Biology subjects

Henry, R.

Publications and source records attributed to Henry, R..

13 recordsLinked to original sources

bioRxiv2026

MECP2-mutant marmosets exhibit primate-specific phenotypes of Rett syndrome

We used genome editing to generate MECP2-knockout marmosets and establish a new primate model for Rett syndrome (RTT), a neurodevelopmental disorder. MRI analysis of this marmoset model revealed diminished cortico-cortical connections, particularly those originating in the prefrontal cortex. Detailed histological analysis revealed reduced dendritic arborization and synaptic density, particularly in the upper layers of the cerebral cortex. Cortical layer II/III excitatory neurons appeared to be immature based on single-nucleus RNA sequencing and spatial transcriptomics, while PVALB-positive interneurons exhibited upregulation of neuronal maturation-related transcripts. Moreover, the neurodevelopmental disease gene GABAB receptor 2 (GABBR2) emerged as a conserved downstream target of MECP2, illuminating a cellular cascade that could be targeted in preclinical and therapeutic drug development. Many of the gene expression changes observed in the marmoset model are common in RTT patients, thereby highlighting molecular links from cell type-specific phenotypes in the marmoset model to the RTT clinical presentation.

neuroscience↗

bioRxiv2026

Cellular stemness identifies high-risk ductal carcinoma in situ and offers a therapeutic interception opportunity

Ductal carcinoma in situ (DCIS) exhibits substantial heterogeneity in its risk of progression to invasive breast cancer, yet the cellular and molecular determinants of high-risk lesions remain incompletely defined. Using spatially resolved single-cell transcriptomic and epigenomic profiling of 43 patient-derived DCIS and DCIS/invasive ductal carcinoma (IDC) samples, we delineate cellular programs, spatial organization, and epigenetic regulatory mechanisms associated with invasive potential. We identify an epithelial population with stemness features within luminal hormone-responsive (LumHR) cells that progressively expands from benign tissue to DCIS and IDC, and is strongly associated with invasive progression and recurrence-linked transcriptional programs. Spatial mapping reveals discrete DCIS niches enriched for stem-like LumHR cells, characterized by elevated CEACAM6 expression and enhanced ligand-receptor interactions, including CEACAM6-EGFR signaling between epithelial and stromal compartments, including cancer-associated fibroblasts, macrophages (APOC1-positive) and perivascular cells. These niches define a microenvironmental context that supports stemness and invasive potential. Epigenomic analyses implicate FOXA1 as a key regulator of these stem-like transcriptional states. Pharmacologic disruption of FOXA1-regulatory network using LSD1 inhibition suppresses stemness-associated transcriptional programs in vitro and significantly restrains tumor growth in vivo. Collectively, these findings define high-risk DCIS as a stemness-driven disease embedded within specialized microenvironments, and identify associated regulatory networks as candidate biomarkers and therapeutic vulnerabilities.

cancer biology↗

bioRxiv2025

Control of a Bi-Stable Genetic System via Parallelized Reinforcement Learning

Achieving real-time control of genetic systems is critical for improving the reliability, efficiency, and reproducibility of biological research and engineering. Yet the intrinsic stochasticity of these systems makes this goal difficult. Prior efforts have faced three recurring challenges: (a) predictive models of gene expression dynamics are often inaccurate or unavailable, (b) nonlinear dynamics and feedback in genetic circuits frequently lead to multi-stability, limiting the effectiveness of deterministic control strategies, and (c) slow biological response times make data collection for learning-based methods prohibitively time-consuming. Recent experimental advances now allow the parallel observation and manipulation of over a million individual cells, opening the door to model-free, data-driven control strategies. Here we investigate the use of Parallelized Q-Networks (PQN), a recently-developed reinforcement learning algorithm, to learn control policies for a simulated bi-stable gene regulatory network. We show that PQN can not only control this self-activating system more accurately than other model-free and model-based control methods previously used in the field, but also converges efficiently enough to be practical for experimental application. Our results suggest that parallelized experiments coupled with advances in reinforcement learning provide a viable path for real-time, model-free control of complex, multi-stable biological systems.

systems biology↗

bioRxiv2024

Machine learning driven image segmentation and shape clustering of algal microscopic images obtained from various water types

Algae and cyanobacteria are microorganisms found in almost all fresh and marine waters, where they can pose environmental and public health risks when they grow excessively and produce blooms. Accurate identification and quantification of these microorganisms are vital for ecological research, water quality monitoring, and public health safety. However, traditional methods of manually counting and morphologically identifying these microorganisms are time-consuming and prone to human error. Application of the machine learning-driven Fast Segment Anything Model (FastSAM), an image segmentation model, automates and potentially enhances the accuracy and efficiency of cell identification and enumeration from microscopic images. We assessed FastSAM for algal cell image segmentation, and three clustering evaluation metrics. Segmentation of microscopic images of algal and cyanobacterial cells in water and treated wastewater samples using the Convolutional Neural Network based FastSAM algorithm demonstrated benefits and challenges of this machine learning-driven image processing. Notably, the pre-trained algorithm segmented entire elements in all microscopic images used in this study. Depending on the shape, 50-100% similarity was observed between machine-based segmentation and manual validation of all segmented elements, with 100% of single cells being correctly segmented by FastSAM. The performance of clustering metrics varied between 57-94% with the Spectral Angle Mapper achieving the most accurate performance, 84-94%, compared to the manually chosen clustering benchmarks. Cyanobacterial and algal communities are biologically diverse and have ecological significance. The application of image clustering techniques in studying their cell shapes marks an important advancement in microbial ecology and environmental monitoring. As technology progresses, these methods will become increasingly utilised to decipher the complex roles that algae and cyanobacteria play in our ecosystems supporting mitigation and public health protection measures.

microbiology↗

bioRxiv2024

Analysis of genetic variation in Macadamia shows evidence of extensive reticulate evolution

The genus Macadamia in the Proteaceae family includes four species. To explore diversity in macadamia genetic resources, a total of 166 wild genotypes, representing all four species, were sequenced. The four species were clearly distinguished as four separate clades in a phylogenetic analysis of nuclear gene CDS. M. integrifolia and M. tetraphylla formed a clade that had diverged from a clade including M. ternifolia and M. jansenii. The greatest diversity in nuclear and chloroplast genomes was found in the more widely distributed M. integrifolia while the rare M. jansenii showed little diversity. The chloroplast phylogeny revealed a much more complex evolutionary history. Multiple chloroplast capture events have resulted in chloroplast genome clades including genotypes from different species. This suggests extensive reticulate evolution in Macadamia despite the emergence of the four distinct species that are supported by the analysis of their nuclear genomes. The chloroplast genomes showed strong associations with geographical distribution reflecting limited maternal gene movement in these species having large seeds. The nuclear genomes showed lesser geographical differences, probably reflecting longer distance movement of pollen. This improved understanding of the distribution of diversity in Macadamia will aid conservation of these rare species now found in highly fragmented rainforest remnants. HighlightsWhole genome sequencing of population of the four species in the Macadamia genus allowed phylogenetic relationships to be determined and revealed significant reticulate evolution.

evolutionary biology↗

bioRxiv2024

A flow cytometry protocol for accurate and precise measurement of plant genome size using frozen material

Flow cytometry is a technique widely applied to infer the ploidy and genome size of plant nuclei. The conventional approach of sample preparation, reliant on fresh plant material to release intact nuclei, requires protocol optimisation for application to many species. The approach often results in poor yields of nuclei, impeding the accurate measurement of genome size and confines the optimal resource allocation and efficiency in genome sequencing which relies on genome size estimation. Here, we present a novel method using frozen plant material that facilitates the release of intact nuclei for genome size estimation. Genome estimates from frozen material are similar to those from fresh material. Accurate and precise estimates can be made by complementing the fluorescence of frozen nuclei with histogram modelling and debris compensation algorithms. This method of nuclei isolation from frozen plant material for flow cytometry-based genome size estimations has special value in estimating the genome size of samples collected and frozen for use in plant genome sequencing. Plant material can be conveniently stored, resampled, and used for DNA or RNA extractions. HighlightFrozen leaf material can be used to isolate nuclei for the accurate estimation of genome size The method proved suitable for difficult samples and did not require specific optimization. The method was especially useful where plant material could not be immediately processed through flow cytometry and allowed the same sample to be used for genomes size estimation and genome sequencing.

genomics↗

bioRxiv2022

Comparative genomic insights into bacterial induction of larval settlement and metamorphosis in the upside-down jellyfish Cassiopea

Bacterial biofilm is crucial in inducing the larval transition from pelagic to benthic environments for marine organisms. Bacteria can therefore dictate species distribution and success of the individual. Despite the importance of marine bacteria to animal ecology, the identity of inductive microbes for many invertebrates are unknown. We isolated bacteria belonging to multiple phyla are capable of inducing settlement and metamorphosis in the upside-down jellyfish Cassiopea xamachana. The most inductive isolates belonged to the genus Pseudoalteromonas, a marine bacterium known to induce the pelago-benthic transition in other marine invertebrates. In sequencing the genome of the isolated Pseudoalteromonas and an inductive Vibrio, we found biosynthetic pathways previously implicated in larval settlement were absent in these Cassiopea inducing taxa. Comparative analysis of the Pseudoalteromonas and Vibrio revealed shared genes that could underlie the inductive capacity of these two bacteria. Thus, C. xamachana are capable of responding to multiple bacterial species, but they may be responding to a common cue produced by multiple taxa. These findings could provide hints to the ecological success of C. xamachana compared to sympatric congeneric species within mangrove environments and provide avenues to investigate the evolution of animal-microbe interactions.

microbiology↗

bioRxiv2022

Beyond energy balance in agrivoltaic food production: Emergent crop traits from color selective solar cells

The integration of semi-transparent organic solar cells (ST-OSCs) in greenhouses offers new agrivoltaic opportunities to meet the growing demands for sustainable food production. The tailored absorption/transmission spectra of ST-OSCs impacts the power generated as well as crop growth, development and responses to the biotic and abiotic environments. We grew lettuce and tomato, traditional greenhouse crops, under three ST-OSC filters that create different light spectra. Lettuce yield and early tomato development are not negatively affected by the modified light environment. Our genomic analysis reveals that lettuce production exhibits beneficial traits involving nutrient content and nitrogen utilization while select ST-OSCs impact regulation of flowering initiation in tomato. ST-OSCs integrated into greenhouses are not only a promising technology for energy-neutral, sustainable and climate-change protected crop production, but can deliver benefits beyond energy considerations.

plant biology↗

bioRxiv2021

De-novo chromosome level assembly of plant genomes from long read sequence data

Recent advances in the sequencing and assembly of plant genomes have allowed the generation of genomes with increasing contiguity and sequence accuracy. The chromosome level assembly of the contigs generated from long read sequencing has involved the use of proximity analysis (Hi-C) or traditional genetic maps to guide the placement of sequence contigs within chromosomes. The development of highly accurate long reads by repeated sequencing of circularized DNA (PacBio HiFi) has greatly increased the size of contigs. We now report the use of HiFiasm to assemble the genome of Macadamia jansenii. a genome that has been used as model to test sequencing and assembly. This achieved almost complete chromosome level assembly from the sequence data alone without the need for higher level chromosome map information. Eight of the 14 chromosomes were represented by a single large contig and the other 6 assembled into 2-4 main contigs. The small number of chromosome breaks appear to be due to highly repetitive regions of ribosomal genes that cannot be assembled by these approaches. De novo assembly of near complete chromosome level plant genomes now seems possible using these sequencing and assembly tools. Further targeted strategies might allow these remaining gaps to be closed. Significance statement (of up to two sentences)De novo assembly of near complete chromosome level plant genomes is now possible using current long read sequencing and assembly tools.

genomics↗

bioRxiv2021

The genome of the endangered Macadamia jansenii displays little diversity but represents an 1 important genetic resource for plant breeding

Macadamia, a recently domesticated expanding nut crop in the tropical and subtropical regions of the world, is one of the most economically important genera in the diverse and widely adapted Proteaceae family. All four species of Macadamia are rare in the wild with the most recently discovered, M. jansenii, being endangered. The M. jansenii genome has been used as a model for testing sequencing methods using a wide range of long read sequencing techniques. Here we report a chromosome level genome assembly, generated using a combination of Pacific Biosciences sequencing and Hi-C, comprising 14 pseudo-molecules, with a N50 of 58 Mb and a total 758 Mb genome assembly size of which 56% is repetitive. Completeness assessment revealed that the assembly covered 96.9% of the conserved single copy genes. Annotation predicted 31,591 protein coding genes and allowed the characterization of genes encoding biosynthesis of cyanogenic glycosides, fatty acid metabolism and anti-microbial proteins. Re-sequencing of seven other genotypes confirmed low diversity and low heterozygosity within this endangered species. Important morphological characteristics of this species such as small tree size and high kernel recovery suggest that M. jansenii is an important source of these commercial traits for breeding. As a member of a small group of families that are sister to the core eudicots, this high-quality genome also provides a key resource for evolutionary and comparative genomics studies.

genomics↗

bioRxiv2020

TaqMan Array Cards enable monitoring of diverse enteric pathogens across environmental and host reservoirs

BackgroundMultiple bacteria, viruses, protists, and helminths cause enteric infections that greatly impact human health and wellbeing. These enteropathogens are transmitted via several pathways through human, animal, and environmental reservoirs. Individual quantitative PCR (qPCR) assays have been extensively used to detect enteropathogens within these types of samples, whereas the TaqMan Array Card (TAC) that allows simultaneous detection of multiple enteropathogens has only previously been validated in human clinical samples. MethodsHere, we performed a comprehensive double-blinded comparison of the performance of a custom TAC relative to standard qPCR for the detection of eight enteric targets, by using spiked samples, wastewater from Melbourne (Australia), and human, animal, and environmental samples from informal settlements in Suva, Fiji. FindingsBoth methods exhibited high and comparable specificity (TAC: 100%, qPCR: 94%), sensitivity (TAC: 92%; qPCR: 100%), and quantitation accuracy (TAC: 91%; qPCR: 99%) in non-inhibited sample matrices. PCR inhibitors substantially impacted detection via TAC, though this issue was alleviated by 10-fold sample dilution. Among samples from informal settlements, the two techniques were comparable for detection (89% agreement) and quantitation (R2 = 0.82). The TAC additionally included 38 other targets, enabling detection of diverse faecal pathogens and extensive environmental contamination that would be prohibitively labour intensive to assay by standard qPCR. InterpretationOverall, the two techniques produce comparable results across diverse sample types, with qPCR prioritising greater sensitivity and quantitation accuracy, and TAC trading small reductions in these for a cost-effective larger enteropathogen panel that enables a greater number of enteric pathogens to be analysed concurrently, which is beneficial given the abundance and variety of enteric pathogens in environments such as urban informal settlements. The ability to monitor multiple enteric pathogens across diverse reservoirs in turn allows better resolution of pathogen exposure pathways, and the design and monitoring of interventions to reduce pathogen load. FundingWellcome Trust Our Planet, Our Health program [OPOH grant 205222/Z/16/Z].

microbiology↗

bioRxiv2019

Chloroplast SRP43 Subunit Prevents Aggregation of Proteins

Integration of light-harvesting chlorophyll binding proteins into the thylakoid membrane requires a specific chaperone, being the cpSRP43 subunit, of the signal recognition particle pathway in chloroplasts. cpSRP43, unique to the chloroplast, is responsible for transport of LHCPs through the stroma as well as assisting in the correct folding, assembly and disaggregation of these proteins for the acquisition of light energy. cpSRP43 is a highly flexible, multidomain protein capable of binding distinct partners in the cpSRP pathway. cpSRP43 is an irreplaceable component, necessary for the accurate and successful integration of LHCPs. It can act as a disaggregase without any input of external energy. Its action is based on the ability to associate with variable regions of different proteins owing to the domains and flexibility within its distinctive structure. Understanding the unique capabilities of cpSRP43 in the chloroplast begs the question of its usefulness outside of the plant cell, as well as its yet unknown roles still within the plant cell. Although the capabilities of cpSRP43 as a hub protein, adept to binding many unknown partners, has been alluded to in other works, it has yet to be thoroughly investigated. In this study we discover that cpSRP43 can act as a generic chaperone for proteins other than LHCP/not native to the chloroplast. The high thermal stability of cpSRP43 has been demonstrated in the previous chapter by its ability to retain its secondary structure as well as withstand aggregation upon heating and cooling cycles as confirmed by absorbance, intrinsic tryptophan fluorescence and far UV circular dichroism spectroscopy. This property gives cpSRP43 the basis to act as a generic chaperone and provide protection like that of typical heat shock proteins. Carbonic anhydrase, Concanavalin A and hFGF1 (acidic human fibroblast growth factor), were selected as candidates for chaperoning activity by cpSRP43. In all three cases, heat-induced aggregation of the candidate protein was either eliminated or significantly reduced in the presence of cpSRP43. In the case of hFGF1, the bioactivity was preserved after heat-treatment in the presence of cpSRP43. We have proposed a mechanism by which cpSRP43 is able to execute this action however further investigation is warranted to determine the exact mechanism(s) which may vary dependent on the target protein.

biochemistry↗

bioRxiv2016

Mindcontrol: A Web Application for Brain Segmentation Quality Control

Tissue classification plays a crucial role in the investigation of normal neural development, brain-behavior relationships, and the disease mechanisms of many psychiatric and neurological illnesses. Ensuring the accuracy of tissue classification is important for quality research and, in particular, the translation of imaging biomarkers to clinical practice. Assessment with the human eye is vital to correct various errors inherent to all currently available segmentation algorithms. Manual quality assurance becomes methodologically difficult at a large scale - a problem of increasing importance as the number of data sets is on the rise. To make this process more efficient, we have developed Mindcontrol, an open-source web application for the collaborative quality control of neuroimaging processing outputs. The Mindcontrol platform consists of a dashboard to organize data, descriptive visualizations to explore the data, an imaging viewer, and an in-browser annotation and editing toolbox for data curation and quality control. Mindcontrol is flexible and can be configured for the outputs of any software package in any data organization structure. Example configurations for three large, open-source datasets are presented: the 1000 Functional Connectomes Project (FCP), the Consortium for Reliability and Reproducibility (CoRR), and the Autism Brain Imaging Data Exchange (ABIDE) Collection. These demo applications link descriptive quality control metrics, regional brain volumes, and thickness scalars to a 3D imaging viewer and editing module, resulting in an easy-to-implement quality control protocol that can be scaled for any size and complexity of study.

bioinformatics↗