Biology subjects

Fowler, M.

Publications and source records attributed to Fowler, M..

10 recordsLinked to original sources

bioRxiv2026

The ultrastructure of subarachnoid trabeculae in non-human primates varies by tissue region within the central nervous system

The subarachnoid space (SAS) plays an important role in central nervous system (CNS) physiology, housing cerebrospinal fluid (CSF), providing nutrients, clearing waste, and protecting CNS tissues from injury. The SAS also contains an intricate arrangement of collagenous fibers, known as subarachnoid trabeculae, which serve as biomechanical support for the subarachnoid space and modulate the flow of CSF. Despite their myriad of roles in health and disease, the ultrastructure of trabeculae is incompletely described, with a specific gap in understanding how fiber structure varies across different regions of the CNS. In this work, we used optimized fixation techniques and scanning electron microscopy (SEM) imaging to study ultrastructural differences in trabeculae that were obtained from different regions of the nonhuman primate (NHP) brain and spinal cord. Qualitative assessments included evaluation of the relative prevalence of different kinds of fiber networks by region, leading us to a redefinition of terminology for fiber morphology. Quantitative measurements yielded dramatic differences in fiber diameter, density, and network porosity between different regions of the CNS. Broadly, trabeculae supporting cauda equina, cervical spinal cord, and exiting nerve roots were observed to have a very high density of small diameter fibers, whereas larger fibers and more complex arrangements were observed in other regions of the CNS. These data contribute to a growing field understanding of CNS-region specific differences in tissue ultrastructure.

neuroscience↗

bioRxiv2025

ALS/FTD-associated TDP-43 mutations promote fragility of genes governing excitatory neurotransmission via topoisomerase IIβ impairment

Abnormal TAR DNA/RNA-binding protein 43 (TDP-43) is a hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), characterized by cytoplasmic mis-localization, aggregation, and pathogenic mutations. Altered excitatory neuronal transmission is an early functional defect in these diseases; however, the underlying mechanisms remain unclear. Neuronal activity can induce DNA double-strand breaks (DSBs), suggesting a potential link between altered excitability and genomic instability. Here, we demonstrate for the first time that TDP-43 is involved in neuronal activity-induced DSBs. Moreover, we show that ALS/FTD-associated TDP-43 mutations (A90V and A315T) disrupt this mechanism, leading to the accumulation of DSBs and altered neuronal activity compared to wild-type TDP-43 protein. Using the BLISS technique, we mapped genome-wide DSBs in primary mouse neurons expressing wild-type or mutant (A90V, A315T) TDP-43 and found enrichment of DSBs within genes regulating excitatory transmission. Mechanistically, the TDP-43 A90V mutation impairs topoisomerase II{beta} function, resulting in enzyme trapping and/or DNA supercoiling that predisposes DNA to breaks. Notably, this impairment is partially rescued by tyrosyl-DNA phosphodiesterase 2 (Tdp2) overexpression. These findings uncover a novel mechanism linking aberrant neuronal activity and DNA damage, bridging two key pathological hallmarks of ALS/FTD associated with TDP-43 dysfunction. It also paves the way for developing novel therapeutic approaches that rely on targeted DSB repair and/or modulating topoisomerase II{beta}-DNA complexes. HighlightsO_LIALS/FTD linked TDP-43 mutants, unlike wild type, induce DSBs in key neuronal genes C_LIO_LITDP-43 driven DSBs impair neuronal transmission, linking two ALS/FTD pathologies C_LIO_LITDP-43 pathology impairs topoisomerase II{beta}, leading to DSB C_LI

neuroscience↗

bioRxiv2025

TDP-43 dysfunction leads to impaired proteostasis and predisposes mice to worse neurological outcomes after brain injury

BackgroundPathological TAR DNA-binding protein 43 (TDP-43) dysfunction is associated with multiple neurodegenerative disorders. However, the mechanistic link between TDP-43 dysfunction and neurodegeneration is poorly understood and likely involves a combination of genetic and environmental risk factors. A major risk factor for neurodegenerative disease is exposure to traumatic brain injury (TBI). Here, we investigated the synergistic interplay between TDP-43 dysfunction and TBI in a murine model of amyotrophic lateral sclerosis (ALS)/frontotemporal dementia (FTD). MethodsA model of TDP-43 dysfunction caused by a knock-in Q331K mutation in Tardbp was combined with a mild model of TBI. Control conditions included both WT mice and mice with sham surgery. Animals were evaluated for behavioral deficits at timepoints pre- and post-surgery. Additionally, post-mortem brain tissues were examined using RNA sequencing and mass spectrometry-based quantitative proteomics together with histological and biochemical analyses. ResultsExpression of dysfunctional TDP-43 in vivo caused deficits in multiple branches of the proteostasis network, including protein folding, protein synthesis, and protein turnover. Examples include mis-expression of chaperones and genes within the ubiquitin-proteosome pathway in mutant TDP-43 versus WT mice. Further, mutant TDP-43 expression correlated with reduced thermostability of proteins associated with the ribosome and the chaperonin containing TCP-1 complex. In response to TBI, mutant TDP-43 mice exhibited significantly worse neurological outcomes relative to WT animals. Heightened neurological deficits in mutant TDP-43 mice following TBI coincided with a robust upregulation of proteostasis- and stress-related genes at the transcript level. However, this upregulation was not detected at the protein level. ConclusionsOur data demonstrate that expression of dysfunctional TDP-43 leads to deficits within the proteostasis network in vivo at baseline. Despite an upregulation of proteostasis-related genes at the transcript level in mutant TDP-43 mice after TBI, mutant TDP-43 mice exhibit an impaired response to, and recovery from, brain trauma relative to their WT counterparts. Restoring proteostasis is expected to protect against the detrimental effects of TDP-43 dysfunction, especially under stress conditions that promote neurodegenerative disease.

neuroscience↗

bioRxiv2025

ChromeCRISPR - A High Efficacy Hybrid Machine Learning Model for CRISPR/Cas On-Target Predictions

Genome editing has the potential to treat genetic disorders at the source. This can be achieved by modifying the defective DNA through the intentional insertion, deletion, or substitution of genomic content. Among all genome editing technologies, CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein) is considered the gold standard. CRISPR/Cas uses a single guide RNA (sgRNA) to direct the Cas nuclease to a target DNA region. Due to the ease at creating small RNA molecules, it is possible to have the CRISPR/Cas complex target any arbitrary DNA sequence, thus making it a versatile tool. The efficacy of the complex is dependent on the ability of the sgRNA to bind to a complementary DNA sequence, which varies based on the sequence. Thus, a major challenge is finding sgRNA sequences that have good efficacy. This is where computational models can aid scientists: by predicting the activity of sgRNAs to help narrow the search space of finding the optimal sgRNA. We have used a large new dataset to build and compare the ability of several different machine learning architectures ability to predict on-target CRISPR/Cas activity. Additionally, we explored how adding GC content affects our sgRNA activity predictions. Our novel hybrid model, ChromeCRISPR, combines the strengths of Convolutional Neural Networks (CNN) with Recurrent Neural Network (RNN) models, has outperformed state-of-the-art models, including DeepHF and AttCrispr, establishing a new benchmark for predictive accuracy in CRISPR/Cas9 efficacy predictions.

bioinformatics↗

bioRxiv2024

Hydrocarbon-degrading microbial populations in permanently cold deep-sea sediments in the NW Atlantic

Permanently cold deep-sea sediments (2500-3500 m water depth) with or without indications of thermogenic hydrocarbon seepage were exposed to naphtha to examine the presence and potential of aerobic hydrocarbon-degrading microbial populations. Monitoring these microcosms for volatile hydrocarbons by GC-MS revealed sediments without in situ hydrocarbons responded more rapidly to naphtha amendment than hydrocarbon seep sediments overall, but seep sediments removed BTEX compounds more readily. Naphtha-driven aerobic respiration was more evident in surface sediment (0-20 cmbsf) than deeper anoxic layers (>130 cmbsf) that responded less rapidly. In all cases, enrichment of Gammaproteobacteria included lineages of Oleispira, Pseudomonas, and Alteromonas known to be associated with marine oil spills. On the other hand, taxa known to be prevalent in situ and diagnostic for thermogenic hydrocarbon seepage in deep sea sediment did not respond to naphtha amendment. This suggests a limited role for seep-associated populations in the context of oil spill biodegradation.

microbiology↗

bioRxiv2022

Bacterial anomalies in seabed sediments associated with deep water hydrocarbon seepage

Deep sea hydrocarbon seep detection relies predominantly on geochemical analyses of seabed marine sediment cores to identify the presence of gas or oil. The presence of seeping hydrocarbons in these locations alters resident microbial community structure, leading to culture-based biodegradation assays as a complement to geochemical tools for seep detection. Biodiversity surveys of microbial communities can offer a similar proxy for seeping hydrocarbons, but this strategy has not been extensively investigated in deep water settings. In this study, 16S rRNA gene sequencing of bacterial communities was performed on sediment cores obtained in >2500 m water depth at 43 different locations in the NW Atlantic Ocean. Core samples from as deep as 10 metres below seafloor (mbsf) were assessed for gas composition, gas isotopes and liquid hydrocarbons. Over 650 bacterial 16S rRNA gene amplicon libraries were constructed from different sediment depths at these locations. Select sites showed strong evidence for the presence of thermogenic or biogenic hydrocarbons such that bacterial population analyses revealed significant differences between hydrocarbon seep and non-seep locations. Specific bacterial indicators were associated with different sediment depth intervals. Caldatribacteriota and Campilobacterota OTUs were observed in high relative sequence abundance in hydrocarbon seep sediments, particularly in the 20-50 cmbsf interval. Furthermore, these groups were differentially abundant between sites with thermogenic and biogenic hydrocarbons. The patterns revealed here suggest that microbial screening has the potential to play a key role in hydrocarbon seep detection and characterisation in remote deep-sea environments.

microbiology↗

bioRxiv2021

Flying In-formation: A computational method for the classification of host seeking mosquito flight patterns using path segmentation and unsupervised machine learning

The rational design of effective vector control tools requires detailed knowledge of vector behaviour. Yet, behavioural observations, interpretations, evaluations and definitions by even the most experienced researcher are constrained by subjectivity and perceptual limits. Seeking an objective alternative to expertise, we developed and tested an unsupervised method for the automatic identification of video-tracked mosquito flight behaviour. This method unites path-segmentation and unsupervised machine learning in an innovative workflow and is implemented using a combination of R and python. The workflow (1) records movement trajectories; (2) applies path-segmentation; (3) clusters path segments using unsupervised learning; and (4) interprets results. Analysis of the flight patterns of An. gambiae s.s., responding to human-baited insecticide-treated bednets (ITNs), by the new method identified four distinct behaviour modes: with swooping and approaching modes predominant at ITNs; increased walking behaviours at untreated nets; similar rates of reacting at both nets; and higher overall activity at treated nets. The methods validity was tested by comparing these findings with those from a similar setting using an expertise-based method. The level of correspondence found between the studies validated the accuracy of the new method. While researcher-defined behaviours are inherently subjective, and prone to corollary shortcomings, the new approachs mathematical method is objective, automatic, repeatable and a validated alternative for analysing complex vector behaviour. This method provides a novel and adaptable analytical tool and is freely available to vector biologists, ethologists and behavioural ecologists. Author summaryVector control targets the insects and arachnids that transmit 1 in every 6 communicable diseases worldwide. Since the effectiveness of many vector control tools depends on exploiting or changing vector behaviour, a firm understanding of this behaviour is required to maximise the impact of existing tools and design new interventions. However, current methods for identifying such behaviours are based primarily on expert knowledge, which can be inefficient, difficult to scale and limited by perceptual abilities. To overcome this, we present, detail and validate a new method for categorising vector behaviour. This method combines existing path segmentation and unsupervised machine learning algorithms to identify changes in vector movement trajectories and classify behaviours. The accuracy of the new method is demonstrated by replicating existing, expert-derived, findings covering the behaviour of host-seeking mosquitos around insecticide treated bednets, compared to nets without insecticide. As the method found the same changes in mosquito activity as previous research, it is said to be validated. The new method is significant, as it improves the analytical capabilities of biologists working to reduce the burden of vector-borne diseases, such as malaria, through an understanding of behaviour.

animal behavior and cognition↗

bioRxiv2021

Geological processes mediate a subsurface microbial loop in the deep biosphere

Summary paragraphThe deep biosphere is the largest microbial habitat on Earth and features abundant bacterial endospores1,2. Whereas dormancy and survival at theoretical energy minima are hallmarks of subsurface microbial populations3, the roles of fundamental ecological processes like dispersal and selection in these environments are poorly understood4. Here we combine geophysics, geochemistry, microbiology and genomics to investigate biogeography in the subsurface, focusing on bacterial endospores in a deep-sea setting characterized by thermogenic hydrocarbon seepage. Thermophilic endospores in permanently cold seabed sediments above petroleum seep conduits were correlated with the presence of hydrocarbons, revealing geofluid-facilitated cell migration pathways originating in deep oil reservoirs. Genomes of thermophilic bacteria highlight adaptations to life in anoxic petroleum systems and reveal that these dormant populations are closely related to oil reservoir microbiomes from around the world. After transport out of the subsurface and into the deep-sea, thermophilic endospores re-enter the geosphere by sedimentation. Viable thermophilic endospores spanning the top several metres of the seabed correspond with total endospore counts that are similar to or exceed the global average. Burial of dormant cells enables their environmental selection in sedimentary formations where new petroleum systems establish, completing a geological microbial loop that circulates living biomass in and out of the deep biosphere.

microbiology↗

bioRxiv2020

Thermogenic hydrocarbons sustain diverse subseafloor microbial communities in deep sea cold seep sediments

At marine cold seeps, gaseous and liquid hydrocarbons migrate from deep subsurface origins to the sediment-water interface. Cold seep sediments are known to host taxonomically diverse microorganisms, but little is known about their metabolic potential and depth distribution in relation to hydrocarbon and electron acceptor availability. In this work, we combined geochemical, metagenomic and metabolomic measurements in distinct sediment redox regimes to profile microbial activities within the uppermost 350 cm of a newly discovered cold seep in the NW Atlantic deep sea (2.3 km water depth). Depth-resolved metagenomic profiling revealed compositional and functional differentiation between near-surface sediments (dominated by Proteobacteria) and deeper subsurface layers (dominated by Atribacteria, Chloroflexi, Euryarchaeota and Lokiarchaeota). Metabolic capabilities of community members were inferred from 376 metagenome-assembled genomes spanning 46 phyla (including five novel candidate phyla). In deeper sulfate-reducing and methanogenic sediments, various community members are capable of anaerobically oxidizing short-chain alkanes (alkyl-CoM reductase pathway), longer-chain alkanes (fumarate addition pathway), and aromatic hydrocarbons (fumarate addition and subsequent benzoyl-CoA pathways). Geochemical profiling demonstrated that hydrocarbon substrates are abundant in this location, thermogenic in origin, and subject to biodegradation. The detection of alkyl-/arylalkylsuccinate metabolites, together with carbon isotopic signatures of ethane, propane and carbon dioxide, support that microorganisms are actively degrading hydrocarbons in these sediments. Hydrocarbon oxidation pathways operate alongside other deep seabed metabolisms such as sulfide oxidation, hydrogen oxidation, carbon fixation, fermentation and reductive dehalogenation. Upward migrated thermogenic hydrocarbons thus sustain diverse microbial communities with activities that affect subseafloor biogeochemical processes across the redox spectrum in deep sea cold seeps.

microbiology↗

bioRxiv2018

Telomere length, individual quality and fitness in female European starlings (Sturnus vulgaris) during breeding

Telomeres, short guanine-rich repeats that cap linear chromosomes, are involved in cell senescence and organismal ageing. Our present understanding of telomere function oscillates between a marker of individual quality, which should be positively correlated with reproduction, to a marker of costs of reproduction (e.g. due to DNA damage). To test these quality and cost hypotheses, we tested the output of very simple predictions in a free-living population of European starlings Sturnus vulgaris where reproductive success of adult females was followed over 2 breeding seasons (with 2 broods per breeding). If telomere length indicate individual quality, low quality females (LQ, no fledgling) should have lower telomere lengths than high quality females (which produced fledglings in 1st and 2nd broods). Additionally, physiological determinants of adult individual quality (established in a previous study) and provisioning rate should be positively associated with adult telomere lengths. Finally, telomere length should predict future reproductive success. Adult telomere length was lower in LQ females but only during the chick-rearing period. Females producing larger clutches at fledging in the 1st brood of the 1st year also had longer telomeres. Provisioning rate was positively related to telomere length, as were plasma markers of oxidative damage, non-esterified fatty acids and triglycerides. Despite these associations, we found weak support for telomeres as indicators of individual quality. Telomere length failed in predicting future reproduction success and there was a lack of consistency in within-individual telomere length over the breeding season. In starlings, we suggest that telomere length may indicate current breeding capacities and energy status of female adults, rather than future fecundity/survival.

evolutionary biology↗