title: Seeing light from a different angle: the effects of diffuse light on the function, structure, and growth of tomato plants

abstract: While considerable attention has been paid to how plants respond to changes in the spectral distribution and quantity of light, less attention has been paid to how plants respond to changes in the angular qualities of light. Evidence from both leaf- and ecosystem-scale measurements indicate that plants vary in their response to diffuse compared to direct light growing environments. Because of the significant implications for agricultural production, we quantified how changes in light quality affect the structure, function, and growth of Roma tomatoes in an open-air greenhouse experiment with direct and diffuse light treatments. Diffuse light conditions (ca. 50-60% diffuse) were created with a glass coating to diffuse light without significantly reducing the quantity of light. We measured leaf physiology and structure, as well as whole plant physiology, morphology, and growth. Light-saturated photosynthetic rates were set by the growing light environment and were unchanged by short-term exposure to the opposite light environment. Thus, after two months, plants in the diffuse light treatment demonstrated lower photosynthesis and had thinner leaves with higher chlorophyll concentration. However, relative growth rates did not differ between treatments and plants grown in diffuse light had significantly higher biomass at the conclusion of the experiment. While there was no difference in leaf or whole-plant water-use efficiency, plants in the diffuse light treatment demonstrated significantly lower leaf temperatures, highlighting the potential for diffuse light coatings and/or materials to reduce greenhouse energy use. Our results highlight the need to advance our understanding of the effects of diffuse light conditions on agricultural crops growing on a changing planet.

category: plant biology


title: Predicting TCR-peptide recognition based on residue-level pairwise statistical potential

abstract: T cell receptor (TCR) recognition of foreign peptides presented by major histocompatibility complex (MHC) proteins is a crucial step in triggering the adaptive immune response. Prediction of TCR:peptide recognition is important for many clinically relevant problems: prediction of cross-reactivity of TCRs used in adoptive T-cell-based therapies, identification of targets for antigen-specific therapies of autoimmune disorders and cancer, vaccine design. In this work, we describe a novel computational method that ranks TCR-peptide pairs based on statistical estimation of binding energy to select the most likely cognate epitopes. Our method starts from a structure of a peptide-MHC complex with the TCR of interest (either experimentally derived or based on a homology model) and a set of candidate epitopes and generates a ranked list of these peptides with predicted recognition probabilities. In our method interaction energy between TCR and peptide residues is estimated using statistical potential TCRen which we derived via statistical analysis of amino acid contact preferences in TCR-peptide interfaces from crystal structures of TCR-peptide-MHC complexes. We demonstrate excellent performance of our method for two tasks related to TCR-peptide recognition: 1) discrimination between cognate epitopes and unrelated peptides; 2) discrimination between real and mocked TCR-peptide-MHC complexes. Comparison of TCRen with potentials reflecting the rules of general protein-protein interaction and protein folding reveals the distinctive features of TCR-peptide interactions, such as intrinsic asymmetry of the interface, a complex interplay between different physico-chemical properties of contacting residues and lower impact of hydrophobic interactions. Finally, we demonstrate the use of our method for identification of cancer neo-epitopes recognized by tumor-infiltrating lymphocytes.

category: immunology


title: Squamation and scale morphology at the root of jawed vertebrates

abstract: Placoderms, the most basal jawed vertebrates, are crucial to understanding how the characters of crown gnathostomes comprising Chondrichthyes and Osteichthyes evolved from their stem relatives. Despite the growing knowledge on the anatomy and diversity of placoderms over the past decade, the dermal scales of placoderms are predominantly known from isolated material, either morphologically or histologically, resulting in their squamation being poorly understood. Here we provide a comprehensive description of the squamation and scale morphology of a primitive taxon of Antiarcha (a clade at the root of jawed vertebrates), Parayunnanolepis xitunensis, based on the virtual restoration of an articulated specimen by using X-ray computed tomography. Thirteen morphotypes of scales are classified to exhibit how the morphology changes with their position on the body in primitive antiarchs, based on which nine areas of the post-thoracic body are distinguished to show their scale variations in the dorsal, flank, ventral, and caudal lobe regions. In this study, the histological structure of yunnanolepidoid scales was described for the first time based on disarticulated scales from the type locality and horizon of P. xitunensis, demonstrating that yunnanolepidoid scales are remarkably different from the dermal plates of antiarchs including yunnanolepidoids in the absence of developed middle layer. Together, our study reveals that the high regionalization of squamation and the bipartite histological structure of scale might be plesiomorphic for antiarchs, and jawed vertebrates in general.

category: evolutionary biology


title: Uniformity of spheroid-on-chip by surface treatment of PDMS microfluidic platforms

abstract: Spheroids have emerged as a more reliable model for drug screening when compared with 2D culture models. Microfluidic based biochips have many advantages over other 3D cell culture models for drug testing on spheroids, including precise control of the cellular microenvironment. The control of the cell adhesion to the surface is one of the most important challenges affecting the size and the geometry of the spheroids which could be controlled by appropriate surface engineering methods. We have studied the modification of the PDMS surface properties treated by applying different concentrations of the two anti-fouling coatings (BSA and Pluronic F-68). The desired treatment of PDMS surface effectively inhibits cell adhesion to the surface and promotes cells self-aggregations to form more uniform and healthy spheroids for a longer period of time. The microscopic observations with qualitative and quantitate data revealed that surface properties drastically affect the number of the spheroids formed on-chip and their geometry. We used human breast cancer cell line (MDA-MB-231-GFP) while the concentration of the chemical coatings and incubation time were adjusted. Proper repellent PDMS surfaces were provided with minimum cell attachment and facilitated spheroid formation when compared with non-treated PDMS. The results demonstrate fundamental and helpful patterns for microfluidic based cell culture applications to improve the quantity and quality of spheroid formation on-chip which are strongly manipulated by surface properties (i.e., morphology, roughness, wettability and etc.)

category: bioengineering


title: TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile

abstract:
Determining transcriptional factor binding sites (TFBSs) is critical for understanding the molecular mechanisms regulating gene expression in different biological conditions. Biological assays designed to directly mapping TFBSs require large sample size and intensive resources. As an alternative, ATAC-seq assay is simple to conduct and provides genomic cleavage profiles that contain rich information for imputing TFBSs indirectly. Previous footprint-based tools are inheritably limited by the accuracy of their bias correction algorithms and the efficiency of their feature extraction models. Here we introduce TAMC (Transcriptional factor binding prediction from ATAC-seq profile at Motif-predicted binding sites using Convolutional neural networks), a deep-learning approach for predicting motif-centric TF binding activity from paired-end ATAC-seq data. TAMC does not require bias correction during signal processing. By leveraging a onedimensional convolutional neural network (1D-CNN) model, TAMC captures both footprint and non-footprint features at binding sites for each TF and outperforms existing footprinting tools in TFBS prediction particularly for ATAC-seq data with limited sequencing depth.

AUTHOR SUMMARYApplications of deep-learning models are rapidly gaining popularity in recent biological studies because of their efficiency in analyzing non-linear patterns from feature-rich data. In this study, we developed a 1D-CNN model to predict TFBSs from ATAC-seq data. Compared to previous models using scoring functions and classical machine learning algorithms, our 1D-CNN model forgoes the need for bias correction during signal processing and significantly increases the efficiency in extracting features for TFBS prediction. In addition, the performance of our 1D-CNN model improves when the sequencing depth of training ATAC-seq data increases. Importantly, we showed that our method outperforms existing tools in TFBS prediction particularly when the sequencing depth of training ATAC-seq data is higher than the ATAC-seq data for prediction. This widened the applicability of our model to ATAC-seq data with both deep and shallow sequencing depth. Based on these results, we discussed about the potential application of our method to TFBS predication using bulk and single-cell ATAC-seq data.

category: bioinformatics


title: scDVF: Data-driven Single-cell Transcriptomic Deep Velocity Field Learning with Neural Ordinary Differential Equations

abstract:
Recent advances in single-cell RNA sequencing technology have provided unprecedented opportunities to simultaneously measure the gene expression profile and transcriptional velocity of individual cells, enabling us to sample gene regulatory network dynamics along developmental trajectories. However, traditional methods have faced challenges in modeling gene expression dynamics within individual cells due to sparse, non-linear (e.g., obligate heterodimer transcription factors), and high-dimensional measurements. Here, we present DeepVelo, a neural-network-based ordinary differential equation model that can learn non-linear, high-dimensional single-cell transcriptome dynamics and describe continuous gene expression changes within individual cells across time. We applied DeepVelo to multiple published datasets from different technical platforms and demonstrated its utility to 1) formulate transcriptome dynamics on different timescales, 2) measure the instability of cell states, and 3) identify developmental driver genes upstream of a signaling cascade. Benchmarking against state-of-the-art methods shows that DeepVelo can improve velocity field representation accuracy by at least 50% in out-of-sample cells. Further, perturbation studies revealed that single-cell dynamical systems may exhibit properties similar to those of chaotic systems. In summary, DeepVelo allows for the data-driven discovery of differential equations that delineate single-cell transcriptome dynamics.

TeaserEmbedding neural networks into ordinary differential equations to model gene expression changes within single cells across time.


title: DeepVelo: Data-driven Single-cell Transcriptomic Deep Velocity Field Learning with Neural Ordinary Differential Equations


title: RAID: Regression Analysis based Inductive DNA microarray for Precise Read-Across

abstract: Chemical structure-based read-across represents a promising method for chemical toxicity evaluation without the need for animal testing; however, a chemical structure is not necessarily related to toxicity. Therefore, in vitro studies were often used for read-across reliability refinement; however, their external validity has been hindered by the gap between in vitro and in vivo conditions. Thus, we developed a virtual DNA microarray, Regression Analysis based Inductive DNA microarray (RAID), which quantitatively predicts in vivo gene expression profiles based on the chemical structure and/or in vitro transcriptome data. For each gene, elastic-net models were constructed using chemical descriptors and in vitro transcriptome data to predict in vivo data from in vitro data (in vitro to in vivo extrapolation; IVIVE). In feature selection, useful genes for assessing the quantitative structure activity relationship (QSAR) and IVIVE were identified. Predicted transcriptome data derived from the RAID system reflected the in vivo gene expression profiles of characteristic hepatotoxic substances. Moreover, gene ontology and pathway analyses indicated that xenobiotic response and metabolic activation via nuclear receptors are related to those gene expressions. The identified IVIVE-related genes were associated with fatty acid-, xenobiotic-, and drug metabolism, indicating that in vitro studies were effective in evaluating these key events. Furthermore, validation studies revealed that chemical substances associated with these key events could be detected as hepatotoxic biosimilar substances. These results indicate that the RAID system could represent an alternative screening test for repeated-dose toxicity test and toxicogenomic analyses. Our technology provides a critical solution to IVIVE-based read-across by considering the mode of action and chemical structures.

category: pharmacology and toxicology


title: AAV2/9-mediated gene transfer into murine lacrimal gland leads to a long-term targeted tear film modification

abstract: Corneal blindness is the fourth leading cause of blindness worldwide. Since the corneal epithelium is constantly renewed, non-integrative gene transfer cannot be used to treat corneal diseases. In numerous of these diseases, the tear film has been reported to be defective. Tears are a complex biological fluid secreted by the lacrimal apparatus. Their composition is modulated according to the context. For instance, after a corneal wound, the lacrimal gland secretes reflex tears, which contain specific growth factors supporting the wound healing process. In specific pathological contexts, such as dry eye diseases, the tear composition can support neither corneal homeostasis, nor wound healing. Here, we propose to use the lacrimal gland as bioreactor to produce and secrete specific factors to support corneal physiology. In this study, we used an AAV2/9-mediated gene transfer to supplement the tear film. First, we demonstrate that a single injection of AAV2/9 is sufficient to transduce all epithelial cell types of the lacrimal gland efficiently and widely. Then, we show that lacrimal gland physiology and corneal integrity are maintained after the injection of an AAV2/9-mediated nerve growth factor expression in the lacrimal gland. Remarkably, this injection induces an important and long-lasting secretion of this growth factor in the tear film. Altogether, our findings provide a new clinically applicable approach to tackle corneal blindness.

category: physiology


title: Niche differentiation following whole-genome duplication? The importance of considering the intricate evolutionary history of polyploids when assessing climatic niche evolution

abstract:
AimAlthough whole genome duplication (WGD) is an important speciation force, we still lack a consensus on the role of niche differentiation in polyploid evolution. In addition, the role of genome doubling per se vs. later divergence on polyploids niche evolution remains obscure. One reason for this might be that the intraspecific genetic structure of polyploid complexes and interploidy gene flow is often neglected in ecological studies. Here, we aim to investigate to which extent these evolutionary processes impact our inference on niche differentiation of autopolyploids.

LocationEurope

TaxonArabidopsis arenosa (Brassicaceae)

MethodsLeveraging a total of 352 cytotyped populations of diploid-autotetraploid A. arenosa, we examined differences among climatic niches of diploid and tetraploid lineages both globally, and independently for each tetraploid lineage with respect to the niche of its evolutionary closest relative. Then, we tested if there was an effect of additional interploidy introgression from other sympatric but more ancestral diploid lineages of A. arenosa on climatic niches of tetraploids.

ResultsEcological niche shift of tetraploids is only detected when the assignment of populations to intraspecific genetic lineages is considered. We found different patterns of climatic niche evolution (i.e. niche conservatism, contraction or expansion) in each tetraploid lineage when compared to its evolutionary closest relatives. We observed an effect of interploidy gene flow in patterns of climatic niche evolution of tetraploid ruderal plants of A. arenosa.

Main conclusionsThe niche shift of tetraploids in A. arenosa is not driven by WGD per se but rather reflects dynamic post-WGD evolution in the species, involving tetraploid migration out of their ancestral area and interploidy introgression with other diploid lineages. Our study supports that evolutionary processes following WGD - which usually remain undetected by studies neglecting evolutionary history of polyploids - may play a key role in the adaptation of polyploids to challenging environments.


title: Hematological and gene co-expression network analyses of high-risk beef cattle defines immunological mechanisms and biological complexes involved in bovine respiratory disease and weight gain

abstract:
Bovine respiratory disease (BRD), the leading disease complex in beef cattle production systems, remains highly elusive regarding diagnostics and disease prediction. Previous research has employed cellular and molecular techniques to describe hematological and gene expression variation that coincides with BRD development. Here, we utilized weighted gene co-expression network analysis (WGCNA) to leverage total gene expression patterns from cattle at arrival and generate hematological and clinical trait associations to describe mechanisms that may predict BRD development.

Gene expression counts of previously published RNA-Seq data from 23 cattle (2017; n=11 Healthy, n=12 BRD) were used to construct gene co-expression modules and correlation patterns with complete blood count (CBC) and clinical datasets. Modules were further evaluated for cross-populational preservation of expression with RNA-Seq data from 24 cattle in an independent population (2019; n=12 Healthy, n=12 BRD). Genes within well-preserved modules were subject to functional enrichment analysis for significant Gene Ontology terms and pathways. Genes which possessed high module membership and association with BRD development, regardless of module preservation ("hub genes"), were utilized for protein-protein physical interaction network and clustering analyses.

Five well-preserved modules of co-expressed genes were identified. One module ("steelblue"), involved in alpha-beta T-cell complexes and Th2-type immunity, possessed significant correlation with increased erythrocytes, platelets, and BRD development. One module ("purple"), involved in mitochondrial metabolism and rRNA maturation, possessed significant correlation with increased eosinophils, fecal egg count per gram, and weight gain over time. Fifty-two interacting hub genes, stratified into 11 clusters, may possess transient function involved in BRD development not previously described in literature. This study identifies co-expressed genes and coordinated mechanisms associated with BRD, which necessitates further investigation in BRD-prediction research.

Author SummaryBovine respiratory disease (BRD), the leading disease in beef cattle, is a highly dynamic disease complex. Through simultaneous sequencing of thousands of genes active in the blood of cattle at arrival, we pursued the co-expression patterns of these genes to evaluate associations with BRD development and severity overtime. This approach allows for a better understanding of gene expression active in cattle at arrival, and the discovery of new molecules and biological complexes that may predict BRD before the onset of clinical signs. Our work provides evidence that genes related to T-cells, a type of immune cell, are strongly co-expressed when cattle arrive to beef production system, and correlate with increased red blood cell (RBC) factors and BRD development. Further analysis shows that genes involved in cellular energy production and the respiratory electron transport are strongly co-expressed when cattle arrive to beef production system, and correlate with increased eosinophils, a type of immune cell, and weight gain overtime. Additionally, using genes which strongly correlate with BRD development and severity overtime, we identify a novel protein interaction complex that may drive future research for discovering new ways to manage and treat BRD in beef cattle.

category: systems biology


title: Mechanistic model for human brain metabolism and the neurovascular coupling.

abstract: The neurovascular coupling (NVC) connects cerebral activity, blood flow, and metabolism. This interconnection is used in for instance functional imaging, which analyses the blood-oxygen-dependent (BOLD) signal. The mechanisms underlying the NVC are complex, which warrants a model-based analysis of data. We have previously developed a mechanistically detailed model for the NVC, and others have proposed detailed models for cerebral metabolism. However, existing metabolic models are still not fully utilizing available magnetic resonance spectroscopy (MRS) data and are not connected to detailed models for NVC. Therefore, we herein present a new model that integrates mechanistic modelling of both MRS and BOLD data. The metabolic model covers central metabolism, and can describe time-series data for glucose, lactate, aspartate, and glutamine, measured after visual stimuli. Statistical tests confirm that the model can describe both estimation data and predict independent validation data, not used for model training. The interconnected NVC model can simultaneously describe BOLD data and can be used to predict expected metabolic responses in experiments where metabolism has not been measured. This model is a step towards a useful and mechanistically detailed model for cerebral blood flow and metabolism, with potential applications in both basic research and clinical applications.


title: Demise of Marimermithida refines primary routes of transition to parasitism in roundworms

abstract: Nematodes (roundworms) are ubiquitous animals commonly dominating in ecological communities and networks, with many parasites and pathogen vectors of great economic and medical significance. Nematode parasites are remarkably diverse in life strategies and adaptations at a great range of hosts and dimension scales, from whales to protozoan cells. Their life history is intricate and requires understanding to study the genomic, structural and ecological bases of successful transitions to parasitism. Based on analyses of rDNA for a representative sampling of host-associated and free-living groups, we dismiss the last higher-rank nematode taxon uniting solely parasitic forms (Marimermithida) and show that primarily marine parasitism emerged independently and repeatedly within only few free-living lineages. We re-evaluate the significance of some traditionally important phenotypic characters and report the phenomenon of dramatic adaptation to parasitism on very short evolutionary timescales. A cross-phylum character interpretation vindicates that non-intestinal (in-tissue or cavitary) host capture was likely a primary route of transition to truly exploitive parasitism (vs. intestinal commensalism) in roundworms, and extant nematode parasitoids (larval parasites) infesting the host body cavity or internal organs realise this primary lifestyle. Parasitism may have evolved in nematodes as part of innate pre-adaptations to crossing environmental boarders, and such transitions have been accomplished multiple times successfully in the phylum history.

category: zoology


title: Vaccine-linked chemotherapy with a low dose of benznidazole plus a bivalent recombinant protein vaccine prevents the development of cardiac fibrosis caused by Trypanosoma cruzi in BALB/c mice.

abstract:
BackgroundChagas disease (CD) is caused by Trypanosoma cruzi and affects 6-7 million people worldwide. Approximately 30% of chronic patients develop chronic chagasic cardiomyopathy (CCC) after decades. Benznidazole (BNZ), one of the first-line chemotherapy approved for CD, induces toxicity and fails to halt the progression of CCC in chronic patients. The recombinant parasite-derived antigens, including Tc24, Tc24-C4, TSA-1, and TSA-1-C4 with Toll-like receptor 4 (TLR-4) agonist-adjuvants reduce cardiac parasite burdens, heart inflammation, and fibrosis, leading us to envision their use as immunotherapy together with BNZ. Given genetic immunization (DNA vaccines) encoding Tc24 and TSA-1 induce protective immunity in mice and dogs, we propose that immunization with the corresponding recombinant proteins offers an alternative and feasible strategy to develop these antigens as a bivalent human vaccine. We hypothesized that a low dose of BNZ in combination with a therapeutic vaccine (TSA-1-C4 and Tc24-C4 antigens formulated with a synthetic TLR-4 agonist-adjuvant, E6020-SE) could provide antigen-specific T cell immunity and prevent cardiac fibrosis progression.

Methodology/ Principal findingsWe evaluated the therapeutic vaccine candidate plus BNZ (25 mg/kg/day/7 days) given at days 72 and 79 post-infection (p.i) (early chronic phase). Fibrosis, inflammation, and parasite burden were quantified in heart tissue at day 200 p.i. (late chronic phase). Further, spleen cells were collected to evaluate antigen-specific CD4+ and CD8+ T cell immune responses, using flow cytometry. We found that vaccine-linked BNZ treated mice had lower cardiac fibrosis compared to the infected untreated control group. Moreover, cells from mice that received the immunotherapy had higher stimulation index of antigen-specific CD8+Perforin+ T cells as well as antigen-specific central memory T cells compared to infected untreated control.

ConclusionsOur results suggest that the bivalent immunotherapy together with BNZ treatment protects mice against cardiac fibrosis and activates strong CD8+ T cell responses by in vitro restimulation, evidencing the induction of a long-lasting T. cruzi-immunity.

Author summaryChagas disease (CD) is a neglected tropical disease caused by the parasite Trypanosoma cruzi, transmitted through contact with infected feces of vectors bugs. CD can induce cardiac abnormalities including the development of fibrosis and eventually death. Benznidazole (BNZ) is the first-line drug approved against CD, however, its toxicity and lack of efficacy in the chronic phase have limited its use. Previous studies have demonstrated the feasibility of reducing doses of BNZ given in combination with therapeutic vaccines during the acute phase of CD, which increases its tolerability and reduces adverse side effects. Considering that patients are often diagnosed until prolonged stages of the disease, its necessary to evaluate therapies given in the chronic phase of CD. In this study, we evaluated a vaccine formulated with the recombinant T. cruzi-antigens TSA-1-C4 and Tc24-C4 and the adjuvant E6020-SE in combination with a low dose of BNZ given during the chronic phase of T. cruzi-infection using a murine model. The authors found that the combination therapy protects mice against cardiac fibrosis, allow the activation of a CD8+ T cell response and induce a prolonged memory response against T. cruzi. This study supports the development of the vaccine-linked chemotherapy approach in order to prevent T. cruzi chronic infection.


title: MoveApps - a serverless no-code analysis platform for animal tracking data

abstract:
BackgroundBio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills.

ResultsWe developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface.

Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository.

The platform was beta launched in spring 2021 and currently contains 44 Apps that are used by 156 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements.

ConclusionsThe MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.

category: ecology


title: Managing beach access and vehicle impacts following reconfiguration of the landscape by a natural hazard event

abstract: After New Zealands 7.8 Mw Kaik[o]ura earthquake in late 2016 an unexpected anthropogenic effect involved increased motorised vehicle access to beaches. We show how these effects were generated by landscape reconfiguration associated with coastal uplift and widening of high-tide beaches, and present analyses of the distribution of natural environment values in relation to vehicle movements and impacts. Access changes led to extensive vehicle tracking in remote areas that had previously been protected by natural barriers. New dunes formed seaward of old dunes and have statutory protection as threatened ecosystems, yet are affected by vehicle traffic. Nesting grounds of nationally vulnerable banded dotterel (Charadrius bicinctus bicinctus) co-occur with vehicle tracking. An artificial nest experiment showed that vehicle strikes pose risks to nesting success, with 91% and 83% of nests destroyed in high and moderate-traffic areas, respectively, despite an increase in suitable habitat. Despite gains for recreational vehicle users there are serious trade-offs with environmental values subject to legal protection and associated responsibilities for management authorities. In theory, a combination of low-impact vehicle access and environmental protection could generate win-win outcomes from the landscape changes, but is difficult to achieve in practice. Detailed information on sensitive areas would be required to inform designated vehicle routes as a potential solution, and such sensitivities are widespread. Alternatively, vehicle access areas that accommodate longstanding activities such as boat launching could be formally established using identified boundaries to control impacts further afield. Difficulties for the enforcement of regulatory measures in remote areas also suggest a need for motivational strategies that incentivise low-impact behaviours. We discuss options for user groups to voluntarily reduce their impacts, the importance of interactions at the recreation-conservation nexus, and need for timely impact assessments across the social-ecological spectrum after physical environment changes -- all highly transferable principles for other natural hazard and disaster recovery settings worldwide.


title: Transcriptional background effects on a tumor driver gene in a transgenic medaka melanoma model

abstract: The Xiphophorus melanoma receptor kinase gene, xmrk, is a bona fide oncogene driving melanocyte tumorigenesis of Xiphophorus fish. When ectopically expressed in medaka, it not only induces development of several pigment cell tumor types in different strains of medaka, but also induces different tumor types within the same animal, suggesting its oncogenic activity has a transcriptomic background effect. Although the central pathways that xmrk utilizes to lead to melanomagenesis are well documented, genes and genetic pathways that modulate the oncogenic effect, and alter the course of disease have not been studied so far. To understand how the genetic networks between different histocytes of xmrk-driven tumors are composed, we isolated two types of tumors, melanoma and xanthoerythrophoroma, from the same xmrk transgenic medaka individuals, established the transcriptional profiles of both xmrk-driven tumors, and compared (1) genes that are co-expressed with xmrk in both tumor types, and (2) differentially expressed genes and their associated molecular functions, between the two tumor types. Transcriptomic comparisons between the two tumor types show melanoma and xanthoerythrophoroma are characterized by transcriptional features representing varied functions, indicating distinct molecular interactions between the driving oncogene and the cell type-specific transcriptomes. Melanoma tumors exhibited gene signatures that are relevant to proliferation and invasion while xanthoerythrophoroma tumors are characterized by expression profiles related metabolism and DNA repair. We conclude the transcriptomic backgrounds, exemplified by cell-type specific genes that are downstream of xmrk effected signaling pathways, contribute the potential to change the course of tumor development and may affect overall tumor outcomes.

category: genetics


title: Phenotypic Characterization of indigenous goat population in Southern, Ethiopia

abstract: A study was conducted at Abaya and Yirgachafe districts to characterize indigenous goat types phenotypically. Data were collected through field measurements and visual observation of qualitative traits. Totally 540 goats were used for metric and morphometric measurement. Results of the study revealed that the goat populations found in Abaya and Yirgachafe district were different characteristics which are physically Abaya goats were closest with Arsi-Bale whereas yirgachafee with Woyto-Guji which are mostly distributed goat breeds in southern Ethiopia. The dominant coat color pattern in study area was plain, patchy, and spotted with proportions of 55.19, 37.04, and 7.78% and 46.67, 38.89, and 14.44% in Abaya and Yirgachafee district respectively. A strong and positive correlation(r = 0.83, 0.76) was observed between heart girth and body weight for male and female goat populations respectively. Generally, the indigenous goat population has its own difference in its morphological and morphometric traits. Traits have their own economic contribution. Therefore, identifying these important traits for further genetic improvements, conservation and sustainable utilization of the genetic resources of the diversified goat population is important.


title: Hamiltonian Monte Carlo with strict convergence criteria reduces run-to-run variability in forensic DNA mixture deconvolution

abstract:
MotivationAnalysing mixed DNA profiles is a common task in forensic genetics. Due to the complexity of the data, such analysis is often performed using Markov Chain Monte Carlo (MCMC)-based genotyping algorithms. These trade off precision against execution time. When the default settings are used, as large as a 10-fold changes in inferred likelihood ratios (LR) are observed when the software is run twice on the same case. So far, this uncertainty has been attributed to the stochasticity of MCMC algorithms. Since LRs translate directly to strength of the evidence in a criminal trial, forensic laboratories desire LR with small run-to-run variability.

ResultsWe present a Hamiltonian Monte Carlo (HMC) algorithm that reduces run-to-run variability in forensic DNA mixture deconvolution by around an order of magnitude without increased runtime. We achieve this by enforcing strict convergence criteria. We show that the choice of convergence metric strongly influences precision. We validate our method by reproducing previously published results for benchmark DNA mixtures (MIX05, MIX13, and ProvedIt). We also present a complete software implementation of our algorithm that is able to leverage GPU acceleration, accelerating the inference process. In the benchmark mixtures, on consumer-grade hardware, the runtime is less than 7 minutes for 3 contributors, less than 35 minutes for 4 contributors, and less than an hour for 5 contributors with one known contributor.


title: Engineering of an electrically charged hydrogel implanted into a traumatic brain injury model for stepwise neuronal tissue reconstruction

abstract:
Neural regeneration is extremely difficult to achieve. In traumatic brain injuries, the loss of brain parenchyma volume hinders neural regeneration. In this study, neuronal tissue engineering was performed by using electrically charged hydrogels composed of cationic and anionic monomers in a 1:1 ratio (C1A1 hydrogel), which served as an effective scaffold for the attachment of neural stem cells (NSCs). In the 3D environment of porous C1A1 hydrogels engineered by the cryogelation technique, NSCs differentiated into neuroglial cells. The C1A1 porous hydrogel was implanted into brain defects in a mouse traumatic damage model. The VEGF-immersed C1A1 porous hydrogel promoted host-derived vascular network formation together with the infiltration of macrophages/microglia and astrocytes into the gel. Furthermore, the stepwise transplantation of GFP-labeled NSCs supported differentiation to glial and neuronal cells. Therefore, this two-step method for neural regeneration may become a new approach for therapeutic brain tissue reconstruction after brain damage in the future.

One Sentence SummaryBrain tissue reconstruction using charged hydrogel and stepwise NCS injection


title: PycoMeth: A toolbox for differential methylation testing from Nanopore methylation calls

abstract: AO_SCPLOWBSTRACTC_SCPLOWAdvances in Nanopore sequencing have opened up the possibility for the simultaneous analysis of genomic and epigenetic variation by way of base-calling and methylation-calling of the same long reads. Methylation analysis based on long read technologies requires a re-evaluation of data storage and analysis approaches previously developed for either CpG-methylation arrays or short-read bisulfite sequencing data. To address this, we here present a toolbox for the segmentation and differential methylation analysis of (haplotyped) methylation calls from Nanopore data. Additionally, we describe a storage format for read-level and reference-anchored methylation call data, which simultaneously allows for efficient storage and rapid data access.


title: Salt Induced Transitions in the Conformational Ensembles of Intrinsically Disordered Proteins

abstract: Salts modulate the behavior of intrinsically disordered proteins (IDPs). In low ionic strength solutions, IDP conformations are primarily perturbed by the screening of electrostatic interactions, independent of the identity of the salt. In this regime, insight into the IDP behavior can be obtained using the theory for salt-induced transitions in charged polymers. However, in high ionic strength solutions, salt-specific interactions with the charged and uncharged residues, known as the Hofmeister effect, influence IDP behavior. There is a lack of reliable theoretical models in high salt concentration regimes to predict the salt effect on IDPs. Using a coarse-grained simulation model for the IDPs and experimentally measured water to salt solution transfer free-energies of various chemical groups, we studied the salt-specific transitions induced in the IDPs conformational ensemble. We probed the effect of three different salts, ranging from protective osmolyte to denaturant, on five IDPs belonging to various polymer classes classified based on charge content. The transitions observed in the IDP conformational ensembles are dependent on the salt used and the IDP polymer class. An important implication of these results is that a suitable salt can be identified to induce condensation of an IDP through liquid-liquid phase separation.

category: biophysics


title: Transglutaminase 2 associated with PI3K and PTEN in a putative membrane-bound signalosome platform blunts cell death

abstract: Atypically expressed transglutaminase 2 (TG2) has been identified as a poor prognostic factor in a variety of cancers. In this study, we evaluated the contribution of TG2 to the prolonged cell survival of differentiated acute promyelocytic leukaemia (APL) cells in response to the standard treatment with combined retinoic acid (ATRA) and arsenic trioxide (ATO). We report that one advantage of ATRA + ATO treatment compared to ATRA alone diminishes the amount of activated and non-activated CD11b/CD18 and CD11c/CD18 cell surface integrin receptors. These changes suppress ATRA-induced TG2 docking on the cytosolic part of CD18 {beta}2-integrin subunits and reduce cell survival. In addition, TG2 overexpresses and hyperactivates the phosphatidylinositol-3-kinase (PI3K), phospho-AKT S473, and phospho-mTOR S2481 signalling axis. mTORC2 acts as a functional switch between cell survival and death by promoting the full activation of AKT. We show that TG2 presumably triggers the formation of a signalosome platform, hyperactivates downstream mTORC2-AKT signalling, which in turn phosphorylates and inhibits the activity of FOXO3, a key pro-apoptotic transcription factor. In contrast, the absence of TG2 restores basic phospho-mTOR S2481, phospho-AKT S473, PI3K, and PTEN expression and activity, thereby sensitising APL cells to ATO-induced cell death. We conclude, that atypically expressed TG2 may serve as a hub, facilitating signal transduction via signalosome formation by the CD18 subunit with both PI3K hyperactivation and PTEN inactivation through the PI3K PTEN cycle in ATRA-treated APL cells.

category: cancer biology


title: Hypoxia modulates cellular endocytic pathways and organelles with enhanced cell migration and 3D cell invasion

abstract:
Hypoxia, a decrease in cellular or tissue level oxygen content, is characteristic of most tumours and shown to drive cancer progression by altering multiple subcellular processes. We hypothesized that the cancer cells in a hypoxic environment might have slower proliferation rates and increased invasion and migration rate with altered endocytosis when compared to the cancer cells in the periphery of the tumour mass that experiences normoxic condition. Using chemically induced hypoxia, a short hypoxic exposure increased the uptake of clathrin independent endocytic marker Galectin-3, but a prolonged hypoxic exposure decreased clathrin-independent endocytic uptake, while clathrin mediated endocytosis remained unaffected. Subcellular organelles such as mitochondria showed enhanced intensity to withstand the hypoxic stress, while other organelles such as ER were significantly decreased. The proliferation rates decreased, and the migration and invasion rate increased in cancer cells in hypoxic condition compared to normoxic cancer cells.These data suggest that hypoxia modulates cellular endocytic pathways with decreased proliferation and enhanced cell migration and invasion.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/480665v1_ufig1.gif" ALT="Figure 1">
View larger version (53K):
org.highwire.dtl.DTLVardef@56841corg.highwire.dtl.DTLVardef@1fb82dborg.highwire.dtl.DTLVardef@14c3253org.highwire.dtl.DTLVardef@17c0381_HPS_FORMAT_FIGEXP  M_FIG C_FIG


title: Periductal bile acid exposure causes cholangiocyte injury and fibrosis

abstract:
IntroductionBile duct integrity is essential for the maintenance of the structure and function of the biliary tree. We previously showed that cholangiocyte injury in a toxic model of biliary atresia leads to increased monolayer permeability. Increased epithelial permeability was also shown in other cholangiopathies. We hypothesized that after initial cholangiocyte injury, leakage of bile acids into the duct submucosa propagates cholangiocyte damage and fibrosis. We thus aimed to determine the impact of bile acid exposure on cholangiocytes and the potential therapeutic effect of a non-toxic bile acid.

Materials and methodsExtrahepatic bile duct explants were isolated from adult and neonatal BALB/c mice. Explants were cultured with or without glycochenodeoxycholic acid and ursodeoxycholic acid. They were then fixed and stained.

ResultsExplants treated with glycochenodeoxycholic acid demonstrated cholangiocyte injury with monolayer disruption and partial lumen obstruction compared to control ducts. Massons trichrome stains revealed increased collagen fibers. Myofibroblast marker -SMA stains were significantly elevated in the periductal region. The addition of ursodeoxycholic acid resulted in decreased cholangiocyte injury and reduced fibrosis.

ConclusionsBile acid leakage into the submucosa after initial cholangiocyte injury may serve as a possible mechanism of disease propagation and progressive fibrosis in cholangiopathies.


title: Secondary sexual dimorphism traits under abiotic stress in dioecious species: The case of Amaranthus palmeri

abstract: The evolution of secondary sex-specific traits of dioecious species under abiotic stress conditions has received limited research, especially in the case of Amaranthus palmeri, a fast adapting and highly competing plant. Here, we have examined the interactive effects of abiotic stress on mineral accumulation, chlorophyll a and b content, and the operating capacity of Photosystem II (PSII) in both male and female A. palmeri plants grown under three different intensities (150, 450 and 1300 mol photons m-2 s-1) of white light, and under N, K or P deficiency. Mineral profiling of the leaves and stems (with inflorescence) highlighted intra- and intersexual differences in their accumulation pattern and mineral associations. Chlorophyll a and b content was different between the male and the female plants, being lower in the latter, at high light intensity, especially as the flowering progressed, or when they were under K or P deficient condition. Further, the chlorophyll a/b ratio was lower at the higher light intensity in the female, over that in the male, plants. Chlorophyll fluorescence parameters, i.e., steady state (FS) and maximum (FM) fluorescence increased under high light intensity, whereas the PSII operating efficiency ({Phi}PSII) decreased in the female plants, indicating reduced PSII capacity. Sex-specific differences in A. palmeri showed a differential response to stressful conditions because of differences in their ontogeny and physiology, and possibly due to the cost of reproduction. We suggest that the breeding system of dioecious species has weaknesses that can be used for the ecological management of dioecious weed species.


title: Multi-omics approach reveals dysregulation of protein phosphorylation correlated with lipid metabolism in mouse fatty liver

abstract: Obesity caused by overnutrition is a major risk factor for non-alcoholic fatty liver disease (NAFLD). Several lipid intermediates such as fatty acids, glycerophospholipids and sphingolipids are implicated in NAFLD, but detailed characterization of lipids and their functional links to proteome and phosphoproteome remain to be elucidated. To characterize this complex molecular relationship, we used multi-omics approach by conducting comparative proteomic, phoshoproteomic and lipidomic analyses of high fat (HFD) and low fat (LFD) diet fed mice livers. We quantified 2447 proteins and 1339 phosphoproteins containing 1650 class I phosphosites (with localization probability > 0.75), of which 669 phosphosites were significantly different between HFD and LFD mice livers. We detected alterations of proteins associated with cellular metabolic processes such as small molecule catabolic process, monocarboxylic acid, long- and medium-chain fatty acid, and ketone body metabolic processes, and peroxisome organization. We observed significant downregulation of protein phosphorylation in HFD fed mice liver in general. Untargeted lipidomics identified upregulation of triacylglycerols, glycerolipids and ether glycerophosphocholines and downregulation of glycerophospholipids such as lysoglycerophospholipids, as well as ceramides and acylcarnitines. Analysis of differentially regulated phosphosites revealed phosphorylation dependent deregulation of insulin signaling as well as lipogenic and lipolytic pathways during HFD induced obesity. Thus, this study reveals a molecular connection between decreased protein phosphorylation and lipolysis, as well as lipid-mediated signaling in diet-induced obesity.


title: Endocytosis-mediated vitellogenin absorption and lipid metabolism in the hindgut-derived pseudoplacenta of the viviparous teleost Xenotoca eiseni

abstract: Certain viviparous animals possess mechanisms for mother-to-embryo nutrient transport during gestation. Xenotoca eiseni is one such viviparous teleost species in which the mother supplies proteins and other components to the offspring developing in the ovary. The embryo possesses trophotenia, a hindgut-derived pseudoplacenta to receive the maternal supplement. However, the molecular mechanisms underlying viviparous non-mammalian animals remain elusive. We conducted this study to investigate the mechanism for nutrient absorption and degradation in trophoenia of X. eiseni. The tracer assay indicated that a lipid transfer protein, vitellogenin (Vtg), was absorbed into the epithelial layer cells of trophotaenia. Vtg uptake was significantly suppressed by Pitstop-2, an inhibitor of clathrin-mediated endocytosis. Gene expression analysis indicated that the genes involved in endocytosis-mediated lipolysis and lysosomal cholesterol transport were expressed in trophotaenia. In contrast, plasma membrane transporters expressed in the intestinal tract were not functional in trophotaenia. Our results suggested that endocytosis-mediated lysosomal lipolysis is one of the mechanisms underlying maternal component metabolism. Thus, our study demonstrated how viviparous teleost species have acquired a unique developmental system that is based on the hindgut-derived pseudoplacenta.


title: Brain signatures for neuropsychological and everyday memory achieve high replicability and explanatory power in two data cohorts

abstract:
BackgroundThe "brain signature of cognition" concept has garnered interest as a data-driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of clinical outcomes. However, to be a robust brain phenotype, the signature approach requires a statistical foundation showing that model performance replicates across a variety of cohorts. Here, we outline a procedure that provides this foundation for a signature models of two memory-related behavioral domains.

MethodIn each of two independent data cohorts, we derived regional brain gray matter thickness associations for neuropsychological and everyday cognition memory, testing for replicability. In each cohort we computed regional association to outcome in 40 randomly selected "discovery subsets" of size N = 400; we generated spatial overlap frequency maps and selected high-frequency regions as "consensus" signature masks for each cohort. We tested replicability by comparing cohort-based consensus model fits in all discovery sets. We tested explanatory power in each full cohort, compare signature model fits with competing "standard" models of each outcome.

ResultSpatial replications produced strongly convergent consensus signature regions derived from UCD and ADNI. Consensus model fits were highly correlated in 40 random subsets of each cohort indicating high replicability. In comparisons over each full cohort, signature models outperformed other models with one exception.

ConclusionMultiple random model generations, followed by consensus selection of regional brain substrates, produced signature models that replicated model fits to outcome and outperformed other commonly used measures. Robust biomarkers of cognition and everyday function may be achievable by this method.

FundingThis project was funded by R01 AG052132 (NIH/NIA)

category: neuroscience


title: D2 dopamine receptor expression, sensitivity to rewards, and reinforcement learning in a complex value-based decision-making task

abstract: In the basal ganglia, different dopamine subtypes have opposing dynamics at post-synaptic receptors, with the ratio of D1 to D2 receptors determining the relative sensitivity to gains and losses, respectively, during value-based learning. This effective sensitivity to reward feedback interacts with phasic dopamine levels to determine the effectiveness of learning, particularly in dynamic feedback situations where frequency and magnitude of rewards need to be integrated over time to make optimal decisions. Using both simulations and behavioral data in humans, we evaluated how reduced sensitivity to losses, relative to gains, leads to suboptimal learning in the Iowa Gambling Task (IGT), a complex value-learning task. In the behavioral data, we tested individuals with a variant of the human dopamine receptor D2 (DRD2; -141C Ins/Del and Del/Del) gene that associates with lower levels of D2 receptor expression (N=119) and compared their performance to non-carrier controls (N=319). The magnitude of the reward response was measured by looking at ventral striatal (VS) reactivity to rewards in the Cards task using fMRI. DRD2 variant carriers had generally lower performance in the IGT than non-carriers, consistent with reduced sensitivity to losses. There was also a positive association between VS reactivity and performance in the IGT, however, we found no statistically significant difference in this effect between DRD2 carriers and non-carriers. Thus, while reduced D2 receptor expression was associated with less efficient learning in the IGT, we did not find evidence for the moderation of this effect by the magnitude of the reward response.


title: Silencing KCC2 in mouse dorsal hippocampus compromises spatial and contextual memory

abstract: Delayed upregulation of the neuronal chloride extruder KCC2 underlies the progressive shift in GABA signaling polarity during development. Conversely, KCC2 downregulation is observed in a variety of neurological and psychiatric disorders often associated with cognitive impairment. Reduced KCC2 expression and function in mature networks may disrupt GABA signaling and promote anomalous network activities underlying these disorders. However, the causal link between KCC2 downregulation, altered brain rhythmogenesis and cognitive function remains elusive. Here, by combining behavioral exploration with in vivo electrophysiology we assessed the impact of chronic KCC2 silencing in mouse dorsal hippocampus and showed it compromises both spatial and contextual memory. This was associated with altered hippocampal rhythmogenesis and neuronal hyperexcitability, with increased CA1 pyramidal cell burst firing during non-REM sleep. Reducing neuronal excitability with terbinafine, a specific Task-3 leak potassium channel activator, occluded the impairment of contextual memory upon KCC2 silencing. Our results establish a causal relationship between KCC2 expression and cognitive performance and suggest that impaired rhythmopathies and neuronal hyperexcitability are central to the deficits caused by KCC2 silencing in the adult mouse brain.


title: Polyfunctional pathogen-specific CD4+ T cells reside in the lungs and tumors of NSCLC patients

abstract: Local T cell responses are required for optimal protection of the lungs against airborne pathogens. This localized protection is mediated by various immune cells, including resident memory T cells (TRM). While human lung CD8+ TRM line the epithelium and are enriched for recognition of respiratory viruses, we found CD4+ TRM to exhibit more heterogeneous localization patterns, surrounding airways, forming clusters in the lung parenchyma, and lining the epithelium. This heterogeneity was also reflected functionally, as lung CD4+ TRM were enriched for recognition of diverse classes of respiratory pathogens. Upon stimulation, lung CD4+ TRM expressed different polyfunctional cytokine profiles depending on the pathogen recognized. CD4+ TRM responding to respiratory viruses and bacteria were biased for production of IFN-{gamma} and IL-17, respectively. Strikingly, pathogen-specific CD4+ TRM also represent a significant fraction in NSCLC tumors that remained polyfunctional despite high PD-1 expression. These findings are not only important for vaccine design, but also provide a rationale for reinvigorating anti-tumor immunity through triggering of polyfunctional pathogen-specific CD4+ tumor infiltrating lymphocytes.


title: Every single conidium in Aspergillus fumigatus caspofungin tolerant strains are intrinsically caspofungin tolerant

abstract: Aspergillus fumigatus is a human fungal pathogen that causes a disease named aspergillosis. Echinocandins, such as the fungistatic drug caspofungin (CAS) are used as second-line therapy. Some A. fumigatus clinical isolates can survive and grow in higher CAS concentrations, a phenomenon known as "caspofungin paradoxical effect" (CPE). Here we investigate if CPE is due to a subpopulation of conidia produced by a CAS tolerant strain, indicative of a persistence phenotype or is caused by all the conidia which would be consistent with a tolerance phenotype. We evaluated 67 A. fumigatus clinical isolates for CPE growth and used a novel CPE Index (CPEI) classified them as CPE+ (CPEI [≥] 0.40) or CPE- (CPEI [≤] 0.20). Conidia produced by three CPE+ clinical isolates, CEA17 (CPEI=0.52), Af293 (CPEI=0.64), CM7555 (CPEI=0.58) all showed the ability to grow in high levels of CAS while all conidia produced by the CPE- isolate IFM61407 (CPEI=0.12) strain showed no evidence of tolerance. Given the importance of calcium/calcineurin/transcription factor CrzA pathway in CPE regulation, we also evaluated {Delta}crzAAf293 (CPE-) and {Delta}crzACEA17 (CPE+) conidia tolerance to CAS. All {Delta}crzACEA17 conidia showed CPE+ while 100 % of {Delta}crzAAf293 spores are CPE-. As all spores derived from an individual strain are phenotypically indistinct with respect to CPE it is likely that CPE is a genetically encoded adaptive trait that should be considered an antifungal tolerant phenotype. As the CPEI shows that the strength of the CPE is not uniform between strains we propose that the mechanisms that govern this phenomenon are multi-factorial.

category: microbiology


title: Activation and inhibition of the C-terminal kinase domain of p90 ribosomal S6 kinases

abstract: The p90 ribosomal S6 kinases (RSKs) contain two distinct catalytic kinase domains, the N-terminal and C-terminal kinase domains (NTKD and CTKD, respectively). The activation of CTKD is regulated by phosphorylation by extracellular signal-regulated kinase (ERK1/2) and an autoinhibitory L helix. Through a mutational series in vitro of the RSK CTKDs, we found a complex mechanism lifting autoinhibition that led us to design constitutively active RSK CTKDs. These are based on a phosphomimetic mutation and a C-terminal truncation (e.g. RSK2 T577E D694*) where a high activity in absence of ERK phosphorylation is obtained. Using these constructs, we characterize IC50 values of ATP-competitive inhibitors and provide a setup for determining specificity constants (kinact/Ki) of covalent CTKD inhibitors.

category: biochemistry


title: Dual-Drug Loaded Biomimetic Chitosan-Collagen Hybrid Nanocomposite Scaffolds for Ameliorating Potential Tissue Regeneration in Diabetic Wounds

abstract: Diabetes Mellitus (DM) is one of the most concerning conditions, and its chronic complications are nearly synonymous with inflammation, oxidative stress, and infections. In the acute inflammatory phase of diabetic wound healing (DWH), reducing excessive reactive oxygen species (ROS) and inflammatory response of the wound is a necessary treatment. The current work used a mix of emulsification and lyophilization approaches to investigate the effects of resveratrol microparticles (RES-GMS) loaded chitosan-collagen (CS-CLG) scaffold with doxycycline (DOX) on DWH. Resveratrol (RES) is a powerful antioxidant that promotes cell proliferation in the dermis by improving fibroblast function and enhancing CLG production. DOX can potentially shift the balance away from the chronic wounds pro-inflammatory, proteolytic status toward an environment that promotes vascular ingrowth and, eventually, epithelial development. Cross-linked scaffolds had optimal porosity, reduced matrix degradation, and prolonged drug release when compared to non-cross-linked scaffolds, according to the results of composite scaffold characterization. Cell proliferation assay employing mouse fibroblasts was used to study the kinetics and bioactivity of growth factors produced from the scaffold. The RES-DOX-CS-CLG scaffold was biocompatible and promoted cell development compared to the control and CS-CLG scaffolds in in vitro experiments. DOX-loaded CS-CLG scaffold loaded with R-GMS delivers a prolonged release of RES, according to in vitro tests.


title: A Bayesian Hierarchical Model for Signal Extraction from Protein Microarrays

abstract: SO_SCPLOWUMMARYC_SCPLOWProtein microarrays are a promising technology that measure protein levels in serum or plasma samples. Due to the high technical variability of these assays and high variation in protein levels across serum samples in any population, directly answering biological questions of interest using protein microarray measurements is challenging. Using within-array ranks of protein levels for analysis can mitigate the impact of between-sample variation on downstream analysis. Although ranks are sensitive to pre-processing steps, ranking methods that accommodate uncertainty provide robust and loss-function optimal ranks. Such ranking methods require Bayesian modeling that produces full posterior distributions for parameters of interest. Bayesian models that produce such outputs have been developed for other assays, for example DNA microarrays, but those modeling assumptions are not appropriate for protein microarrays. We develop and evaluate a Bayesian model to extract a full posterior distribution of normalized fluorescent signals and associated ranks for protein microarrays, and show that it fits well to data from two studies that use protein microrarrays from different manufacturing processes. We validate the model via simulation and demonstrate the downstream impact of using estimates from this model to obtain optimal ranks.


title: Acoustic detection and identification of individual rooks in field recordings using multi-task neural networks

abstract: Individual-level monitoring is essential in many behavioural and bioacoustics studies, but collecting these data is costly in human effort. Many studies of bird vocalisations in particular also involve manipulating the animals or human presence during observations, which can bias vocal production. Autonomous recording units can be used to collect large amounts of data without human supervision, largely removing these sources of bias. Moreover, the recent progress of deep learning greatly facilitated analysing these large amounts of data, for instance to extract vocalisations, classify the species, or classify the vocalisation types in recordings. Acoustic individual identification, however, has so far largely remained limited to a single vocalisation type for a given species, preventing the use of these techniques for automated data collection. We developed a deep convolutional neural network to detect vocalisations as well as identify individuals regardless of the vocalisation produced. We tested it in a group of rooks, a Eurasian social corvid with a diverse vocal repertoire, and found the system to work reliably for these tasks. Our system represents a powerful tool to individually monitor groups of animals in both outdoor and indoor settings, even across long periods of time, and regardless of a species vocal complexity.


title: Comprehensive dissection of immune microenvironment in the progression of early gastric cancer at spatial and single-cell resolution

abstract: While the changes of tumor immune microenvironment (TME) have critical implications for most tumor progression, works that could reveal the compositions and immunity features of TME are needed. Profiling gastric malignant cells at single-cells resolution has shown the transcriptional heterogeneity is represented at different states of gastric cancer, implying that diverse cell states may exist, including immune cells, and all components in TME make some balances in early gastric cancer (EGC) progression. However, it remains unclear how immune cells contributing malignancy of gastritis, constituting general characteristics of gastric TME. Furthermore, the role of specific interactions among cells in gastric TME remains to be illustrated. Here, we performed spatial transcriptomes and single-cell RNA-seq analysis across 18 gastric samples, identifying 17 celltypes and reconstructing their location information. We found that immune cells represented different degree of dysregulations during the progression from non-atrophic gastritis (NAG), atrophic gastritis (AG) to EGC, including imbalance of cytotoxic and inhibitory effects in T cells, maturation inhibition in B cells and malignant genes up-regulated obviously in myeloid cells. Besides, pathway activities showed that hypoxia, reactive oxygen species and fatty metabolism signaling were activated from AG stage, which may accelerate progression of EGC. Moreover, cellular interactions further identified the roles of hypoxia in gastric TME. Overall, the multi-omics data presented in this study offer a comprehensive view of immune cell types, states changes and locations within the gastric tissues during the progression from NAG, AG to EGC, advancing our understanding of the composition and immunity of different gastric states, offering diagnostic and preventive thoughts for EGC.


title: Inhibition of Glycogen Metabolism Induces Reactive Oxygen Species-Dependent Apoptosis in Anaplastic Thyroid Cancer

abstract:
Anaplastic thyroid cancer (ATC) is one of the most lethal solid tumors, yet there are no effective, long-lasting treatments for ATC patients. Most tumors, including tumors of the endocrine system, exhibit an increased consumption of glucose to fuel cancer progression, and some cancers meet this high glucose requirement by metabolizing glycogen. Our goal was to determine if ATC cells metabolize glycogen and if this could be exploited for treatment. We detected glycogen synthase and glycogen phosphorylase (PYG) isoforms in normal thyroid and thyroid cancer cell lines and patient-derived biopsy samples. Inhibition of PYG using CP-91,149 induced apoptosis in ATC cells but not normal thyroid cells. CP-91,149 decreased NADPH levels and induced reactive oxygen species accumulation. CP-91,149 severely blunted ATC tumor growth in vivo. Our work establishes glycogen metabolism as a novel metabolic process in thyroid cells that presents a unique, oncogenic target that could offer an improved clinical outcome.

SignificanceGlycogen metabolism plays an important role in combating reactive oxygen species and apoptosis in anaplastic thyroid cancer. Glycogen phosphorylase was inhibited with small molecule inhibitors that limited cell proliferation in vitro and blunted tumor growth in a nude mouse xenograft. This study demonstrates that glycogen metabolism is a viable target in one of the most lethal solid tumors.


title: Notch signaling in tumor vasculature programs cancer-associated fibroblasts to suppress anti-tumor immunity

abstract:
Scarcity of tumor-infiltrating T cells poses significant challenges to cancer treatment, but mechanisms that regulate T cell recruitment into the tumor microenvironment are unclear. Here we ask if the endothelial lining of tumor vasculature suppresses T cell infiltration. Using mouse pancreatic ductal adenocarcinoma models, we found that Notch signaling in endothelial cells (ECs) inhibits the pro-inflammatory functions of cancer-associated fibroblasts (CAFs) and prevents CAFs from secreting CXCL10, a chemokine that recruits anti-tumor T cells via its receptor CXCR3. Abrogation of canonical Notch signaling in ECs reprogrammed the phenotype of CAFs from myofibroblasts into pro-inflammatory fibroblasts, unleashed interferon gamma (IFN{gamma}) responses in the tumor, and stimulated CXCL10/CXCR3-mediated recruitment of T cells to inhibit tumor growth. Collectively, these data uncover an important role of endothelial Notch signaling in shaping the tumor immune microenvironment, and suggest the potential of targeting EC-CAF crosstalk as an approach to enhance anti-tumor immunity in immunologically cold tumors.

In briefHow blood vasculature shapes the tumor immune microenvironment is poorly defined. This study demonstrates that tumor endothelial cells reprogram cancer-associated fibroblasts to limit anti-tumor T cell recruitment, and suggests the potential of targeting endothelium-fibroblast crosstalk to overcome T cell scarcity in "cold" tumors and enhance anti-tumor immunity.


title: The GDF15-GFRAL pathway is dispensable for the effects of metformin on energy balance

abstract: Metformin is a blood glucose lowering medication with physiological effects that extend beyond its anti-diabetic indication. Recently, it was reported that metformin lowers body weight via induction of growth differentiation factor 15 (GDF15), which suppresses food intake by binding to the GDNF family receptor -like (GFRAL) in the hindbrain. At the same time, we demonstrated that recombinant GDF15 suppresses voluntary exercise in a GFRAL-dependent fashion. Here, we corroborate that metformin increases circulating GDF15 in mice and humans, but that it does not reduce voluntary running activity in mice. Unexpectedly, we fail to confirm previous reports that the GDF15-GFRAL pathway is necessary for the weight-lowering effects of metformin. Instead, our studies in wild-type, GDF15 knockout and GFRAL knockout mice suggest that the GDF15-GFRAL pathway is dispensable for the effects of metformin on energy balance. The data presented here question whether metformin is a sufficiently strong stimulator of GDF15 to drive anorexia and weight loss and emphasize that additional work is needed to untangle the relationship among metformin, GDF15 and energy balance.


title: Apiaceae FNS I originated from F3H through tandem gene duplication

abstract:
BackgroundFlavonoids are specialized metabolites with numerous biological functions in stress response and reproduction of plants. Flavones are one subgroup that is produced by the flavone synthase (FNS). Two distinct enzyme families evolved that can catalyze the biosynthesis of flavones. While the membrane-bound FNS II is widely distributed in seed plants, one lineage of soluble FNS I appeared to be unique to Apiaceae species.

ResultsWe show through phylogenetic and comparative genomic analyses that Apiaceae FNS I evolved through tandem gene duplication of flavanone 3-hydroxylase (F3H) followed by neofunctionalization. Currently available datasets suggest that this event happened within the Apiaceae in a common ancestor of Daucus carota and Apium graveolens. The results also support previous findings that FNS I in the Apiaceae evolved independent of FNS I in other plant species.

ConclusionWe validated a long standing hypothesis about the evolution of Apiaceae FNS I and predicted the phylogenetic position of this event. Our results explain how an Apiaceae-specific FNS I lineage evolved and confirm independence from other FNS I lineages reported in non-Apiaceae species.


title: Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum using Multiscale Phenotypes

abstract: Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.


title: Sexually dimorphic architecture and function of a mechanosensory circuit in C. elegans

abstract: How sensory perception is processed by the two sexes of an organism is still only partially understood. Despite some evidence for sexual dimorphism in auditory and olfactory perception, whether touch is sensed in a dimorphic manner has not been addressed. Here we find that the neuronal circuit for tail mechanosensation in C. elegans is wired differently in the two sexes and employs a different combination of sex-shared sensory neurons and interneurons in each sex. Reverse genetic screens uncovered cell- and sex-specific functions of the alpha-tubulin mec-12 and the sodium channel tmc-1 in sensory neurons, and of the glutamate receptors nmr-1 and glr-1 in interneurons, revealing the underlying molecular mechanisms that mediate tail mechanosensation. Moreover, we show that only in males, the sex-shared interneuron AVG is strongly activated by tail mechanical stimulation, and accordingly is crucial for their behavioral response. Importantly, sex reversal experiments demonstrate that the sexual identity of AVG determines both the behavioral output of the mechanosensory response and the molecular pathways controlling it. Our results present for the first time extensive sexual dimorphism in a mechanosensory circuit at both the cellular and molecular levels.


title: Interaction Interface between 5-HT3A serotonin receptor and chaperone RIC-3

abstract: Serotonin or 5-hydroxytryptamine receptors type 3 (5-HT3) belong to the family of pentameric ligand-gated ion channels (pLGICs), which also includes other neurotransmitter-gated ion channels such as nicotinic acetylcholine receptors, {gamma}-amino butyric acid A receptors, and glycine receptors. pLGICs have been long-standing clinical targets for treating psychiatric disorders such as anxiety, schizophrenia, addiction, and neurological diseases like Alzheimers and Parkinsons disease. Due to the highly-homologous structures of pLGICs extracellular and transmembrane domains, clinical trials for drug candidates targeting these domains have been largely hampered by undesired effects mediated by off-subunit modulation. With the present study, we explore the interaction interface of the 5-HT3A intracellular domain (ICD) with the resistance to inhibitors of choline esterase (RIC-3) chaperone. Protein-protein interactions are attractive and successful targets for contemporary drug development. Previously, we have shown that RIC-3 physically interacts with 5-HT3A subunits, and we identified the L1-MX fragment of the ICD fused to maltose-binding protein as sufficient for interaction. For the present study, synthetic L1-MX-based fragments and Ala-scanning were used to probe binding to RIC-3 using a pull-down assay. In complementary studies with full-length 5-HT3A subunits, we investigated the impact of these substitutions on modulation of functional surface expression by RIC-3 using two-electrode voltage-clamp recording after expression in Xenopus laevis oocytes. Our data demonstrate that the 5-HT3A-MX segment contains the interaction interface, and that residues W347, R349, and L353 are critical for the interaction with RIC-3.


title: Maximizing citizen scientists' contribution to automated species recognition

abstract: Technological advances and data availability have enabled artificial intelligence-driven tools that can increasingly successfully assist in identifying species from images. Especially within citizen science, an emerging source of information filling the knowledge gaps needed to solve the biodiversity crisis, such tools can allow participants to recognize and report more poorly known species. This can be an important tool in addressing the substantial taxonomic bias in biodiversity data, where broadly recognized, charismatic species are highly overrepresented. Meanwhile, the recognition models are trained using the same biased data, so it is important to consider what additional images are needed to improve recognition models. In this study, we investigated how the amount of training data influenced the performance of species recognition models for various taxa. We utilized a large Citizen Science dataset collected in Norway, where images are added independently from identification. We demonstrate that while adding images of currently under-represented taxa will generally improve recognition models more, there are important deviations from this general pattern. Thus, a more focused prioritization of data collection beyond the basic paradigm that "more is better" is likely to significantly improve species recognition models and advance the representativeness of biodiversity data.


title: Prey Size Spectra and Predator:Prey ratios of 7 Species of New Zealand Salps

abstract: While the importance of salp grazing has become increasingly apparent in shaping their local ecosystems, little is known about the size ranges of their prey in the field. This study investigated the feeding habits of 7 different species of salp of both solitary and aggregate life stages representing a variety of sizes across subtropical and subantarctic waters east of New Zealand. Scanning electron microscopy was used to examine the gut contents of 58 salps, which were then compared to water column communities sampled via epifluorescence microscopy, FlowCam, and flow cytometry. While most of the gut size spectra and taxonomy resembled ambient waters, substantial differences were found amongst some co-occurring species, such as increased retention of submicron bacteria by Thalia democratica. We find that even for such salps capable of feeding on bacteria efficiently, the majority of gut biomass was still made up by nanoplankton and small microplankton. Larger particles were much rarer in the guts than in the water column, potentially suggesting an upper size-threshold in addition to the lower size-threshold that has been the focus of much previous work. Salp carbon-weighted predator to prey size ratios were variable, with the majority falling between 1000:1 and 10000:1 depending largely on the size of the salp. Taken together our results indicate that despite being able to feed on submicron particles, picoplankton are relatively unimportant to the energetics of most salps in this region compared to nanoplankton such as small dinoflagellates and diatoms.


title: Measuring drift by mean deviation: unequal breeding sex ratio revisited

abstract: When it comes to estimating the magnitude of genetic drift, there is hardly any indexes other than the effective population size. Starting from the binomial sampling distribution, this research proposed using mean deviation of allele frequency change as a direct measurement of drift, then tested it in a classical example concerning unequal breeding sex ratio. This study found that: (1) mean deviation offers a new dimension in measuring the magnitude of drift; (2) the measurement displays a "half-half" pattern; (3) allele frequency determines the efficacy of hitchhiking effect of rare alleles, and in what way that "half-half" pattern should be divided.


title: Assessing base-resolution DNA mechanics on the genome scale

abstract: Intrinsic DNA properties such as bending play a crucial role in diverse biological systems. A recent advantage in the high-throughput method called loop-seq makes it possible to determine bendability of hundred thousand 50-bp DNA duplexes in one experiment. However, its still infeasible to assess whole sequence bendability in large genomes such as human, which needs thousands of loop-seq experiments. Here we introduce  BendNet - a neural network to accurately predict the intrinsic DNA bending at base-resolution by only given DNA sequences. BendNet can increase the resolution of experimental results, and can predict DNA bendability for any new given sequences in high accuracy. We applied BendNet to the human genome and observed high-stiffness regions located at both transcriptional start sites and transcriptional end sites. Such stiffness patterns are different for coding and non-coding genes, which matches distinct nucleosome occupancy patterns. As expected, most transcription factors (TFs) bind in DNA of low bendability. In contrast, we observed an unusually high bendability within binding elements of specific TFs such as EBF1 and regulators of genome folding such as CTCF. These factors either co-bind or compete with nucleosomes to carry out their functions. More interestingly, CTCF binding regions exhibit the highest bendability than other DNA elements, implying their potential role in trapping and holding the CTCF in the exact locations to make sure CTCF as stable anchor in loop extrusion process. Our work provides a tool to assess DNA bendability for large-scale DNA sequences and expands our understanding on DNA mechanics in chromatin regulation and genome folding.

category: genomics


title: Multi-ancestry genome-wide analysis identifies common genetic variants for self-reported sleep duration and shared genetic effects

abstract: Both short and long sleep duration are associated with increased risk of chronic diseases, but the genetic determinants of sleep duration are largely unknown outside of European populations. Here we report transferability of a polygenic score of 78 European ancestry sleep duration SNPs to an African (n=7,288; p=0.003), a South Asian (n=7,485; p=0.025), and a Japanese (n=13,618; p=6x10-4) cohort, but not to a cohort of Hispanic/Latino (n- XXX; p=0.71) participants. Furthermore, in a pan-ancestry (N = 483,235) meta-analysis of genome-wide association studies (GWAS) for habitual sleep duration, 5 novel and 68 known loci are associated with genome-wide significance. For the novel loci, sleep duration signals colocalize with expression-QTLs for PRR12 and COG5 in brain tissues, and pleiotropic associations are observed with cardiovascular and neuropsychiatric traits. Overall, our results suggest that the genetic basis of sleep duration is at least partially shared across diverse ancestry groups.


title: Generating an in vitro gut model with physiologically relevant biophysical mucus properties

abstract:
IntroductionGastrointestinal (GI) in vitro models have received lasting attention as an effective tool to model drug and nutrient absorption, study GI diseases, and design new drug delivery vehicles. A complete model of the GI epithelium should at a minimum include the two key functional components of the GI tract: mucus and the underlying epithelium. Mucus plays a key role in protecting and lubricating the GI tract, poses a significant barrier to orally administered therapies and pathogens, and serves as the microbiome niche microenvironment. These functions are reliant on the biophysical material properties of the mucus produced, including viscosity and pore size.

MethodsIn this study, we generated in vitro models containing Caco-2 enterocyte-like cells and HT29-MTX goblet-like cells and determined the effects of coculture and mucus layer on epithelial permeability and biophysical properties of mucus using multiple particle tracking (MPT).

ResultsWe found that mucus height increased as the amount of HT29-MTX goblet-like cells increased. Additionally, we found that increasing the amount of HT29-MTX goblet-like cells within culture corresponded to an increase in mucus pore size and mucus microviscosity, measured using MPT. When compared to ex vivo mucus samples from mice and pigs, we found that an 80:20 ratio of Caco-2:HT29-MTX coculture displayed similar mucus pore size, microviscosity, and elastic modulus to those of porcine ileum.

ConclusionsThese coculture models could be valuable tools in simulating the mucus barrier and mucus microenvironment and can be utilized for a variety of applications including the study of GI diseases, food absorption, or therapeutic development.


title: Protein Stability Changes upon Point Mutations Identified with a Gaussian Network Model Simulating Protein Unfolding Behavior

abstract:
Understanding the effects of missense mutations on protein stability is a widely acknowledged significant biological problem. Genomic missense mutations may alter one or more amino acids leading to increased or decreased stability of the encoded proteins. In this study, we propose a novel approach - Protein Stability Prediction with a Gaussian Network Model (PSP-GNM) to study the effect of single amino acid substitutions on protein stability. Specifically, PSP-GNM employs a coarse-grained Gaussian Network Model (GNM) that has interactions between amino acids weighted by the Miyazawa-Jernigan (MJ) statistical potential. We use PSP-GNM to simulate partial unfolding of the wildtype and mutant structures and then, use the difference in energies of the unfolded wildtype and mutant protein structures to estimate the experimentally obtained unfolding free energy change ({Delta}{Delta}G). We verify the extent of correspondence between the {Delta}{Delta}G calculated by PSP-GNM and the {Delta}{Delta}G obtained experimentally using three datasets: 350 forward mutations from 66 proteins, 2298 forward mutations from 126 proteins and 611 forward and reverse mutations from 66 proteins and observe Pearson correlation coefficient (PCC) as high as 0.58 and root mean-squared error (RMSE) as low as 1.24 kcal/mol. The performance is comparable to the existing state of the art methods. Importantly, we do observe an increase in the correlation to 0.73 and decrease in RMSE to 1.07 when considering only those measurements made close to 25{degrees}C and neutral pH, suggesting a strong dependence on temperature and pH. PSP-GNM is written in Python and is available as a free downloadable package at https://github.com/sambitmishra0628/PSP-GNM.

Author SummaryUnderstanding how genomic missense mutations impact the thermodynamic stability of encoded proteins is important to understand disease etiology. Specifically, mutant proteins are often functionally inactive and underlie numerous genetic and neurodegenerative diseases. A classic example is sickle cell anemia - a single amino acid change significantly affects hemoglobins binding affinity for oxygen. To be able to identify mutations that would likely impact the protein function and stability is therefore essential and is the focus of our study. We present an approach that relies on utilizing the intrinsic dynamics of protein structures to predict the effect of single amino acid mutations (point mutations) on protein stability. In our approach, we model proteins as coarse-grained beads (amino acids) and springs (interactions), simulate protein unfolding and identify putative residue-residue contacts that are broken during the unfolding process. We demonstrate that the knowledge of broken contacts and their order is essential in describing the thermodynamic differences between wildtype and mutant proteins. We also highlight the importance of residue-residue interactions at the mutation site in the context of protein stability prediction. Our findings present novel avenues to interpret how genomic mutations may manifest in the encoded proteins.


title: DGMP: Identifying Cancer Driver Genes by Jointing DGCN and MLP from Multi-omics Genomic Data

abstract: Identification of cancer driver genes plays an important role in precision oncology research, which is helpful to understand the cancer initiation and progression. However, most of existing computational methods mainly used the protein-protein interaction networks (PPIs), or treated the directed gene regulatory networks (GRNs) as the undirected gene-gene association networks to identify the cancer driver genes, which will lose the unique structure regulatory information in the directed GRNs, and then affect the outcome of the cancer driver genes identification. Here, based on the multi-omics pan-cancer data (i.e., gene expression, mutation, copy number variation and DNA methylation), we proposed a novel method (called DGMP) to identify cancer driver genes by jointing Directed Graph Convolution Network (DGCN) and Multilayer Perceptron (MLP). DGMP learns the multi-omics features of genes as well as the topological structure features in GRN with DGCN model, and uses MLP to weight more on gene features for mitigating the bias toward the graph topological features in DGCN learning process. The results on three gene regulation networks show that DGMP outperforms other existing state-of-the-art methods. It can not only identify highly mutated cancer driver genes but also the driver genes harboring other kinds of alterations (e.g., differential expression, aberrant DNA methylation) or genes involved in GRNs with other cancer genes. The source code of DGMP can be freely downloaded from https://github.com/NWPU-903PR/DGMP.


title: CRISPR-Detector: Fast and Accurate Detection, Visualization, and Annotation of Genome Wide Mutations Induced by Gene Editing Events

abstract: The leading edge of genome editing, driven especially by CRISPR/Cas technology, is revolutionizing life sciences. In pace with the burst of novel genome editing methods, bioinformatic tools to monitor the on/off-target events need to be more accurate and capable of detecting true editing-induced mutations. Existing tools suffer from limitations in speed and scalability, especially struggle in the whole genome sequencing data analysis which is believed to replace amplicon sequencing and become mainstream data type due to the rapidly decreasing sequencing cost. Here, we introduce our CRISPR-detector tool, which is either a web-hosted or locally deployable pipeline with five key innovations: 1) optimized scalability allowing for whole genome sequencing data analysis beyond BED file-defined regions; 2) improved accuracy benefited from haplotype based variant calling to handle sequencing errors; 3) treated and control sample co-analysis to remove background variants existing prior to genome editing; 4) integrated structural variation (SV) calling with additional focus on vector insertions from viral-mediated genome editing; 5) functional and clinical annotation of editing-induced mutations.


title: Detecting Cell Contact-dependent Gene Expression from Spatial Transcriptomics Data

abstract: Understanding the cellular microenvironment promises to deliver insights into disease and development, yet we still lack the ability to systematically leverage high resolution spatial transcriptomics to understand cell-cell interactions. With the aim of identifying cell-contact dependent genes, we propose a novel approach that explores the transcriptome of spatial beads composed of multiple cell types (heterotypic beads). Our approach identifies cell-contact dependent expression beyond what ligand-receptor co-expression can identify.


title: Assessing Protein Homology Models with Docking Reproducibility

abstract: Results of the most recent Critical Assessment of Protein Structure (CASP) competition demonstrate that protein backbones can be predicted with very high accuracy. In particular, the artificial intelligence methods of AlphaFold 2 from DeepMind were able to produce structures that were similar enough to experimental structures that many described the problem of protein prediction solved. However, for such structures to be used for drug docking studies requires precision in the placement of side chain atoms as well. Here we built a library of 1334 small molecules and examined how reproducibly they bound to the same site on a protein using QuickVina-W, a branch of the program Autodock that is optimized for blind searches. We discovered that the higher the backbone quality of the homology model the greater the similarity between the small molecule docking to the experimental and modeled structures. Furthermore, we found that specific subsets of this library were particularly useful for identifying small differences between the best of the best modeled structures. Specifically, when the number of rotatable bonds in the small molecule increased, differences in binding sites became more apparent.


title: The infiltration pattern of microenvironmental cells and different immune escape mechanisms in colorectal cancer

abstract:
BackgroundThe tumour microenvironment (TME) plays a crucial role in tumour progression and metastasis. However, the infiltration pattern of TME cells in CRC samples and the immune escape mechanism underneath have not been studied sufficiently.

MethodsTranscriptomic data from public datasets were retrieved online. In total, 1802 samples from the microarray dataset and 619 samples from the TCGA dataset were enrolled. The ssGSEA algorithm and unsupervised clustering were used for TME cells infiltration speculation and infiltration pattern recognition.

ResultsCRC samples can be classified into three distinct TME cell subtypes. Subtype 1, the immune-active subtype, was characterised by high infiltration of activated adaptive immune cells. Subtype 2, the immune-desert subtype, featured high tumour purity and low infiltration of immune and stromal cells. And subtype 3, stroma-rich subtype, had high infiltration of stromal cells. The stroma-rich subtype conferred a significantly worse prognosis. Three subtypes had different immune escape mechanisms. The immune-active subtype has the highest immune checkpoint expression level. In comparison, the immune-desert subtype had the lowest immunogenicity and the defective antigen presentation. And the stroma-rich subtype lacked activated immune cells.

ConclusionsDistinct TME cell subtypes and immune escape mechanisms may provide inspiration and direction for further researches on CRC immunotherapy.


title: Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer

abstract: Mismatch repair deficient colorectal cancers have high mutation loads and many respond to immune checkpoint-inhibitors. We investigated how genetic and immune landscapes co-evolve in these tumors. All cases had high truncal mutation loads. Driver aberrations showed a clear hierarchy despite pervasive intratumor heterogeneity: Those in WNT/{beta}Catenin, mitogen-activated protein kinase and TGF{beta} receptor family genes were almost always truncal. Immune evasion drivers were predominantly subclonal and showed parallel evolution. Pan-tumor evolution, subclonal evolution, and evolutionary stasis of genetic immune evasion drivers defined three MMRd CRC subtypes with distinct T-cell infiltrates. These immune evasion drivers have been implicated in checkpoint-inhibitor resistance. Clonality and subtype assessments are hence critical for predictive immunotherapy biomarker development. Cancer cell PD-L1 expression was conditional on loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and likely contributes to the high recurrence risk of MMRd CRCs with impaired CDX2 expression.