Biology subjects

Wright, R.

Publications and source records attributed to Wright, R..

17 recordsLinked to original sources

bioRxiv2026

Hunting for Helminths: short- and long-read shotgun metagenomics for parasite detection in faecal samples

Soil-transmitted helminths (STHs) pose significant challenges to public health in endemic areas, necessitating reliable methods for their detection. Shotgun metagenomics enables simultaneous detection of STHs and microbes in a sample without prior knowledge of what is present. However, validation of shotgun metagenomics with known infection intensity or across different sequencing platforms has not been carried out for eukaryote parasites including STHs, and false positives remain a pervasive issue. We validated shotgun metagenomics as a method of STH detection in faecal samples. Using the Strongyloides ratti laboratory model of a STH infection we investigated how analytical methods (nucleotide-nucleotide matching, nucleotide-protein matching, marker gene detection, mitochondrial mapping), infection intensity and sequencing technology (short-read vs. long-read) affects sensitivity and specificity of detection. S. ratti was accurately detected at a standard laboratory dose, but low intensity infections were more difficult to detect. Only mitochondrial sequence mapping was 100% accurate at identifying S. ratti with no false positives. Overall, short-read outperformed long-read sequencing methods. We applied the same analytical methods to human faecal samples with confirmed infections for at least one of four STHs. Mitochondrial sequence mapping was also the most effective method for detecting STHs in human faecal samples, detecting 100% of Necator americanus and 92% of Ascaris spp. infections, but could not reliably detect STHs where DNA levels are expected to be low or variable. In conclusion, mitochondrial mapping was the most effective method of detection for sensitivity and specificity in both the laboratory system and human faecal samples. Our findings indicate that shotgun metagenomics should be approached cautiously using validated methods, particularly when infection intensity or DNA levels are expected to be low. Author SummarySoil-transmitted helminths (STH) such as the parasite Strongyloides, are important gastrointestinal parasites of humans and livestock. Accurate methods of detection for diagnostics and monitoring are important to implement suitable control and treatment strategies. Here we validate a shotgun metagenomics approach, where all DNA in a sample is sequenced, for detecting STH in faecal samples using a Strongyloides laboratory model for infection. Strongyloides was reliability detected in faecal samples at higher infection levels, but mitochondrial genome mapping of the sequences was the only analytical method that reliably detected Strongyloides at lower infections levels. These results were reflected in stool samples from humans infected with STH, where mitochondrial mapping was also the most reliable method. However, species that were associated with low levels of parasite material or DNA in the faeces including Strongyloides stercoralis, were more difficult to detect. We compared two sequencing methods: short-read Illumina and long-read Oxford Nanopore Technologies, but short-read outperformed long-read shotgun metagenomics. Contamination of bacteria sequences in parasite genome assemblies was problematic for analysis and contributed to false positive results. Future work should focus on specific targeting of eukaryote DNA either at the laboratory or bioinformatic stage to improve STH detection further.

molecular biology↗

bioRxiv2026

Brain-derived ketone bodies can replace glucose to power neural function

The vertebrate brain is exquisitely sensitive to disruptions in glucose metabolism, and failure of adequate glucose delivery causes neurological dysfunction. Here, we discovered an animal with the capacity to defy this rule: We show that neural activity in frogs, animals with seemingly typical glucose demands, can stop metabolizing glucose by, in part, shifting to ketone bodies made exclusively within the brain after emergence from hibernation. This involves ketone body synthesis and transport from astrocytes to neurons to power synaptic transmission, along with the upregulation of gene expression that controls fatty acid catabolism and ketone body transport. Brain-derived ketone bodies also prevent decrements in activity that occur during hypoxia. These results provide insight into how frogs restart brain circuits following months of underwater hibernation when facing severe hypoxia and hypoglycemia that otherwise strongly impair neural performance in most animals. More broadly, they reveal the vertebrate brain has the capacity to serve as its own fuel reserve during the cessation of glucose metabolism, switching seamlessly to locally sourced ketone bodies while maintaining neural activity. This reframes glucose metabolism in the vertebrate brain not as a hard-wired necessity, but as a plastic trait that can in some cases be entirely abandoned. SignificanceThe brain relies on a continuous supply of glucose from the blood to support the large energy demands of neural activity. When glucose delivery is disrupted, neural activity collapses within minutes. Here, we demonstrate that hibernation induces a large capacity for frogs, animals with seemingly normal glucose needs, to operate neural circuits without glucose metabolism, replacing it ketone bodies produced exclusively within the brain. These results reveal that a brain-derived, non-glucose fuel reserve can power neural function in the absence of glucose delivery. These findings reframe neural activitys reliance on continuous glucose metabolism as a plastic trait, rather than a hard-wired constraint.

physiology↗

bioRxiv2025

Arthropod predator nutrient content changes with crop sowing period with implications for biocontrol

Conservation biocontrol is crucial for crop pest management, but the impact of agricultural management practices on natural enemies of crop pests is poorly characterised. The timing of crop sowing could impact arthropod communities by altering basal resource availability and quality, manifesting in altered nutrient availability and cascading impacts to natural enemy fitness and function. This study aims to understand these potential modifiers of conservation biocontrol, by investigating how the timing of crop sowing impacts arthropod predator nutrition and whether associated differences relate to changes in prey availability. Arthropod predators and their prey were collected from adjacent plots of winter- and spring-sown wheat. The biochemical macronutrient (carbohydrate, lipid and protein) content of predators was determined by colorimetric assays and compared between winter-and spring-sown crops using multivariate models. Predator nutrient contents were compared to predator-prey interactions inferred using null network models based on both recent and current prey availability. The nutrient contents of arthropod predators differed significantly between winter- and spring-sown wheat, and the prey available to predators similarly differed, but neither recent nor current prey availability explained differences in predator nutrition. These findings may indicate that prey quality, rather than identity, changes with the developmental stages of crops sown at different times. This has important implications for the spillover of natural enemies of crop pests between crops sown at different times. This is especially true following harvest of winter-sown crops, which may disrupt biocontrol by altering the nutrients available to and sought by natural enemies of crop pests.

ecology↗

bioRxiv2025

Identifying Effective Cryoprotectant Agents for Emerging Bacterial Model Species

Host-associated bacteria live amongst eukaryotes within varied niches and form relationships ranging from facultative to obligate. With advancement in studies of such symbiotic associations, fastidious bacteria are increasingly becoming targets for genetic manipulation. However, there are limited resources for screening possible agents enabling in vitro culturing and storage of these microbes. In this study, we present a simple protocol for optimizing cryopreservation of non-model organisms in laboratory settings using conventional chemicals. Our initial motivation for this observation was to discover a cryoprotection agent for independently cultured Mycetohabitans spp., a fungal endosymbiont. We tested several common bacterial cryoprotection agents like glycerol, bovine serum albumin (BSA), and dimethyl sulfoxide (DMSO) over an ultralow freeze-thaw cycle to determine an adequate method of cryoprotection for assorted bacteria. We observed different recovery rates across bacterial species and cryopreservation methods, and identified cryoprotectants that reliably resulted in viable bacteria for each of the strains tested. We present this as a resource for those working with other fastidious and host-associated bacteria that may be missing effective cryopreservation methods.

microbiology↗

bioRxiv2025

Duplications in the Chlorophyll a oxygenase (CAO) gene across the Viridiplantae

Viridiplantae, a diverse group of green plants and alga that have evolved from a common ancestor, are unified in their ability to produce and use two types of chlorophyll (chlorophyll a and chlorophyll b) to capture light energy. In addition to playing a role in light harvesting, chlorophyll b is required at the appropriate level for the accumulation, assembly, and stability of light harvesting complexes within the photosynthetic apparatus. Chlorophyll b is synthesized from chlorophyll a by the enzyme chlorophyllide a oxygenase (CAO), a Rieske-type mononuclear non-heme iron oxygenase. A regulatory degron sequence, described in detail only in land plants, regulates the stability of CAO proteins based on the availability of chlorophyll b. Recent identification of CAO gene duplication in bryophyte and green algal species, combined with expanded availability of sequenced genomes within the Viridiplantae, prompted further investigation into the role of gene duplication in the evolution of chlorophyll b biosynthesis. Examination of genomes from 246 plant and algae species revealed independently occurring CAO duplications throughout the Viridiplantae, with a higher prevalence of duplication in land plants compared to their algal relatives. Additionally, we demonstrate that the degron sequence is poorly conserved in chlorophytes, but first appears as a conserved sequence in charophytes, and is very highly conserved among the embryophytes. The evolutionary history and functional role of CAO throughout the Viridiplantae lineage is discussed based on these key observations, adding to our understanding of chlorophyll b biosynthesis and the role of CAO in photosynthetic species.

plant biology↗

bioRxiv2024

Aerobic exercise promotes PDAC vascular normalization through S1PR1 signaling in tumor endothelial cells

Pancreatic Ductal Adenocarcinoma (PDAC) is characterized by high resistance to anti-cancer therapies. This resistance is caused in part by hypo-vascularization and dysfunctional vessels which inefficiently deliver chemotherapy. Here, we define the mechanism of aerobic exercise-induced tumor vascular remodeling and improved chemotherapy delivery and efficacy. We found that aerobic exercise was able to improve tumor vascular function and increase the number of lymphatic vessels, and these effects were associated with increased gemcitabine delivery to and efficacy against PDAC in mice. Further, exercise increased sphingosine-1-phosphate (S1P) in plasma and the activation of sphingosine-1-phosphate receptor 1 (S1PR1) in tumor endothelial cells. S1PR1 endothelial cell-specific deletion blunted the exercise-induced improvements in tumor vascular function, gemcitabine efficacy and drug concentration. Preclinical findings were validated in a patient cohort in which we found that exercise during neoadjuvant chemotherapy remodeled PDAC vasculature and improved tumor vascular function. These findings provide direct evidence that exercise increases chemotherapy delivery and efficacy by improving vascular function, defining S1PR1 as a necessary mediator of exercise-induced vascular remodeling.

cancer biology↗

bioRxiv2022

Monozygotic twins discordant for schizophrenia differ in maturation and synaptic transmission

Schizophrenia affects approximately 1% of the world population. Genetics, epigenetics, and environmental factors are known to play a role in this psychiatric disorder. While there is a high concordance in monozygotic twins, about half of twin pairs are discordant for schizophrenia. We characterized human-induced pluripotent stem cell (iPSC)-derived hippocampal neurons from two pairs of monozygotic twins that are discordant for a schizophrenia diagnosis. We compared the affected and the non-affected siblings and compared all of them to twin sets where none of the siblings suffered from schizophrenia. We found that the neurons derived from the schizophrenia patients were less arborized, were hypoexcitable with immature spike features, and exhibited a significant reduction in synaptic activity with dysregulation in synapse-related genes. Interestingly, the neurons derived from the co-twin siblings who did not have schizophrenia formed another distinct group that was different from the neurons in the group of the affected twin siblings but also different from the neurons in the group of the control twins. The neurons in the unaffected co-twin group were also less arborized than the neurons from controls but more arborized than those from affected siblings. Some of their spike features were immature (but less immature than neurons derived from the affected siblings). Importantly, their synaptic activity was not affected. Since schizophrenia is a genetically complex disorder, our twin study allows the measurement of neuronal phenotypes with a similar genetic background. The differences between the siblings may arise due to changes that occurred after the split of the egg into twins. Therefore, our study confirms that dysregulation of synaptic pathways, as well as changes in the rate of synaptic events, distinguishes between individuals affected with schizophrenia and unaffected individuals, even in those having a very similar genetic background.

neuroscience↗

bioRxiv2021

Microbiome differential abundance methods produce disturbingly different results across 38 datasets

Identifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods have been applied for this purpose, which are largely used interchangeably in the literature. Although it has been observed that these tools can produce different results, there have been very few large-scale comparisons to describe the scale and significance of these differences. In addition, it is challenging for microbiome researchers to know which differential abundance tools are appropriate for their study and how these tools compare to one another. Here, we have investigated these questions by analyzing 38 16S rRNA gene datasets with two sample groups for differential abundance testing. We tested for differences in amplicon sequence variants and operational taxonomic units (referred to as ASVs for simplicity) between these groups with 14 commonly used differential abundance tools. Our findings confirmed that these tools identified drastically different numbers and sets of significant ASVs, however, for many tools the number of features identified correlated with aspects of the tested study data, such as sample size, sequencing depth, and effect size of community differences. We also found that the ASVs identified by each method were dependent on whether the abundance tables were prevalence-filtered before testing. ALDEx2 and ANCOM produced the most consistent results across studies and agreed best with the intersect of results from different approaches. In contrast, several methods, such as LEfSe, limma voom, and edgeR, produced inconsistent results and in some cases were unable to control the false discovery rate. In addition to these observations, we were unable to find supporting evidence for a recent recommendation that limma voom, corncob, and DESeq2 are more reliable overall compared with other methods. Although ALDEx2 and ANCOM are two promising conservative methods, we argue that those researchers requiring more sensitive methods should use a consensus approach based on multiple differential abundance methods to help ensure robust biological interpretations.

bioinformatics↗

bioRxiv2021

Deep Generative Analysis for Task-Based Functional MRI Experiments

While functional magnetic resonance imaging (fMRI) remains one of the most widespread and important methods in basic and clinical neuroscience, the data it produces--time series of brain volumes--continue to pose daunting analysis challenges. The current standard ("mass univariate") approach involves constructing a matrix of task regressors, fitting a separate general linear model at each volume pixel ("voxel"), computing test statistics for each model, and correcting for false positives post hoc using bootstrap or other resampling methods. Despite its simplicity, this approach has enjoyed great success over the last two decades due to: 1) its ability to produce effect maps highlighting brain regions whose activity significantly correlates with a given variable of interest; and 2) its modeling of experimental effects as separable and thus easily interpretable. However, this approach suffers from several well-known drawbacks, namely: inaccurate assumptions of linearity and noise Gaussianity; a limited ability to capture individual effects and variability; and difficulties in performing proper statistical testing secondary to independently fitting voxels. In this work, we adopt a different approach, modeling entire volumes directly in a manner that increases model flexibility while preserving interpretability. Specifically, we use a generalized additive model (GAM) in which the effects of each regressor remain separable, the product of a spatial map produced by a variational autoencoder and a (potentially nonlinear) gain modeled by a covariate-specific Gaussian Process. The result is a model that yields group-level effect maps comparable or superior to the ones obtained with standard fMRI analysis software while also producing single-subject effect maps capturing individual differences. This suggests that generative models with a decomposable structure might offer a more flexible alternative for the analysis of task-based fMRI data.

neuroscience↗

bioRxiv2020

Signalling Network of Breast Cancer Cells in Response to Progesterone

Breast cancer cells enter into the cell cycle following progestin exposure by the activation of signalling cascades involving a plethora of enzymes, transcription factors and co-factors that transmit the external signal from the cell membrane to chromatin, ultimately leading to a change of the gene expression program. Although many of the events within the signalling network have been described in isolation, how they globally team up to generate the final cell response is unclear. In this study we use antibody microarrays and phosphoproteomics to provide a dynamic global signalling map that reveals new key regulated proteins and links between previously known and novel pathways. Detailed analysis of the data revealed intriguing changes in protein complexes involved in nuclear structure, EMT, cell adhesion, as well as transcription factors previously not associated with breast cancer proliferation. As different post-translational modifications can mediate complex crosstalk mechanisms and massive PARylation is also rapidly induced by progestins, we provide details of important chromatin regulatory complexes containing both phosphorylated and PARylated proteins. This study contributes an important resource for the scientific community, as it identifies novel players and connections meaningful for breast cancer cell biology and potentially relevant for cancer management. (197 w)

molecular biology↗

bioRxiv2020

Environmental DNA metabarcoding provides enhanced detection of the European eel Anguilla anguilla and fish community structure in pumped river catchments

The European eel Anguilla anguilla (eel hereafter) is critically endangered and has a catadromous lifecycle, which means adult eels that live in pumped catchments must pass through pumps during their downstream spawning migration. We are currently lacking detailed site-by-site eel distribution information in order to estimate the overall impact of individual pumping stations on eel escapement, and as such lack the data to enable informed prioritisation of pumping station management and targeted mitigation. In this study, we investigated whether environmental DNA (eDNA) metabarcoding can provide increased detection sensitivity for eel and fish community structure in highly regulated pumped catchments, when compared directly to current standard practice fish survey protocols (seine netting/electric fishing). Eels were detected in 14/17 sites (82.4%) using eDNA metabarcoding in contrast to 3/17 (17.6%) using traditional catch methods. Additionally, when using eDNA monitoring species richness was higher in 16/17 sites (94.1%) and site occupancy [≥] traditional methods for 23/26 of the fish species detected (88.5%). While eDNA methods presented significantly higher average species richness and species site occupancy overall, eDNA and Catch methods were positively correlated in terms of species richness and site occupancy. We therefore found that eDNA metabarcoding was a high sensitivity method for detecting eels in pumped catchments, while also increasing the detection of overall fish community structure compared to traditional catch methods. In addition, we highlight how eDNA monitoring is especially suited to increased detection of particular species, with traditional methods sufficient for others. This high sensitivity, coupled with the ability to sample multiple sites in a short time frame suggests eDNA metabarcoding could be an invaluable tool when prioritising pumping station management.

ecology↗

bioRxiv2018

Excitatory GABAergic signalling is associated with acquired benzodiazepine resistance in status epilepticus

Status epilepticus (SE) is defined as a state of unrelenting seizure activity. It is associated with a rapidly rising mortality rate, and thus constitutes a medical emergency. Benzodiazepines, which act as positive modulators of chloride (Cl-) permeable GABAA receptors, are indicated as the first line of treatment, but this is ineffective in many cases. We found that 48% of children presenting with SE were unresponsive to benzodiazepine treatment, and critically, that the duration of SE at the time of treatment is an important predictor of non-responsiveness. We therefore investigated the cellular mechanisms that underlie acquired benzodiazepine resistance, using rodent organotypic brain slices. Removing Mg2+ ions leads to an evolving pattern of epileptiform activity, and eventually to a persistent state of repetitive discharges that strongly resembles clinical EEG recordings of SE. We show that the persistent SE-like activity is associated with a reduction in GABAA receptor conductance and Cl- extrusion capability. We explored the effect on intraneuronal Cl- using both gramicidin, perforated-patch clamp recordings and Cl- imaging. This showed that during SE-like activity, reduced Cl- extrusion capacity was further exacerbated by activity-dependent Cl- loading, resulting in a persistently high intraneuronal Cl-. Consistent with these results, we found that optogenetic stimulation of GABAergic interneurons in the SE-like state, actually enhanced epileptiform activity in a GABAAR dependent manner. Together our findings describe a novel potential mechanism underlying benzodiazepine-resistant SE, with relevance to how this life-threatening condition should be managed in the clinic.

neuroscience↗

bioRxiv2018

Resilience to oxidative and nitrosative stress is mediated by the stressosome, RsbP and SigB in Bacillus subtilis.

A bacteriums ability to thrive in the presence of multiple environmental stressors simultaneously determines its resilience. We showed that activation of the SigB-controlled general stress response by mild environmental or nutritional stress provided significant cross-protection to subsequent lethal oxidative, disulfide and nitrosative stress exposure. SigB activation is mediated via the stressosome and RsbP, the main conduits of environmental and nutritional stress, respectively. Cells exposed to mild environmental stress while lacking the major stressosome components RsbT or RsbRA were highly sensitive to subsequent oxidative stress, whereas rsbRB, rsbRC, rsbRD and ytvA null mutants showed a spectrum of sensitivity, confirming their redundant roles and suggesting they could modulate the signal generated by environmental stress or oxidative stress. Furthermore, from mutant analysis we infer that RsbRA phosphorylation by RsbT was important for this cross-resistance to oxidative stress. By contrast, cells encountering stationary phase stress required RsbP but not RsbT to survive subsequent oxidative stress caused by hydrogen peroxide and diamide. Interestingly, optimum cross-protection against nitrosative stress caused by SNP required SigB but not the known regulators, RsbT and RsbP, suggesting an additional and as yet uncharacterized route of SigB activation independent of the known environmental and energy-stress pathways. Together, these results provide a mechanism for how Bacillus subtilis promotes enhanced resistance against lethal oxidative stress during likely physiologically relevant conditions such as mild environmental or nutrient stress.

microbiology↗

bioRxiv2017

Barriers to Integration of Bioinformatics into Undergraduate Life Sciences Education

Bioinformatics, a discipline that combines aspects of biology, statistics, and computer science, is increasingly important for biological research. However, bioinformatics instruction is rarely integrated into life sciences curricula at the undergraduate level. To understand why, the Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE, \"nibbles\") recently undertook an extensive survey of life sciences faculty in the United States. The survey responses to open-ended questions about barriers to integration were subjected to keyword analysis. The barrier most frequently reported by the ~1,260 respondents was lack of faculty training. Faculty at associates-granting institutions report the least training in bioinformatics and the least integration of bioinformatics into their teaching. Faculty from underrepresented minority groups (URMs) in STEM reported training barriers at a higher rate than others, although the number of URM respondents was small. Interestingly, the cohort of faculty with the most recently awarded PhD degrees reported the most training but were teaching bioinformatics at a lower rate than faculty who earned their degrees in previous decades. Other barriers reported included lack of student interest in bioinformatics; lack of student preparation in mathematics, statistics, and computer science; already overly full curricula; and limited access to resources, including hardware, software, and vetted teaching materials. The results of the survey, the largest to date on bioinformatics education, will guide efforts to further integrate bioinformatics instruction into undergraduate life sciences education.

scientific communication and education↗

bioRxiv2017

Multimodal Surface Matching with Higher-Order Smoothness Constraints

The accurate alignment of brains is fundamental to the statistical sensitivity and spatial localisation of group studies in brain imaging, and cortical surface-based alignment is generally accepted to be superior to volume-based approaches at aligning cortical areas. However, human subjects have considerable variation in cortical folding, and in the location of cortical areas relative to these folds, which makes aligning cortical areas based on folding alone a challenging problem. The Multimodal Surface Matching (MSM) tool is a flexible spherical registration approach that enables accurate registration of surfaces based on a variety of different features. Using MSM, we have previously shown that using areal features such as resting state-networks and myelin maps to drive cross-subject surface alignment improves group task fMRI statistics and map sharpness. However, the initial implementation of MSMs regularisation function did not penalize all forms of surface distortion evenly. In some cases, this allowed peak distortions to exceed neurobiologically plausible limits unless the regularisation strength was increased, in which case this prevented the algorithm from fully maximizing surface alignment. Here, we propose a new regularisation penalty, derived from physically relevant equations of strain (deformation) energy, and demonstrate that its use leads to improved and more robust alignment of multi-modal imaging data. In addition, since spherical warps incorporate projection distortions that are unavoidable when mapping from a convoluted cortical surface to the sphere, we also propose constraints to enforce smooth deformation of cortical anatomies. We test the impact of this approach for longitudinal modeling of cortical development for neonates (born between 32 and 45 weeks) and demonstrate that the proposed method increases the biological interpretability of the distortion fields and improves the statistical significance of population-based analysis relative to other spherical methods.

neuroscience↗

bioRxiv2017

Bioinformatics Core Competencies for Undergraduate Life Sciences Education

Bioinformatics is becoming increasingly central to research in the life sciences. However, despite its importance, bioinformatics skills and knowledge are not well integrated in undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing genomic research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of life sciences faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists, as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondents degree of training, time since degree earned, and/or the Carnegie classification of the respondents institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate life sciences students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula.\n\nSignificance StatementBioinformatics, an interdisciplinary field that uses techniques from computer science and mathematics to store, manage, and analyze biological data, is becoming increasingly central to modern biology research. Given the widespread use of bioinformatics and its impacts on societal problem-solving (e.g., in healthcare, agriculture, and natural resources management), there is a growing need for the integration of bioinformatics competencies into undergraduate life sciences education. Here, we present a set of bioinformatics core competencies for undergraduate life scientists developed using the results of a large national survey and the expertise of our working group of bioinformaticians and educators. We also present results from the survey on the importance of bioinformatics skills and the current state of integration of bioinformatics into biology education.

bioinformatics↗

bioRxiv2017

The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

neuroscience↗