title: Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

abstract: To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.


title: A reference-quality, fully annotated genome from a Puerto Rican individual

abstract: Until 2019, the human genome was available in only one fully-annotated version, GRCh38, which was the result of 18 years of continuous improvement and revision. Despite dramatic improvements in sequencing technology, no other genome was available as an annotated reference until 2019, when the genome of an Ashkenazi individual, Ash1, was released. In this study, we describe the assembly and annotation of a second individual genome, from a Puerto Rican individual whose DNA was collected as part of the Human Pangenome project. The new genome, called PR1, is the first true reference genome created from an individual of African descent. Due to recent improvements in both sequencing and assembly technology, and particularly to the use of the recently completed CHM13 human genome as a guide to assembly, PR1 is more complete and more contiguous than either GRCh38 or Ash1. Annotation revealed 37,755 genes (of which 19,999 are protein-coding), including 12 additional gene copies that are present in PR1 and missing from CHM13. 57 genes have fewer copies in PR1 than in CHM13, 9 map only partially, and 3 genes (all non-coding) from CHM13 are entirely missing from PR1.

category: genomics


title: A Novel Local Ablation Approach for Explaining Multimodal Classifiers

abstract: With the growing use of multimodal data for deep learning classification in healthcare research, more studies have begun to present explainability methods for insight into multimodal classifiers. Among these studies, few have utilized local explainability methods, which could provide (1) insight into the classification of each sample and (2) an opportunity to better understand the effects of demographic and clinical variables within datasets (e.g., medication of subjects in electrophysiology data). To the best of our knowledge, this opportunity has not yet been explored within multimodal classification. We present a novel local ablation approach that shows the importance of each modality to the correct classification of each class and explore the effects of demographic and clinical variables upon the classifier. As a use-case, we train a convolutional neural network for automated sleep staging with electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) data. We find that EEG is the most important modality across most stages, though EOG is particular important for non-rapid eye movement stage 1. Further, we identify significant relationships between the local explanations and subject age, sex, and state of medication which suggest that the classifier learned specific features associated with these variables across multiple modalities and correctly classified samples. Our novel explainability approach has implications for many fields involving multimodal classification. Moreover, our examination of the degree to which demographic and clinical variables may affect classifiers could provide direction for future studies in automated biomarker discovery.

category: bioinformatics


title: Accuracy of somatic variant detection workflows for whole genome sequencing experiments

abstract:
Whole genome sequencing (WGS) becomes increasingly important for advancing personalized cancer care, driving not only basic science studies but also entering into clinical applications. Translating raw WGS data into the right clinical decision requires high accuracy of somatic variant detection, therefore novel data analysis methods have to be carefully evaluated.

In this work we tested the performance of well-established somatic variant detection workflows: GATK, CPG-WGS, DRAGEN and Strelka2. By utilizing both real data, with well-defined mutations, and synthetic mutations spiked-in into real data, we were able to assess sensitivity and precision of each workflow, for various coverage and tumor purity levels.

Individual tools excelled in different evaluation approaches, however the results demonstrated that DRAGEN has the highest overall performance when sensitivity is preferred over precision, and the opposite is true for CGP-WGS. The differences in results obtained using synthetic and real datasets, indicate that benchmarks based only on a single reference set may provide an incomplete picture.


title: Clustering and visualizing the distribution of overlapping reading frames in virus genomes

abstract: Gene overlap occurs when two or more genes are encoded by the same nucleotides. This phenomenon is found in all taxonomic domains, but is particularly common in viruses, where it may increase the information content of compact genomes or influence the creation of new genes. Here we report a global comparative study of overlapping reading frames (OvRFs) of 12,609 virus reference genomes in the NCBI database. We retrieved metadata associated with all annotated reading frames in each genome record to calculate the number, length, and frameshift of OvRFs. Our results show that while the number of OvRFs increases with genome length, they tend to be shorter in longer genomes. The majority of overlaps involve +2 frameshifts, predominantly found in ds-DNA viruses. However, the longest overlaps involve no shift in reading frame (+0), increasing the selective burden of the same nucleotide positions within codons, instead of exposing additional sites to purifying selection. Next, we develop a new graph-based representation of the distribution of OvRFs among the reading frames of genomes in a given virus family. In the absence of an unambiguous partition of reading frames by homology at this taxonomic level, we used an alignment-free k-mer based approach to cluster protein coding sequences by similarity. We connect these clusters with two types of directed edges to indicate (1) that constituent reading frames are adjacent in one or more genomes, and (2) that the reading frames overlap. These adjacency graphs not only provide a natural visualization scheme, but also a novel statistical framework for analyzing the effects of gene- and genome-level attributes on the frequencies of overlaps.


title: Using networks to analyze and visualize the distribution of overlapping reading frames in virus genomes


title: Diverse routes of Club cell evolution in lung adenocarcinoma

abstract: The high plasticity of lung epithelial cells, has for many years, confounded the correct identification of the cell-of-origin of lung adenocarcinoma (LUAD), one of the deadliest malignancies worldwide. Here, we address the cell-of-origin of LUAD, by employing lineage-tracing mouse models combined with a CRISPR/Cas9 system to induce an oncogenic Eml4-Alk rearrangement in virtually all epithelial cell types of the lung. We find that Club cells give rise to lung tumours with a higher frequency than AT2 cells. Based on whole genome methylome, we identified that tumours retain an  epigenetic memory derived from their originating cell type but also develop a tumour-specific pattern regardless of their origin. Single-cell transcriptomic analyses identified two trajectories of Club cell evolution which are similar to the ones used during lung regeneration, providing a link between lung regeneration and cancer initiation. On both routes, tumours lose their Club cell identity and gain an AT2- like phenotype. Together, this study highlights the role of Club cells in LUAD initiation and unveils key mechanisms conferring LUAD heterogeneity.

category: cancer biology


title: Drug-dependent morphological transitions in spherical and worm-like polymeric micelles define stability and pharmacological performance of micellar drugs

abstract: Significant advances in physicochemical properties of polymeric micelles enable optimization of therapeutic drug efficacy, supporting nanomedicine manufacturing and clinical translation. Yet, the effect of micelle morphology on pharmacological efficacy has not been adequately addressed. We addressed this gap by assessing pharmacological efficacy of polymeric micelles with spherical and worm-like morphologies. We observed that poly(2-oxazoline)-based polymeric micelles can be elongated over time from a spherical structure to worm-like structure, with elongation influenced by several conditions, including the amount and type of drug loaded into the micelles. We further evaluated the role of different morphologies of olaparib micelles on pharmacological performance against a triple-negative breast cancer tumor (TNBC) model. Spherical micelles accumulated rapidly in the tumor tissue while retaining large amounts of drug; worm-like micelles accumulated more slowly and only upon releasing significant amounts of drug. These findings suggest that the dynamic character of the drug-micelle structure and the micelle morphology play a critical role in pharmacological performance, and that spherical micelles are better suited for systemic delivery of anticancer drugs to tumors when drugs are loosely associated with the polymeric micelles.

category: pharmacology and toxicology


title: Autonomic and respiratory components of orienting behaviors are mediated by descending pathways originating from the superior colliculus

abstract: The ability to discriminate competing, external stimuli, and initiate contextually appropriate behaviors, is a key brain function. Neurons in the deep superior colliculus (dSC) integrate multisensory inputs and activate descending projections to premotor pathways responsible for orienting and attention, behaviors which involve adjustments to respiratory and cardiovascular parameters. However, the neural pathways that subserve the physiological components of orienting are poorly understood. We report that orienting responses to optogenetic dSC stimulation are accompanied by short-latency autonomic, respiratory and electroencephalographic effects in awake rats, closely mimicking those evoked by naturalistic alerting stimuli. Physiological responses were not accompanied by detectable aversion or fear and persisted under urethane anesthesia, indicating independence from emotional stress. Moreover, autonomic responses were replicated by selective stimulation of dSC inputs to a subregion in the ventromedial medulla containing spinally-projecting premotor neurons. This putative disynaptic pathway from the dSC represents a likely substrate for autonomic components of orienting.

category: neuroscience


title: Consciousness is supported by near-critical cortical electrodynamics

abstract:
Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition, and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, for the first time, we empirically identify the specific critical point near which conscious cortical dynamics operate as the edge-of-chaos critical point, or the boundary between periodicity/stability and chaos/instability. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magne-toencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, GABAergic anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of cortical dynamics away from this critical point; conversely, we show that psychedelics may increase the information-richness of cortical activity by tuning cortical electrodynamics closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC), and show that assessing the proximity of cortical electrodynamics to the edge-of-chaos critical point may be clinically useful as a new biomarker of consciousness.

Significance StatementWhat changes in the brain when we lose consciousness? One possibility is that the loss of consciousness corresponds to a transition of the brains electric activity away from edge-of-chaos criticality, or the knifes edge in between stability and chaos. Recent mathematical developments have produced novel tools for testing this hypothesis, which we apply for the first time to cortical recordings from diverse brain states. We show that the electric activity of the cortex is indeed poised near the boundary between stability and chaos during conscious states and transitions away from this boundary during unconsciousness, and that this transition disrupts cortical information processing.


title: PATAN-domain response regulators interact with the Type IV pilus motor to control phototactic orientation in the cyanobacterium Synechocystis sp. PCC 6803

abstract: Many prokaryotes show complex behaviors that require the intricate spatial and temporal organization of cellular protein machineries, leading to asymmetrical protein distribution and cell polarity. One such behavior is cyanobacterial phototaxis which relies on the dynamic localization of the Type IV pilus motor proteins in response to light. In the cyanobacterium Synechocystis, various signaling systems encompassing chemotaxis-related CheY- and PatA-like response regulators are critical players in switching between positive and negative phototaxis depending on the light intensity and wavelength. In this study, we show that PatA-type regulators evolved from chemosensory systems. Using fluorescence microscopy and yeast-two-hybrid analysis, we demonstrate that they localize to the inner membrane, where they interact with the N-terminal cytoplasmic domain of PilC and the pilus assembly ATPase PilB1. By separately expressing the subdomains of the response regulator PixE, we confirm that only the N-terminal PATAN domain interacts with PilB1, localizes to the membrane, and is sufficient to reverse phototactic orientation. These experiments established that the PATAN domain is the principal output domain of PatA-type regulators which we presume to modulate pilus extension by binding to the pilus motor components.

category: microbiology


title: Sustained mechanical tension governs fibrogenic activation of tendon stromal cells in systemic sclerosis

abstract: Fibrosis is a pathological outcome of aberrant repair responses in systemic sclerosis and affects many tissues, including tendons. Progressive matrix stiffening is a key feature of this pathological remodeling. How dysregulated tissue mechanics contribute to the persistence of the fibrotic phenotype has been obscured by limited availability of experimental tissue models that are both controllable and capture essential aspects of the tendon biophysical niche. Here, we developed a modular, cantilever-based platform that allows culture of 3D tendon-like constructs under easily variable static tension, emulating this central tendon-specific structure function relationship. The system reveals that elevated matrix tension instigates fibroblast-to-myofibroblast activation eliciting scar-like phenotypes in vitro. By using this mechano-culture system and preclinical and clinical models of systemic sclerosis, we further show that 3D matrix stiffness is inversely correlated with the transcription of major pro-fibrotic collagens, but positively correlate with the expression of markers of stromal-immune interactions. Co-culture of tendon stromal fibroblasts and bone marrow-derived macrophages override stiffness-mediated downregulation of matrix transcription, suggesting that normal tension mediated checkpoints are superseded by the local tissue immune state. Our study highlights the power of 3D reductionist approaches in dissecting the contribution of the elevated matrix tension to the positive feedforward loops between activated fibroblasts and progressive ECM stiffening in systemic sclerosis.

category: cell biology


title: Exploiting node metadata to predict interactions in large networks using graph embedding and neural networks

abstract: Collecting network interaction data is difficult. Non-exhaustive sampling and complex hidden processes often result in an incomplete data set. Thus, identifying potentially present but unobserved interactions is crucial both in understanding the structure of large scale data, and in predicting how previously unseen elements will interact. Recent studies in network analysis have shown that accounting for metadata (such as node attributes) can improve both our understanding of how nodes interact with one another, and the accuracy of link prediction. However, the dimension of the object we need to learn to predict interactions in a network grows quickly with the number of nodes. Therefore, it becomes computationally and conceptually challenging for large networks. Here, we present a new predictive procedure combining a graph embedding method with machine learning techniques to predict interactions on the base of nodes metadata. Graph embedding methods project the nodes of a network onto a--low dimensional--latent feature space. The position of the nodes in the latent feature space can then be used to predict interactions between nodes. Learning a mapping of the nodes metadata to their position in a latent feature space corresponds to a classic--and low dimensional--machine learning problem. In our current study we used the Random Dot Product Graph model to estimate the embedding of an observed network, and we tested different neural networks architectures to predict the position of nodes in the latent feature space. Flexible machine learning techniques to map the nodes onto their latent positions allow to account for multivariate and possibly complex nodes meta-data. To illustrate the utility of the proposed procedure, we apply it to a large dataset of tourist visits to destinations across New Zealand. We found that our procedure accurately predicts interactions for both existing nodes and nodes newly added to the network, while being computationally feasible even for very large networks. Overall, our study highlights that by exploiting the properties of a well understood statistical model for complex networks and combining it with standard machine learning techniques, we can simplify the link prediction problem when incorporating multivariate node metadata. Our procedure can be immediately applied to different types of networks, and to a wide variety of data from different systems. As such, both from a network science and data science perspective, our work offers a flexible and generalisable procedure for link prediction.

category: ecology


title: Greenland's thaw pushes the biodiversity crisis

abstract: Anthropogenic greenhouse gas emissions have led to sustained global warming over the last decades1. This is already reshaping the distribution of biodiversity across the world and can lead to the occurrence of large-scale singular events, such as the melting of polar ice sheets2,3. The potential impacts of such a melting event on species persistence across taxonomic groups - in terms of magnitude and geographic extent - remain unexplored. Here we assess impacts on biodiversity of global warming and melting of Greenlands ice sheet on the distribution of 21,146 species of vascular plants and tetrapods across twelve megadiverse countries. We show that high global warming would lead to widespread reductions in species geographic ranges (median range loss, 35-78%), which are magnified (median range loss, 95-99%) with the added contribution of Greenlands melting and its potentially large impact on oceanic circulation and regional climate changes. Our models project a decline in the geographical extent of species hotspots across countries (median reduction, 48-95%) and a substantial alteration of species composition in the near future (mean temporal dissimilarity, 0.26-0.89). These results imply that, in addition to global warming, the influence of Greenlands melting can lead to the collapse of biodiversity across the globe, providing an added domino in its cascading effects.


title: Imprecisely georeferenced specimen data provide unique information on species' distributions and environmental tolerances: Don't let the perfect be the enemy of the good

abstract: Museum and herbarium specimen records are frequently used to assess species conservation status and responses to climate change. Typically, records of occurrence with imprecise geolocality information are discarded because they cannot be matched confidently to environmental conditions, and are thus expected to increase uncertainty in downstream analyses. However, using only those records that can be precisely georeferenced risks undersampling of species environmental and geographic distributions. Using simulated and real species, we compared the effect of discarding versus retaining imprecise records on the accuracy of ecological niche models (ENMs), and estimates of niche breadth and extent of occurrence. Imprecise records were assigned to locations or climate values using a conservative approach. For simulated species, including imprecisely-georeferenced records alongside precisely-georeferenced records improved the accuracy of ENMs projected to the present and the future. Improvements were especially notable for species with <~20 precise occurrences, but accuracy continued to improve and eventually matched the accuracy of ENMs using all records with no georeferencing error. Using only precise records underestimated loss in suitable habitat and overestimated the amount of suitable habitat in both the present and future. Including imprecise records also improved univariate and multivariate estimates of niche breadth, and of species extent of occurrence. An analysis of 44 species in the genus Asclepias (milkweeds) revealed similarly large differences between cases using only precise records and those using precise plus imprecise records. Although the inclusion of imprecisely-georeferenced occurrence records may not always be appropriate, careful consideration must be made regarding the trade-offs between fidelity of the match between occurrences and the environment, versus sample size and how well precisely-geolocated records sample species environmental and geographic distributions. The preponderance of imprecisely georeferences specimens in museums and herbaria could be gainfully employed to address known shortfalls in sampling of species distributions and climatic niche tolerances.


title: Including imprecisely georeferenced specimens improves accuracy of species distribution models and estimates of niche breadth: Don't let the perfect be the enemy of the good


title: A putative de novo evolved gene required for spermatid chromatin condensation in Drosophila melanogaster

abstract:
Comparative genomics has enabled the identification of genes that potentially evolved de novo from non-coding sequences. Many such genes are expressed in male reproductive tissues, but their functions remain poorly understood. To address this, we conducted a functional genetic screen of over 40 putative de novo genes with testis-enriched expression in Drosophila melanogaster and identified one gene, atlas, required for male fertility. Detailed genetic and cytological analyses showed that atlas is required for proper chromatin condensation during the final stages of spermatogenesis. Atlas protein is expressed in spermatid nuclei and facilitates the transition from histone- to protamine-based chromatin packaging. Complementary evolutionary analyses revealed the complex evolutionary history of atlas. The protein-coding portion of the gene likely arose at the base of the Drosophila genus on the X chromosome but was unlikely to be essential, as it was then lost in several independent lineages. Within the last [~]15 million years, however, the gene moved to an autosome, where it fused with a conserved non-coding RNA and evolved a non-redundant role in male fertility. Altogether, this study provides insight into the integration of novel genes into biological processes, the links between genomic innovation and functional evolution, and the genetic control of a fundamental developmental process, gametogenesis.

Author SummaryGenomes are in flux, as genes are constantly added and lost throughout evolution. New genes were once thought to arise almost exclusively via the modification or duplication of existing genes. Recently, however, interest has grown in alternative modes of new gene origination, such as de novo evolution from genetic material that previously did not encode proteins. Many de novo genes are expressed in male reproductive tissues, but their significance for fertility is not well understood. We screened likely de novo genes expressed in the Drosophila testis for reproductive roles and found one gene, atlas, essential for male fertility. We leveraged genetic and cell biological experiments to investigate roles for Atlas protein in reproduction and found that it is required during sperm development for proper packaging of DNA in the sperm nucleus. Evolutionary analyses of this gene revealed a complicated history, including loss in some lineages, movement between chromosomes, and fusion with a non-protein-coding gene. Studying both the functions and evolutionary histories of new proteins illustrates how they might evolve critical roles in biological processes despite their relative novelty. Furthermore, the study of atlas identifies an essential genetic player in the fly testis, an important model system for understanding how gametes are produced.

category: genetics


title: Evolutionary analysis of DNA methyltransferases in microeukaryotes: Insights from the model diatom Phaeodactylum tricornutum

abstract: Cytosine DNA methylation is an important epigenetic mark in eukaryotes that is involved in the transcriptional control of mainly transposable elements in mammals, plants, and fungi. Eukaryotes encode a diverse set of DNA methyltransferases that were iteratively acquired and lost during evolution. The Stramenopiles-Alveolate-Rhizaria (SAR) lineages are a major group of ecologically important marine microeukaryotes that include the main phytoplankton classes such as diatoms and dinoflagellates. However, little is known about the diversity of DNA methyltransferases and their role in the deposition and maintenance of DNA methylation in microalgae. We performed a phylogenetic analysis of DNA methyltransferase families found in marine microeukaryotes and show that they encode divergent DNMT3, DNMT4, DNMT5 and DNMT6 enzymes family revisiting previously established phylogenies. Furthermore, we reveal a novel group of DNMTs with three classes of enzymes within the DNMT5 family. Using a CRISPR/Cas9 strategy we demonstrate that the loss of the DNMT5 gene correlates with a global depletion of DNA methylation and overexpression of transposable elements in the model diatom Phaeodactylum tricornutum. The study provides a pioneering view of the structure and function of a DNMT family in the SAR supergroup.


title: Elucidation of Structural Mechanism of ATP Inhibition at the AAA1 Subunit of Cytoplasmic Dynein 1 Using a Chemical "Toolkit"

abstract: Dynein is a cytoskeletal motor protein that carries organelles via retrograde transport in eukaryotic cells. The motor protein belongs to the ATPase family of proteins associated with diverse cellular activities and plays a critical role in transporting cargoes to the minus end of the microtubules. The motor domain of dynein possesses a hexameric head, where ATP hydrolysis occurs. The AAA1 binding site is the leading ATP hydrolytic site, followed by the AAA3 subsite. Small-molecule ATP competitive inhibitors of dynein are thought to target the AAA1 site. The presented work elucidates the structure-activity relationship of dynapyrazole A and B, ciliobrevin A and D in their various protonated states and their 46 analogs for their binding properties in the nucleotide-binding site of the AAA1 subunit and their effects on the functionally essential subsites of the motor domain of cytoplasmic dynein 1, as there is currently no similar experimental structural data available. Ciliobrevin and its analogs bind to the ATP motifs of the AAA1, namely the Walker-A or P-loop, the Walker-B, and the sensor I and II. Ciliobrevin A shows a better binding affinity to the AAA1 binding site of dynein 1 than its D analog. Although the double bond in ciliobrevin A and D was expected to decrease the ligand potency, they show a better affinity to the AAA1 binding site than dynapyrazole A and B, lacking the bond. Protonation of the nitrogen in ciliobrevin A, D, dynapyrazole A, and B at the N9 site of ciliobrevin, and the N7 of the latter increased their binding affinity. Exploring ciliobrevin A geometrical configuration suggests the E isomer has a superior binding profile over the Z due to binding at the critical ATP motifs. Utilizing the refined structure of the motor domain obtained through protein conformational search in this study exhibits that Arg1852 of the yeast cytoplasmic dynein could involve in the "glutamate switch" mechanism in cytoplasmic dynein 1 in lieu of the conserved Asn in AAA+ protein family, as the guanidine moiety of the Arg engages in an H-bond with the carboxylate moiety of Glu1849.

category: biochemistry


title: Cargo surface fluidity reduces inter-motor interference, promotes load-sharing and enhances run-lengths in an ATP dependent manner

abstract:
In cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of cytoskeletal filaments. How motors that typically mechanically interfere with each other, work as teams is unclear. Here we explored the possibility that purely physical mechanisms may potentially enhance teamwork, both at the single motor and cargo level. To explore these mechanisms, we developed a 3D dynamical simulation of cargo transport along microtubules by teams of canonically non-cooperative kinesin-1 motors. We accounted for cargo membrane fluidity by explicitly simulating the Brownian dynamics of motors on the cargo surface and considered both the load and ATP dependence of single motor functioning. We showed explicitly, for the first time, that surface fluidity leads to the reduction of negative mechanical interference between kinesins, enhancing load sharing thereby decreasing single motor off-rates and increasing processivity. Remarkably, we also showed that, independent of fluidity, increasing numbers of bound motors pull the cargo closer to the microtubule, increasing the on-rates of individual unbound motors, resulting in a cooperative increase in bound motor numbers that depends on 3D cargo geometry. At the cargo level, surface fluidity makes more motors available for binding, though this effect is significant only at low ATP or high motor density. Interestingly, we find that the fluidity induced reduction in mechanical interference dominates over the increased availability of motors for typical physiological and in vitro conditions, this allowing us to reconcile different experimental results in different regimes. Finally, we show that these effects can altogether result in enhanced mechanical efficiency and tunable cargo run-lengths for teams of molecular motors over physiological ranges of fluidity with implications for new experimental validation efforts, transport in vivo, artificial cargo design and multi-motor-driven mechanical processes in general.

Author summaryIn cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of protein filaments. How do intrinsically non-cooperative motors function as teams within cells? In this paper, we show, using computer simulations, that the fluid surfaces of cellular cargo reduce the mechanical interference between motors allowing better load sharing and decreasing their detachment rates, thereby increasing the distance over which they can carry cargo. We additionally found that motors pull cargo closer to the filament increasing the attachment rates of other unbound motors. These effects act synergistically with an increased availability of motors due to fluidity to further increase travel distances. Our simulation model accounted for the dynamics of the motors on the cargo surface and their load and ATP dependent kinetics, allowing us to connect single motor properties to overall transport. Our work on understanding how teamwork arises in mechanically coupled motors sheds new light on cellular processes, reconciles existing observations, encourages new experimental validation efforts and can also suggest new ways of improving mechanical efficiency and transport of artificial cargo powered by motor teams.

category: biophysics


title: Cargo surface fluidity reduces inter-motor mechanical interference, promotes load-sharing and enhances run-lengths in an ATP dependent manner


title: Cargo-mediated mechanisms reduce inter-motor mechanical interference, promote load-sharing and enhance processivity in teams of molecular motors


title: Measuring the metabolic evolution of glioblastoma throughout tumor development, regression, and recurrence with hyperpolarized magnetic resonance

abstract: Rapid diagnosis and therapeutic monitoring of aggressive diseases such as glioblastoma can improve patient survival by providing physicians the time to optimally deliver treatment. This research tested whether metabolic imaging with hyperpolarized MRI could detect changes in tumor progression faster than conventional anatomic MRI in patient-derived glioblastoma murine models. To capture the dynamic nature of cancer metabolism, hyperpolarized MRI, NMR spectroscopy, and immunohistochemistry were performed at several time-points during tumor development, regression, and recurrence. Hyperpolarized MRI detected significant changes of metabolism throughout tumor progression whereas conventional MRI was less sensitive. This was accompanied by aberrations in amino acid and phospholipid lipid metabolism and MCT1 expression. Hyperpolarized MRI can help address clinical challenges such as identifying malignant disease prior to aggressive growth, differentiating pseudoprogression from true progression, and predicting relapse. The individual evolution of these metabolic assays as well as their correlations with one another provides context for further academic research.


title: Using generalized additive models to analyze biomedical non-linear longitudinal data

abstract:
1In biomedical research, the outcome of longitudinal studies has been traditionally analyzed using the repeated measures analysis of variance (rm-ANOVA) or more recently, linear mixed models (LMEMs). Although LMEMs are less restrictive than rm-ANOVA as they can work with unbalanced data and non-constant correlation between observations, both methodologies assume a linear trend in the measured response. It is common in biomedical research that the true trend response is nonlinear and in these cases the linearity assumption of rm-ANOVA and LMEMs can lead to biased estimates and unreliable inference.

In contrast, GAMs relax the linearity assumption of rm-ANOVA and LMEMs and allow the data to determine the fit of the model while also permitting incomplete observations and different correlation structures. Therefore, GAMs present an excellent choice to analyze longitudinal data with non-linear trends in the context of biomedical research. This paper summarizes the limitations of rm-ANOVA and LMEMs and uses simulated data to visually show how both methods produce biased estimates when used on data with non-linear trends. We present the basic theory of GAMs and using reported trends of oxygen saturation in tumors, we simulate example longitudinal data (2 treatment groups, 10 subjects per group, 5 repeated measures for each group) to demonstrate their implementation in R. We also show that GAMs are able to produce estimates with non-linear trends even when incomplete observations exist (with 40% of the simulated observations missing). To make this work reproducible, the code and data used in this paper are available at: https://github.com/aimundo/GAMs-biomedical-research.


title: Mechanical stress in pancreatic cancer: Signaling pathway adaptation activates cytoskeletal remodeling and enhances cell migration

abstract: New treatments for patients with advanced or metastatic pancreatic cancers are urgently needed due to their resistance to all current therapies. Current studies focus on alternative treatment approaches that target or normalize the abnormal microenvironment of pancreatic tumors, which among others, is responsible for elevated mechanical stress in the tumor interior. Nevertheless, the underlying mechanisms by which mechanical stress regulates pancreatic cancer metastatic potential remain elusive. Herein, we used a large-scale proteomic assay to profile mechanical stress-induced signaling cascades that drive the motility of pancreatic cancer cells. Proteomic analysis, together with selective protein inhibition and siRNA treatments, revealed that mechanical stress enhances cell migration through activation of the p38 MAPK/HSP27 and JNK/c-Jun signaling axes, and activation of the actin cytoskeleton remodelers: Rac1, cdc42, and Myosin II. Our results highlight targeting aberrant signaling in cancer cells that are adapted to the mechanical tumor microenvironment as a novel approach to effectively limit pancreatic cancer cell migration.


title: Genetic architecture underlying HPPD-inhibitor resistance in a Nebraska Amaranthus tuberculatus population

abstract:
BACKGROUNDAmaranthus tuberculatus is a primary driver weed species throughout the American Midwest. Inhibitors of 4-hydroxyphenylpyruvate dioxygenase (HPPD) are an important chemistry for weed management in numerous cropping systems. Here, we characterize the genetic architecture underlying the HPPD-inhibitor resistance trait in an A. tuberculatus population (NEB).

RESULTSDose-response studies of an F1 generation identified HPPD-inhibitor resistance as a dominant trait with a resistance/sensitive ratio of 15.0-21.1. Segregation analysis in a pseudo-F2 generation determined the trait is moderately heritable (H2 = 0.556), and complex. Bulk segregant analysis and validation with molecular markers identified two quantitative trait loci (QTL), one on each of Scaffold 4 and 12.

CONCLUSIONSResistance to HPPD-inhibitors is a complex, largely dominant trait within the NEB population. Two large-effect QTL were identified controlling HPPD-inhibitor resistance in A. tuberculatus. This is the first QTL mapping study to characterize herbicide resistance in a weedy species.

category: plant biology


title: Bamboos flower after the return of an appropriate sun-moon phasing

abstract:
All Asian woody bamboo species of economic importance are semelparous. They remain vegetative during time intervals that are specific to each species and range from three to 120 years, with notable concentrations around a series of values (3, 7-8, 14-17, 29-36, 42-48, 61-64, and 120 years). Then, they flower gregariously within a short period. Entire forests temporarily disappear during these periods, and the dates of these dramatic events have been recorded over the last 200 years.

While searching for a correlated environmental cue, I have found that the concentrations of flowering cycles were highly correlated with the series of successive returns of almost the same sun-moon phasing as at seedling emergence. On basis of knowledge on plant photoperiod sensitivity, I hypothesize that bamboo plants i) run a lunar cellular clock that is set at the full moon, ii) retain in their cellular memory the exact sun-moon phasing of the year of their emergence as seedlings, and iii) inhibit flowering until the occurrence of a unique, species-specific sun-moon phasing that is shifted by a precise amount from the sun-moon phasing at their emergence. Recent evidence of plant responses to lunar cycles supports this hypothesis, for which experimental evidence is now anticipated.

HighlightThe long-standing enigma of the triggering of the gregarious flowering of bamboos is possibly solved. Flowering would be inhibited until the occurrence of the species-specific sun-moon phasing.


title: Bamboos flower after the return of almost the same sun-moon phasing as at seedling emergence


title: Distinct neural dynamics underlie the encoding of visual speed in stationary and running mice

abstract: Sensory experiences are often driven by an animals self-motion and locomotion is known to modulate neural responses in the mouse visual system. This modulation is hypothesised to improve the processing of behaviourally relevant visual inputs, which may change rapidly during locomotion. However, little is known about how locomotion modulates the temporal dynamics (time courses) of visually-evoked neural responses. Here, we analysed the temporal dynamics of single neuron and population responses to dot field stimuli moving at a range of visual speeds using the Visual Coding dataset from the Allen Institute for Brain Science1. Single neuron responses had diverse temporal dynamics that varied between stationary and running sessions. Increased dynamic range and more reliable responses in running sessions enabled faster, stronger and more persistent encoding of visual speed. Population activity reflected the temporal dynamics of single neuron responses, including their modulation by locomotor state - neural trajectories of population activity made more direct transitions between baseline and stimulus steady states in running sessions. The structure of population coding also changed with locomotor state - population activity prioritised the encoding of visual speed in running, but not stationary sessions. Our results reveal a profound influence of locomotion on the temporal dynamics of neural responses. We demonstrate that during locomotion, mouse visual areas prioritise the encoding of potentially fast-changing, behaviourally relevant visual features.


title: Profiling Human CMV-specific T cell responses reveals novel immunogenic ORFs

abstract:
Despite the prevalence and medical significance of human cytomegalovirus (HCMV) infections, a systematic analysis of the targets of T cell recognition in humans that spans the entire genome and includes recently described potential novel ORFs is not available. Here, we screened a library of epitopes predicted to bind HLA class II that spans over 350 different HCMV ORFs and includes [~]150 previously described and [~]200 recently described potential novel ORFs using an ex vivo IFN{gamma} fluorospot assay. We identified 235 unique HCMV specific epitopes derived from 100 ORFs, some previously described as immunodominant and others that were not previously described to be immunogenic. Of those, 41 belong to the set of recently reported novel ORFs, thus providing evidence that at least some of these are actually expressed in vivo in humans. These data reveal that the breadth of the human T cell response to HCMV is much greater than previously thought. The ORFs and epitopes identified will help elucidate how T cell immunity relates to HCMV pathogenesis and instruct ongoing HCMV vaccine research.

ImportanceTo understand the crucial role of adaptive immunity in controlling cytomegalovirus infection and disease, we systematically analyzed the CMV ORFeome to identify new CMV epitopes targeted primarily by CD4 T cells in humans. Our study identified >200 new T cell epitopes derived from both canonical and novel ORFs, highlighting the substantial breadth of anti-CMV T cell response and providing new targets for vaccine design.

category: immunology


title: MKP-1 modulates Ubiquitination/Phosphorylation of TLR signaling

abstract: Ubiquitination and phosphorylation are reversible post-translational protein modifications regulating physiological and pathological processes. MAPK phosphatase (MKP)-1 regulates innate and adaptive immunity. The multifaceted roles of MKP-1 were attributed to dephosphorylation of p38 and JNK mitogen activated kinases (MAPKs). We show that the lack of MKP-1 modulates the landscape of ubiquitin ligases and deubiquitinase enzymes (DUBs). MKP-1 deficient mice showed an aberrant regulation of several DUBs and increased expression of proteins and genes involved in IL-1/TLR signaling upstream of MAPK, including IL-1R1, IRAK1, TRAF6, phosphorylated TAK1 and an increased K63-polyubiquitination on TRAF6. Increased K63-polyubiquitination on TRAF6 was associated with an enhanced phosphorylated form of A20. Among abundant DUBs, Ubiquitin-specific-protease-13 (USP13), which cleaves polyubiquitin- chains on client proteins, was substantially enhanced in murine MKP-1 deficient BMDMs. An inhibitor of USP13 decreased the K63-polyubiquitination on TRAF6, TAK1-phosphorylation, IL-1{beta} and TNF- induction in response to LPS in BMDMs. Our data show for the first time that MKP-1 modulates the ligase activity of TRAF6 through modulation of specific DUBs.


title: Genomic consequences of colonisation, migration and genetic drift in barn owl insular populations of the eastern Mediterranean

abstract: The study of insular populations was key in the development of evolutionary theory. The successful colonisation of an island depends on the geographic context, and specific characteristics of the organism and the island, but also on stochastic processes. As a result, apparently identical islands may harbour populations with contrasting histories. Here, we use whole genome sequences of 65 barn owls to investigate the patterns of inbreeding and genetic diversity of insular populations in the eastern Mediterranean Sea. We focus on Crete and Cyprus, islands with similar size, climate and distance to mainland, that provide natural replicates for a comparative analysis of the impacts of microevolutionary processes on isolated populations. We show that barn owl populations from each island have a separate origin, Crete being genetically more similar to other Greek islands and mainland Greece, and Cyprus more similar to the Levant. Further, our data show that their respective demographic histories following colonisation were also distinct. On the one hand, Crete harbours a small population and maintains very low levels of gene flow with neighbouring populations. This has resulted in low genetic diversity, strong genetic drift, increased relatedness in the population and remote inbreeding. Cyprus, on the other hand, appears to maintain enough gene flow with the mainland to avoid such an outcome. Our work provides a comparative population genomic analysis of the effects of neutral processes on a classical island-mainland model system. It provides empirical evidence for the role of stochastic processes in determining the fate of diverging isolated populations.

category: evolutionary biology


title: A Novel Local Explainability Approach for Spectral Insight into Raw EEG-Based Deep Learning Classifiers

abstract: The frequency domain of electroencephalography (EEG) data has developed as a particularly important area of EEG analysis. EEG spectra have been analyzed with explainable machine learning and deep learning methods. However, as deep learning has developed, most studies use raw EEG data, which is not well-suited for traditional explainability methods. Several studies have introduced methods for spectral insight into classifiers trained on raw EEG data. These studies have provided global insight into the frequency bands that are generally important to a classifier but do not provide local insight into the frequency bands important for the classification of individual samples. This local explainability could be particularly helpful for EEG analysis domains like sleep stage classification that feature multiple evolving states. We present a novel local spectral explainability approach and use it to explain a convolutional neural network trained for automated sleep stage classification. We use our approach to show how the relative importance of different frequency bands varies over time and even within the same sleep stages. Furthermore, to better understand how our approach compares to existing methods, we compare a global estimate of spectral importance generated from our local results with an existing global spectral importance approach. We find that the {delta} band is most important for most sleep stages, though {beta} is most important for the non-rapid eye movement 2 (NREM2) sleep stage. Additionally, {theta} is particularly important for identifying Awake and NREM1 samples. Our study represents the first approach developed for local spectral insight into deep learning classifiers trained on raw EEG time series.


title: A comprehensive in silico investigation into the nsSNPs of Drd2 gene predicts significant functional consequences in dopamine signaling and pharmacotherapy

abstract: DRD2 is a neuronal cell surface protein involved in brain development and function. Variations in the Drd2 gene have clinical significance since DRD2 is a pharmacotherapeutic target for treating psychiatric disorders like ADHD and schizophrenia. Despite numerous studies on the disease association of single nucleotide polymorphisms (SNPs) in the intronic regions, investigation into the coding regions is surprisingly limited. In this study, we aimed at identifying potential functionally and pharmaco-therapeutically deleterious non-synonymous SNPs of Drd2. A wide array of bioinformatics tools was used to evaluate the impact of nsSNPs on protein structure and functionality. Out of 260 nsSNPs retrieved from the dbSNP database, initially 9 were predicted as deleterious by 15 tools. Upon further assessment of their domain association, conservation profile, homology models and inter-atomic interaction, the mutant F389V was considered as the most impactful. In-depth analysis of F389V through Molecular Docking and Dynamics Simulation revealed a decline in affinity for its native agonist dopamine and an increase in affinity for the antipsychotic drug risperidone. Remarkable alterations in binding interactions and stability of the protein-ligand complex in simulated physiological conditions were also noted. These findings will improve our understanding of the consequence of nsSNPs in disease-susceptibility and therapeutic efficacy.


title: Maintaining and escaping feedback control in hierarchically organised tissue: a case study of the intestinal epithelium

abstract: The intestinal epithelium is one of the fastest renewing tissues in mammals. It shows a hierarchical organisation, where intestinal stem cells at the base of crypts give rise to rapidly dividing transit amplifying cells that in turn renew the pool of short-lived differentiated cells. Upon injury and stem-cell loss, cells can also dedifferentiate. Tissue homeostasis require a tightly regulated balance of differentiation and stem cell proliferation, and failure can lead to tissue extinction or to unbounded growth and cancerous lesions. Here, we present a two-compartment mathematical model of intestinal epithelium population dynamics that includes a known feedback inhibition of stem cell differentiation by differentiated cells. The model shows that feedback regulation stabilises the number of differentiated cells as these become invariant to changes in their apoptosis rate. Stability of the system is largely independent of feedback strength and shape, but specific thresholds exist after unbounded growth occurs. When dedifferentiation is added to the model, we find that the system can recover more gracefully after certain external perturbations. However, dedifferentiation makes the system more prone to loosing homoeostasis. Taken together, our mathematical model shows how a feedback-controlled hierarchical tissue can maintain homeostasis and can be robust to many external perturbations.


title: Hybridization potential between Amaranthus tuberculatus and Amaranthus albus

abstract: The genus Amaranthus is composed of numerous annual herbs, several of which are primary driver weeds within annual production agricultural systems. In particular, Amaranthus tuberculatus, a dioecious species, is noteworthy for rapid growth rates, high fecundity, and an expanding geographic distribution. Interspecific hybridization within and between the subgenera Amaranthus and Acnidia is reported both in controlled environment and field studies, however a gap in knowledge exists with the subgenus Albersia. Interspecific hybridization may contribute to genetic diversity, and may contribute to the current range expansion of A. tuberculatus. Recently, a herbicide resistance survey of A. tuberculatus across five Midwestern states reported alleles of PPX2 similar to sequences of Amaranthus albus, a monoecious species. Here, we seek to generate empirical data for the hybridization potential of A. albus and A. tuberculatus through replicated, controlled crosses in a greenhouse. Of 65,000 progeny screened from A. albus grown with A. tuberculatus males, three were confirmed as hybrids. Hybrids were dioecious, possessed phenotypic traits of both species, and had limited to no fertility. DNA content analysis of backcross progeny suggested a polyploid state may be required for hybrid formation. Screening of 120 progeny of A. tuberculatus females grown with A. albus identified no hybrids, though a skew to female progeny was observed. The female skew may be due to apomixis or auto-pollination, the spontaneous generation of male flowers on otherwise female plants. Our results indicate that introgression between A. albus and A. tuberculatus will occur less frequently than what has often been reported from hybridization studies with different pairs of Amaranthus species.


title: Unraveling the functions of uncharacterized transcription factors in Escherichia coli using ChIP-exo

abstract: Bacteria regulate gene expression to adapt to changing environments through transcriptional regulatory networks (TRNs). Although extensively studied, no TRN is fully characterized since the identity and activity of all the transcriptional regulators that comprise a TRN are not known. Here, we experimentally evaluate 40 uncharacterized proteins in Escherichia coli K-12 MG1655, which were computationally predicted to be transcription factors (TFs). First, we used a multiplexed ChIP-exo assay to characterize genome-wide binding sites for these candidate TFs; 34 of them were found to be DNA-binding protein. We then compared the relative location between binding sites and RNA polymerase (RNAP). We found 48% (283/588) overlap between the TFs and RNAP. Finally, we used these data to infer potential functions for 10 of the 34 TFs with validated DNA binding sites and consensus binding motifs. These TFs were found to have various roles in regulating primary cellular processes in E. coli. Taken together, this study: (1) significantly expands the number of confirmed TFs, close to the estimated total of about 280 TFs; (2) predicts the putative functions of the newly discovered TFs, and (3) confirms the functions of representative TFs through mutant phenotypes.

category: systems biology


title: Spatial neglect in the digital age - Influence of presentation format on patients' test behavior

abstract: Computerization of diagnostic neglect tests can deepen our knowledge of neglect specific abnormalities, by effortlessly providing additional behavioral markers that are hardly extractable from existing paper-and-pencil versions. However, so far it is not known whether the digitization and/or a change in size format impact neglect patients search behavior and test scores and thus require adjustments of cut-off criteria. We compared the Center of cancellation (CoC) measure of right hemisphere stroke patients with spatial neglect in two cancellation tasks across different modalities (paper-and-pencil vs. digital) and display sizes (small, medium, large). We found that the CoC measure did neither vary considerably between paper-and-pencil versus digital versions, nor between different digital size formats. The CoC derived from cancellation tasks thus seems robust to test digitization. A further aim of the present study was to evaluate three additional parameters of search behavior which became available through digitization. We observed slower search behavior, increased distance between two consecutively identified items, and signs of a more strategic search for neglect patients than control patients without neglect. Machine learning classifications indicated that - beyond the CoC measure - the latter three variables can help to differentiate stroke patients with spatial neglect from thosewithout.


title: Essential role of hyperacetylated microtubules in innate immunity escape orchestrated by the EBV-encoded BHRF1 protein

abstract: Innate immunity constitutes the first line of defense against viruses, in which mitochondria play an important role in the induction of the interferon (IFN) response. BHRF1, a multifunctional viral protein expressed during Epstein-Barr virus reactivation, modulates mitochondrial dynamics and disrupts the IFN signaling pathway. Mitochondria are mobile organelles that move through the cytoplasm thanks to the cytoskeleton and in particular the microtubule (MT) network. MTs undergo various post-translational modifications, among them tubulin acetylation. In this study, we demonstrated that BHRF1 induces MT hyperacetylation to escape innate immunity. Indeed, the expression of BHRF1 induces the clustering of shortened mitochondria next to the nucleus. This "mito-aggresome" is organized around the centrosome and its formation is MT-dependent. We also observed that the -tubulin acetyltransferase ATAT1 interacts with BHRF1. Using ATAT1 knockdown or a non-acetylatable -tubulin mutant, we demonstrated that this hyperacetylation is necessary for the mito-aggresome formation. Similar results were observed during EBV reactivation. We investigated the mechanism leading to the clustering of mitochondria, and we identified dyneins as motors that are required for mitochondrial clustering. Finally, we demonstrated that BHRF1 needs MT hyperacetylation to block the induction of the IFN response. Moreover, the loss of MT hyperacetylation blocks the localization of autophagosomes close to the mito-aggresome, impeding BHRF1 to initiate mitophagy, which is essential to inhibiting the signaling pathway. Therefore, our results reveal the role of the MT network, and its acetylation level, in the induction of a pro-viral mitophagy.


title: Mechanisms for Electron Uptake by Methanosarcina acetivorans During Direct Interspecies Electron Transfer

abstract:
Direct interspecies electron transfer (DIET) between bacteria and methanogenic archaea appears to be an important syntrophy in both natural and engineered methanogenic environments. However, the electrical connections on the outer surface of methanogens and the subsequent processing of electrons for carbon dioxide reduction to methane are poorly understood. Here we report that the genetically tractable methanogen Methanosarcina acetivorans can grow via DIET in co-culture with Geobacter metallireducens serving as the electron-donating partner. Comparison of gene expression patterns in M. acetivorans grown in co-culture versus pure culture growth on acetate revealed that transcripts for the outer-surface, multi-heme, c-type cytochrome MmcA were higher during DIET-based growth. Deletion of mmcA inhibited DIET. The high aromatic amino acid content of M. acetivorans archaellins suggests that they might assemble into electrically conductive archaella. A mutant that could not express archaella was deficient in DIET. However, this mutant grew in DIET-based co-culture as well as the archaella-expressing parental strain in the presence of granular activated carbon, which was previously shown to serve as a substitute for electrically conductive pili as a conduit for long-range interspecies electron transfer in other DIET-based co-cultures. Transcriptomic data suggesting that the membrane-bound Rnf, Fpo, and HdrED complexes also play a role in DIET were incorporated into a charge-balanced model illustrating how electrons entering the cell through MmcA can yield energy to support growth from carbon dioxide reduction. The results are the first genetics-based functional demonstration of likely outer-surface electrical contacts for DIET in a methanogen.

ImportanceThe conversion of organic matter to methane plays an important role in the global carbon cycle and is an effective strategy for converting wastes to a useful biofuel. The reduction of carbon dioxide to methane accounts for approximately a third of the methane produced in anaerobic soils and sediments as well as waste digesters. Potential electron donors for carbon dioxide reduction are H2 or electrons derived from direct interspecies electron transfer (DIET) between bacteria and methanogens. Elucidating the relative importance of these electron donors has been difficult due to a lack of information on the electrical connects on the outer surface of methanogens and how they process the electrons received from DIET. Transcriptomic patterns and gene deletion phenotypes reported here provide insight into how a group of Methanosarcina that play an important role in methane production in soils and sediments participate in DIET.


title: Genetically engineered insects with sex-selection and genetic incompatibility enable population suppression

abstract: Engineered Genetic Incompatibility (EGI) is a method to create species-like barriers to sexual reproduction. It has applications in pest control that mimic Sterile Insect Technique when only EGI males are released. This can be facilitated by introducing conditional female-lethality to EGI strains to generate a sex-sorting incompatible male system (SSIMS). Here we demonstrate a proof of concept by combining tetracycline-controlled female lethality constructs with a pyramus-targeting EGI line in the model insect Drosophila melanogaster. We show that both functions (incompatibility and sex-sorting) are robustly maintained in the SSIMS line and that this approach is effective for population suppression in cage experiments. Further we show that SSIMS males remain competitive with wild-type males for reproduction with wild-type females, including at the level of sperm competition.

category: bioengineering


title: An efficient GUI-based clustering software for simulation and Bayesian cluster analysis of single-molecule localization microscopy data

abstract:
Ligand binding of membrane proteins triggers many important cellular signaling events by the lateral aggregation of ligand-bound and other membrane proteins in the plane of the plasma membrane. This local clustering can lead to the co-enrichment of molecules that create an intracellular signal or bring sufficient amounts of activity together to shift an existing equilibrium towards the execution of a signaling event. In this way, clustering can serve as a cellular switch. The underlying uneven distribution and local enrichment of the signaling cluster's constituting membrane proteins can be used as a functional readout. This information is obtained by combining single-molecule fluorescence microscopy with cluster algorithms that can reliably and reproducibly distinguish clusters from fluctuations in the background noise to generate quantitative data on this complex process.

Cluster analysis of single-molecule fluorescence microscopy data has emerged as a proliferative field, and several algorithms and software solutions have been put forward. However, in most cases, such cluster algorithms require multiple analysis parameters to be defined by the user, which may lead to biased results. Furthermore, most cluster algorithms neglect the individual localization precision connected to every localized molecule, leading to imprecise results. Bayesian cluster analysis has been put forward to overcome these problems, but so far, it has entailed high computational cost, increasing runtime drastically. Finally, most software is challenging to use as they require advanced technical knowledge to operate.

Here we combined three advanced cluster algorithms with the Bayesian approach and parallelization in a user-friendly GUI and achieved up to an order of magnitude faster processing than for previous approaches. Our work will simplify access to a well-controlled analysis of clustering data generated by SMLM and significantly accelerate data processing. The inclusion of a simulation mode aids in the design of well-controlled experimental assays.


title: Deep integrative models for large-scale human genomics

abstract: Polygenic risk scores (PRSs) are expected to play a critical role in achieving precision medicine. Currently, PRS predictors are generally based on linear models using summary statistics, and more recently individual-level data. However, these predictors mainly capture additive relationships and are limited in data modalities they can use. Here, we developed a deep learning framework (EIR) for PRS prediction which includes a model, genome-local-net (GLN), specifically designed for large scale genomics data. The framework supports multi-task (MT) learning, automatic integration of other clinical and biochemical data, and model explainability. When applied to individual level data in the UK Biobank, we found that GLN outperformed LASSO for a wide range of diseases and in particularly autoimmune diseases. Furthermore, we show that this was likely due to modelling epistasis, and we showcase this by identifying widespread epistasis for Type 1 Diabetes. Furthermore, we trained PRS by integrating genotype, blood, urine and anthropometrics and found that this improved performance for 93% of 290 diseases and disorders considered. Finally, we found that including genotype data provided better calibrated PRS models compared to using measurements alone. EIR is available at https://github.com/arnor-sigurdsson/EIR.


title: Prediction and Characterization of Disorder-Order Transition Regions in Proteins by Deep Learning

abstract:
The biological functions of proteins are traditionally thought to depend on well-defined three-dimensional structures, but many experimental studies have shown that disordered regions lacking fixed three-dimensional structures also have crucial biological roles. In some of these regions, disorder-order transitions are also involved in various biological processes, such as protein-protein interaction and ligand binding. Therefore, it is crucial to study disordered regions and structural transitions for further understanding of protein functions and folding. Owing to the costs and time requirements of experimental identification of natively disordered or transitional regions, the development of effective computational methods is a key research goal. In this study, we used overall residue dependencies and deep representation learning for prediction and reused the obtained disordered regions for the prediction of disorder-order transitions. Two similar and related prediction tasks were combined. Firstly, we developed a novel deep learning method, Res-BiLstm, for residue-wise disordered region prediction. Our method outperformed other predictors with respect to almost all criteria, as evaluated using an independent test set. For disorder-order transition prediction, we proposed a transfer learning method, Res-BiLstm-NN, with an acceptable but unbalanced performance, yielding reasonable results. To grasp underlining biophysical principles of disorder-order transitions, we performed qualitative analyses on the obtained results and discovered that most transitions have strong disordered or ordered preferences, and more transitions are consistent with the ordered state than the disordered state, different from conventional wisdom. To the best of our knowledge, this is the first sizable-scale study of transition prediction.

Availabilityhttps://github.com/Yanzziang/Transition_Disorder_Prediction

Contactkengo@ecei.tohoku.ac.jp


title: Allele-specific epigenetic activity in prostate cancer and normal prostate tissue implicates prostate cancer risk mechanisms

abstract:
BackgroundGenome-wide association studies of prostate cancer have identified >250 significant risk loci, but the causal variants and mechanisms for these loci remain largely unknown. Here, we sought to identify and characterize risk harboring regulatory elements by integrating epigenomes from primary prostate tumor and normal tissues of 27 patients across the H3K27ac, H3K4me3, and H3K4me2 histone marks and FOXA1 and HOXB13 transcription factors.

ResultsWe identified 7,371 peaks with significant allele-specificity (asQTL peaks). Showcasing their relevance to prostate cancer risk, H3K27ac T-asQTL peaks were the single annotation most enriched for prostate cancer GWAS heritability (40x), significantly higher than corresponding non-asQTL H3K27ac peaks (14x) or coding regions (14x). Surprisingly, fine-mapped GWAS risk variants were most significantly enriched for asQTL peaks observed in tumors, including asQTL peaks that were differentially imbalanced with respect to tumor-normal states. These data pinpointed putative causal regulatory elements at 20 GWAS loci, of which 11 were detected only in the tumor samples. More broadly, tumor-specific asQTLs were enriched for expression QTLs in benign tissues as well as accessible regions found in stem cells, supporting a hypothesis where some germline variants become reactivated during/after transformation and can be captured by epigenomic profiling of the tumor.

ConclusionOur study demonstrates the power of allele-specificity in chromatin signals to uncover GWAS mechanisms, highlights the relevance of tumor-specific regulation in the context of cancer risk, and prioritizes multiple loci for experimental follow-up.


title: Does time matter in phylogeny? A perspective from the fossil record

abstract: The role of time (i.e. taxa ages) in phylogeny has been a source of intense debate within palaeontology for decades and has not yet been resolved fully. The fossilised birth-death range process is a model that explicitly accounts for information about species through time. It presents a fresh opportunity to examine the role of stratigraphic data in phylogenetic inference of fossil taxa. Here, we apply this model in a Bayesian framework to an exemplar dataset of well-dated conodonts from the Late Devonian. We compare the results to those obtained using traditional unconstrained tree inference. We show that the combined analysis of morphology and stratigraphic data under the FBD range process reduces overall phylogenetic uncertainty, compared to unconstrained tree inference. We find that previous phylogenetic hypotheses based on parsimony and stratophenetics are closer to trees generated under the FBD range process. However, the results also highlight that irrespective of the inclusion of age data, a large amount of topological uncertainty will remain. Bayesian inference provides the most intuitive way to represent the uncertainty inherent in fossil datasets and new flexible models increase opportunities to refine hypotheses in palaeobiology.

category: paleontology


title: Cerebral hemodynamics: a mathematical model including autoregulation, baroreflex and extracranial peripheral circulation

abstract: Cerebral autoregulation, the physiological capability to regulate cerebral blood flow, may be assisted by short-term mean arterial pressure control via baroreflex, which, among several effects, modulates total peripheral resistance. It is unclear, however, whether the resistance of the head and neck vasculatures is also affected by baroreflex and whether these extracranial vessels assist autoregulation. Since sensing technologies such as functional Near-Infrared Spectroscopy and noninvasive intracranial pressure monitoring by strain gauge may be influenced by superficial tissue, it is clinically relevant to understand the relations between intracranial and extracranial hemodynamics. Therefore, we created an autoregulation model consisting of arteries and arterioles regulated by the intralumial pressure and microcirculation regulated by local blood flow. As the first critical step to quantify the signal deterioration introduced by the extracranial circulation on superficial sensors, the extracranial peripheral circulation of the head and neck and baroreflex regulation of the peripheral vasculature and of heart rate were also included. During simulations of a bout of acute hypotension, the model predicts a rapid return of cerebral blood flow to baseline levels and a prolonged suppression of the blood flow to the external carotid vasculature, in accordance with experimental evidence. The inclusion of peripheral control via baroreflex at the external carotid vasculature did not assist cerebral autoregulation, thus we raise the hypothesis that baroreflex may act on the head and neck vasculatures but this action has negligible effects on regulation of cerebral blood flow. When autoregulation is impaired, results suggest that the blood flow of the brain and of the head and neck present similar dynamics, while they are weakly coupled when autoregulation is intact. The model also provides a mechanistic explanation of the protection brought by cerebral autoregulation to the microvasculature and to the brain parenchyma. Our model forms the foundation for predicting the interference introduced by the superficial tissue to nonivasive sensors.

category: physiology


title: Salivary oxytocin co-varies with parturition and nursing behavior in domestic pigs (Sus scrofa domesticus)

abstract: Domestic pigs produce twice as many offspring as wild boars, but little is known about the effects of selection pressures for increased productivity on pig behavior and welfare. From an evolutionary perspective, producing larger litters is expected to increase parent-offspring conflict, which may help to explain why piglets from larger litters are more likely to die by starvation or infant-crushing. Our goals were to identify behavioral and physiological correlates of variation in maternal care that may be useful as selection criteria in breeding programs to improve pig welfare. We observed eleven sows regularly during their lactational period and recorded their hourly postural changes and the proportion of time that piglets had contact with teats (nursing contact) or any physical contact with the sow (social contact). As a potential physiological indicator of maternal care, we measured oxytocin concentrations in 119 saliva samples from sows following observations. Samples were extracted and measured in an Enzyme Immunoassay. As a biological validation, we measured changes in salivary oxytocin during parturition in an additional eleven sows. Laboratory validations confirmed that the assay is suitable for measuring salivary oxytocin in pigs, and oxytocin increased almost three-fold during parturition. Sows nursing contact was positively correlated with social contact and negatively correlated with postural changes. Sow oxytocin concentrations were predicted by their nursing contact, but not by their overall social contact with piglets. We compare our results with current evidence regarding best practice methods for salivary oxytocin measurements and discuss the potential to use indicators of maternal care as selection criteria to improve pig welfare.


title: Ectopic expression of lipid homeostasis genes in rare cells of the teleost pituitary gland

abstract: Directing both organismal homeostasis and physiological adaptation, the pituitary is a key endocrine gland in all vertebrates. It communicates the needs of the organism to different organs by secreting hormones into the bloodstream. Here, we have used the model fish medaka to investigate the developmental dynamics in the pituitary using a comprehensive RNA-seq time series. By linking developmental expression trends to single-cell RNA-seq profiles, we show how the transcriptional activities of cell types change during sexual maturation. One of the most prominent changes is the decline of the non-endocrine folliculo-stellate cell populations, and especially of rare cells expressing genes encoding secreted lipid transport proteins. As these genes are typically associated with the liver, this reveals the existence of unexpected connections between endocrine communication, lipid homeostasis, and sexual maturation.


title: Integrative transcriptomics reveals ectopic lipid homeostasis mechanisms in non-endocrine cells of the teleost pituitary


title: INDEHISCENT regulates explosive seed dispersal

abstract: How traits evolve to produce novelty or stasis is an open question in biology. We investigate this question in Cardamine hirsuta, a relative of Arabidopsis thaliana that employs explosive fracture to disperse its seeds. This trait evolved through key morphomechanical innovations that distinguish the otherwise very similar, dehiscent fruit of these two species. Using CRISPR/Cas9, we show that dehiscence zone formation is absolutely required for explosive fracture in C. hirsuta, and is controlled by the bHLH transcription factor INDEHISCENT (IND). Using mutant screens, we identified the MADS-box transcription factor FRUITFULL (FUL) as a negative regulator of IND in C. hirsuta. Although FUL function is conserved in C. hirsuta, the consequences of IND mis-expression differ in ful mutants of C. hirsuta versus A. thaliana. In ful mutants of both species, valve tissue is replaced by dehiscence zone tissue, which comprises two distinct cell types: lignified layer and separation layer cells. While A. thaliana ful mutants develop stunted fruit with ectopic lignified layer cells, C. hirsuta ful mutants have elongated fruit with ectopic separation layer cells. We show that IND dose determines the proportion of these two cell types in ectopic dehiscence zones. We also show that the extent of ectopic lignification caused by IND mis-expression determines fruit length. Our findings indicate developmental system drift in the conserved gene network patterning dehiscent fruit in two related Brassicaceae species.


title: Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies

abstract: When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here we developed a comprehensive metabolic model of the yeast cell, based on its full metabolic reaction network extended with protein synthesis and degradation reactions (16304 reactions in total). The model predicts metabolic fluxes and corresponding protein expression by constraining compartment-specific protein pools and maximising growth rate. Comparing model predictions with quantitative experimental data revealed that under glucose limitation, a mitochondrial constraint limits growth at the onset of ethanol formation - known as the Crabtree effect. Under sugar excess, however, a constraint on total cytosolic volume dictates overflow metabolism. Our comprehensive model thus identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimization, providing a framework to understand metabolic adaptation in eukaryal cells.


title: Transcranial stimulation of alpha oscillations upregulates the default mode network

abstract:
The default mode network (DMN) is the most prominent intrinsic connectivity network, serving as a key architecture of the brains functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly, alpha (8-12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition (HD) alpha-frequency transcranial alternating current stimulation (-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous EEG-fMRI, we demonstrated that -tACS (vs. sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can upregulate the DMN further highlights an effective non-invasive intervention to normalize DMN functioning in various disorders.

Significance StatementIn the brains functional organization, the default mode network (DMN) represents a key architecture, whose dysregulation is involved in a host of major neuropsychiatric disorders. However, insights into the regulation of the DMN remain scarce. Through neural synchrony, the alpha-frequency oscillation represents another key underpinning of the brains organization and is thought to share an inherent interdependence with the DMN. Here, we demonstrated that transcranial alternating current stimulation of alpha oscillations (-tACS) not only augmented alpha activity but also strengthened connectivity of the DMN, with the former serving as a mediator of the latter. These findings reveal that alpha oscillations can support DMN functioning. In addition, they identify an effective non-invasive approach to regulate the DMN via -tACS.


title: The incentive circuit: memory dynamics in the mushroom body of Drosophila melanogaster

abstract: Insects adapt their response to stimuli, such as odours, according to their pairing with positive or negative reinforcements, such as sugar or shock. Recent electrophysiological and imaging findings in Drosophila melanogaster allow detailed examination of the neural mechanisms supporting the acquisition, forgetting and assimilation of memories. We propose that this data can be explained by the combination of a dopaminergic plasticity rule that supports a variety of synaptic strength change phenomena, and a circuit structure (derived from neuroanatomy) between dopaminergic and output neurons that creates different roles for specific neurons. Computational modelling shows that this circuit allows for rapid memory acquisition, transfer from short-term to long-term, and exploration/exploitation trade-off. The model can reproduce the observed changes in the activity of each of the identified neurons in conditioning paradigms and can be used for flexible behavioural control.


title: Effect of levodopa on human brain connectome in Parkinsons disease

abstract:
ObjectiveLevodopa-based drugs are widely used for mitigating the complications induced by PD. Despite the positive effects, several issues regarding the way that levodopa changes brain activities have remained unclear.

MethodsA combined strategy using EEG data and graph theory was used for investigating how levodopa changed connectome and processing hubs of the brain during resting-state. Obtained results were subjected to ANOVA test and multiple-comparison post-hoc correction procedure.

ResultsResults showed that graph topology of PD patients was not significantly different with the healthy group during eyes-closed condition while in eyes-open condition statistical significant differences were found. The main effect of levodopa medication was observed for gamma-band activity of the brain in which levodopa changed the brain connectome toward a star-like topology. Considering the beta subband of EEG data, graph leaf number increased following levodopa medication in PD patients. Enhanced brain connectivity in gamma band and reduced beta band connections in basal ganglia were also observed after levodopa medication. Furthermore, source localization using dipole fitting showed that levodopa prescription suppressed the activity of collateral trigone.

ConclusionOur combined EEG and graph analysis showed that levodopa medication changed the brain connectome, especially in the high-frequency range of EEG (beta and gamma).

HighlightsO_LINo differences were found between graph features between ON and OFF PD cases in eyes-closed.
C_LIO_LILevodopa enhanced connectivity in gamma band in PD patients.
C_LIO_LILevodopa inhibited brain connectivity in beta band.
C_LI


title: High-affinity, neutralizing antibodies to SARS-CoV-2 can be made in the absence of T follicular helper cells

abstract:
T follicular helper (Tfh) cells are the conventional drivers of protective, germinal center (GC)-based antiviral antibody responses. However, loss of Tfh cells and GCs has been observed in patients with severe COVID-19. As T cell-B cell interactions and immunoglobulin class switching still occur in these patients, non-canonical pathways of antibody production may be operative during SARS-CoV-2 infection. We found that both Tfh-dependent and -independent antibodies were induced against SARS-CoV-2 as well as influenza A virus. Tfh-independent responses were mediated by a population we call lymph node (LN)-Th1 cells, which remain in the LN and interact with B cells outside of GCs to promote high-affinity but broad-spectrum antibodies. Strikingly, antibodies generated in the presence and absence of Tfh cells displayed similar neutralization potency against homologous SARS-CoV-2 as well as the B.1.351 variant of concern. These data support a new paradigm for the induction of B cell responses during viral infection that enables effective, neutralizing antibody production to complement traditional GCs and even compensate for GCs damaged by viral inflammation.

One-Sentence SummaryComplementary pathways of antibody production mediate neutralizing responses to SARS-CoV-2.


title: Anti-SARS-CoV-2 hyperimmune immunoglobulin provides potent and robust neutralization capacity and antibody-dependent cellular cytotoxicity and phagocytosis induction through N and S proteins

abstract:
BackgroundAlthough progressive COVID-19 vaccinations provide a significant reduction of infection rate in the short-to mid-term, effective COVID-19 treatments will continue to be an urgent need.

MethodsWe have functionally characterized the anti-SARS-CoV-2 hyperimmune immunoglobulin (hIG) prepared from human COVID-19 convalescent plasma. SARS-CoV-2 virus neutralization was evaluated by four different methodologies (plaque reduction, virus induced cytotoxicity, TCID50 reduction and immunofluorimetry-based methodology) performed at four different laboratories and using four geographically different SARS-CoV-2 isolates (one each from USA and Italy; two from Spain). Two of the isolates contained the D614G mutation. Neutralization capacity against the original Wuhan SARS-CoV-2 straom and variants (D614G mutant, B.1.1.7, P.1 and B.1.351 variants) was evaluated using a pseudovirus platform expressing the corresponding spike (S) protein. The capacity to induce antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP) was also evaluated.

ResultsAll the SARS-CoV-2 isolates tested were effectively neutralized by hIG solutions. This was confirmed by all four methodologies showing potent neutralization capacity. Wild-type SARS-CoV-2 and variants were effectively neutralized as demonstrated using the pseudovirus platform. The hIG solutions had the capacity to induce ADCC and ADCP against SARS-CoV-2 N and S proteins but not the E protein. Under our experimental conditions, very low concentrations (25-100 {micro}g IgG/mL) were required to induce both effects. Besides the S protein, we observed a clear and potent effect triggered by antibodies in the hIG solutions against the SARS-CoV-2 N protein.

ConclusionsThese results show that, beyond neutralization, other IgG Fc-dependent pathways may play a role in the protection from and/or resolution of SARS-CoV-2 infection when using hIG COVID-19 products. This could be especially relevant for the treatment of more neutralization resistant SARS-CoV-2 variants of concern.


title: B.1.1.7 and B.1.351 SARS-CoV-2 variants display enhanced Spike-mediated fusion

abstract:
Severe COVID-19 is characterized by lung abnormalities, including the presence of syncytial pneumocytes. Syncytia form when SARS-CoV-2 spike protein expressed on the surface of infected cells interacts with the ACE2 receptor on neighbouring cells. The syncytia forming potential of spike variant proteins remain poorly characterized. Here, we first assessed Alpha and Beta spread and fusion in cell cultures. Alpha and Beta replicated similarly to D614G reference strain in Vero, Caco-2, Calu-3 and primary airway cells. However, Alpha and Beta formed larger and more numerous syncytia. Alpha, Beta and D614G fusion was similarly inhibited by interferon induced transmembrane proteins (IFITMs). Individual mutations present in Alpha and Beta spikes differentially modified fusogenicity, binding to ACE2 and recognition by monoclonal antibodies. We further show that Delta spike also triggers faster fusion relative to D614G. Thus, SARS-CoV-2 emerging variants display enhanced syncytia formation.

SynopsisThe Spike protein of the novel SARS-CoV-2 variants are comparative more fusogenic than the earlier strains. The mutations in the variant spike protein differential modulate syncytia formation, ACE2 binding, and antibody escape.

O_LIThe spike protein of Alpha, Beta and Delta, in the absence of other viral proteins, induce more syncytia than D614G
C_LIO_LIThe ACE2 affinity of the variant spike proteins correlates to their fusogenicity
C_LIO_LIVariant associated mutations P681H, D1118H, and D215G augment cell-cell fusion, while antibody escape mutation E484K, K417N and {Delta}242-244 hamper it.
C_LIO_LIVariant spike-mediated syncytia formation is effectively restricted by IFITMs
C_LI


title: SARS-CoV-2 Alpha, Beta and Delta variants display enhanced Spike-mediated Syncytia Formation


title: Deprivation of dietary fiber in specific-pathogen-free mice promotes susceptibility to the intestinal mucosal pathogen Citrobacter rodentium

abstract: The change of dietary habits in Western societies, including reduced consumption of fiber, is linked to alterations in gut microbial ecology. Nevertheless, mechanistic connections between diet-induced microbiota changes that affect colonization resistance and enteric pathogen susceptibility are still emerging. We sought to investigate how a diet devoid of soluble plant fibers impacts the structure and function of a conventional gut microbiota in specific-pathogen-free (SPF) mice and how such changes alter susceptibility to a rodent enteric pathogen. We show that absence of dietary fiber intake leads to shifts in the abundances of specific taxa, microbiome-mediated erosion of the colonic mucus barrier, a reduction of intestinal barrier-promoting short-chain fatty acids, and increases in markers of mucosal barrier integrity disruption. Importantly, our results highlight that these low fiber diet-induced changes in the gut microbial ecology collectively contribute to a lethal colitis by the mucosal pathogen Citrobacter rodentium, which is used as a mouse model for enteropathogenic and enterohemorrhagic Escherichia coli (EPEC and EHEC, respectively). Our study indicates that modern, low-fiber Western diets might make individuals more prone to infection by enteric pathogens via the disruption of mucosal barrier integrity by diet-driven changes in the gut microbiota, illustrating possible implications for EPEC and EHEC infections.


title: Paraoxonase and acylated homoserine lactones in urine from patients with urinary tract infections--relationship to microbial diversity by 16S rRNA gene sequencing

abstract: Paraoxonase (PON) comprises a trio of mammalian enzymes that have been reported to have a number of roles including the inhibition of bacterial virulence and biofilm formation by microorganisms that quorum sense with acylated homoserine lactones (AHLs). PON have previously been reported to inhibit P. aeruginosa biofilm formation in mammalian airways and skin. An innate immune role for PON in urinary tract infection has not previously been reported. We performed western blots for PON1 in urine from patients with urinary tract infection (UTI), and also tested UTI urine for the presence of AHLs using a cellular reporter system. Urine sample microbiota was assessed through sequencing of the 16S rRNA marker gene. We report here that PON1 was not found in the urine of control subjects, however, in patients with UTI, PON1 was associated with the presence of E. coli in urine. AHLs, but not PON, were found in the bulk urine of those with P. aeruginosa UTI. Microbial consortia of PON positive UTI urine was found to be distinct from PON negative UTI urine; differentially over-represented bacteria in PON positive samples included a number of environmental opportunists. We hypothesize that PON may inhibit the quorum sensing activity of AHLs in UTI, as has previously described in skin and airways.


title: In vitro inhibition of H. pylori in a preferential manner using bioengineered L. lactis releasing guided Antimicrobial peptides

abstract:
ObjectivesTargeted therapies seek to selectively eliminate a pathogen without disrupting the resident microbial community. This is even more important when a pathogen like H. pylori resides in stomach, a sensitive microbial ecosystem. Using a probiotic like Lactococcus lactis and bioengineering it to release a guided Antimicrobial Peptide (AMP) targeted towards the pathogen offers a pathway to specifically knock-out the deleterious species and not disturbing the stomach microbiome.

ResultsThree AMPs, Alyteserin, CRAMP and Laterosporulin, were genetically fused to a guiding peptide MM1, which selectively binds to Vacuolating Toxin A (VacA) of H. pylori and cloned into an excretory vector pTKR inside L. lactis. When cultured together in vitro, the L. lactis bioengineered with guided AMPs selectively killed H. pylori when compared to E. coli or Lactobacillus plantarum, as determined by qPCR. Chemically synthesized Alyteserin and MM1-Alyteserin showed similar preferential inhibition of H. pylori when compared against E. coli, with the MIC of MM1-Alyteserin becoming significantly higher for E. coli than Alytserin whereas no such effet was observed against H. pylori.

ConclusionsProbiotics bioengineered to excrete guided AMPs can be a novel and useful approach for combating pathogens without endangering the natural microbial flora. Given the wealth of AMPs and guiding ligands, both natural and synthetic, this approach can be adapted to develop a diverse array of chimeric guided AMPs and can be cloned into probiotics to create a safe and effective alternative to conventional chemical antibiotics.

category: molecular biology


title: Differential growth is a critical determinant of zebrafish pigment pattern formation

abstract: The skin patterns of vertebrates are formed by complex interactions between pigment-producing cells during development. Adult zebrafish (Danio rerio), a model organism for investigating the underlying patterning processes, display alternating horizontal blue and golden stripes, generated by the self-organisation of three pigment cell-types. Mathematical studies in which these cells are modelled as individual agents communicating via short- and long-range interactions have produced breakthroughs in the understanding of pattern development. These models, incorporating all experimentally evidenced cell-cell interactions, replicate many aspects of wild-type and mutant zebrafish patterns. Although received wisdom suggested that initial iridophore distribution was pivotal in orienting patterning, here we show that growth can override its influence. Altered growth sequences can generate further pattern modulation, including vertical stripes and maze-like patterns. We demonstrate that ventrally-biased (asymmetric) growth of the skin field explains two key zebrafish pattern development features which are otherwise obscure (dorso-ventral pattern asymmetry, and predominant ventral-to-dorsal migration of melanophores) in wild-type and multiple zebrafish mutants, and in the related species Danio nigrofasciatus. By identifying biased growth as a novel patterning mechanism, our study will inform future investigations into the mechanisms and evolution of fish pigment patterning and vertebrate pigment pattern formation. Furthermore, our work has implications for the mechanistic basis of human pigmentation defects.

category: developmental biology