Biology subjects

Pinto, J.

Publications and source records attributed to Pinto, J..

17 recordsLinked to original sources

bioRxiv2026

Strong habitat-associated differentiation of microbial communities across a fine-scale land-water interface

Microbial communities can remain strongly differentiated across environmental boundaries despite their potential for widespread dispersal. However, the extent to which habitat differences structure microbial communities at fine spatial scales remains poorly understood. Here, we investigated bacterial and fungal communities across a 350-m land-water interface in Lake Vanern, Sweden, including mainland soil, two small terrestrial islands and lake water. Using 16S and ITS amplicon sequencing, we compared microbial diversity and community composition across habitats and with increasing distance from the shoreline. Both bacterial and fungal communities showed pronounced habitat-associated differentiation, with the strongest contrasts between terrestrial and aquatic samples. Despite being surrounded by lake water, island communities were compositionally more similar to mainland soil communities, suggesting that geographic proximity alone does not necessarily lead to microbial community homogenization. Fungal, but not bacterial community composition varied significantly with shoreline position within both terrestrial and aquatic habitats, indicating contrasting spatial patterns between the two groups. Fungal genera also showed greater taxonomic overlap between terrestrial and aquatic habitats than bacterial genera, although overall community composition remained distinct. Taxonomically inferred functional profiles and ecological guilds further reflected habitat-associated differences. Together, our findings reveal strong microbial community differentiation across a fine-scale land-water interface and highlight how habitat identity and spatial context are associated with distinct patterns of bacterial and fungal community assembly.

microbiology↗

bioRxiv2026

Transcriptomic profiling reveals multiple mechanisms of insecticide resistance in Aedes aegypti from Angola

Control of arboviruses remains heavily reliant on insecticide-based vector control targeting adult Aedes aegypti, especially during outbreaks, but the effectiveness of these tools can be compromised by insecticide resistance. While the mechanisms underlying resistance have been widely studied in Latin American and South East Asian Ae. aegypti, knowledge from African populations is limited, particularly regarding metabolic resistance. To address this knowledge gap, we sequenced the transcriptomes of Ae. aegypti collected in Angola, from both unexposed individuals and survivors of exposure to the organophosphate fenitrothion, alongside two insecticide-susceptible laboratory reference strains. Many overexpressed genes belonged to the major detoxification enzyme families, including 96 cytochrome P450 monooxygenases (CYP450s), 18 glutathione S-transferases (GSTs), and 35 carboxylesterases, with multiple genes previously detected as upregulated in Latin American and Asian populations. These included frequently reported, functionally-validated, metabolic resistance genes such as CYP9J24, CYP9J26, and CYP6BB2. However, expression of auxiliary resistance families including hexamerins, heat shock proteins, and odorant binding proteins were linked to the insecticide resistance phenotype, whilst numerous cuticular genes differentiated the Angolan population from both susceptible laboratory strains. A novel candidate, CYP6AG7, that was overexpressed after fenitrothion exposure was experimentally validated, and surprisingly metabolised fenitrothion into its toxic oxon form, which it did not subsequently break down. The antioxidant response element (ARE) motif, to which the transcription factor Maf-S binds, was detected in all CYP450 overexpressed in the fenitrothion treatment suggesting their potential coordinated induction. Analysis of genetic differentiation revealed several resistance-linked genes under potential selection, and SNP screening identified both known and novel non-synonymous mutations in the voltage-gated sodium channel (VGSC) gene, the target for pyrethroid insecticides. This is the first RNAseq dataset for Ae. aegypti from Africa in the context of insecticide resistance, providing insight into the complexity of resistance mechanisms, including some shared, and others potentially novel, compared to better studied populations from other geographical regions. Author summaryDengue, chikungunya, yellow fever, and Zika are diseases that exert an increasing public health burden across Africa, primarily transmitted by the mosquito Aedes aegypti. We rely heavily on insecticides to control these mosquitoes, but populations are increasingly developing resistance, making control efforts less effective. While resistance mechanisms have been well-studied in the Americas and Asia, comparatively little is known about how African Ae. aegypti resist insecticides. We collected Ae. aegypti mosquitoes from Angola and compared the genes expressed in fenitrothion resistant versus susceptible mosquitoes using RNA sequencing. We identified overexpressed candidate insecticide resistance genes from the detoxification enzyme families that mosquitoes use to break down insecticides, including several genes previously linked to resistance in other regions. One novel enzyme identified, CYP6AG7, was experimentally validated and found to convert the pro-insecticide fenitrothion into its harmful form but interestingly not break down this harmful metabolite further. Mutations potentially linked to insecticide resistance were also detected in detoxification genes and insecticide target site genes. Our study provides the first comprehensive molecular characterization of insecticide resistance mechanisms in African Aedes aegypti, offering crucial data to inform vector control strategies and insecticide resistance management across the continent as dengue and related diseases continue to spread.

bioinformatics↗

bioRxiv2026

Anopheles azevedoi (Ribeiro, 1969) in Angola: New geographical records, molecular characterization, and insecticide susceptibility profile of a commonly misidentified species

BACKGROUNDAngola ranks among the five countries with the highest malaria burden globally. The Ministry of Health in Angola has consistently partnered with international donors to sustain entomological surveillance and vector control strategies in a context of high malaria burden. METHODSVector surveillance was carried out in Luanda, Benguela, Namibe and Cuanza Sul provinces from 2016-2022. Collected adult mosquitoes were tested to assess the presence of Plasmodium parasites and determine blood sources. Larvae collections provided live material to test insecticide susceptibility in local Anopheles populations. Taxonomic determination of mosquitoes was based on external morphology and confirmed with molecular assays. The presence of Anopheles azevedoi was confirmed through morphology and genetic sequences, and errors in the original species determination were detected, discussed and corrected. OBJECTIVESThe study aimed to update the geographical range of Anopheles azevedoi in Angola and monitor the species susceptibility to public health insecticides. FINDINGS and MAIN CONCLUSIONSWe report on populations of Anopheles azevedoi occurring along the western coast of Angola, a highly abundant species with anthropophilic behavior in urban areas. Anopheles azevedoi is widely resistant to pyrethroids and DDT but fully susceptible to chlorfenapyr. We contribute with COI and ITS-2 barcoding sequences for future species identification and explain the reasons for which this species has been for long misidentified in Angola.

zoology↗

bioRxiv2025

Fermentative yeast diversity at the northern range limit of their oak tree hosts

Fermentative yeasts play important roles in both ecological and industrial processes but their distribution and abundance in natural environments is not well understood. We investigated the diversity of yeast species associated with oak trees (Quercus spp.) in the northern range limit of oak in Sweden, and identified climatic and ecological conditions governing their distribution. We isolated yeasts from oak bark collected from 28 forests and identified them to the species level using metabarcoding. Most communities were dominated by species in the Saccharomycetaceae family, especially by species of Saccharomyces, Kluyveromyces, and Pichia. Each of these genera showed a distinct latitudinal and longitudinal distribution, and both temperature and precipitation metrics predicted significant variation in their abundance. Consistent with this, laboratory assays revealed significant effects of temperature on the growth of strains collected from different longitudes and latitudes. We further found that older trees harbour more diverse and more balanced microbial communities with more evenly distributed species abundances, and that communities across trees were more similar when sharing a common dominant genus. This work provides a baseline for future studies on the impact of climate change on the microbial biodiversity of temperate forests in northern latitudes, and contributes to a growing collection of fermentative yeasts isolated from the wild with potential for biotechnological applications.

microbiology↗

bioRxiv2024

The long-term evolutionary potential of four yeast species and their hybrids in extreme temperature conditions

Accelerating climate change and extreme temperatures urge us to better understand the potential of populations to tolerate and adapt to thermal challenges. Interspecific hybridization can facilitate adaptation to novel or extreme environments. However, predicting the long-term fitness effects of hybridization remains a major challenge in evolutionary and conservation biology. Experimental evolution with microbes provides a powerful tool for tracking adaption, across generations and in real time. We investigated the thermal adaptation dynamics of four species of budding yeast (Saccharomyces) and their interspecific F2 hybrids, for 140 generations under cold (5{degrees}C) and warm (31{degrees}C) conditions.We found significant variation in the evolutionary potential of species and hybrids, strongly determined by their natural temperature tolerance. The largest fitness improvements occurred in hybrids, with some populations nearly quadrupling in fitness in the cold environment, exceeding both parents in thermal adaptive potential. Reciprocal transplanting of evolved populations from the endpoint of evolution into opposite temperatures revealed that hybrids had greater resilience when challenged with sudden temperature shifts. Our results highlight that hybridization alters the fitness outcomes of long-term adaptation to extreme environments and may render populations more resilient to sudden environmental change, presenting both opportunities and challenges for conservation and sustainable agriculture.

evolutionary biology↗

bioRxiv2024

Dynamic spatiotemporal activation of a pervasive neurogenic competence in striatal astrocytes supports continuous neurogenesis following injury

Adult brain neural stem cells (NSCs) are conventionally regarded as rare cells restricted to two niches: the subventricular zone (SVZ) and the subgranular zone. Parenchymal astrocytes can also contribute to neurogenesis after injury, however the prevalence, distribution, and behaviour of these latent NSCs remained elusive. To tackle these issues, we reconstructed the spatiotemporal pattern of striatal astrocytes neurogenic activation after excitotoxic lesion in mice. Our results indicate that a neurogenic potential is broadly distributed throughout the striatum but is focally activated at the lesion border. In this region, similarly to canonical niches, steady state neurogenesis is ensured by the continuous stochastic activation of local astrocytes. Activated astrocytes quickly return to quiescence, while their progeny locally proliferate for about 10 days following a stochastic behaviour that features an acceleration in differentiation propensity. Notably, striatal astrocytes activation rate matches that of SVZ astrocytes indicating a comparable prevalence of NSC potential.

neuroscience↗

bioRxiv2024

Exploring adaptation routes to low temperatures in the Saccharomyces genus

The identification of traits that affect adaptation of microbial species to external abiotic factors, such as temperature, is key for our understanding of how biodiversity originates and can be maintained in a constantly changing environment. The Saccharomyces genus, which includes eight species with different thermotolerant profiles, represent an ideal experimental platform to study the impact of adaptive alleles in different genetic backgrounds. Previous studies identified a group of genes important for maintenance of growth at lower temperatures. Here, we carried out a genus-wide functional analysis in all eight Saccharomyces species for six candidate genes. We showed that the cold tolerance trait of S. kudriavzevii and S. eubayanus is likely to be evolved from different routes, involving genes important for the conservation of redox-balance, and for the long-chain fatty acid metabolism, respectively. For several loci, temperature- and species-dependent epistasis was detected, underlying the plasticity and complexity of the genetic interactions. The natural isolates of S. kudriavzevii, S. jurei and S. mikatae had a significantly higher expression of the genes involved in the redox balance compared to S. cerevisiae, raising the question of what proportion of the trait is accounted for solely due to transcriptional strength. To tease apart the role of gene expression from that of allelic variation, for two genes we independently replaced in four yeast species either the promoters or the alleles with those derived from S. kudriavzevii. Our data consistently showed a significant fitness improvement at cold temperatures in the strains carrying the S. kudriavzevii promoter, while growth was lower upon allele swapping. These results suggest that transcriptional strength plays a bigger role in growth maintenance at cold over the allele type and supports a model of adaptation centred on stochastic tuning of the expression network. Author summaryThe decline in biodiversity due to environmental changes influences the stability of ecosystems by altering the geographic distribution of several microbial and fungal species. Temperature is one of the leading factors that drive adaptation and different organisms share the same habitat because of their different thermal profiles. It is therefore important to study the genes that affect the fitness of microorganisms at different temperatures in order to understand both how biodiversity originated and how can be maintained. The Saccharomyces genus, which includes species with different thermotolerant profiles, represent an ideal experimental platform to investigate the impact of adaptive alleles in response to temperature changes. Here, we carried out a functional analysis for putative cold-tolerant genes and showed that this trait is likely to be evolved from different routes in different species, involving the conservation of redox-balance and alteration of membrane fluidity. Furthermore, for several species, genetic interactions display fitness tradeoffs in different environments. Finally, by unravelling the interplay between gene expression, allele variation, genetic background and environment, this study shed light on the intricate nature of transcriptional regulation and its pivotal role in facilitating cold adaptation in Saccharomyces species.

genetics↗

bioRxiv2024

Bayesian Modelling Approaches for Breath-Hold Induced Cerebrovascular Reactivity

Cerebrovascular reactivity (CVR) reflects the ability of blood vessels to dilate and constrict in response to a vasoactive stimulus and is an important indicator of cerebrovascular health. CVR can be mapped non-invasively with functional magnetic resonance imaging (fMRI) based on blood oxygen level-dependent (BOLD) contrast in combination with a breath-hold (BH) task. There are several ways to analyse this type of data and retrieve individual CVR amplitude and timing information. The most common approach involves employing a time-shifted general linear model with the measured end-tidal carbon dioxide signal as a regressor of interest. In this work, we introduce a novel method for CVR mapping based on a variational Bayesian approach. We analysed BOLD fMRI data from six participants that performed a BH task in ten different sessions each, and computed the corresponding CVR amplitude and delay maps for each session/subject. No statistically significant differences were observed between the modelling approaches in the CVR delay and amplitude maps in grey matter. Notably, the largest difference between methods was apparent in the case of low CVR amplitude, attributed to how each method addressed noisy voxels, particularly in white matter and cerebral spinal fluid. Both approaches showed highly reproducible CVR amplitude maps where between-subject variability was significantly larger than between-session variability. Furthermore, our results illustrated that the Bayesian approach is more computationally efficient, and future implementations could incorporate more complex noise models, non-linear fitting, and physiologically meaningful information into the model in the form of priors. This work demonstrates the utility of variational Bayesian modelling for CVR mapping and highlights its potential for characterising BOLD fMRI dynamics in the study of cerebrovascular health and its application to clinical settings.

neuroscience↗

bioRxiv2024

Large language models overcome the challenges of unstructured text data in ecology

The vast volume of currently available unstructured text data, such as research papers, news, and technical report data, shows great potential for ecological research. However, manual processing of such data is labour-intensive, posing a significant challenge. In this study, we aimed to assess the application of three state-of-the-art prompt-based large language models (LLMs), GPT 3.5, GPT 4, and LLaMA-2-70B, to automate the identification, interpretation, extraction, and structuring of relevant ecological information from unstructured textual sources. We focused on species distribution data from two sources: news outlets and research papers. We assessed the LLMs for four key tasks: classification of documents with species distribution data, identification of regions where species are recorded, generation of geographical coordinates for these regions, and supply of results in a structured format. GPT 4 consistently outperformed the other models, demonstrating a high capacity to interpret textual data and extract relevant information, with the percentage of correct outputs often exceeding 90% (average accuracy across tasks: 87-100%). Its performance also depended on the data source type and task, with better results achieved with news reports, in the identification of regions with species reports and presentation of structured output. Its predecessor, GPT 3.5, exhibited reasonably low accuracy across all tasks and data sources (average accuracy across tasks: 81-97%), whereas LLaMA-2-70B showed the worst performance (37- 73%). These results demonstrate the potential benefit of integrating prompt-based LLMs into ecological data assimilation workflows as essential tools to efficiently process large volumes of textual data.

ecology↗

bioRxiv2023

Unmasking Hidden Systemic Effects of Neurodegenerative Diseases: A Two-Pronged Approach to Biomarker Discovery

Identification of reliable blood biomarkers for neurodegenerative diseases (NDs) is crucial for translational and clinical research. However, conventional omics struggle with blood samples complexity, hindering desired outcomes. In this work the potential of High Molecular Weight (HMW) fractionation under non-denaturing conditions as a complementary approach to the conventional proteomics for identifying serum biomarkers in NDs was explored. A cohort of 58 serum samples of Alzheimers disease (AD), Parkinsons disease (PD) patients and control (CT) individuals was used to compare the two proteomics strategies: i) direct analysis of whole serum and ii) non-denaturing fractionation using 300 kDa cut-off filters (HMW serum). Although both approaches quantified a similar set of proteins, each approach captured a distinct subset of differentially altered proteins, suggesting that HMW fractionation identified additional types of alterations beyond conventional protein level changes. A discriminant model combining altered proteins from both datasets effectively distinguished between the three groups (AUC = 0.999 and median sensitivity and specificity of 97.4% and 91.7%, respectively). Importantly, this performance surpassed that of any model created using each method individually. Altogether, this work demonstrated that HMW fractionation can be a valuable complementary method to direct serum analysis and could enhance biomarker discovery. The 10 proteins included in the model (5 from each strategy), comprise clear evidence for the contribution of apolipoproteins for the diagnosis of NDs, revealing potential changes within lipid metabolism and the organization of macromolecules and their complexes, thereby uncovering effects that remain hidden from a conventional serum proteome analysis.

biochemistry↗

bioRxiv2023

Notes on the diet composition of Anoles lizards, Anolis (Dactyloidae), in the Yasuni National Park (Ecuador)

In this study, we observed and briefly described the diet of six species of lizards of the genus Anolis in the Yasuni National Park, located in the western part of the Amazon Rainforest. A total of 241 items found in the stomachs of the lizards were classified. We noted that Aranea and Hymenoptera were the most frequent diet categories used by the lizard community. In terms of volume, Hemiptera and insect larvae were the most representative prey. We aim that the description of the diet of Anolis provided by this study can be further combined with information pertaining to their natural history, thus shedding light on ecological mechanisms that influence adaptation.

ecology↗

bioRxiv2023

Dissecting the subcellular forces sculpting early C. elegans embryos

Embryo shape is determined by individual cell mechanics, intercellular interaction strength, and geometrical constraints. Models based on surface tensions at cell interfaces can predict 3D static cellular arrangements within aggregates. However, predicting the dynamics of such arrangements is challenging due to difficulties in measuring temporal changes in tensions. Here, we characterise the spatiotemporal changes in cellular tensions shaping the early nematode embryo using AFM, live microscopy, and tension inference. Using excoriated embryos, we validate a hybrid inference pipeline that calibrates relative inferred tensions temporally using cortical myosin enrichment and absolute tensions using AFM measurements. Applied to embryos within their native shell, we infer a spatiotemporal map of absolute tensions, revealing that ABa, ABp, and EMS compaction is driven by increased tension at free surfaces, while P2s initial exclusion is due to high tension at intercellular contacts. We uncover a direct and non-affine contribution of cadherins to cell-cell contact tension, comparable to cadherins indirect contribution via actomyosin regulation. HighlightsO_LIP lineage cells have lower cortical tensions than AB lineage cells C_LIO_LIEnrichment of Myosin-II at the cell cortex is a good predictor of cell-medium tension but is not sufficient to determine tension at cell-cell contacts. C_LIO_LIMyosin-informed tension inference allows determination of the spatiotemporal evolution of all surface tensions within the embryo. C_LIO_LIABa, ABp, and EMS compact due to high tensions at their cell-medium interfaces compared to their cell-cell interfaces, while P2 is initially excluded due to high cell-cell contact tensions. C_LIO_LICadherins contribute directly in a non-linear way by reducing cell-cell contact tension by nearly 50%. C_LI Open AccessFor the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.

biophysics↗

bioRxiv2022

Screening of natural Wolbachia infection in mosquitoes (Diptera: Culicidae) from Cape Verde Islands

BackgroundWolbachia pipientis is an endosymbiont bacteria that induce cytoplasmic incompatibility and inhibit arboviral replication in mosquitoes. This study aimed at estimating the prevalence and genetic diversity of Wolbachia in different mosquito (Diptera: Culicidae) species from Cape Verde. MethodsMosquitoes were collected in six islands of Cape Verde using dippers/pipettes, BG-sentinel(R) traps, CDC light traps, and dorsal aspirators. Samples were identified to species using morphological keys and PCR-based molecular assays. Wolbachia was detected by amplifying a fragment of the surface protein gene (wsp). Multilocus sequence typing (MLST) was performed with five housekeeping genes (coxA, gatB, ftsZ, hcpA and fbpA) and the wsp hypervariable region (HVR) for strain identification. Identification of wPip groups (wPip-I to wPip-V) was performed using PCR-RFLP assay on the ankyrin-domain gene pk1. ResultsNine mosquito species were collected, including the major vectors Aedes aegypti, Anopheles arabiensis, Culex pipiens s.s. and Culex quinquefasciatus. Wolbachia was detected in Cx. pipiens s.s. (100% prevalence), Cx. quinquefasciatus (98.3%), Cx. pipiens/quinquefasciatus hybrids (100%) and Culex tigripes (100%). Results from MLST and wsp hypervariable region typing showed that Wolbachia from Cx. pipiens s.l. belong to Sequence Type 9, wPip clade and supergroup B Wolbachia. Phylogenetic analyses indicate that Wolbachia isolated from Cx. tigripes belongs to Supergroup B but integrates a distinct clade from wPip with no attributed MLST profile. PCR-RFLP revealed wPip-II, wPip-III and wPip-IV groups in Culex pipiens s.l. wPip-IV was the dominant group, while wPip-II and wPip-III were restricted to Maio and Fogo islands, respectively. ConclusionOur study showed a high prevalence and diversity of Wolbachia in Cx pipiens s.l. from Cape Verde islands and, to the best of our knowledge, is the first to detect Wolbachia in Cx. tigripes, being represented in this species by a previously undescribed MLST Sequence Type.

molecular biology↗

bioRxiv2022

A general deep hybrid model for bioreactor systems: combining first Principles equations with deep neural networks

Numerous studies have reported the use of hybrid semiparametric systems that combine shallow neural networks with mechanistic models for bioprocess modeling. Here we revisit the general bioreactor hybrid modeling problem and introduce some of the most recent deep learning techniques. The single layer networks were extended to multi-layer networks with varying depths and combined with First Principles equations in the form of deep hybrid models. Deep learning techniques, namely the adaptive moment estimation method (ADAM), stochastic regularization and depth-dependent weights initialization were evaluated. Modified sensitivity equations are proposed for the computation of gradients in order to reduce CPU time for the training of deep hybrid models. The methods are illustrated with applications to a synthetic dataset and a pilot 50 L MUT+ Pichia pastoris process expressing a single chain antibody fragment. All in all, the results point to a systematic generalization improvement of deep hybrid models over its shallow counterpart. Moreover, the CPU cost to train the deep hybrid models is shown to be lower than for the shallow counterpart. In the pilot 50L MUT+ Pichia pastoris data set, the prediction accuracy was increased by 18.4% and the CPU decreased by 43.4%. HighlightsO_LIShallow hybrid models have been widely used for bioprocess modeling and optimization C_LIO_LINon-deep training using e.g. the Levenberg - Marquardt method, cross-validation and indirect sensitivity equations have been the methods of choice C_LIO_LIDeep learning with ADAM, stochastic regularization and indirect sensitivity significantly reduces the training CPU C_LIO_LIThe generalization capacity of deep hybrid models systematically outperforms that of shallow hybrid models C_LI

systems biology↗

bioRxiv2021

Myofibril orientation as a metric for characterizing heart disease

Myocyte disarray is a hallmark of many cardiac disorders. However, the relationship between alterations in the orientation of individual myofibrils and myofilaments to disease progression has been largely underexplored. This oversight has predominantly been due to a paucity of methods for objective and quantitative analysis. Here we introduce a novel, less-biased approach to quantify myofibrillar and myofilament orientation in cardiac muscle under near physiological conditions and demonstrate its superiority as compared to conventional histological assessments. Using small-angle X-ray diffraction, we first investigated changes in myofibrillar orientation at increasing sarcomere lengths in permeabilized, relaxed, wildtype mouse myocardium by assessing the angular spread of the 1,0 equatorial reflection (angle {sigma}). At a sarcomere length (SL) of 1.9 m, the angle {sigma} was 0.23{+/-}0.01 rad, decreased to 0.19{+/-}0.01 rad at a SL of 2.1 m, and further decreased to 0.15{+/-}0.01 rad at a SL of 2.3 m (p<0.0001). Angle {sigma} was significantly larger in R403Q, a MYH7 hypertrophic cardiomyopathy (HCM) model, porcine myocardium (0.24{+/-}0.01 rad) compared to WT myocardium (0.14{+/-}0.005 rad, p<0.0001) as well as in human heart failure tissue (0.19{+/-}0.006 rad) when compared to non-failing samples (0.17{+/-}0.007 rad, p=0.01). These data indicate that diseased myocardium suffers from greater myofibrillar disorientation compared to healthy controls. Finally, we showed that conventional, histology-based analysis of disarray can be subject to user bias and/or sampling error and lead to false positives. Our method for directly assessing myofibrillar orientation avoids the artifacts introduced by conventional histological approaches that assess myocyte orientation and only indirectly evaluate myofibrillar orientation, and provides a precise and objective metric for phenotypically characterizing myocardium. The ability to obtain excellent X-ray diffraction patterns from frozen human myocardium provides a new tool for investigating structural anomalies associated with cardiac diseases. Statement of SignificanceWe introduce a precise and quantitative approach to directly measure myofibrillar and myofilament orientation in cardiac muscle under near physiological conditions as a novel tool for phenotypically characterizing striated muscle systems. We use this technique to demonstrate that myocardium from disease model organisms and failing human myocardium suffers from greater myofibrillar disorientation compared to healthy controls. We also demonstrate that excellent diffraction patterns can be obtained from frozen and thawed human myocardium. Given the ready availability of frozen human heart tissue in tissue banks, this capability opens up a large space of potential experiments relating sarcomere structure to dysfunction in cardiac disorders.

biophysics↗

bioRxiv2021

PyPlr: A versatile, integrated system of hardware and software for researching the human pupillary light reflex

We introduce PyPlr--a versatile, integrated system of hardware and software to support a broad spectrum of research applications concerning the human pupillary light reflex (PLR). PyPlr is a custom Python library for integrating a research-grade video-based eye-tracker system with a light source and streamlining stimulus design, optimisation and delivery, device synchronisation, and extraction, cleaning, and analysis of pupil data. We additionally describe how full-field, homogenous stimulation of the retina can be realised with a low-cost integrating sphere that serves as an alternative to a more complex Maxwellian view setup. Users can integrate their own light source, but we provide full native software support for a high-end, commercial research-grade 10-primary light engine that offers advanced control over the temporal and spectral properties of light stimuli as well as spectral calibration utilities. Here, we describe the hardware and software in detail and demonstrate its capabilities with two example applications: 1) pupillometer-style measurement and parametrisation of the PLR to flashes of white light, and 2) comparing the post-illumination pupil response (PIPR) to flashes of long and short-wavelength light. The system holds promise for researchers who would favour a flexible approach to studying the PLR and the ability to employ a wide range of temporally and spectrally varying stimuli, including simple narrowband stimuli.

physiology↗

bioRxiv2020

Speeding up the detection of invasive aquatic species using environmental DNA and nanopore sequencing

Traditional detection of aquatic invasive species, via morphological identification is often time-consuming and can require a high level of taxonomic expertise, leading to delayed mitigation responses. Environmental DNA (eDNA) detection approaches of multiple species using Illumina-based sequencing technology have been used to overcome these hindrances, but sample processing is often lengthy. More recently, portable nanopore sequencing technology has become available, which has the potential to make molecular detection of invasive species more widely accessible and to substantially decrease sample turnaround times. However, nanopore-sequenced reads have a much higher error rate than those produced by Illumina platforms, which has so far hindered the adoption of this technology. We provide a detailed laboratory protocol and bioinformatic tools to increase the reliability of nanopore sequencing to detect invasive species, and we test its application using invasive bivalves. We sampled water from sites with pre-existing bivalve occurrence and abundance data, and contrasting bivalve communities, in Italy and Portugal. We extracted, amplified and sequenced eDNA with a turnaround of 3.5 days. The majority of processed reads were [≥] 99 % identical to reference sequences. There were no taxa detected other than those known to occur. The lack of detections of some species at some sites could be explained by their known low abundances. This is the first reported use of MinION to detect aquatic invasive species from eDNA samples. The approach can be easily adapted for other metabarcoding applications, such as biodiversity assessment, ecosystem health assessment and diet studies.

ecology↗