive domain-specific, are time-of-day dependent, coincide with reduced levels of the N-methyl D-aspartate receptor (NMDAR) co-agonist D-serine, and are fully restored by D-serine supplementation. Further, an 7nAChR partial agonist previously evaluated in Phase III trials for cognitive enhancement in schizophrenia and AD fails to augment behavior in mice lacking astrocytic 7nAChRs. Together, these findings identify astrocytes and D-serine/NMDAR signaling as a central mechanism through which 7nAChR, a major drug target, promotes cognitive behavior.

neuroscience↗

bioRxiv2026

Predator avoidance promotes inter-bacterial symbiosis with myxobacteria in polymicrobial communities

Myxobacteria are predatory soil bacteria with the largest known bacterial genomes, rich in biosynthetic gene clusters for specialized metabolites. Despite their ecological importance as potential keystone taxa in soil food webs, there is a disconnect between laboratory-isolated myxobacteria and abundant Myxococcota detected in environmental metagenomic studies. Here, we report the isolation and characterization of stable myxobacterial swarm consortia from rhizospheric soil, consisting of myxobacteria associated with novel Microvirga species. Using metagenomic sequencing, we assembled metagenome-assembled genomes (MAGs) for four consortia, revealing phylogenetically distinct yet stably associated bacterial partnerships. Comparative genomics identified evidence of horizontal gene transfer, including acyl-homoserine lactone (AHL) synthases and ankyrin repeat (ANKYR) proteins shared between consortium members, and genome-scale metabolic modeling predicted complementary auxotrophies. Remarkably, time-lapse microscopy revealed that Archangium exhibited markedly reduced predation toward its Microvirga companion (0.7% predation rate) compared to non-symbiotic Myxococcus xanthus (14.9% predation rate), while maintaining robust predatory capacity against Escherichia coli prey. These findings indicate that predation avoidance and metabolic complementarity can drive stable inter-bacterial symbiosis in predatory myxobacterial communities, providing foundational insights into previously overlooked myxobacterial partnerships that may be prevalent in natural soil ecosystems.

microbiology↗

bioRxiv2025

The craniofacial shape of modern humans embodies genomic signatures of evolution, diversity, and clinical conditions

Human craniofacial morphology is a hallmark of our species diversity and evolutionary history, shaped by adaptation, introgression, and global dispersal. Cranial globularization and chin emergence are well-documented morphological transformations whose genetic basis remains poorly understood, whereas Neandertal introgression is primarily documented through genomic evidence. How these evolutionary phenomena relate to craniofacial variation in present-day humans remains largely unresolved. Here, we leverage 3D craniofacial data from over 50,000 UK Biobank participants and employ a multivariate, multiscale genome-wide association approach to define axes of variation aligned with inter-population allele frequency shifts, evolutionary processes, and clinical conditions. We identify continuous craniofacial trends within our cohort that mirror global patterns of genetic diversity, indicating that facial differences between human populations arise at the phenotypic axes already present within a single population. We further demonstrate that modern human-derived alleles underlie the origins of the human chin by reducing midfacial projection relative to other hominins and reveal the persistent effects of Neandertal introgression on craniofacial diversity today. We also model genetically informed endophenotypes for orofacial clefts, obstructive sleep apnoea, and myopia. These findings provide insights into our species evolutionary history and endophenotypes of clinical conditions and establish a framework for contextualizing craniofacial diversity into biologically meaningful axes of variation relevant to diverse scientific disciplines.

genetics↗

bioRxiv2025

Prenatal Zika Virus Exposure Disrupts Social-Emotional Development and Cortical Visual Function in Infant Macaques

Prenatal exposure to Zika virus (ZIKV) results in a spectrum of outcomes, ranging from severe birth defects and early childhood developmental delays to no apparent deficits. However, the mechanisms underlying these outcomes, particularly in the context of different maternal infection conditions, remain poorly defined. In this study, we employed a translational rhesus macaque model of prenatal ZIKV infection to evaluate longitudinal visual and auditory development from 1 to 12 months of age and characterize neurodevelopmental outcomes at 12 months. Pregnant macaques, either flavivirus-naive or with prior dengue virus (DENV) exposure, were inoculated in the first trimester ([~]30 or 45 gestational days) with an Asian or African lineage of ZIKV or received a saline injection as controls. Maternal plasma viremia duration, viral RNA burden at the maternal-fetal interface, and neutralizing antibody titers did not differ between inoculation cohorts or controls. At 12 months, ZIKV-exposed infants demonstrated altered maternal attachment behaviors and reduced inhibition when approaching sensory stimuli compared to controls. Visual pathway function, assessed by electrophysiology, was significantly impaired at 3 months but normalized by 12 months. Hearing loss was more common among ZIKV-exposed infants, although not statistically significant. Developmental outcomes were associated with prenatal ZIKV exposure itself, independent of viremia duration, neutralizing antibody titer, viral lineage, or maternal DENV immunity, and were not mediated by visual impairment or hearing loss. These findings highlight that any prenatal ZIKV exposure can disrupt early neurobehavioral development and visual function, underscoring the need for prevention strategies focused on maternal infection and early intervention.

microbiology↗

bioRxiv2024

Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data

MotivationCombining omics and images, can lead to a more comprehensive clustering of individuals than classic single-view approaches. Among the various approaches for multi-view clustering, nonnegative matrix tri-factorization (NMTF) and nonnegative Tucker decomposition (NTD) are advantageous in learning low-rank embeddings with promising interpretability. Besides, there is a need to handle unwanted drivers of clusterings (i.e. confounders). ResultsIn this work, we introduce a novel multi-view clustering method based on NMTF and NTD, named INMTD, that integrates omics and 3D imaging data to derive unconfounded subgroups of individuals. In the application to real-life facial-genomic data, INMTD generated biologically relevant embeddings for individuals, genetics and facial morphology. By removing confounded embedding vectors, we derived an unconfounded clustering with better internal and external quality; the genetic and facial annotations of each derived subgroup highlighted distinctive characteristics. In conclusion, INMTD can effectively integrate omics data and 3D images for unconfounded clustering with biologically meaningful interpretation. Availability and implementationhttps://github.com/ZuqiLi/INMTD

bioinformatics↗

bioRxiv2024

Exploring ancestry inference of the Middle East

The capability to infer biogeographic ancestry with curated panels of ancestry informative markers (AIMs) is a critical component to DNA intelligence. There are many AIM panels that resolve population differentiation at a continental level. Of late, several studies have directed marker discovery to the Middle East because of the difficulties for AIM panels to resolve this region amongst populations in Eurasia. The AIM discovery process has remained largely unchanged, except for the most recent additions of whole-genome sequence (WGS) data repositories which now include Middle Eastern individuals. Here, the latest WGS data from 1000 Genomes Project and Human Genome Diversity Project was paired with novel Middle Eastern population data from Lebanon for AIMs discovery. An unbiased genetic clustering approach was employed for selecting population clusters for allelic frequency comparisons. Two candidate AIMs were reported, compared, and evaluated together with the autosomal AIMs from the VISAGE Enhanced Tool. These comparisons involved a validation dataset from Middle Eastern WGS data published by the Wellcome Sanger Institute and resulted in slight gains of Middle Eastern ancestry proportions for several Middle Eastern samples with varying levels of co-ancestries. The validation samples also underwent an unsupervised worldwide ADMIXTURE analysis alongside previously mentioned WGS datasets using nearly two million markers (r2 < 0.1) to establish a ground truth population membership. Lastly, a novel application of the deep learning dimensional reduction algorithm popVAE is provided as an open-source web tool to illustrate the AIM panels variance among these population clusters within two dimensions for easy global ancestry visualization in addition to providing a closest population membership metric.

genetics↗

bioRxiv2024

The dynamic gene regulatory landscape of the mouse brain in response to sleep deprivation

Sleep deprivation (SD) negatively impacts nearly all brain functions including cognition, memory consolidation and metabolism. However, the gene regulatory networks that underlie these biological effects are not well understood. In order to identify these networks, we conducted a multiomic analysis to analyse how gene expression, chromatin accessibility, enhancer activity and DNA methylation change with acute SD in mice. By studying three brain regions involved in different aspects of sleep - the cortex (CTX), dentate gyrus (DG), and suprachiasmatic nucleus (SCN) - we found that the effects of SD on the multiome varied widely, impacting physiological processes specific to each area, from spine formation in the dentate gyrus to neuropeptide release in the SCN. Our integrated analysis showed that distinct brain region-specific networks of regulatory factors dynamically alter the epigenomic landscape in response to SD to orchestrate transcriptional responses. These findings provide new understanding of the regulatory grammar encoded within the genome, which enables a general physiological signal like SD to produce unique effects in a tissue-specific context.

neuroscience↗

bioRxiv2024

Mapping genes for human face shape: exploration of univariate phenotyping strategies

Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author SummaryAdvancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.

genetics↗

bioRxiv2024

Norepinephrine Signals Through Astrocytes To Modulate Synapses

AbstractLocus coeruleus (LC)-derived norepinephrine (NE) drives network and behavioral adaptations to environmental saliencies by reconfiguring circuit connectivity, but the underlying synapse-level mechanisms are elusive. Here, we show that NE remodeling of synaptic function is independent from its binding on neuronal receptors. Instead, astrocytic adrenergic receptors and Ca2+ dynamics fully gate the effect of NE on synapses as the astrocyte-specific deletion of adrenergic receptors and three independent astrocyte-silencing approaches all render synapses insensitive to NE. Additionally, we find that NE suppression of synaptic strength results from an ATP-derived and adenosine A1 receptor-mediated control of presynaptic efficacy. An accompanying study from Chen et al. reveals the existence of an analogous pathway in the larval zebrafish and highlights its importance to behavioral state transitions. Together, these findings fuel a new model wherein astrocytes are a core component of neuromodulatory systems and the circuit effector through which norepinephrine produces network and behavioral adaptations, challenging an 80-year-old status quo.

neuroscience↗

bioRxiv2024

Varying phylogenetic signal to four bacterial pathogens across species of Drosophilidae

Bacterial infections are one of the major sources threatening public health. Pathogen host shifts - where a pathogen jumps from one host species to another - are important sources of emerging infectious diseases. However, compared to viruses, we know relatively little about the factors that determine whether a bacteria can infect a novel host, such as how host phylogenetics constrains variation in pathogen-host range and the link between host phylogeny and the infectivity and virulence of a pathogen. Here, we experimentally examined susceptibility to bacterial infections using a panel of 36 Drosophilidae species and four pathogens (Providencia rettgeri, Pseudomonas entomophila, Enterococcus faecalis, Staphylococcus aureus). The outcomes of infection differed greatly among pathogens and across host species. The host phylogeny explains a considerable amount of variation in susceptibility, with the greatest phylogenetic signal for P. rettgeri infection, explaining 94% of the variation in mortality. Positive correlations were observed between mortality and bacterial load for three out of the four pathogens. Correlations in susceptibility between the four pathogens were positive but largely non-significant, suggesting susceptibility is mostly pathogen-specific. These results suggest that susceptibility to bacterial pathogens may be predicted by the host phylogeny, but the effect may vary in magnitude between different bacteria.

evolutionary biology↗

bioRxiv2024

Automated 3D Landmarking of the Skull: A Novel Approach for Craniofacial Analysis

Automatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising 9,999 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (>0.988), and automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.

bioinformatics↗

bioRxiv2023

Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population

Human craniofacial shape is highly variable yet highly heritable with genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the normal population. We compared three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores revealed a polygenic basis for normal facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples showed craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing new insights into the genetic intersection of complex traits and Mendelian disorders.

genetics↗

bioRxiv2023

ILIAD: A suite of automated Snakemake workflows for processing genomic data for downstream applications

BackgroundProcessing raw genomic data for downstream applications such as imputation, association studies, and modeling requires numerous third-party bioinformatics software tools. It is highly time-consuming and resource-intensive with computational demands and storage limitations that pose significant challenges that increase cost. The use of software tools independent of one another, in a disjointed stepwise fashion, increases the difficulty and sets forth higher error rates because of fragmented job executions in alignment, variant calling, and/or build conversion complications. As sequencing data availability grows, the ability of biologists to process it using stable, automated, and reproducible workflows is paramount as it significantly reduces the time to generate clean and reliable data. ResultsThe Iliad suite of genomic data workflows was developed to provide users with seamless file transitions from raw genomic data to a quality-controlled variant call format (VCF) file for downstream applications. Iliad benefits from the efficiency of the Snakemake best practices framework coupled with Singularity and Docker containers for repeatability, portability, and ease of installation. This feat is accomplished from the onset with download acquisitions of any raw data type (FASTQ, CRAM, IDAT) straight through to the generation of a clean merged data file that can combine any user-preferred datasets using robust programs such as BWA, Samtools, and BCFtools. Users can customize and direct their workflow with one straightforward configuration file. Iliad is compatible with Linux, MacOS, and Windows platforms and scalable from a local machine to a high-performance computing cluster. ConclusionIliad offers automated workflows with optimized time and resource management that are comparable to other workflows available but generates analysis-ready VCF files from the most common datatypes using a single command. The storage footprint challenge of genomic data is overcome by utilizing temporary intermediate files before the final VCF is generated. This file is ready for use in imputation, genome-wide association study (GWAS) pipelines, high-throughput population genetics studies, select gene candidate studies, and more. Iliad was developed to be portable, compatible, scalable, robust, and repeatable with a simplistic setup, so biologists who are less familiar with programming can manage their own big data with this open-source suite of workflows.

bioinformatics↗

bioRxiv2023

Data-driven trait heritability-based extraction ofhuman facial phenotypes

A genome-wide association study (GWAS) of a complex, multi-dimensional morphological trait, such as the human face, typically relies on predefined and simplified phenotypic measurements, such as inter-landmark distances and angles. These measures are predominantly designed by human experts based on perceived biological or clinical knowledge. To avoid use handcrafted phenotypes (i.e., a priori expert-identified phenotypes), alternative automatically extracted phenotypic descriptors, such as features derived from dimension reduction techniques (e.g., principal component analysis), are employed. While the features generated by such computational algorithms capture the geometric variations of the biological shape, they are not necessarily genetically relevant. Therefore, genetically informed data-driven phenotyping is desirable. Here, we propose an approach where phenotyping is done through a data-driven optimization of trait heritability, defined as the degree of variation in a phenotypic trait in a population that is due to genetic variation. The resulting phenotyping process consists of two steps: 1) constructing a feature space that models shape variations using dimension reduction techniques, and 2) searching for directions in the feature space exhibiting high trait heritability using a genetic search algorithm (i.e., heuristic inspired by natural selection). We show that the phenotypes resulting from the proposed trait heritability-optimized training differ from those of principal components in the following aspects: 1) higher trait heritability, 2) higher SNP heritability, and 3) identification of the same number of independent genetic loci with a smaller number of effective traits. Our results demonstrate that data-driven trait heritability-based optimization enables the automatic extraction of genetically relevant phenotypes, as shown by their increased power in genome-wide association scans.

bioinformatics↗

bioRxiv2023

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity

Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these classes. NetMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures. Author summaryIn recent years, we see the increasing possibility of collecting data from multiple modalities in various fields, requesting novel methods to exploit the consensus among different data types. As exemplified in systems biology or epistasis analyses, the interactions between features may contain more information than the features themselves, thereby necessitating the use of feature networks. Furthermore, in real-life scenarios, subjects, such as patients or individuals, may originate from diverse populations, which underscores the importance of subtyping or clustering these subjects to account for their heterogeneity. In this study, we present a novel pipeline for selecting the most relevant features from multiple data types, constructing a feature network for each subject, and obtaining a subgrouping of samples informed by a phenotype of interest. We validated our method on synthetic data and demonstrated its superiority over several state-of-the-art multi-view clustering approaches. Additionally, we applied our method to a real-life, large-scale dataset of genomic data and facial images, where it effectively identified a meaningful BMI subtyping that complemented existing BMI categories and offered new biological insights. Our proposed method has wide applicability to complex multi-view or multi-omics datasets for tasks such as disease subtyping or personalized medicine.

bioinformatics↗

bioRxiv2022

Joint Multi-Ancestry and Admixed GWAS Reveals the Complex Genetics behind Human Cranial Vault Shape

The cranial vault - the portion of the skull surrounding the brain and cerebellum - is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conducted a joint multi-ancestry and admixed multivariate GWAS on 3D cranial vault shape extracted from magnetic resonance images of 6,772 children from the ABCD study cohort, identifying 30 genome-wide significant genetic loci and replicating 20 of these signals in 16,947 additional individuals of the UK Biobank. This joint multi-ancestry GWAS was enriched for genetic components of cranial vault shape shared across ancestral groups and yielded a greater discovery than a European-only GWAS. We present supporting evidence for parietal versus frontal bone localization for several of the identified genes based on expression patterns in E15.5 mice. Collectively, our GWAS loci were enriched for processes related to skeletal development and showed elevated activity in cranial neural crest cells, suggesting a role during early craniofacial development. Among the identified genes, were RUNX2 and several of its upstream and downstream actors, highlighting the prominent role of intramembranous ossification - which takes place at the cranial sutures - in influencing cranial vault shape. We found that mutations in many genes associated with craniosynostosis exert their pathogenicity by modulating the same pathways involved in normal cranial vault development. This was further demonstrated in a non-syndromic sagittal craniosynostosis case-parent trio dataset of 63 probands (n = 189), where our GWAS signals near BMP2, BBS9, and ZIC2 contributed significantly to disease risk. Moreover, we found strong evidence of overlap with genes influencing the morphology of the face and the brain, suggesting a common genetic architecture connecting these developmentally adjacent structures. Overall, our study provides a comprehensive overview of the genetics underlying normal cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.

genetics↗

bioRxiv2022

LGR5 targeting molecules as therapeutic agents for multiple cancer types

Leucine-rich repeat-containing G-protein receptor 5 (LGR5) has been characterised as a stem cell and cancer stem cell marker. Previous analyses of LGR5 transcript levels indicate high level expression discriminates malignancies such as colorectal cancer (CRC) and pre-B acute lymphoblastic leukaemia (pre-B ALL) from healthy tissues suggesting LGR5 protein expression may provide a molecular handle for prognosis and treatment. We have developed highly specific, high affinity antibodies to the extracellular domain of human LGR5 (-LGR5) that detect high LGR5 protein levels in colorectal cancer (CRC), hepatocellular carcinoma (HCC), and pre-B ALL. In contrast, there is low to undetectable levels of LGR5 protein in normal colon and rectal epithelia, liver, ovarian tissues, brain and immune cell types. LGR5 is rapidly internalised from the plasma membrane and trafficked to intracellular vesicular compartments including lysosomes. Treatment of high LGR5-expressing CRC and pre-B ALL cancer cell lines with an antibody-drug conjugate version of -LGR5 (-LGR5-ADC) lead to effective cell killing at nanomolar concentrations. Interventional treatment of pre-B ALL tumours with -LGR5-ADC in vivo led to rapid tumour attrition. We further demonstrated the therapeutic utility of humanised -LGR5 by using the corresponding scFv fragment for the generation of -LGR5 chimeric antigen receptors (CARs) and a Bispecific T cell Engager (BiTE). -LGR5-CAR-NK cells were effective at killing LGR5-expressing cells while -LGR5/-CD3 BiTEs induce T cell activation and killing of NALM6 cells by cytotoxic CD8+ T cells. Taken together, this study establishes -LGR5-based therapeutic modalities that effectively discriminate and target CRC, HCC and pre-B ALL tumour cells. One Sentence SummaryWe generated novel antibodies against the cancer cell marker LGR5, validated diagnostic use in prioritizing specific cancer types for targeting, and developed antibody-based therapeutics.

cell biology↗