title: A yeast with muscle does not run faster: full humanization of the glycolytic pathway in Saccharomyces cerevisiae

abstract:
While transplantation of single genes in yeast plays a key role in elucidating gene functionality in metazoans, technical challenges hamper the humanization of full pathways and processes. Empowered by advances in synthetic biology, this study demonstrates the feasibility and implementation of full humanization of glycolysis in yeast. Single gene and full pathway transplantation revealed the remarkable conservation of both glycolytic and moonlighting functions and, combined with evolutionary strategies, brought to light novel, context-dependent responses. Remarkably, human hexokinase 1 and 2, but not 4, required mutations in their catalytic or allosteric sites for functionality in yeast, while hexokinase 3 was unable to complement its yeast ortholog. Comparison with human tissues cultures showed the preservation of turnover numbers of human glycolytic enzymes in yeast and human cell cultures. This demonstration of transplantation of an entire, essential pathway paves the way to the establishment of species, tissue and disease-specific metazoan models.

One Sentence SummaryThis work demonstrates the successful humanization of an entire pathway in Saccharomyces cerevisiae and establishes an attractive strategy to study (human) glycolysis architecture and regulation.

HighlightsO_LIThe successful humanization of the entire glycolytic pathway in yeast offers new microbial models for both fundamental and applied studies.
C_LIO_LIBoth glycolytic and moonlighting functions and turnover numbers of glycolytic enzymes are highly conserved between yeast and human.
C_LIO_LIFunctionality of human hexokinases 1 and 2 in yeast requires mutations in the catalytic or allosteric binding sites.
C_LIO_LICombination of single gene and full transplantation with laboratory evolution reveals context-dependent activity and evolution of glycolytic enzymes.
C_LI

category: systems biology


title: An open-source method for analysis of confocal calcium imaging with sparse cells

abstract:
BackgroundThe research in the neuroscience field has evolved to use complex imaging and computational tools to extract comprehensive information from data sets. Calcium imaging is a widely used technique that requires sophisticated software to get precise and reproducible results. Many laboratories struggle to adopt computational methods due to the lack of computational knowledge and paywalls for software.

New MethodHere we propose a calcium imaging analysis method using TrackMate, an open-source Fiji plugin, to track neurons at single-cell resolution, detect regions of interest (ROIs), and extract fluorescence intensities. For confocal images, this method uses the maximal value to represent the cell intensity for each z stack. This method can be done without coding or be combined with Python or Jupyter Notebook scripts to accelerate the analysis.

ResultsThis method is validated in fly larval cool neurons, whose calcium changes in these neurons respond to temperature fluctuation. It also identifies potential problems in approaches that extract signals from maximal projection images.

Comparison with existing methodsThis method does not depend on programming knowledge and/or commercial software but uses open-source software and requires no coding abilities. Since TrackMate automatically defines ROIs, this method greatly avoids human error and increases reproducibility. In addition, practice images and a step-by-step guide are provided to help users adopt this method in their experiments.

ConclusionsTherefore, this open-source method allows for the analysis of calcium imaging data at single-cell resolution with high reproducibility and has the potential to be applied in various cell types and animal models by researchers with different programming abilities.

HighlightsO_LITrackMate is applied to analyze calcium changes at single-cell resolution.
C_LIO_LIThis method depends on an open-source Fiji software, ensures reproducibility, and requires no coding ability.
C_LIO_LIPractice images and a step-by-step guide are provided to implement this method in various cell types and animal models.
C_LI

category: neuroscience


title: Real-time decoding of 5 finger movements from 2 EMG channels for mixed reality human-computer interaction

abstract: The search for optimized forms of human-computer interaction (HCI) has intensified alongside the growing potential for the combination of biosignals with virtual reality (VR) and augmented reality (AR) to enable the next generation of personal computing. At the core, this requires decoding the users biosignals into digital commands. Electromyography (EMG) is a biosensor of particular interest due to the ease of data collection, the relatively high signal-to-noise-ratio, its non-invasiveness, and the ability to interpret the signal as being generated by (intentional) muscle activity. Here, we investigate the potential of using data taken from a simple 2-channel EMG setup to differentiate 5 distinct movements. In particular, EMG was recorded from two bipolar sensors over small hand muscles (extensor digitorum, flexor digitorum profundus) while a subject performed 50 trials of dorsal extension and return for each of the five digits. The maximum and the mean values across the trial were determined for each channel and used as features. A k-nearest neighbors (kNN) classification was performed and overall 5-class classification accuracy reached 94% when using the full trials time window, while simulated real-time classification reached 90.4% accuracy when using the constructed kNN model (k=3) with a 280ms sliding window. Additionally, unsupervised learning was performed and a homogeneity of 85% was achieved. This study demonstrates that reliable decoding of different natural movements is possible with fewer than one channel per class, even without taking into account temporal features of the signal. The technical feasibility of this approach in a real-time setting was validated by sending real-time EMG data to a custom Unity3D VR application through a Lab Streaming Layer to control a user interface. Further use-cases of gamification and rehabilitation were also examined alongside the integration of eye-tracking and gesture recognition for a sensor fusion approach to HCI and user intent.


title: Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging

abstract:
Two-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion related intensity changes or motion artifacts cannot easily be separated from neural activity induced signals. While lateral motion within the focal plane can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected.

Here, we develop an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using at least two simultaneously recorded focal planes, the algorithm separates motion related and neural activity induced changes in fluorescence intensity. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.


title: Computational Fingerprints: Modeling Interactions Between Brain Regions as Points in a Function Space

abstract: In this paper we propose a novel technique to investigate the nonlinear interactions between brain regions that captures both the strength and the type of the functional relationship. Inspired by the field of functional analysis, we propose that the relationship between activity in two different brain areas can be viewed as a point in function space, identified by coordinates along an infinite set of basis functions. Using Hermite Polynomials as basis functions, we estimate from fMRI data a truncated set of coordinates that serve as a "computational fingerprint," characterizing the interaction between two brain areas. We provide a proof of the convergence of the estimates in the limit, and we validate the method with simulations in which the ground truth is known, additionally showing that computational fingerprints detect statistical dependence also when correlations ("functional connectivity") is near zero. We then use computational fingerprints to examine the neural interactions with a seed region of choice: the Fusiform Face Area (FFA). Using k-means clustering across each voxels computational fingerprint, we illustrate that the addition of the nonlinear basis functions allows for the discrimination of inter-regional interactions that are otherwise grouped together when only linear dependence is used. Finally, we show that regions in V5 and medial occipital and temporal lobes exhibit significant nonlinear interactions with the FFA.


title: Performance-optimized neural networks as an explanatory framework for decision confidence

abstract: Previous work has sought to understand decision confidence as a prediction of the probability that a decision will be correct, leading to debate over whether these predictions are optimal, and whether they rely on the same decision variable as decisions themselves. This work has generally relied on idealized, low-dimensional modeling frameworks, such as signal detection theory or Bayesian inference, leaving open the question of how decision confidence operates in the domain of high-dimensional, naturalistic stimuli. To address this, we developed a deep neural network model optimized to assess decision confidence directly given high-dimensional inputs such as images. The model naturally accounts for a number of puzzling dissociations between decisions and confidence, suggests a novel explanation of these dissociations in terms of optimization for the statistics of sensory inputs, and makes the surprising prediction that, despite these dissociations, decisions and confidence depend on a common decision variable.


title: Nanometer-Scale Imaging of Compartment-Specific Localization and Dynamics of Voltage-Gated Sodium Channels

abstract: Membrane excitability and cell-to-cell communication in the brain are tightly regulated by diverse ion channels and receptor proteins localized to distinct membrane compartments. Currently, a major technical barrier in cellular neuroscience is lack of reliable methods to label these membrane proteins and image their sub-cellular localization and dynamics. To overcome this challenge, we devised optical imaging strategies that enable systematic characterization of subcellular composition, relative abundances and trafficking dynamics of membrane proteins at nanometer scales in cultured neurons as well as in the brain. Using these methods, we revealed exquisite developmental regulation of subcellular distributions of voltage-gated sodium channel (VGSC) Nav1.2 and Nav1.6, settling a decade long debate regarding the molecular identity of sodium channels in dendrites. In addition, we discovered a previously uncharacterized trafficking pathway that targets Nav1.2 to unmyelinated fragments in the distal axon. Myelination counteracts this pathway, facilitating the installment of Nav1.6 as the dominant VGSC in the axon. Together, these imaging approaches unveiled compartment-specific trafficking mechanisms underpinning differential membrane distributions of VGSCs and open avenues to decipher how membrane protein localization and dynamics contribute to neural computation in the brain.


title: Light-regulated SIK1 remodels the synaptic phosphoproteome to induce sleep

abstract: The sleep and circadian systems act in concert to regulate sleep-wake timing, yet the molecular mechanisms that underpin their interaction to induce sleep remain unknown. Synaptic protein phosphorylation, driven by the kinase SIK3, correlates with sleep pressure, however it is unclear whether these phosphoproteome changes are causally responsible for inducing sleep. Here we show that the light-dependent activity of SIK1 controls the phosphorylation of a subset of the brain phosphoproteome to induce sleep in a manner that is independent of sleep pressure. By uncoupling phosphorylation and sleep induction from sleep pressure, we establish that synaptic protein phosphorylation provides a causal mechanism for the induction of sleep under different environmental contexts. Furthermore, we propose a framework that details how the salt-inducible kinases regulate the synaptic phosphoproteome to integrate exogenous and endogenous stimuli, thereby providing the molecular basis upon which the sleep and circadian systems interact to control the sleep-wake cycle.


title: Enhanced Production of Mesencephalic Dopaminergic Neurons from Lineage-Restricted Human Undifferentiated Stem Cells

abstract: The differentiation of human pluripotent stem cells (hPSCs) into mesencephalic dopaminergic (mesDA) neurons requires a precise combination of extrinsic factors that recapitulates the in vivo environment and timing. Current methods are capable of generating authentic mesDA neurons after long-term culture in vitro; however, when mesDA progenitors are transplanted in vivo, the resulting mesDA neurons are only minor components of the graft. This low yield hampers the broad use of these cells in the clinic. In this study, we genetically modified pluripotent stem cells to generate a novel type of stem cells called lineage-restricted undifferentiated stem cells (LR-USCs), which robustly generate mesDA neurons. LR-USCs are prevented from differentiating into a broad range of nondopaminergic cell types by knocking out genes that are critical for the specification of cells of alternate lineages. Specifically, we target transcription factors involved in the production of spinal cord and posterior hindbrain cell types. When LR-USCs are differentiated under caudalizing condition, which normally give rise to hindbrain cell types, a large proportion adopt a midbrain identity and develop into authentic mesDA neurons. We show that the mesDA neurons are electrophysiologically active, and due to their higher purity, are capable of restoring motor behavior eight weeks after transplantation into 6-hydroxydopamine (6-OHDA)-lesioned rats. This novel strategy improves the reliability and scalability of mesDA neuron generation for clinical use.


title: Evaluating the reliability, validity, and utility of overlapping networks: Implications for cognitive control

abstract: Brain regions can be consistently clustered together into a small number of large-scale networks based on the correlation of their activity across time. However, the methods typically used to assign regions to these networks typically force non- or minimal overlap between the networks, losing information about how particular regions may connect to multiple networks. However, new methods are emerging that allow networks to overlap. Here, we examined the reliability and validity of one such assignment method, the mixed membership algorithm, and the utility of overlapping assignment for identifying potential gaps in existing network models of behavior. Analyses were conducted on resting state data from a large set of participants. First, we split the data into two halves and generated group-level overlapping networks for each subgroup. We then used a bootstrapped Dice similarity analysis to demonstrate that the binarized network topographies showed good agreement between subgroups. Next, we generated nonoverlapping networks in the combined data using a typical k-means clustering method. Using the same Dice Similarity analysis, we compared these nonoverlapping networks both with previously published nonoverlapping networks (Yeo et al, 2011) and with overlapping networks likewise generated for the combined data. The nonoverlapping networks generally recapitulated known networks in the literature, and the overlapping networks captured large portions of one to three nonoverlapping network topographies. Following this, we used a relative entropy analysis to assess the uniformity of each regions distribution of connections across the overlapping networks. While many regions were indeed assigned to one network, more were assigned to multiple networks. Furthermore, regions assigned to multiple networks did not necessarily show stronger connection to one network over the others. Finally, we assessed the network membership of regions of the fronto-parietal and cingulo-opercular networks of the Dual-Networks model of cognitive control. In combination, the regions were members of all of the overlapping networks, and the majority were assigned to multiple networks. Together, these results indicate that overlapping assignment produces consistent and biologically plausible network topographies, and that a complete network model of cognitive control, or indeed any network model of behavior needs to be updated to account for multiple-network membership and the complex interactions that occur between the relevant networks as a function of their overlapping nature.


title: Spectral graph theory of brain oscillations -- revisited and improved

abstract:
Mathematical modeling of the relationship between the functional activity and the structural wiring of the brain has largely been undertaken using non-linear and biophysically detailed mathematical models with regionally varying parameters. While this approach provides us a rich repertoire of multistable dynamics that can be displayed by the brain, it is computationally demanding. Moreover, although neuronal dynamics at the microscopic level are nonlinear and chaotic, it is unclear if such detailed nonlinear models are required to capture the emergent meso- (regional population ensemble) and macroscale (whole brain) behavior, which is largely deterministic and reproducible across individuals. Indeed, recent modeling effort based on spectral graph theory has shown that an analytical model without regionally varying parameters can capture the empirical magnetoencephalography frequency spectra and the spatial patterns of the alpha and beta frequency bands accurately.

In this work, we demonstrate an improved hierarchical, linearized, and analytic spectral graph theorybased model that can capture the frequency spectra obtained from magnetoencephalography recordings of resting healthy subjects. We reformulated the spectral graph theory model in line with classical neural mass models, therefore providing more biologically interpretable parameters, especially at the local scale. We demonstrated that this model performs better than the original model when comparing the spectral correlation of modeled frequency spectra and that obtained from the magnetoencephalography recordings. This model also performs equally well in predicting the spatial patterns of the empirical alpha and beta frequency bands.

HighlightsO_LIWe show an improved hierarchical, linearized, and analytic spectral graph theory-based model that can capture the frequency spectra obtained from magnetoencephalography recordings
C_LIO_LIThis model also accurately captures the spatial patterns of the empirical alpha and beta frequency bands, requiring only 5-10 graph eigenmodes to do so
C_LI


title: tiRNA-Val promotes angiogenesis via Sirt1-Hif-1α axis in mice with diabetic retinopathy

abstract: Diabetic retinopathy (DR) is a specific microvascular complication arising from diabetes, and its pathogenesis is notcompletely understood. tRNA-derived stress-induced RNAs (tiRNAs), a new type of small noncoding RNA generated by specific cleavage of tRNAs, has become a promising target forseveral diseases. However, the regulatory function of tiRNAs in DR and its detailed mechanism remain unknown. Here, we analyzed the tiRNA profiles of normal and DR retinal tissues. The expression level of tiRNA-Val was significantly upregulated in DR retinal tissues. Consistently, tiRNA-Val was upregulated in human retinal microvascular endothelial cells (HRMECs) under high glucose conditions. The overexpression of tiRNA-Val enhanced cell proliferation and inhibited cell apoptosis in HRMECs, but the knockdown of tiRNA-Val decreased cell proliferation and promoted cell apoptosis. Mechanistically, tiRNA-Val, derived from mature tRNA-Val with Ang cleavage, decreased Sirt1 expression level by interacting with sirt1 3UTR, leading to the accumulation of Hif-1, a key target for DR. In addition, subretinal injection of adeno-associated virus to knock down tiRNA-Val in DR mice ameliorated the symptoms of DR. Therefore, these data suggest that tiRNA-Val is a potential target in treating diabetic retinopathy.

category: molecular biology


title: Cell-ACDC: a user-friendly toolset embedding state-of-the-art neural networks for segmentation, tracking and cell cycle annotations of live-cell imaging data

abstract:
Live-cell imaging is a powerful tool to study dynamic cellular processes on the level of single cells with quantitative detail. Microfluidics enables parallel high-throughput imaging, creating a downstream bottleneck at the stage of data analysis. Recent progress on deep learning image analysis dramatically improved cell segmentation and tracking. Nevertheless, manual data validation and correction is typically still required and broadly used tools spanning the complete range of live-cell imaging analysis, from cell segmentation to pedigree analysis and signal quantification, are still needed. Here, we present Cell-ACDC, a user-friendly graphical user-interface (GUI)-based framework written in Python, for segmentation, tracking and cell cycle annotation. We included two state-of-the-art and high-accuracy deep learning models for single-cell segmentation of yeast and mammalian cells implemented in the most used deep learning frameworks TensorFlow and PyTorch. Additionally, we developed and implemented a cell tracking method and embedded it into an intuitive, semi-automated workflow for label-free cell cycle annotation of single cells. The open-source and modularized nature of Cell-ACDC will enable simple and fast integration of new deep learning-based and traditional methods for cell segmentation or downstream image analysis.

Source codehttps://github.com/SchmollerLab/Cell_ACDC

category: cell biology


title: Direct cryopreservation of poultry/avian embryonic reproductive cells: A low-tech, cost-effective and efficient method for safeguarding genetic diversity

abstract: Chickens are an important resource for smallholder farmers who raise locally adapted, genetically distinct breeds for eggs and meat. The development of efficient reproductive technologies to conserve and regenerate chicken breeds safeguards existing biodiversity and secures poultry genetic resources for climate resilience, biosecurity, and future food production. The majority of the over 1600 breeds of chicken are raised in low and lower to middle income countries (LMICs) under resource limited, small scale production systems, which necessitates a low tech, cost effective means of conserving diversity is needed. Here, we validate a simple biobanking technique using cryopreserved embryonic chicken gonads. The gonads are quickly isolated, visually sexed, pooled by sex, and cryopreserved. Subsequently, the stored material is thawed and dissociated before injection into sterile host chicken embryos. By using pooled GFP and RFP-labelled donor gonadal cells and Sire Dam Surrogate (SDS) mating, we demonstrate that chicks deriving entirely from male and female donor germ cells are hatched. This technology will enable ongoing efforts to conserve chicken genetic diversity for both commercial and small holder farmers, and to preserve existing genetic resources at poultry research facilities.

category: developmental biology


title: Birth and delineation of the intestinal stem cell niche

abstract: Wnt and Rspondin (RSPO) signaling triggers proliferation, and bone morphogenetic protein inhibitors (BMPi) impede differentiation, of intestinal stem cells (ISCs). Here we report that the functional ISC niche is a complex, multi-layered mesenchymal structure that includes distinct smooth muscle populations and describe how that niche organizes early in mouse life. Diverse sub-cryptal cells provide redundant supportive factors, with distinct BMPi and the most potent Wnt agonist, RSPO2, restricted to single cell types. Two functionally opposing elements arise in tandem during a critical period of crypt morphogenesis: a prominent shelf of BMP+ sub-epithelial myofibroblasts that promote epithelial differentiation and the muscularis mucosae, a specialized muscle layer generated de novo to supplement other RSPO and BMPi sources. In vivo ablation of smooth muscle, while preserving trophocytes, raises crypt BMP activity and potently limits crypt expansion. Thus, distinct and progressively refined mesenchymal components together create the milieu necessary to propagate crypts during rapid organ growth and to sustain ISCs in the adult niche.


title: 16S rRNA gene sequences of Candidatus Methylumidiphilus (Methylococcales), a putative methanotrophic genus in lakes and ponds

abstract: A putative novel methanotrophic genus, Candidatus Methylumidiphilus (Methylococcales), was recently shown to be ubiquitous and one of the most abundant methanotrophic genera in water columns of oxygen-stratified lakes and ponds of boreal and subarctic area. However, it has probably escaped detection in many previous studies using 16S rRNA gene amplicon sequencing due to insufficient database coverage, which is because Ca. Methylumidiphilus lacks cultured representatives and previously analysed metagenome assembled genomes (MAGs) affiliated with it do not contain 16S rRNA genes. Therefore, we screened MAGs affiliated with the genus for their 16S rRNA gene sequences in a recently published lake and pond MAG dataset. Among 66 MAGs classified as Ca. Methylumidiphilus (with completeness over 40% and contamination less than 5%) originating from lakes in Finland, Sweden and Switzerland as well as from ponds in Canada, we could find 5 MAGs each containing one 1532 bp long sequence spanning the V1-V9 regions of the 16S rRNA gene. After removal of sequence redundancy, this resulted in two unique 16S rRNA gene sequences. These sequences represented two different putative species, i.e. Ca. Methylumidiphilus alinenensis (Genbank accession: OK236221) as well as another so far unnamed species of Ca. Methylumidiphilus (Genbank accession: OK236220). We suggest that including these two sequences in reference databases will enhance 16S rRNA gene - based detection of members of this genus from environmental samples.

category: ecology


title: The evolutionary maintenance of Levy flight foraging: a numerical simulation.

abstract:
Levy flight is a type of random walk that models the behaviour of many phenomena across a multiplicity of academic disciplines; within biology specifically, the behaviour of fish, birds, insects, mollusks, bacteria, plants, slime molds, t-cells, and human populations. The Levy flight foraging hypothesis states that because Levy flights can maximize an organisms search efficiency, natural selection should result in Levy-like behaviour. Empirical and theoretical research has provided ample evidence of Levy walks in both extinct and extant species, and its efficiency across models with a diversity of resource distributions. However, no model has addressed the maintenance of Levy flight foraging through evolutionary processes, and existing models lack ecological breadth. We use numerical simulations, including lineage-based models of evolution with a distribution of move lengths as a variable and heritable trait, to test the Levy flight foraging hypothesis. We include biological and ecological contexts such as population size, searching costs, lifespan, resource distribution, speed, and consider both energy accumulated at the end of a lifespan and averaged over a lifespan. We demonstrate that selection often results in Levy-like behaviour, although conditional; smaller populations, longer searches, and low searching costs increase the fitness of Levy-like behaviour relative to Brownian behaviour. Interestingly, our results also evidence a bet-hedging strategy; Levy-like behaviour reduces fitness variance, thus maximizing geometric mean fitness over multiple generations.

Author summaryIn heterotrophs, incuding animals, survival depends on the net energy gained through foraging. The expectation, then, is that natural selection results in adaptations for efficient foraging that optimize the balance of searching costs and rewards. Levy flight foraging has been proposed as an optimal foraging solution. The hypothesis states, if no information about resource locations are available, and the locations are re-visitable, then selection will result in adaptations for Levy flight foraging, a type of random walk. It has been argued that Levy-like foraging behaviour may simply reflect how resources are distributed, but empirical and theoretical research suggests that this behaviour is intrinsic or innate. However, this research does not address evolutionary mechanisms, and lacks ecological breadth. We extend the current theoretical framework by including evolutionary ecological contexts. We treat an organisms random walk as a heritable trait, and explore ecological contexts such as population size, lifespan, carrying capacity, searching costs, reproductive strategies, and different distributions of food. Our evolutionary simulations overwhelmingly resulted in selection for Levy-like foraging, regardless of the distribution of food, and evidences Levy flight foraging as a bet-hedging strategy. Thus, here we provide some of the first evidence for the evolutionary maintenance of Levy flight foraging.

category: evolutionary biology


title: Fine scale population structure and extensive gene flow within an Eastern Nearctic snake complex (Pituophis melanoleucus)

abstract: Understanding the processes and mechanisms that promote lineage divergence is a central goal in evolutionary biology. For instance, studies investigating the spatial distribution of genomic variation often highlight biogeographic barriers underpinning geographic isolation, as well as patterns of isolation by environment and isolation by distance that can also lead to lineage divergence. However, the patterns and processes that shape genomic variation and drive lineage divergence may be taxa-specific, even across closely related taxa co-occurring within the same biogeographic region. Here, we use molecular data in the form of ultra-conserved elements (UCEs) to infer the evolutionary relationships and population genomic structure of the Eastern Pinesnake complex (Pituophis melanoleucus) - a polytypic wide-ranging species that occupies much of the Eastern Nearctic. In addition to inferring evolutionary relationships, population genomic structure, and gene flow, we also test relationships between genomic diversity and putative barriers to dispersal, environmental variation, and geographic distance. We present results that reveal shallow population genomic structure and ongoing gene flow, despite an extensive geographic range that transcends geographic features found to reduce gene flow among many taxa, including other squamate reptiles within the Eastern Nearctic. Further, our results indicate that the observed genomic diversity is spatially distributed as a pattern of isolation by distance and suggest that the current subspecific taxonomy do not adhere to independent lineages, but rather, show a significant amount of admixture across the entire P. melanoleucus range.


title: The distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii inferred using frequency changes under experimental evolution

abstract: The distribution of fitness effects (DFE) for new mutations is fundamental for many aspects of population and quantitative genetics. In this study, we have inferred the DFE in the single-celled alga Chlamydomonas reinhardtii by estimating changes in the frequencies of 254 spontaneous mutations under experimental evolution and equating the frequency changes of linked mutations with their selection coefficients. We generated seven populations of recombinant haplotypes by crossing seven independently derived mutation accumulation lines carrying an average of 36 mutations in the homozygous state to a mutation-free strain of the same genotype. We then allowed the populations to evolve under natural selection in the laboratory by serial transfer in liquid culture. We observed substantial and repeatable changes in the frequencies of many groups of linked mutations, and, surprisingly, as many mutations were observed to increase as decrease in frequency. We developed a Bayesian Monte Carlo Markov Chain method to infer the DFE. This computes the likelihood of the observed distribution of changes of frequency, and obtains the posterior distribution of the selective effects of individual mutations, while assuming a two-sided gamma distribution of effects. We infer that the DFE is a highly leptokurtic distribution, and that approximately equal proportions of mutations have positive and negative effects on fitness. This result is consistent with what we have observed in previous work on a different C. reinhardtii strain, and suggests that a high fraction of new spontaneously arisen mutations are advantageous in a simple laboratory environment.


title: Investigating the genetic architecture of eye colour in a Canadian cohort

abstract:
The main factors that determine eye colour are the amount of melanin concentrated in iris melanocytes, as well as the shape and distribution of melanosomes. Eye colour is highly variable in populations with European ancestry, in which eye colour categories cover a continuum of low to high quantities of melanin accumulated in the iris. A few polymorphisms in the HERC2/OCA2 locus in chromosome 15 have the largest effect on eye colour in these populations, although there is evidence of other variants in the locus and across the genome also influencing eye colour. To improve our understanding of the genetic loci determining eye colour, we performed a meta-analysis of genome-wide association studies in a Canadian cohort of European ancestry (N= 5,641) and investigated putative causal variants. Our fine-mapping results indicate that there are several candidate causal signals in the HERC2/OCA2 region, whereas other significant loci in the genome likely harbour a single causal signal (TYR, TYRP1, IRF4, SLC24A4). Furthermore, a short subset of the associated eye colour regions was colocalized with the gene expression or methylation profiles of cultured melanocytes (HERC2, OCA2), and transcriptome-wide association studies highlighted the expression of two genes associated with eye colour: SLC24A4 and OCA2. Finally, genetic correlations of eye and hair colour from the same cohort suggest high pleiotropy at the genome level, but locus-level evidence hints at several differences in the genetic architecture of both traits. Overall, we provide a better picture of how polymorphisms modulate eye colour variation, particularly in the HERC2/OCA2 locus, which may be a consequence of specific molecular processes in the iris melanocytes.

Author SummaryEye colour differences among humans are the result of different amounts of melanin produced, as well as due to differences in the shape and distribution of the organelles in charge of producing melanin. Eye colour is a highly heritable trait, where several genes across the genome are involved in the process, but we currently do not fully understand which are the causal variants and how they modulate eye colour variation. By performing genome-wide association studies of eye colour across Canadian individuals of European ancestry, we identify several candidate causal signals in and near the gene OCA2, and one candidate signal in other genes, such as TYR, TYRP1, IRF4 and SLC24A4. Furthermore, we provide insights about how significant loci may modulate eye colour variation by testing for shared signals with polymorphisms associated with the expression of genes and DNA methylation. Overall, we provide a better picture of the genetic architecture of eye colour and the molecular mechanisms contributing to its variation.

category: genetics


title: The use of barcoded Asaia bacteria in mosquito in vivo screens for identification of systemic insecticides and inhibitors of malaria transmission

abstract: This work addresses the need for new chemical matter in product development for control of pest insects and vector-borne diseases. We present a barcoding strategy that enables phenotypic screens of blood-feeding insects against small molecules in microtiter plate-based arrays and apply this to discovery of novel systemic insecticides and compounds that block malaria parasite development in the mosquito vector. Encoding of the bloodmeals was achieved through recombinant DNA-tagged Asaia bacteria that successfully colonized Aedes and Anopheles mosquitoes. An arrayed screen of a collection of pesticides showed that chemical classes of avermectins, phenylpyrazoles and neonicotinoids were enriched for compounds with systemic adulticide activity against Anopheles. Using a luminescent Plasmodium falciparum reporter strain, barcoded screens identified 48 drug-like transmission blocking compounds from a 400-compound antimicrobial library. The approach significantly increases the throughput in phenotypic screening campaigns using adult insects, and identifies novel candidate small molecules for disease control.

category: bioengineering


title: Extracellular Electron Transfer Enables Cellular Control of Cu(I)-catalyzed Alkyne-Azide Cycloaddition

abstract: Extracellular electron transfer (EET) is an anaerobic respiration process that couples carbon oxidation to the reduction of metal species. In the presence of a suitable metal catalyst, EET allows for cellular metabolism to control a variety of synthetic transformations. Here, we report the use of EET from the model electroactive bacterium Shewanella oneidensis for metabolic and genetic control over Cu(I)-catalyzed Alkyne-Azide Cycloaddition (CuAAC). CuAAC conversion under anaerobic and aerobic conditions was dependent on live, actively respiring S. oneidensis cells. In addition, reaction progress and kinetics could be further manipulated by tailoring the central carbon metabolism of S. oneidensis. Similarly, CuAAC activity was dependent on specific EET pathways and could be manipulated using inducible genetic circuits controlling the expression of EET-relevant proteins including MtrC, MtrA, and CymA. EET-driven CuAAC also exhibited modularity and robustness in ligand tolerance and substrate scope. Furthermore, the living nature of this system could be exploited to perform multiple reaction cycles without requiring regeneration, something inaccessible to traditional chemical reductants. Finally, S. oneidensis enabled bioorthogonal CuAAC membrane labelling on live mammalian cells without affecting cell viability, suggesting that S. oneidensis can act as a dynamically tunable biocatalyst in complex environments. In summary, our results demonstrate how EET can expand the reaction scope available to living systems by enabling cellular control of CuAAC.


title: Sustained Released of Bioactive Mesenchymal Stromal Cell-Derived Extracellular Vesicles from 3D-Printed Gelatin Methacrylate Hydrogels

abstract: Extracellular vesicles (EVs) represent an emerging class of therapeutics with significant potential and broad applicability. However, a general limitation is their rapid clearance after administration. Thus, methods to enable sustained EV release are of great potential value. Here, we demonstrate that EVs from mesenchymal stem/stromal cells (MSCs) can be incorporated into 3D-printed gelatin methacrylate (GelMA) hydrogel bioink, and that the initial burst release of EVs can be reduced by increasing the concentration of crosslinker during gelation. Further, the data show that MSC EV bioactivity in an endothelial gap closure assay is retained after the 3D printing and photocrosslinking processes. Our group previously showed that MSC EV bioactivity in this assay correlates with pro-angiogenic bioactivity in vivo, thus these results indicate therapeutic potential of MSC EV-laden GelMA bioinks.


title: In Situ Surface-Directed Assembly of 2D Metal Nanoplatelets for Drug-Free Treatment of Antibiotic-Resistant Bacteria

abstract: The development of antibiotic resistance among bacterial strains is a major global public health concern. To address this, drug-free antibacterial approaches are needed. High-touch surfaces in particular can serve as a means for the spread of bacteria and other pathogens from one infected person to another. Copper surfaces have long been known for their antibacterial properties. To further enhance the surfaces antibacterial properties, we used a one-step surface modification technique to assemble 2D copper chloride nanoplatelets directly onto copper surfaces such as copper tape, transmission electron microscopy (TEM) grids, electrodes, and granules. The nanoplatelets were formed using copper ions from the copper surfaces, enabling their direct assembly onto these surfaces in a one-step process that does not require separate nanoparticle synthesis. The synthesis of the nanoplatelets was confirmed with TEM, scanning electron microscopy, energy dispersive spectroscopy (EDS), x-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). Antibacterial properties of the surfaces with copper chloride nanoplatelets were demonstrated in multi-drug-resistant (MDR) E. coli. The presence of copper chloride nanoplatelets on the surface led to a marked improvement in antibacterial properties compared to the untreated copper surfaces. Surfaces with copper chloride nanoplatelets affected bacterial cell morphology, prevented bacterial cell division, reduced their viability, damaged bacterial deoxyribonucleic acid (DNA), and altered protein expression. In particular, proteins corresponding to cell division, DNA division, and mediation of copper toxicity were down-regulated. This work presents a robust method to directly assemble copper chloride nanoplatelets onto any copper surface to imbue it with improved antibacterial properties. To demonstrate that our method of particle generation can be used with other metal surfaces, we also demonstrate the synthesis of other metal-derived nanoarchitectures on a variety of metal surfaces.


title: All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons

abstract: Accurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing cells genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All2, which enables accurate filtering of mutations in a cell from exhaustive comparison of cells genomes to each other without data for bulk(s). Based on all pair-wise comparisons, every variant call (point mutation, indel, and structural variant) is classified as either a germline variant, mosaic mutation, or false positive. As All2 allows for considering dropped-out regions, it is applicable to whole genome and exome analysis of cloned and amplified cells. By applying the approach to a variety of available data, we showed that its application reduces false positives, enables sensitive discovery of high frequency mutations, and is indispensable for conducting high resolution cell lineage tracing. All2 is freely available at https://github.com/abyzovlab/All2.

category: bioinformatics


title: Computational design of peptide therapeutics: how useful are sequence-based protein-protein interaction predictors?

abstract: Engineering peptides to achieve a desired therapeutic effect through the inhibition of a specific target activity or protein interaction is a non-trivial task. Few of the existing in silico peptide design algorithms generate target-specific peptides. Instead, many methods produce peptides that achieve a desired effect through an unknown mechanism. In contrast with resource-intensive high-throughput experiments, in silico screening is a cost-effective alternative that can prune the space of candidates when engineering target-specific peptides. Using a set of FDA-approved peptides we curated specifically for this task, we assess the applicability of several sequence-based protein-protein interaction predictors as a screening tool within the context of peptide therapeutic engineering. We show that similarity-based protein-protein interaction predictors are more suitable for this purpose than the state-of-the-art deep learning methods publicly available at the time of writing. We also show that this approach is mostly useful when designing new peptides against targets for which naturally-occurring interactors are already known, and that deploying it for de novo peptide engineering tasks may require gathering additional target-specific training data. Taken together, this work offers evidence that supports the use of similarity-based protein-protein interaction predictors for peptide therapeutic engineering, especially peptide analogs.


title: Assessing sequence-based protein-protein interaction predictors for use in therapeutic peptide engineering


title: Direct quantification of ligand-induced lipid and protein microdomains with distinctive signaling properties

abstract: Lipid rafts are known as highly ordered lipid domains that are enriched in saturated lipids such as the ganglioside GM1. While lipid rafts are believed to exist in cells and to serve as signaling platforms through their enrichment in signaling components, they have never been directly observed in the plasma membrane without treatments that artificially cluster GM1 into large lattices. Here we report that microscopic GM1-enriched domains can form, without lipid cross-linking, in the plasma membrane of live mammalian cells expressing the EphA2 receptor tyrosine kinase in response to its ligand ephrinA1-Fc. The GM1-enriched microdomains form concomitantly with EphA2-enriched microdomains, but only partially co-localize with them. To gain insight into how plasma membrane heterogeneity controls signaling, we quantify the degree of EphA2 segregation and study initial EphA2 signaling steps in both EphA2-enriched and EphA2-depleted domains. By measuring dissociation constants, we demonstrate that EphA2 oligomerization is the same in EphA2-enriched and -depleted domains. However, EphA2 interacts preferentially with its downstream effector SRC in EphA2-depleted domains. The ability to induce microscopic GM1-enriched domains in live cells using a ligand for a transmembrane receptor will give us unprecedented opportunities to study the biology of lipid rafts.

category: biophysics


title: Rotational Activity Around an Obstacle in 2D Cardiac Tissue in Presence of Cellular Heterogeneity

abstract: Waves of electrical excitation rotating around an obstacle is one of the important mechanisms of dangerous cardiac arrhythmias occurring in the heart damaged by post-infarction scar. Such a scar also has a border zone around it, which has electrophysiological properties different from the rest of normal myocardial tissue. Spatial patterns of wave rotation in the presence of such tissue heterogeneity are poorly studied. In this paper we perform a comprehensive numerical study of various regimes of rotation of a wave in a plane layer of the ventricular tissue around an obstacle surrounded by a gray zone. We use a TP06 cellular ionic model which reproduces the electrophysiological properties of cardiomyocytes in the left ventricle of human heart. We vary the extent of obstacle and gray zone and study the pattern of wave rotation and its period. We observed different regimes of wave rotation that can be subdivided into several classes: (1) functional rotation and (2) scar rotation regimes, which were identified in the previous studies, and new (3) gray zone rotation regime: where the wave instead of rotation around the obstacle, rotates around the gray zone (an area of tissue heterogeneity) itself. For each class, the period of rotation is determined by different factors, which we discuss and quantify. We also found that due to regional pathological remodeling of myocardial tissue, we can obtain additional regimes associated with dynamical instabilities of two types which may affect or not affect the period of rotation.

category: physiology


title: Dynamics of deep water and N uptake under varied N and water supply

abstract:
AimsEnhanced nitrogen (N) and water uptake from deep soil layers may increase resource use efficiency whilst maintaining yield under stressed conditions. Winter oilseed rape (Brassica napus L.) can develop deep roots and access deep-stored resources such as N and water, while this potential has large uncertainties in variable environments. In this study, we aimed to evaluate the effects of reduced N and water supply on deep N and water uptake.

MethodsOilseed rape plants grown in outdoor rhizotrons were supplied with 240 and 80 kg N ha-1 respectively in 2019 whereas a well-watered and a water-deficit treatment were established in 2020. To track deep water and N uptake, a mixture of 2H2O and Ca(15NO3)2 was injected into the soil column at 0.5 and 1.7 m depths. {delta}2H in transpiration water and {delta}15N in leaves were measured after injection. {delta}15N in biomass samples were also measured.

ResultsDifferences in N or water supply had little effect on root growth. The low N treatment reduced water uptake throughout the soil profile, but caused a non-significant increment in 15N uptake efficiency at both 0.5 and 1.7 m. Water deficit in the upper soil layers led to compensatory deep water, while N uptake was not altered by soil water status.

ConclusionOur findings demonstrate that for winter oilseed rape, high N application and water deficiency in shallow layers increases deep water uptake, and that the efficiency of deep N uptake is mainly sensitive to N supply rather than water supply.

category: plant biology


title: Face masks impair reconstruction of acoustic speech features and higher-level segmentational features in the presence of a distractor speaker

abstract:
Multisensory integration enables stimulus representation even when the sensory input in a single modality is weak. In the context of speech, when confronted with a degraded acoustic signal, congruent visual inputs promote comprehension. When this input is occluded speech comprehension consequently becomes more difficult. But it still remains inconclusive which levels of speech processing are affected under which circumstances by occlusion of the mouth area. To answer this question, we conducted an audiovisual (AV) multi-speaker experiment using naturalistic speech. In half of the trials, the target speaker wore a (surgical) face mask, while we measured the brain activity of normal hearing participants via magnetoencephalography (MEG). We additionally added a distractor speaker in half of the trials in order to create an ecologic difficult listening situation. A decoding model on the clear AV speech was trained and used to reconstruct crucial speech features in each condition. We found significant main effects of face masks on the reconstruction of acoustic features, such as the speech envelope and spectral speech features (i.e. pitch and formant frequencies), while reconstruction of higher level features of speech segmentation (phoneme and word onsets) were especially impaired through masks in difficult listening situations. As we used surgical face masks in our study, which only show mild effects on speech acoustics, we interpret our findings as the result of the occluded lip movements. This idea is in line with recent research showing that visual cortical regions track spectral modulations. Our findings extend previous behavioural results, by demonstrating the complex contextual effects of occluding relevant visual information on speech processing.

HighlightsO_LISurgical face masks impair neural tracking of speech features
C_LIO_LITracking of acoustic features is generally impaired, while higher level segmentational features show their effects especially in challenging listening situations
C_LIO_LIAn explanation is the prevention of a visuo-phonological transformation contributing to audiovisual multisensory integration
C_LI


title: Occlusion of lip movements impairs reconstruction of acoustic speech features and higher-level segmentational features in the presence of a distractor speaker


title: Prediction of Inefficient BCI Users based on Cognitive Skills and Personality Traits

abstract: BCI inefficiency is one of the major challenges of motor imagery brain-computer interfaces (MI-BCI). Past research suggests that certain cognitive skills and personality traits correlate with MI-BCI real-time performance. Other studies have examined sensorimotor rhythm changes (also known as  suppression) as a valuable indicator of successful execution of the MI task. This research aims to combine these insights by investigating whether cognitive factors and personality traits can make predictions of a users ability to modulate  rhythms during a MI-BCI task. Data containing 55 subjects who completed a MI task was employed, and a stepwise linear regression model was implemented to select the most relevant features for  suppression prediction. The most accurate model was based on these factors: Spatial Ability, Visuospatial Memory, Autonomy, and Vividness of Visual Imagery. Further correlation analyses showed that a novice users  suppression during a MI-BCI task can be predicted based on their visuospatial memory ability, as measured by the Design Organization Test (DOT).


title: Enhanced nociception in a rabbit model of cerebral palsy

abstract: Spastic cerebral palsy (CP) is a movement disorder marked by hypertonia and hyperreflexia, and the most prevalent comorbidity is pain. Since spinal nociceptive afferents contribute to both the sensation of painful stimuli as well as reflex circuits involved in movement, we investigated the relationship between prenatal hypoxia-ischemia (HI) injury which can cause CP, and possible changes in spinal nociceptive circuitry. To do this, we examined nociceptive afferents and mechanical and thermal sensitivity of New Zealand White rabbit kits after prenatal HI or a sham surgical procedure. As described previously, a range of motor deficits similar to spastic CP was observed in kits born naturally after HI (40 minutes at ~70-80% gestation). We found that HI caused an expansion of peptidergic afferents (marked by expression of calcitonin gene-related peptide; CGRP) in both the superficial and deep dorsal horn at postnatal day (P)5. Non-peptidergic nociceptive afferent arborization (labeled by isolectin B4; IB4) was unaltered in HI kits but overlap of the two populations (peptidergic and non-peptidergic nociceptors) was increased by HI. Density of glial fibrillary acidic protein (GFAP) was unchanged within spinal white matter regions important in nociceptive transmission at P5. We found that mechanical and thermal allodynia was present in HI kits even in the absence of motor deficits. These findings suggest that prenatal HI injury impacts spinal sensory pathways in addition to the more well-established disruptions to descending motor circuits. In conclusion, changes to spinal nociceptive circuitry could disrupt spinal reflexes and contribute to pain experienced by individuals with CP.


title: Enhanced nociceptor sprouting in a rabbit model of cerebral palsy


title: Here's the twist: How the brain updates naturalistic event memories as our understanding of the past changes

abstract: The brain actively reshapes our understanding of past events in light of new incoming information. In the current study, we ask how the brain supports this updating process during the encoding and recall of naturalistic stimuli. One group of participants watched a movie ("The Sixth Sense") with a cinematic "twist" at the end that dramatically changed the interpretation of previous events. Next, participants were asked to verbally recall the movie events, taking into account the new "twist" information. Most participants updated their recall to incorporate the twist. Two additional groups recalled the movie without having to update their memories during recall: one group never saw the twist; another group was exposed to the twist prior to the beginning of the movie, and thus the twist information was incorporated both during encoding and recall. We found that providing participants with information about the twist beforehand altered neural response patterns during movie-viewing in the default mode network (DMN). Moreover, presenting participants with the twist at the end of the movie changed the neural representation of the previously-encoded information during recall in a subset of DMN regions. Further evidence for this transformation was obtained by comparing the neural activation patterns during encoding and recall and correlating them with behavioral signatures of memory updating. Our results demonstrate that neural representations of past events encoded in the DMN are dynamically integrated with new information that reshapes our understanding in natural contexts.


title: Here's the twist: How the brain updates the representations of naturalistic events as our understanding of the past changes


title: A Genetic Platform for Functionally Profiling Odorant Receptors Ex Vivo Using Olfactory Cilia.

abstract:
The molecular basis for odor perception in humans remains an enigma as odorant receptors (ORs) are notoriously difficult to study outside of their native environment. Efforts toward OR expression and functional profiling have been met with limited success due to poor efficiency of in vitro cell surface expression. Olfactory cilia are known to contain all components of the olfactory signal transduction machinery and can be placed into an ex vivo well-plate assay to rapidly measure robust, reproducible odor-specific responses. We now describe the isolation of cilia from mouse nose bioreactors for two human ORs, OR1A1 and OR5AN1, and reveal 10-100 fold more sensitivity compared to previously reported assays. A single animal can produce up to 4,000 384-well assay wells, and isolated olfactory cilia can be stored frozen and thus preserved. This pipeline offers a sensitive, highly scalable ex vivo odor screening platform that opens the door for decoding human olfaction.

One Sentence Summaryolfactory-cilia based odor screening platform.


title: Neurofibromin 1 controls metabolic balance and Notch-dependent quiescence of juvenile myogenic progenitors

abstract: Patients affected by neurofibromatosis type 1 (NF1) frequently show muscle weakness with unknown etiology. Here we show that Neurofibromin-1 (Nf1) is not required in muscle fibers, but specifically in early postnatal myogenic progenitors (MPs), where Nf1 loss led to cell cycle exit and differentiation blockade, depleting the MP pool resulting in reduced myonuclear accrual as well as reduced muscle stem cell numbers. This was caused by precocious induction of stem cell quiescence coupled to metabolic reprogramming of MPs impinging on glycolytic shutdown, which was conserved in muscle fibers. We show that a Mek/Erk/NOS pathway hypersensitizes Nf1-deficient MPs to Notch signaling, consequently, early postnatal Notch pathway inhibition ameliorated premature quiescence, metabolic reprogramming and muscle growth. This reveals an unexpected role of Ras/Mek/Erk signaling supporting postnatal MP quiescence in concert with Notch signaling, which is controlled by Nf1 safeguarding coordinated muscle growth and muscle stem cell pool establishment. Furthermore, our data suggest transmission of metabolic reprogramming across cellular differentiation, affecting fiber metabolism and function in NF1.


title: Host diversity and behavior determine patterns of interspecies transmission and geographic diffusion of avian Influenza A subtypes among North American wild reservoir species

abstract: Wild birds can carry avian influenza viruses (AIV), including those with pandemic or panzootic potential, long distances. Even though AIV has a broad host range, few studies account for host diversity when estimating AIV spread. We analyzed AIV genomic sequences from North American wild birds, including 303 newly sequenced isolates, to estimate interspecies transmission and geographic diffusion patterns among multiple co-circulating subtypes. Our results show high transition rates within Anseriformes and Charadriiformes, but limited transitions between these orders. Patterns of interspecies transmission were positively associated with breeding habitat range overlap, and negatively associated with host genetic distance. Distance between regions (negative correlation) and summer temperature at origin (positive correlation) were strong predictors of diffusion. Taken together, this study demonstrates that host diversity and ecology can determine evolutionary processes that underlie AIV natural history and spread. Understanding these processes can provide important insights for effective control of AIV.


title: Repression of the Hox gene abd-A by ELAV-mediated Transcriptional Interference

abstract: Intergenic transcription is a common feature of eukaryotic genomes and performs important and diverse cellular functions. Here, we investigate the iab-8 ncRNA from the Drosophila Bithorax Complex and show that this RNA is able to repress the transcription of genes located at its 3 end by a sequence-independent, transcriptional interference mechanism. Although this RNA is expressed in the early epidermis and CNS, we find that its repressive activity is limited to the CNS, where in wild-type embryos, it acts on the Hox gene, abd-A located immediately downstream of it. The CNS specificity is achieved through a 3 extension of the transcript, mediated by the neuronal-specific, RNA-binding protein, ELAV. Loss of ELAV activity eliminates the 3 extension and results in the ectopic activation of abd-A. Thus, a tissue-specific change in the length of a ncRNA is used to generate a precise pattern of gene expression in a higher eukaryote.


title: Drop of Prevalence after Population Expansion: A lower prevalence for recessive disorders in a random mating population is a transient phenomenon during and after a growth phase

abstract:
Despite increasing data from population-wide sequencing studies, the risk for recessive disorders in consanguineous partnerships is still heavily debated. An important aspect that has not sufficiently been investigated theoretically, is the influence of inbreeding on mutation load and incidence rates when the population sizes change. We therefore developed a model to study these dynamics for a wide range of growth and mating conditions. In the phase of population expansion and shortly afterwards, our simulations show that there is a drop of diseased individuals at the expense of an increasing mutation load for random mating, while both parameters remain almost constant in highly consanguineous partnerships. This explains the empirical observation in present times that a high degree of consanguinity is associated with an increased risk of autosomal recessive disorders. However, it also states that the higher frequency of severe recessive disorders with developmental delay in inbred populations is a transient phenomenon before a mutation-selection balance is reached again.

Author summaryWhat determines the recessive disease burden? The empirical observation that the proportion of intellectual disability of autosomal recessive cause is usually higher in offspring of consanguineous partnerships may lead to a misunderstanding about the mechanisms at work. In any population, selection removes pathogenic alleles from the gene pool while the de novo mutation rate adds novel pathogenic alleles. For comparable mutation rates, the incidence of severe recessive disease should be comparable in mutation-selection balance, regardless of the mating scheme. Different incidences can therefore only be explained by population dynamics that are not in equilibrium. We studied in simulated populations the time scales in which mutation-selection balance is reached after a growth phase and found that the mating scheme has a big impact on this lag time. When cousins mate preferentially with cousins, a few generations after a ten-fold increase in size the new equilibrium is established. In contrast, for random-mating, the transient advantage of a lower incidence may last for hundreds of generations, while the mutation load increases. By this means, our findings also highlight the importance of better carrier screens in the future for genetic consultations.


title: Tumor cell intrinsic and extrinsic features predicts prognosis in estrogen receptor positive breast cancer

abstract:
Although estrogen-receptor-positive (ER+) breast cancer is generally associated with favorable prognosis, clinical outcome varies substantially among patients. Genomic assays have been developed and applied to predict patient prognosis for personalized treatment. We hypothesize that the recurrence risk of ER+ breast cancer patients is determined by both genomic mutations intrinsic to tumor cells and extrinsic immunological features in the tumor microenvironment. Based on the Cancer Genome Atlas (TCGA) breast cancer data, we identified the 72 most common genomic aberrations (including gene mutations and indels) in ER+ breast cancer and defined sample-specific scores that systematically characterized the deregulated pathways intrinsic to tumor cells. To further consider tumor cell extrinsic features, we calculated immune infiltration scores for six major immune cell types. Many individual intrinsic features are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. In addition, statistical learning models that integrated these features predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay. As a proof-of-concept, our study indicates the great potential of genomic and immunological features in prognostic prediction for improving breast cancer precision medicine. The framework introduced in this work can be readily applied to other cancers.

Author SummaryMany genomic biomarker tests such as Oncotype DX have been developed for breast cancer and have helped guide clinical decisions. We have developed gene signatures to integrate cancer genomic and transcriptomic data to characterize the downstream effect of driver genomic events. These signatures recapitulate the de-regulated pathways underlying the corresponding driver genomic events and are more correlated with clinical phenotypes such as recurrence free survival than mutation status alone. We apply this framework to ER+ breast cancer and define gene signatures for a total of 72 most commonly observed genomic events including gene mutations, amplifications and deletions. We find that many of these gene signatures are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. We combine these tumor-intrinsic signatures with infiltration signatures for major immune cell types (tumor-extrinsic features) to construct integrative models for prognosis prediction. The models predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay.

category: genomics


title: Fast Optoacoustic Mesoscopy of Microvascular Endothelial Dysfunction in Cardiovascular Risk and Disease

abstract: Microvascular endothelial dysfunction (ED) precedes the ED in larger arteries and is an early marker of cardiovascular disease (CVD). While precise assessment of microvascular ED could thus be used for the early detection and risk stratification of CVD, detailed interrogation of skin microvascular ED is limited by the technology available. Herein, we applied a novel approach for the non-invasive assessment of skin microvascular ED by developing fast plane raster-scan optoacoustic mesoscopy (FP-RSOM) to visualize and quantify skin microvasculature perfusion changes during post-occlusive hyperemia (PORH) tests. We combined static three-dimensional RSOM imaging with fast dynamic FP-RSOM measurements (1 frame / second) in human skin in vivo, which allowed for the first time to fully visualize the cutaneous microvascular response and further quantify changes of individual vessel diameter, total blood volume and vessel density during the PORH process. We further computed biomarkers from FP-RSOM images to quantify skin endothelial function within different skin layers as a function of skin depth, while conventional approaches mainly measure overall changes within sampled tissue volumes. FP-RSOM applied on smokers and patients with CVD showed clear ED in both groups compared to healthy volunteers. Moreover, FP-RSOM imaging showed higher sensitivity in quantifying the effects of smoking and CVD on skin microvascular endothelial function compared to clinically used laser Doppler flowmetry and tissue spectrometry (O2C). Our study introduces FP-RSOM as a novel tool to visualize and quantify skin microvascular ED as an early marker for the diagnostics and monitoring of cardiovascular risk and disease.


title: Constructing benchmark test sets for biological sequence analysis using independent set algorithms

abstract: Statistical inference and machine learning methods are benchmarked on test data independent of the data used to train the method. Biological sequence families are highly non-independent because they are related by evolution, so the strategy for splitting data into separate training and test sets is a nontrivial choice in benchmarking sequence analysis methods. A random split is insufficient because it will yield test sequences that are closely related or even identical to training sequences. Adapting ideas from independent set graph algorithms, we describe two new methods for splitting sequence data into dissimilar training and test sets. These algorithms input a sequence family and produce a split in which each test sequence is less than p% identical to any individual training sequence. These algorithms successfully split more families than a previous approach, enabling construction of more diverse benchmark datasets.


title: easyfm : An easy software suite for file manipulation of Next Generation Sequencing data on desktops

abstract:
Storing and manipulating Next Generation Sequencing (NGS) file formats is an essential but difficult task in biological data analysis. The easyfm (easy file manipulation) toolkit (https://github.com/TaekAndBrendan/easyfm) makes manipulating commonly used NGS files more accessible to biologists. It enables them to perform end-to-end reproducible data analyses using a free standalone desktop application (available on Windows, Mac and Linux). Unlike existing tools (e.g. Galaxy), the Graphical User Interface (GUI)-based easyfm is not dependent on any high-performance computing (HPC) system and can be operated without an internet connection. This specific benefit allow easyfm to seamlessly integrate visual and interactive representations of NGS files, supporting a wider scope of bioinformatics applications in the life sciences.

Author summaryThe analysis and manipulation of NGS data for understanding biological phenomena is an increasingly important aspect in the life sciences. Yet, most methods for analysing, storing and manipulating NGS data require complex command-line tools in HPC or web-based servers and have not yet been implemented in comprehensive, easy-to-use software. This is a major hurdle preventing more general application in the field of NGS data analysis and file manipulation. Here we present easyfm, a free standalone Graphical User Interface (GUI) software with Python support that can be used to facilitate the rapid discovery of target sequences (or users interest) in NGS datasets for novice users. For user-friendliness and convenience, easyfm was developed with four work modules and a secondary GUI window (herein secondary window), covering different aspects of NGS data analysis (mainly focusing on FASTA files), including post-processing, filtering, format conversion, generating results, real-time log, and help. In combination with the executable tools (BLAST+ and BLAT) and Python, easyfm allows the user to set analysis parameters, select/extract regions of interest, examine the input and output results, and convert to a wide range of file formats. To help augment the functionality of existing web-based and command-line tools, easyfm, a self-contained program, comes with extensive documentation (hosted at https://github.com/TaekAndBrendan/easyfm) including a comprehensive step-by-step guide.


title: Joint Alignment and Tree Inference

abstract: Multiple sequence alignment and phylogenetic tree inference are connected problems that are often solved as independent steps in the inference process. Several attempts at doing simultaneous inference have been made, however currently the available methods are greatly limited by their computational complexity and can only handle small datasets. In this manuscript we introduce a combinatorial optimisation approach that will allow us to resolve the circularity of the problem and efficiently infer both alignments and trees under maximum likelihood.


title: Niosome encapsulated doxycycline-hyclate for potentiation of acne therapy: formulation and characterization

abstract: Acne is the pilosebaceous units disorder. The most important cause of acne is the colonization of bacteria in the follicles. Among antibiotics, doxycycline-hyclate kills a wide range of bacteria. To prevent oral administrations side effects, overcome the barriers of conventional topical treatment, and improve the therapeutic effectiveness, doxycycline-hyclate was loaded into four niosomal formulations with different percentages of constituents (span 60 and cholesterol) prepared by the thin-film hydration method. Then, one of the four formulations with the most appropriate particle size of 362.88 {+/-} 13.05 nm to target the follicles, percentage of drug entrapment efficiency of 56.3 {+/-} 2.1%, in vitro drug release of 54.93 {+/-} 1.99% after 32 hours, and the lowest permeation of the drug through the Wistar rat skin, was selected. Then, its toxicity on human dermal fibroblasts (HDF) by MTT method after 72 hours, its antibacterial activity against the main acne-causing bacteria via antibiogram test, and its effect on Wistar rat skin drug deposition were measured. Improved cell viability, increased antibacterial activity, and an approximately three-fold increase in drug deposition were the optimal niosomal formulation features relative to the free drug. Overall, this study demonstrated the ability of nano-niosomes containing doxycycline-hyclate to treat skin acne.

category: pharmacology and toxicology


title: A NET4-RabG3 couple mediate the link between actin and the tonoplast and is essential for normal actin cytoskeletal remodelling in stomatal closure to flg22

abstract: Members of the NETWORKED (NET) family are involved in actin-membrane interactions. They tether the cells plasma membrane (PM) to the actin network. Moreover, in a similar manner, they are also involved in the tethering of membrane bound organelles to the actin cytoskeleton; the endoplasmic reticulum (ER) and the ER to the PM. This raises the question as to whether NET proteins are involved in actin cytoskeletal remodelling. Here we show that two members of the NET family, NET4A and NET4B, are essential for normal guard cell actin reorganization, which is a process critical for stomatal closure in plant immunity. NET4 proteins interact with F-actin and with members of the Rab7 GTPase RABG3 family through two distinct domains, allowing for simultaneous localization to actin filaments and the tonoplast. NET4 proteins interact with GTP-bound, active RABG3 members, suggesting their function as downstream effectors. We also show that RABG3b is critical for stomatal closure induced by microbial patterns. Taken together, we conclude that the actin cytoskeletal remodelling during stomatal closure depends on a molecular link between actin filaments and the tonoplast, which is mediated by the NET4-RABG3b interaction. We propose that stomatal closure to microbial patterns involves the coordinated action of immune signalling events and proper actin cytoskeletal remodelling.


title: Biomass formation and sugar release efficiency of Populus modified by altered expression of a NAC transcription factor

abstract: Woody biomass is an important feedstock for biofuel production. Manipulation of wood properties that enable efficient conversion of biomass to biofuel reduces cost of biofuel production. Wood cell wall composition is regulated at several levels that involve expression of transcription factors such as wood-/secondary cell wall-associated NAC domains (WND or SND). In Arabidopsis thaliana, SND1 regulates cell wall composition through activation of its down-stream targets such as MYBs. The functional aspects of SND1 homologs in the woody Populus have been studied through transgenic manipulation. In this study, we investigated the role of PdWND1B, Populus SND1 sequence ortholog, in wood formation using transgenic manipulation through over-expression or silencing under the control of a vascular-specific 4-coumarate-CoA ligase (4CL) promoter. As compared to control plants, PdWND1B-RNAi plants were shorter in height, with significantly reduced stem diameter and dry biomass, whereas there were no significant differences in growth and productivity of PdWND1B over-expression plants. Conversely, PdWND1B over-expression lines showed a significant reduction in cellulose and increase in lignin content, whereas there was no significant impact on lignin content of down-regulated lines. Stem carbohydrate composition analysis revealed a decrease in glucose, mannose, arabinose, and galactose, but an increase in xylose in the over-expression lines. Transcriptome analysis revealed upregulation of several downstream transcription factors and secondary cell wall related structural genes in the PdWND1B over-expression lines that corresponded to significant phenotypic changes in cell wall chemistry observed in PdWND1B overexpression lines. Relative to the control, glucose release and ethanol production from stem biomass was significantly reduced in over-expression lines but appeared enhanced in the RNAi lines. Our results show that PdWND1B is an important factor determining biomass productivity, cell wall chemistry and its conversion to biofuels in Populus.


title: Finding landmarks - An investigation of viewing behavior during spatial navigation in VR using a graph-theoretical analysis approach

abstract:
Vision provides the most important sensory information for spatial navigation. Recent technical advances allow new options to conduct more naturalistic experiments in virtual reality (VR) while additionally gather data of the viewing behavior with eye tracking investigations. Here, we propose a method that allows one to quantify characteristics of visual behavior by using graph-theoretical measures to abstract eye tracking data recorded in a 3D virtual urban environment.

The analysis is based on eye tracking data of 20 participants, who freely explored the virtual city Seahaven for 90 minutes with an immersive VR headset with an inbuild eye tracker. To extract what participants looked at, we defined "gaze" events, from which we created gaze graphs. On these, we applied graph-theoretical measures to reveal the underlying structure of visual attention.

Applying graph partitioning, we found that our virtual environment could be treated as one coherent city. To investigate the importance of houses in the city, we applied the node degree centrality measure. Our results revealed that 10 houses had a node degree that exceeded consistently two-sigma distance from the mean node degree of all other houses. The importance of these houses was supported by the hierarchy index, which showed a clear hierarchical structure of the gaze graphs. As these high node degree houses fulfilled several characteristics of landmarks, we named them "gaze-graph-defined landmarks". Applying the rich club coefficient, we found that these gaze-graph-defined landmarks were preferentially connected to each other and that participants spend the majority of their experiment time in areas where at least two of those houses were visible.

Our findings do not only provide new experimental evidence for the development of spatial knowledge, but also establish a new methodology to identify and assess the function of landmarks in spatial navigation based on eye tracking data.

Author SummaryThe ability to navigate and orient ourselves in an unknown environment is important in everyday life. To better understand how we are able to learn about a new environment, it is important to study our behavior during the process of spatial navigation. New technical advances allow us to conduct studies in naturalistic virtual environments with participants wearing immersive VR-headsets. In addition, we can use eye trackers to observe the participants eye movements. This is interesting, because observing eye movements allows us to observe visual attention and, therefore, important cognitive processes. However, it can be difficult to analyze eye tracking data that was measured in a VR environment, as there is no established algorithm yet. Therefore, we propose a new method to analyze such eye tracking data. In addition, our method allows us to transform the eye tracking data into graphs which we can use to find new patterns in behavior that were not accessible before. Using this methodology, we found that participants who spend 90 min exploring a new virtual town, viewed some houses preferentially and we call them gaze-graph-defined landmarks. Our further analysis reveals also new characteristics of those houses that were not yet associated with landmarks.


title: Decoding Estimates of Curvilinear Self-Motion from Neural Signals in a Model of Primate MSTd

abstract:
Self-motion produces characteristic patterns of optic flow on the eye of the mobile observer. Movement along linear, straight paths without eye movements yields motion that radiates from the direction of travel (heading). The observer experiences more complex motion patterns while moving along more general curvilinear (e.g. circular) paths, the appearance of which depends on the radius of the curved path (path curvature) and the direction of gaze. Neurons in brain area MSTd of primate visual cortex exhibit tuning to radial motion patterns and have been linked with linear heading perception. MSTd also contains neurons that exhibit tuning to spirals, but their function is not well understood. We investigated in a computational model whether MSTd, through its diverse pattern tuning, could support estimation of a broader range of self-motion parameters from optic flow than has been previously demonstrated. We used deep learning to decode these parameters from signals produced by neurons tuned to radial expansion, spiral, ground flow, and other patterns in a mechanistic neural model of MSTd. Specifically, we found that we could accurately decode the clockwise/counterclockwise sign of curvilinear path and the gaze direction relative to the path tangent from spiral cells; heading from radial cells; and the curvature (radius) of the curvilinear path from activation produced by both radial and spiral populations. We demonstrate accurate decoding of these linear and curvilinear self-motion parameters in both synthetic and naturalistic videos of simulated self-motion. Estimates remained stable over time, while also rapidly adapting to dynamic changes in the observers curvilinear self-motion. Our findings suggest that specific populations of neurons in MSTd could effectively signal important aspects of the observers linear and curvilinear self-motion.

Author SummaryHow do we perceive our self-motion as we move through the world? Substantial evidence indicates that brain area MSTd contains neurons that signal the direction of travel during movement along straight paths. We wondered whether MSTd neurons could also estimate more general self-motion along curved paths. We tested this idea by using deep learning to decode signals produced by a neural model of MSTd. The system accurately decoded parameters that specify the observers self-motion along straight and curved paths in videos of synthetic and naturalistic scenes rendered in the Unreal game engine. Our findings suggest that MSTd could jointly signal self-motion along straight and curved paths.


title: Numb reduces Tau levels and prevents neurodegeneration in mouse models of tauopathy in an isoform-specific manner

abstract: Accumulation of the microtubule-associated protein Tau is linked to neuronal cell death in tauopathies, but how exactly intraneuronal Tau levels are regulated in health and disease remains unclear. Here we identify the trafficking adaptor protein Numb as an essential regulator of Tau homeostasis. Conditional inactivation of Numb in retinal ganglion cells (RGCs) increases monomeric and oligomeric Tau levels, leading to axonal blebbing followed by neuronal cell loss in aged mice. Moreover, in a mouse model of tauopathy, inactivation of Numb in RGCs and spinal motoneurons accelerates neurodegeneration, and leads to precocious hindlimb paralysis. Conversely, overexpression of the long isoform of Numb (Numb-72), but not other isoforms, decreases intracellular Tau levels by promoting the extracellular release of monomeric Tau, and AAV-mediated delivery of Numb-72 in RGCs in vivo prevents neurodegeneration in two different mouse models of tauopathy. Taken together, these results uncover Numb as a modulator of intracellular Tau levels and identify Numb-72 as a novel therapeutic factor for tauopathies.


title: Radical pairs may play a role in microtubule reorganization

abstract: The exact mechanism behind general anesthesia remains an open question in neuroscience. It has been proposed that anesthetics selectively prevent consciousness and memory via acting on microtubules (MTs). It is known that the magnetic field modulates MT organization. A recent study shows that a radical pair model can explain the isotope effect in xenon-induced anesthesia and predicts magnetic field effects on anesthetic potency. Further, reactive oxygen species are also implicated in MT stability and anesthesia. Based on a simple radical pair mechanism model and a simple mathematical model of MT organization, we show that magnetic fields can modulate spin dynamics of naturally occurring radical pairs in MT. We show that the spin dynamics influence a rate in the reaction cycle, which translates into a change in the MT density. We can reproduce magnetic field effects on the MT concentration that have been observed. Our model also predicts additional effects at slightly higher fields. Our model further predicts that the effect of zinc on the MT density exhibits isotopic dependence. The findings of this work make a connection between microtubule-based and radical pair-based quantum theories of consciousness.


title: Social framing effects in decision making

abstract: Human decisions are known to be strongly influenced by the manner in which options are presented, the "framing effect". Here, we ask whether decision-makers are also influenced by how advice from other knowledgeable agents are framed, a "social framing effect". For example, do students learn better from a teacher who often frames advice by emphasizing appetitive outcomes, or do they learn better from another teacher who usually emphasizes avoiding options that can be harmful to their progress? We study the computational and neural mechanisms by which framing of advice affect decision-making, social learning, and trust. We found that human participants are more likely to trust and follow an adviser who often uses an appetitive frame for advice compared with another one who often uses an aversive frame. This social framing effect is implemented through a modulation of the integrative abilities of the ventromedial prefrontal cortex. At the time of choice, this region combines information learned via personal experiences of reward with social information, but the combination differs depending on the social framing of advice. Personally-acquired information is weighted more strongly when dealing with an adviser who uses an aversive frame. The findings suggest that social advice is systematically incorporated into our decisions, while being affected by biases similar to those influencing individual value-based learning.


title: Revisiting the role of beta-tubulin in Drosophila development: beta-tubulin60D is not an essential gene, and its novel Pin1 allele has a tissue-specific dominant-negative impact

abstract:
Diversity in cytoskeleton organization and function may be achieved through alternative tubulin isotypes and by a variety of post-translational modifications. The Drosophila genome contains five different {beta}-tubulin paralogs, which may play an isotype tissue-specific function in vivo. One of these genes, the beta-tubulin60D gene, which is expressed in a tissue-specific manner, was found to be essential for fly viability and fertility. To further understand the role of the beta-tubulin60D gene, we generated new beta-tubulin60D null alleles (beta-tubulin60DM) using the CRISPR/Cas9 system and found that the homozygous flies were viable and fertile. Moreover, using a combination of genetic complementation tests, rescue experiments, and cell biology analyses, we identified Pin1, an unknown dominant mutant with bristle developmental defects, as a dominant-negative allele of beta-tubulin60D. We also found a missense mutation in the Pin1 mutant that results in an amino acid replacement from the highly conserved glutamate at position 75 to lysine (E75K). Analyzing the {beta}-tubulin structure suggests that this E75K alteration destabilizes the alpha-helix structure and may also alter the GTP-Mg2+ complex binding capabilities. Our results revisited the credence that beta-tubulin60D is required for fly viability and revealed for the first time in Drosophila, a novel dominant-negative function of missense beta-tubulin60D mutation in bristle morphogenesis.

Author summaryDiversity in cell microtubule cytoskeleton organization and function may be achieved through alternative tubulin isotypes and by a variety of post-translational modifications. The expression pattern of different tubulin isotypes (both  and {beta} subunits) can vary according to cell type and stage of development, which contribute significantly to cell-specific MT organization and function. In this study, we revisited the role of one of the beta-tubulin isotopes in Drosophila, namely, beta-tubulin60D. This is the first study where a well molecularly defined protein null allele of {beta}Tub60D was generated and characterized. This well-characterized {beta}Tub60D allele demonstrated unambiguity that {beta}Tub60D is not an essential gene, as was described before. Moreover, we identified Pin1, an unknown dominant mutant with bristle developmental defects, as a dominant-negative allele of beta-tubulin60D. We also found a missense mutation in the Pin1 mutant that results in an amino acid (E75K). Analyzing the {beta}-tubulin structure suggests that this E75K alteration destabilizes the alpha-helix structure and may also alter GTP-Mg2+ complex binding capabilities. Thus, our results also revealed for the first time in Drosophila, a novel dominant-negative function of a missense beta-tubulin60D mutation, which has a tissue-specific function.


title: Managed culls mean extinction for a marine mammal population when combined with extreme climate impacts

abstract: Human actions led to the worldwide decline of marine mammal populations in the 18th-19th centuries. However, the global uptake in protective legislation during the 20th century has recently allowed many marine mammal populations to recover. This positive trend is particularly true of pinnipeds (e.g., seals and sea lions), whose recovering populations are increasingly in conflict with fisheries. Many fisheries organisations call for managed culls of sea lion populations to reduce competition for target fish species as well as damage to catch and fishing gear through operational interactions. However, despite widespread perceptions that sea lion populations are generally increasing, to-date culls have been considered or implemented without quantitative evidence of their impacts on seal lion population viability. This knowledge gap is particularly concerning given the expected increase in extreme climate conditions, such as extreme El Nino events, which together with culls could push sea lion populations in some parts of the world into the extinction vortex. In this analysis, I develop and parameterise stochastic matrix population models of the South American sea lion (Otaria flavescens) to project the impact of (1) three cull scenarios with different intensity and temporal frequency targeting adult females, (2) extreme El Nino events whose frequency is modelled using a Markovian transition matrix, (3) and the interaction of culls and extreme climate events on population dynamics. I focus on the Chilean population of O. flavescens, where recent increases in sea lion numbers have triggered widespread conflict with small-scale fisheries, and where sea lion populations will increasingly be affected by extreme El Nino conditions. I find that sea lion populations decline below minimum viable population sizes under all scenarios involving culls and extreme climate events. By explicitly considering parameter uncertainty, this approach is a call to action for future research to focus on collecting stage-specific, annual population data to reduce uncertainty regarding marine mammal vital rates.


title: Genome-wide identification of protein binding sites in mammalian cells

abstract: We present GWPBS-Cap, a method to capture genome-wide protein binding sites (PBSs) without using antibodies. Using this technique, we identified many protein binding sites with different binding strengths between proteins and DNA. The PBSs can be useful to predict transcription binding sites and the co-localization of multiple transcription factors in the genome. The results also revealed that active promoters contained more protein binding sites with lower NaCl tolerances. Taken together, GWPBS-Cap can be used to efficiently identify protein binding sites and reveal genome-wide landscape of DNA-protein interactions.


title: Accelerating Identification of Chromatin Accessibility from noisy ATAC-seq Data using Modern CPUs

abstract: Identifying accessible chromatin regions is a fundamental problem in epigenomics with ATAC-seq being a commonly used assay. Exponential rise in single cell ATAC-seq experiments has made it critical to accelerate processing of ATAC-seq data. ATAC-seq data can have a low signal-to-noise ratio for various reasons including low coverage or low cell count. To denoise and identify accessible chromatin regions from noisy ATAC-seq data, use of deep learning on 1D data - using large filter sizes, long tensor widths, and/or dilation - has recently been proposed. Here, we present ways to accelerate the end-to-end training performance of these deep learning based methods using CPUs. We evaluate our approach on the recently released AtacWorks toolkit. Compared to an Nvidia DGX-1 box with 8 V100 GPUs, we get up to 2.27x speedup using just 16 CPU sockets. To achieve this, we build an efficient 1D dilated convolution layer and demonstrate reduced precision (BFloat16) training.


title: Ensemble-function relationships to evaluate catalysis in the ketosteroid isomerase oxyanion hole

abstract: Following decades of insights from structure-function studies, there is now a need to progress from a static to dynamic view of enzymes. Comparison of prior cryo X-ray structures suggested that deleterious effects from ketosteroid isomerase (KSI) mutants arise from misalignment of the oxyanion hole catalytic residue, Y16. However, multi-conformer models from room temperature X-ray diffraction revealed an ensemble of Y16 conformers indistinguishable from WT for Y32F/Y57F KSI and a distinct, non-native ensemble for Y16 in Y57F KSI. Functional analyses suggested rate effects arise from weakened hydrogen bonding, due to disruption of the Y16/Y57/Y32 hydrogen bond network, and repositioning of the general base. In general, catalytic changes can be deconvoluted into effects on the probability of occupying a state (P-effects) and the reactivity of each state (k-effects). Our results underscore the need for ensemble-function analysis to decipher enzyme function and ultimately manipulate their extraordinary capabilities.

category: biochemistry


title: Computational model of 3D cell migration based on the molecular clutch mechanism

abstract: The external environment is a regulator of cell activity. Its stiffness and microstructure can either facilitate or prevent 3D cell migration in both physiology and disease. 3D cell migration results from force feedbacks between the cell and the extracellular matrix (ECM). Adhesions regulate these force feedbacks by working as molecular clutches that dynamically bind and unbind the ECM. Because of the interdependency between ECM properties, adhesion dynamics, and cell contractility, how exactly 3D cell migration occurs in different environments is not fully understood. In order to elucidate the effect of ECM on 3D cell migration through force-sensitive molecular clutches, we developed a computational model based on a lattice point approach. Results from the model show that increases in ECM pore size reduce cell migration speed. In contrast, matrix porosity increases it, given a sufficient number of ligands for cell adhesions and limited crowding of the matrix from cell replication. Importantly, these effects are maintained across a range of ECM stiffnesses, demonstrating that mechanical factors are not responsible for how matrix microstructure regulates cell motility.