Biology subjects

Ward, M.

Publications and source records attributed to Ward, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Classical statistical methods are powerful for the identification of novel targets for the survival of breast cancer patients

Breast cancer is a leading cause of cancer-related deaths among women. The identification of survival-related target genes is critical for improving the prognosis and outcomes of breast cancer patients. Many methods have been applied to this investigation, such as bioinformatics and machine learning approaches, yet few targets identified from these approaches have been applied in clinics. Here, we present a novel approach by using classical statistical methods of Kolmogorov-Smirnov (KS) test and Jensen-Shannon (JS) divergence to analyse the survival time and gene expression data of breast cancer patients (BRCA) from The Cancer Genome Atlas (TCGA). These methods help compare the survival time distributions and differentiate patients into high and low-risk groups based on gene expression profiles. 1,124 survival-related genes were identified based on the KS test and 18 from JS divergence values. We also identified the optimal thresholds of the expression level of these target genes, which enabled the best separation of survival groups for all breast cancer patients and each subtype of breast cancer patients. These targets were further validated through bootstrapping to ensure that significant results are not due to chance. By comparing those survival targets from previous studies, we found two were novel targets, and two were consistent with previous reports. Overall, our study provides a novel approach for identifying survival targets for breast cancer patients by integrating a series of classical statistical methods, such as the KS test, JS divergence, and bootstrapping. Our approach could also be applied to identifying the survival targets for other cancer types and provide valuable insights into cancer research and clinical applications.

bioinformatics↗

bioRxiv2024

Maintenance of neuronal TDP-43 expression requires axonal lysosome transport

TDP-43 mislocalization and pathology occurs across a range of neurodegenerative diseases, but the pathways that modulate TDP-43 in neurons are not well understood. We generated a Halo-TDP-43 knock-in iPSC line and performed a genome-wide CRISPR interference FACS-based screen to identify modifiers of TDP-43 levels in neurons. A meta-analysis of our screen and publicly available screens identified both specific hits and pathways present across multiple screens, the latter likely responsible for generic protein level maintenance. We identified BORC, a complex required for anterograde lysosome transport, as a specific modifier of TDP-43 protein, but not mRNA, levels in neurons. BORC loss led to longer half-life of TDP-43 and other proteins, suggesting lysosome location is required for proper protein turnover. As such, lysosome location and function are crucial for maintaining TDP-43 protein levels in neurons.

neuroscience↗

bioRxiv2024

Widespread occurrence of benzimidazole resistance SNPs in the canine hookworm, Ancylostoma caninum, in Australia

Canine hookworm (Ancylostoma caninum), a gastrointestinal nematode of domestic dogs, principally infects the small intestine of dogs and has the potential to cause zoonotic disease. In greyhounds and pet dogs in the USA, A. caninum has been shown to be resistant to multiple anthelmintics. We conducted a molecular survey of benzimidazole resistance in A. caninum from dogs at veterinary diagnostic centers in Australia and New Zealand. First, we implemented an internal transcribed spacer (ITS)-2 rDNA deep amplicon metabarcoding sequencing approach to ascertain the species of hookworms infecting dogs in the region. Then, we evaluated the frequency of the canonical F167Y and Q134H isotype-1 {beta}-tubulin mutations, which confer benzimidazole resistance, using the same sequencing approach. The most detected hookworm species in diagnostic samples was A. caninum (90%; 83/92); the related Northern hookworm (Uncinaria stenocephala) was identified in 11% (10/92) of the diagnostic samples. There was a single sample with coinfection by A. caninum and U. stenocephala. Both isotype-1 {beta}-tubulin mutations were present in A. caninum, 49% and 67% for Q134H and F167Y, respectively. Mutation F167Y in the isotype-1 {beta}-tubulin mutation was recorded in U. stenocephala for the first known time. Canonical benzimidazole resistance codons 198 and 200 mutations were absent. Egg hatch assays performed on a subset of the A. caninum samples showed significant correlation between 50% inhibitory concentration (IC50) to thiabendazole and F167Y, with an increased IC50 for samples with >75% F167Y mutation. We detected 14% of dogs with >75% F167Y mutation in A. caninum. Given that these samples were collected from dogs across various regions of Australia, the present study suggests that benzimidazole resistance in A. caninum is widespread. Therefore, to mitigate the risk of resistance selection and further spread, adoption of a risk assessment-based approach to limit unnecessary anthelmintic use should be a key consideration for future parasite control.

microbiology↗

bioRxiv2024

TDP43 autoregulation gives rise to shortened isoforms that are tightly controlled by both transcriptional and post-translational mechanisms

The nuclear RNA-binding protein TDP43 is integrally involved in the pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). Previous studies uncovered N-terminal TDP43 isoforms that are predominantly cytosolic in localization, highly prone to aggregation, and enriched in susceptible spinal motor neurons. In healthy cells, however, these shortened (s)TDP43 isoforms are difficult to detect in comparison to full-length (fl)TDP43, raising questions regarding their origin and selective regulation. Here, we show that sTDP43 is created as a byproduct of TDP43 autoregulation and cleared by nonsense mediated RNA decay (NMD). The sTDP43-encoding transcripts that escape NMD can lead to toxicity but are rapidly degraded post-translationally. Circumventing these regulatory mechanisms by overexpressing sTDP43 results in neurodegeneration in vitro and in vivo via N-terminal oligomerization and impairment of flTDP43 splicing activity, in addition to RNA binding-dependent gain-of-function toxicity. Collectively, these studies highlight endogenous mechanisms that tightly regulate sTDP43 expression and provide insight into the consequences of aberrant sTDP43 accumulation in disease.

neuroscience↗

bioRxiv2024

Scalable Differentiable for mRNA Design

mRNA is an emerging therapeutic platform with applications ranging from vaccines to genome editing. However, there are an exponential number of mRNA sequences to deliver a given payload and the choice in nucleotide sequence largely determines stability and translation efficiency. There exist several computational approaches for optimizing mRNA sequences but these algorithms are limited in performance or the choice of optimization metric. In this work we describe a new mRNA design algorithm that overcomes both of these limitations and is based on differentiable folding, a recently developed paradigm for RNA design in which a probabilistic sequence representation is optimized via gradient-based methods. First, we present major improvements to the original differentiable folding algorithm that drastically reduce the memory overhead of the gradient calculation. Second, we formulate the mRNA design problem in the context of continuous sequences, requiring the generalization of existing metrics and careful treatment of constraints. Given this scaled algorithm and our mRNA design formalism, we then developed a generative deep learning approach that treats our differentiable folding algorithm as a module in a larger optimization pipeline to learn a network that samples optimized sequences. As a demonstration of our method, we optimize mRNA sequences via complex, therapeutically relevant objective functions.

bioinformatics↗

bioRxiv2024

Targeting complement C3a receptor resolves mitochondrial hyperfusion and subretinal microglial activation in progranulin-deficient frontotemporal dementia

Mutations in progranulin (GRN) cause frontotemporal dementia (GRN-FTD) due to deficiency of the pleiotropic protein progranulin. GRN-FTD exhibits diverse pathologies including lysosome dysfunction, lipofuscinosis, microgliosis, and neuroinflammation. Yet, how progranulin loss causes disease remains unresolved. Here, we report that non-invasive retinal imaging of GRN-FTD patients revealed deficits in photoreceptors and the retinal pigment epithelium (RPE) that correlate with cognitive decline. Likewise, Grn-/- mice exhibit early RPE dysfunction, microglial activation, and subsequent photoreceptor loss. Super-resolution live imaging and transcriptomic analyses identified RPE mitochondria as an early driver of retinal dysfunction. Loss of mitochondrial fission protein 1 (MTFP1) in Grn-/- RPE causes mitochondrial hyperfusion and bioenergetic defects, leading to NF-kB-mediated activation of complement C3a-C3a receptor signaling, which drives further mitochondrial hyperfusion and retinal inflammation. C3aR antagonism restores RPE mitochondrial integrity and limits subretinal microglial activation. Our study identifies a previously unrecognized mechanism by which progranulin modulates mitochondrial integrity and complement-mediated neuroinflammation.

neuroscience↗

bioRxiv2024

The T3SS structural and effector genes of Chlamydia trachomatis are expressed in distinct phenotypic cell forms.

Bacteria in the chlamydiales order are obligate intracellular parasites of eukaryotic cells. Within this order, the genus Chlamydia contains the causative agents of a number of clinically important infections of humans. Biovars of C. trachomatis are the causative agents of trachoma, the leading cause of preventable blindness worldwide, as well as sexually transmitted infections with the potential to cause pelvic inflammatory disease and infertility. Irrespective of the resulting disease, all chlamydial species share the same obligate intracellular life cycle and developmental cell forms. They are reliant on an infectious cycle consisting of at least three phenotypically distinct cell forms termed the reticulate body (RB), the intermediate body (IB) and the elementary body (EB). The EB is infectious but does not replicate. The RB replicates in the host cell but is non-infectious, while the IB is an intermediate form that transitions to the EB form. In this study, we ectopically expressed the transcriptional repressor Euo, the two nucleoid-associated proteins HctA and HctB, and the two component sensor kinase CtcB in the RB. Transcriptional analysis using RNA-seq, differential expression clustering and fluorescence in situ hybridization analysis show that the chlamydial developmental cycle is driven by three distinct regulons corresponding to the RB, IB or EB cell forms. Moreover, we show that the genes for the T3SS were cell type restricted, suggesting defined functional roles for the T3SS in specific cell forms. ImportanceChlamydia trachomatis, a sexually transmitted bacterial infection, poses a significant global health threat, causing over 100 million infections annually and leading to complications like ectopic pregnancy and infertility. This study investigates the gene expression patterns of Chlamydia trachomatis during its unique life cycle within human cells. As an obligate intracellular parasite, C. trachomatis transitions through distinct developmental stages - one for infection and dissemination, another for replication, and a third for transitioning back to the infectious form. By analyzing gene expression profiles at each stage, we identified key genes involved in these processes. Interestingly, our research also reveals the presence of two separate T3SS (Type III Secretion System) translocons expressed in distinct stages, suggesting their crucial roles in specific functions during the infection cycle.

microbiology↗

bioRxiv2024

A comparative study of circulating tumor cell isolation and enumeration technologies in lung cancer

Circulating tumor cells (CTCs) have potential as diagnostic, prognostic and predictive biomarkers in solid tumors. Despite FDA approval of CTC devices in various cancers, their rarity and limited comparison between analysis methods hinder their clinical integration for lung cancer. This study aimed to evaluate five CTC isolation technologies using a standardized spike-in protocol: the CellMag (EpCAM-based enrichment), EasySep and RosetteSep (blood cell depletion), and the Parsortix(R) PR1 and next generation Parsortix(R) Plus (PX+) (size-based enrichment). The Parsortix(R) systems were also evaluated for any difference in recovery rates between cell harvest versus in- cassette staining. Healthy donor blood (5 mL) was spiked with 100 fluorescently labeled H1975 lung adenocarcinoma cell line, processed through each system and the isolation efficiency was calculated. All tested systems yielded discordant recovery rates with the CellMag having the highest mean recovery (70 {+/-} 14%) followed by the PR1 (in-cassette staining) with a recovery of 49 {+/-} 2% while the EasySep had the lowest recovery (18 {+/-} 8%). The CellMag and Parsortix(R) PR1 may have potential clinical applications for lung cancer patients, albeit needing further optimization and validation.

cancer biology↗

bioRxiv2024

TDP-43 loss induces extensive cryptic polyadenylation in ALS/FTD

Nuclear depletion and cytoplasmic aggregation of the RNA-binding protein TDP-43 is the hallmark of ALS, occurring in over 97% of cases. A key consequence of TDP-43 nuclear loss is the de-repression of cryptic exons. Whilst TDP-43 regulated cryptic splicing is increasingly well catalogued, cryptic alternative polyadenylation (APA) events, which define the 3 end of last exons, have been largely overlooked, especially when not associated with novel upstream splice junctions. We developed a novel bioinformatic approach to reliably identify distinct APA event types: alternative last exons (ALE), 3UTR extensions (3Ext) and intronic polyadenylation (IPA) events. We identified novel neuronal cryptic APA sites induced by TDP-43 loss of function by systematically applying our pipeline to a compendium of publicly available and in house datasets. We find that TDP-43 binding sites and target motifs are enriched at these cryptic events and that TDP-43 can have both repressive and enhancing action on APA. Importantly, all categories of cryptic APA can also be identified in ALS and FTD post mortem brain regions with TDP-43 proteinopathy underlining their potential disease relevance. RNA-seq and Ribo-seq analyses indicate that distinct cryptic APA categories have different downstream effects on transcript and translation. Intriguingly, cryptic 3Exts occur in multiple transcription factors, such as ELK1, SIX3, and TLX1, and lead to an increase in wild-type protein levels and function. Finally, we show that an increase in RNA stability leading to a higher cytoplasmic localisation underlies these observations. In summary, we demonstrate that TDP-43 nuclear depletion induces a novel category of cryptic RNA processing events and we expand the palette of TDP-43 loss consequences by showing this can also lead to an increase in normal protein translation.

neuroscience↗

bioRxiv2023

ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics

Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, personalized medicine, systems biology and biomedical applications. By combining MS with different proteomics approaches such as immunopurification MS, immunopeptidomics, and total protein proteomics, researchers can gain insights into protein-protein interactions, immune responses, cellular processes, and disease mechanisms. The application of MS-based proteomics in these areas continues to advance our understanding of protein function, cellular signaling, and complex biological systems. Data analysis for mass spectrometry is a critical process that includes identifying and quantifying proteins and peptides and exploring biological functions for these proteins in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analysis. ProtPipe provides downstream analysis including identifying differential abundance proteins and peptides, pathway enrichment analysis, protein-protein interaction analysis, and MHC1-peptide binding affinity. ProtPipe generates annotated tables and diagnostic visualizations from statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. ProtPipe is well-documented open-source software and is available at https://github.com/NIH-CARD/ProtPipe, accompanied by a web interface.

bioinformatics↗

bioRxiv2023

memerna: Sparse RNA Folding Including Coaxial Stacking

AO_SCPLOWBSTRACTC_SCPLOWDetermining RNA secondary structure is a core problem in computational biology. Fast algorithms for predicting secondary structure are fundamental to this task. We describe a modified formulation of the Zuker-Stiegler algorithm with coaxial stacking, a stabilizing interaction in which the ends of multi-loops are stacked. In particular, optimal coaxial stacking is computed as part of the dynamic programming state, rather than inline. We introduce a new notion of sparsity, which we call replaceability. The modified formulation along with replaceability allows sparsification to be applied to coaxial stacking as well, which increases the speed of the algorithm. We implemented this algorithm in software we call memerna, which we show to have the fastest exact RNA folding implementation out of several popular RNA folding packages supporting coaxial stacking. We also introduce a new notation for secondary structure which includes coaxial stacking, terminal mismatches, and dangles (CTDs) information.

bioinformatics↗

bioRxiv2023

The impacts of contemporary logging after 250 years of deforestation and degradation on forest-dependent threatened species

Despite the importance of safeguarding forests and woodlands for achieving global climate and biodiversity agendas, logging continues across most forested countries. Forestry advocates often claim logging has minimal impacts, but rarely consider the cumulative threat deforestation and degradation has had, and continue to have, on species. Using New South Wales (Australia) as a case study, we quantify the extent of deforestation and degradation from 1750 - current. Using these estimates of overall loss as a baseline, we then quantify the relative extent of contemporary (2000 - 2022) logging and the condition of the remaining native forest and woodland (quantified by measuring the similarity of a current ecosystem to a historical reference state with high ecological integrity). Using these data, we measure the impacts on distinct vegetation types and on 484 terrestrial forest-dependent now-threatened species. We show that more than half (29 million ha) of pre-1750 (pre-European colonization of Australia) native forest and woodland vegetation in NSW has been lost. Of the remaining 25 million ha, 9 million ha is degraded. We found contemporary degradation from logging affected 244 forest-dependent now-threatened species that had already been affected by this historical deforestation and degradation, but the impacts varied across species and vegetation types. We found that 70 now-threatened species that were impacted by historical deforestation and degradation and continue to be impacted by logging, now have [≤]50% of their pre-1750 extent remaining that is intact (with three species now having <20%). By quantifying the historical impacts of deforestation and degradation, our research sets the impact of contemporary degradation from logging in perspective and highlights shortfalls in current environmental assessments that fail to consider appropriate baselines when reporting on overall impact. Future land management decisions need to consider not only the extent of remaining habitat based on pre-1750 extents, but also its condition. Article impact statementThe impact of logging needs to be placed in perspective by considering past losses and degradation due to human land use decisions.

ecology↗

bioRxiv2023

Differentiable Partition Function Calculation for RNA

AO_SCPLOWBSTRACTC_SCPLOWRibonucleic acid (RNA) is an essential molecule in a wide range of biological functions. In 1990, McCaskill introduced a dynamic programming algorithm for computing the partition function of an RNA sequence. This forward model is widely used for understanding the thermodynamic properties of a given RNA. In this work, we introduce a generalization of McCaskills algorithm that is well-defined over continuous inputs and is differentiable. This allows us to tackle the inverse folding problem--designing a sequence with desired equilibrium thermodynamic properties--directly using gradient optimization. This has applications to creating RNA-based drugs such as mRNA vaccines. Furthermore, it allows McCaskills foundational algorithm to be incorporated into machine learning pipelines directly since we have made it end-to-end differentiable. This work highlights how principles from differentiable programming can be translated to existing physical models to develop powerful tools for machine learning. We provide a concrete example by implementing an effective and interpretable RNA design algorithm.

bioinformatics↗

bioRxiv2023

Proline catabolism is key to facilitating Candida albicans pathogenicity

Candida albicans, the primary etiology of human mycoses, is well-adapted to catabolize proline to obtain energy to initiate morphological switching (yeast to hyphal) and for growth. We report that put1-/- and put2-/- strains, carrying defective Proline UTilization genes, display remarkable proline sensitivity with put2-/- mutants being hypersensitive due to the accumulation of the toxic intermediate P5C, which inhibits mitochondrial respiration. The put1-/- and put2-/- mutations attenuate virulence in Drosophila and murine candidemia models. Using intravital 2-photon microscopy and label-free non-linear imaging, we visualized the initial stages of C. albicans cells colonizing a kidney in real-time, directly deep in the tissue of a living mouse, and observed morphological switching of wildtype but not of put2-/- cells. Multiple members of the Candida species complex, including C. auris, are capable of using proline as a sole energy source. Our results indicate that a tailored proline metabolic network tuned to the mammalian host environment is a key feature of opportunistic fungal pathogens.

microbiology↗

bioRxiv2022

iPSC Motor Neurons with Familial ALS Mutations Capture Gene Expression Changes in Postmortem Sporadic ALS Motor Neurons

Motor neuron degeneration, the defining feature of ALS, is a primary example of cell-type specificity in neurodegenerative diseases. Using isogenic pairs of iPSCs harboring different familial ALS mutations, we assess the capacity of iPSC-derived spinal motor neurons, sensory neurons, astrocytes, and superficial cortical neurons to capture disease features including transcriptional and splicing dysregulation observed in human post-mortem neurons. At surprisingly early time points, differentially regulated genes in iPSC-derived spinal motor neurons, but not other cell types, overlap with one-third of the differentially regulated genes in laser-dissected motor neurons from postmortem spinal cords. The extent of dysregulation correlates well between iPSC-derived and bona fide spinal motor neurons. In iPSC-derived spinal motor neurons, but not other derived cell types, we detect downregulation of genes affected by TDP-43-dependent aberrant splicing. This reduction takes place exclusively within genotypes known to involve TDP-43 pathology and occurs without evidence of TDP-43 mislocalization or protein level alteration.

neuroscience↗

bioRxiv2022

A report card methodology to showcase progress towards threatened species recovery

Among the conservation community, it is well known that Earths mass species extinction crisis is getting worse. Yet, an often neglected problem is the need for effectively communicating the species extinction crisis to diverse audiences in ways that catalyse immediate action. Here we generated a streamlined threatened species recovery report card methodology, which combined two input indicators including planning and funding, one output indicator capturing habitat protection, and one outcome indicator which highlights threatened species trajectories, to provide simple scores for all Australian threatened species. We show that just 41 (2.3%) of species achieved an A grade for the input indicator (i.e., recovery plans and federal funding), 240 (13.3%) achieved a C grade, and 1,521 (84.4%) achieved an F. Five hundred and twenty nine (29.3%) species achieved an A for the output indicator (i.e, habitat protection), 130 (7.2%) achieved a B, 158 (8.8%) achieved a C, 189 (10.5%) achieved a D, 212 (11.8%) achieved an E, and 584 (32.4%) achieved a F. While five (0.3%) species achieved an A for the output indicator (i.e., threat status improvement), every other species (99.7%) achieved an F. We provide a method to combine scores to test how individual jurisdictions are tracking and show that Australia is achieving an F for the input and outcome indicators, and a D for the output indicator. While the threatened species recovery report card highlighted a clear failure in many federal environmental legislation responsibilities, it provides a baseline from which different governments can track policy progress and outlines clear direction for immediate improvement including developing adequate recovery plans, funding the actions in the recovery plans, protecting habitat from further destruction, verifying recovery through monitoring and evaluation of species trajectories, and supporting transparency and collaboration on the execution on the plans through an improved data infrastructure. Without an immediate step change in how Australia communicates and faces its species crisis, we will leave a tragic legacy of extinction and fail our obligations to future generations of Australians, and the international community.

scientific communication and education↗

bioRxiv2022

Predicting the locations of cryptic pockets from single protein structures using the PocketMiner graph neural network

Cryptic pockets expand the scope of drug discovery by enabling targeting of proteins currently considered undruggable because they lack pockets in their ground state structures. However, identifying cryptic pockets is labor-intensive and slow. The ability to accurately and rapidly predict if and where cryptic pockets are likely to form from a protein structure would greatly accelerate the search for druggable pockets. Here, we present PocketMiner, a graph neural network trained to predict where pockets are likely to open in molecular dynamics simulations. Applying PocketMiner to single structures from a newly-curated dataset of 39 experimentally-confirmed cryptic pockets demonstrates that it accurately identifies cryptic pockets (ROC-AUC: 0.87) >1,000-fold faster than existing methods. We apply PocketMiner across the human proteome and show that predicted pockets open in simulations, suggesting that over half of proteins thought to lack pockets based on available structures are likely to contain cryptic pockets, vastly expanding the druggable proteome.

biophysics↗

bioRxiv2022

Fitness Functions for RNA Structure Design

AO_SCPLOWBSTRACTC_SCPLOWAn RNA design algorithm takes a target RNA structure and finds a sequence that folds into that structure. This is fundamentally important for engineering therapeutics using RNA. Computational RNA design algorithms are guided by fitness functions, but not much research has been done on the merits of these functions. We survey current RNA design approaches with a particular focus on the fitness functions used. We experimentally compare the most widely used fitness functions in RNA design algorithms on both synthetic and natural sequences. It has been almost 20 years since the last comparison was published, and we find similar results with a major new result: maximizing probability outperforms minimizing ensemble defect. The probability is the likelihood of a structure at equilibrium and the ensemble defect is the weighted average number of incorrect positions in the ensemble. Also, we observe that many recently published approaches minimize structure distance to the minimum free energy prediction, which we find to be a poor fitness function.

bioinformatics↗