title: Limits and potential of combined folding and docking using PconsDock.

abstract: In the last decade, de novo protein structure prediction accuracy for individual proteins has improved significantly by utilising deep learning (DL) methods for harvesting the co-evolution information from large multiple sequence alignments (MSA). In CASP14, the best groups predicted the structure of most proteins with impressive accuracy. The same approach can, in principle, also be used to extract information about evolutionary-based contacts across protein-protein interfaces. However, most of the earlier studies have not used the latest DL methods for inter-chain contact distance prediction. This paper introduces a fold-and-dock method, PconsDock, based on predicted residue-residue distances with trRosetta. PconsDock can simultaneously predict the tertiary and quaternary structure of a protein pair, even when the structures of the monomers are not known. The straightforward application of this method to a standard dataset for protein-protein docking yielded limited success. However, using alternative methods for MSA generating allowed us to dock accurately significantly more proteins. We also introduced a novel scoring function, PconsDock, that accurately separates 98% of correctly and incorrectly folded and docked proteins. The average performance of the method is comparable to the use of traditional, template-based or ab initio shape-complementarity-only docking methods. However, no a priori structural information for the individual proteins is needed. Moreover, the results of conventional and fold-and-dock approaches are complementary, and thus a combined docking pipeline could increase overall docking success significantly. PconsDocck contributed to the best model for one of the CASP14 oligomeric targets, H1065.


title: STENCIL: A web templating engine for visualizing and sharing life science datasets

abstract: The ability to aggregate experimental data analysis and results into a concise and interpretable format is a key step in evaluating the success of an experiment. This critical step determines baselines for reproducibility and is a key requirement for data dissemination. However, in practice it can be difficult to consolidate data analyses that encapsulates the broad range of datatypes available in the life sciences. We present STENCIL, a web templating engine designed to organize, visualize, and enable the sharing of interactive data visualizations. STENCIL leverages a flexible web framework for creating templates to render highly customizable visual front ends. This flexibility enables researchers to render small or large sets of experimental outcomes, producing high-quality downloadable and editable figures that retain their original relationship to the source data. REST API based back ends provide programmatic data access and supports easy data sharing. STENCIL is a lightweight tool that can stream data from Galaxy, a popular bioinformatic analysis web platform. STENCIL has been used to support the analysis and dissemination of two large scale genomic projects containing the complete data analysis for over 2,400 distinct datasets. Code and implementation details are available on GitHub: https://github.com/CEGRcode/stencil

category: bioinformatics


title: COBREXA.jl: constraint-based reconstruction and exascale analysis

abstract:
COBREXA.jl is a Julia package for scalable, high-performance constraint-based reconstruction and analysis of very large-scale biological models. Its primary purpose is to facilitate the integration of modern high performance computing environments with the processing and analysis of large-scale metabolic models of challenging complexity. We report the architecture of the package, and demonstrate how the design promotes analysis scalability on several use-cases with multi-organism community models.

Availability and implementationhttps://doi.org/10.17881/ZKCR-BT30.

Contactchristophe.trefois@uni.lu, wei.gu@uni.lu

category: systems biology


title: Depth of sedation with dexmedetomidine modulates cortical excitability non-linearly

abstract:
BackgroundCortical excitability changes across conscious states, being higher in unconsciousness compared to normal wakefulness. Anaesthesia offers controlled manipulation to investigate conscious processes and underlying brain dynamics. Among commonly used anaesthetic agents, dexmedetomidine (DEX) effects are not completely known. In this study, we investigated cortical excitability as a function of DEX sedation depth.

MethodsTranscranial magnetic stimulation coupled with electroencephalography was recorded in 20 healthy subjects undergoing DEX sedation in four conditions (baseline, light sedation, deep sedation, recovery). Frontal and parietal cortices were stimulated using a neuronavigation system. Cortical excitability was inferred by slope, amplitude, positive and negative peak latencies of the first component (0-30 ms) of the TMS-evoked potential. Four Generalized Linear Mixed Models (GLMM) were used to test the effect of condition and brain region over cortical excitability.

ResultsDexmedetomidine modulated amplitude (P<0.001), slope (P=0.0001) and positive peak (P=0.042), while the targeted brain region affected amplitude (P<0.001), slope (P<0.001), and negative peak (P=0.001). The interaction between dexmedetomidine and region had an effect over amplitude (P=0.004), and slope (P=0.009) such that cortical excitability was higher during all conditions where DEX was present as compared to the baseline.

ConclusionsCortical excitability changes non-linearly as a function of the depth of DEX sedation, with a paradoxical non dose-dependent increase. The effect is region-specific, being present in the frontal but not in the parietal region. Future research should extend the current results with other anaesthetics to better understand the link between cortical excitability and depth of sedation.

category: neuroscience


title: Depletion of TAX1BP1 amplifies innate immune responses during respiratory syncytial virus infection

abstract:
Respiratory syncytial virus (RSV) is the main cause of acute respiratory infections in young children, and also has a major impact in the elderly and immunocompromised people. In the absence of vaccine or efficient treatment, a better understanding of RSV interactions with the host antiviral response during infection is needed. Previous studies revealed that cytoplasmic inclusion bodies (IBs) where viral replication and transcription occur could play a major role in the control of innate immunity during infection by recruiting cellular proteins involved in the host antiviral response. We recently showed that the morphogenesis of IBs relies on a liquid-liquid phase separation mechanism depending on the interaction between viral nucleoprotein (N) and phosphoprotein (P). These scaffold proteins are expected to play a central role in the recruitment of cellular proteins to IBs. Here, we performed a yeast two-hybrid screen using RSV N protein as a bait, and identified the cellular protein TAX1BP1 as a potential partner of N. This interaction was validated by pulldown and immunoprecipitation assays. We showed that TAX1BP1 suppression has only a limited impact on RSV infection in cell cultures. On the contrary, in vivo experiments showed that RSV replication is decreased in TAX1BP1KO mice, whereas the production of inflammatory and antiviral cytokines is enhanced. In vitro infection of either wild-type or TAX1BP1KO alveolar macrophages confirmed that the innate immune response to RSV infection is enhanced in the absence of TAX1BP1. Altogether, our results suggest that RSV could hijack TAX1BP1 to restrain the host immune response during infection.

ImportanceRespiratory syncytial virus (RSV), which is the leading cause of lower respiratory tract illness in infants, still remains a medical problem in the absence of vaccine or efficient treatment. This virus is also recognized as a main pathogen in the elderly and immunocompromised people, and the occurrence of co-infections (with other respiratory viruses and bacteria) amplifies the risks of developing respiratory distress. In this context, a better understanding of the pathogenesis associated to viral respiratory infections, which depends on both viral replication and the host immune response, is needed. The present study reveals that the cellular protein TAX1BP1, which interacts with the RSV nucleoprotein N, participates in the control of the innate immune response during RSV infection, suggesting that N-TAX1BP1 interaction represents a new target for the development of antivirals.

category: microbiology


title: Comparison of bacterial communities from the surface and adjacent bottom layers water of Billings reservoir

abstract:
Here, we describe the microbial diversity and physicochemical properties in freshwater samples from the surface and bottom layer of Billings reservoir in Sao Paulo state, Brazil. Twenty-two matched samples were characterized using the 16S rRNA gene Illumina MiSeq platform. Taxonomical composition revealed an abundance of Cyanobacteria phyla, followed by Proteobacteria, with 1903 and 2689 known bacterial genera in the surface and deep-water layers, respectively. Shannon diversity index ranging from 2.3 - 5.39 and 4.04 - 6.86 in the surface and bottom layer, respectively. Among the 120 pathogenic genera identified, Flavobacterium was the most predominant genus. Temperature and phosphorus concentration were the most influential factors in shaping the microbial communities of both layers. Predictive functional analysis suggests that the reservoir is enriched in motility genes involved in the flagellar assembly. The overall results present new information on the significantly altered diversity composition of the bacterial community detected in Billings freshwater reservoir.

IMPORTANCEIn this study, we investigated the bacterial distribution, community composition, potential metabolic activity, potentially pathogenic bacteria, and toxin genes of Cyanobacteria in the bottom layers and surface along Billings reservoir in the southeast of Brazi. Our results provide essential information about the pattern of bacterioplankton communities variation inhabiting the Billings reservoir and the combination of environmental that shaped their structure. These results may help pave the way for future studies devoted to control and improve the water quality in the Billings reservoir, which is facing rapid urban development and urbanization.


title: Mapping tree species for restoration potential resilient to climate change

abstract: The restoration of forest ecosystems is associated with key benefits for biodiversity and ecosystem services. Where possible, ecosystem restoration efforts should be guided by a detailed knowledge of the native flora to regenerate ecosystems in a way that benefits natural biodiversity, ecosystem services, and natures contribution to people. Machine learning can map the ecological suitability of tree species globally, which then can guide restoration efforts, especially in regions where knowledge about the native tree flora is still insufficient. We developed an algorithm that combines ecological niche modelling and geographic distributions that allows for the high resolution (1km) global mapping of the native range and suitability of 3,987 tree species under current and future climatic conditions. We show that in most regions where forest cover could be potentially increased, heterogeneity in ecological conditions and narrow species niche width limit species occupancy, so that in several areas with reforestation potential, a large amount of potentially suitable species would be required for successful reforestation. Local tree planting efforts should consider a wide variety of species to ensure that the equally large variety of ecological conditions can be covered. Under climate change, a large fraction of the surface for restoration will suffer significant turnover in suitability, so that areas that are suitable for many species under current conditions will not be suitable in the future anymore. Such a turnover due to shifting climate is less pronounced in regions containing species with broader geographical distributions. This indicates that if restoration decisions are solely based on current climatic conditions, a large fraction of the restored area will become unsuitable in the future. Decisions on forest restoration should therefore take the niche width of a tree species into account to mitigate the risk of climate-driven ecosystem degradation.

category: ecology


title: WeightedLD: The Application of Sequence Weights to Linkage Disequilibrium

abstract:
Sequence-weighting methods are commonly employed to account for biases in sequence datasets. We use a weighting scheme which considers the observed distinctiveness of sequences and apply it to calculations of linkage disequilibrium. Each sequence now contributes a weighted score to linkage disequilibrium measurements of pairwise loci. We demonstrate that this reduces the effect of uneven sampling, as underrepresented groups of sequences will each contribute more individually than redundant, similar sequences.

AvailabilitySource code for a python and rust implementation are freely available at under an MIT license at github.com/ojcharles/WeightedLD.

Contactr.goldstein@ucl.ac.uk or oscar.charles.18@ucl.ac.uk

category: genetics


title: Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity

abstract: Quantitative genetics states that phenotypic variation is a consequence of genetic and environmental factors and their subsequent interaction. Here, we present an enviromic assembly approach, which includes the use of ecophysiology knowledge in shaping environmental relatedness into whole-genome predictions (GP) for plant breeding (referred to as E-GP). We propose that the quality of an environment is defined by the core of environmental typologies (envirotype) and their frequencies, which describe different zones of plant adaptation. From that, we derive markers of environmental similarity cost-effectively. Combined with the traditional genomic sources (e.g., additive and dominance effects), this approach may better represent the putative phenotypic variation across diverse growing conditions (i.e., phenotypic plasticity). Additionally, we couple a genetic algorithm scheme to design optimized multi-environment field trials (MET), combining enviromic assembly and genomic kinships to provide in-silico realizations of the future genotype-environment combinations that must be phenotyped in the field. As a proof-of-concept, we highlight E-GP applications: (1) managing the lack of phenotypic information in training accurate GP models across diverse environments and (2) guiding an early screening for yield plasticity using optimized phenotyping efforts. Our approach was tested using two non-conventional cross-validation schemes to better visualize the benefits of enviromic assembly in sparse experimental networks. Results on tropical maize show that E-GP outperforms benchmark GP in all scenarios and cases tested. We show that for training accurate GP models, the genotype-environment combinations representativeness is more critical than the MET size. Furthermore, we discuss theoretical backgrounds underlying how the intrinsic envirotype-phenotype covariances within the phenotypic records of (MET) can impact the accuracy of GP and limits the potentialities of predictive breeding approaches. The E-GP is an efficient approach to better use environmental databases to deliver climate-smart solutions, reduce field costs, and anticipate future scenarios.


title: SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes

abstract: Spatial transcriptomics has been emerging as a powerful technique for resolving gene expression profiles while retaining tissue spatial information. These spatially resolved transcriptomics make it feasible to examine the complex multicellular systems of different microenvironments. To answer scientific questions with spatial transcriptomics and expand our understanding of how cell types and states are regulated by microenvironment, the first step is to identify cell clusters by integrating the available spatial information. Here, we introduce SC-MEB, an empirical Bayes approach for spatial clustering analysis using a hidden Markov random field. We have also derived an efficient expectation-maximization algorithm based on an iterative conditional mode for SC-MEB. In contrast to BayesSpace, a recently developed method, SC-MEB is not only computationally efficient and scalable to large sample sizes but is also capable of choosing the smoothness parameter and the number of clusters. We performed comprehensive simulation studies to demonstrate the superiority of SC-MEB over some existing methods. We applied SC-MEB to analyze the spatial transcriptome of human dorsolateral prefrontal cortex tissues and mouse hypothalamic preoptic region. Our analysis results showed that SC-MEB can achieve a similar or better clustering performance to BayesSpace, which uses the true number of clusters and a fixed smoothness parameter. Moreover, SC-MEB is scalable to large  sample sizes. We then employed SC-MEB to analyze a colon dataset from a patient with colorectal cancer (CRC) and COVID-19, and further performed differential expression analysis to identify signature genes related to the clustering results. The heatmap of identified signature genes showed that the clusters identified using SC-MEB were more separable than those obtained with BayesSpace. Using pathway analysis, we identified three immune-related clusters, and in a further comparison, found the mean expression of COVID-19 signature genes was greater in immune than non-immune regions of colon tissue. SC-MEB provides a valuable computational tool for investigating the structural organizations of tissues from spatial transcriptomic data.

category: genomics


title: Common Permutation Methods in Animal Social Network Analysis Do Not Control for Non-independence

abstract: The non-independence of social network data is a cause for concern among behavioural ecologists conducting social network analysis. This has led to the adoption of several permutation-based methods for testing common hypotheses. One of the most common types of analysis is nodal regression, where the relationships between node-level network metrics and nodal covariates are analysed using a permutation technique known as node-label permutations. We show that, contrary to accepted wisdom, node-label permutations do not automatically account for the non-independences assumed to exist in network data, because regression-based permutation tests still assume exchangeability of residuals. The same assumption also applies to the quadratic assignment procedure (QAP), a permutation-based method often used for conducting dyadic regression. We highlight that node-label permutations produce the same p-values as equivalent parametric regression models, but that in the presence of non-independence, parametric regression models can also produce accurate effect size estimates. We also note that QAP only controls for a specific type of non-independence between edges that are connected to the same nodes, and that appropriate parametric regression models are also able to account for this type of non-independence. Based on this, we suggest that standard parametric models could be used in the place of permutation-based methods. Moving away from permutation-based methods could have several benefits, including reducing over-reliance on p-values, generating more reliable effect size estimates, and facilitating the adoption of alternative types of statistical analysis.

category: animal behavior and cognition


title: A NOVEL ORGANOID MODEL OF IN VITRO SPERMATOGENESIS USING HUMAN INDUCED PLURIPOTENT STEM CELLS

abstract: Infertility is thought to be caused by genetic mutations and dysfunction in the cellular niche where spermatogenesis takes place. An understanding of the specialized cellular processes which drive spermatogenesis is needed to develop treatments; however, the development of in vitro systems to study these cells has been hindered by our reliance on rarely available human testicular tissues for research. Human induced pluripotent stem cells (hiPSCs) can be used to derive human testicular-like cells, and thus provide an avenue for the development of in vitro testicular model systems. Therefore, this study set out to engineer a human testicular tissue model using hiPSCs for the first time. We demonstrate the ability of hiPSC-derived testicular cells to self-organize and mature into testicular-like tissues using organoid culture. Moreover, we show that hiPSC-derived testicular organoids promote testicular somatic cell maturation and spermatogenesis up to the post-meiotic spermatid stage. These hiPSC-derived testicular organoids have the potential to replace rarely available primary testicular tissues to further infertility research in an in vitro setting.

category: bioengineering


title: A Novel Organoid Model of In Vitro Spermatogenesis Using Human Induced Pluripotent Stem Cells


title: A Xeno-free Media for the In Vitro Expansion of Human Spermatogonial Stem Cells

abstract: In vitro expansion of spermatogonial stem cells (SSCs) has been established using animal-derived fetal bovine serum (FBS) and bovine serum albumin (BSA). However, the use of animal components during cell culture introduces the risk of contaminating cells with pathogens, and leads to animal epitope expression, rendering them unsuitable for medical use. Therefore, this study set out to develop a xeno-free, fully defined media for the expansion of human SSCs. We show that the molecules Prostaglandin D2 (PGD-2) and Insulin-Like Growth Factor 1 (IGF-1) can replace FBS and BSA in cell culture media without loss of viability or expansion capability, and that Rho-Associated, Coiled-Coil Containing Protein Kinase (ROCK) inhibitor Y-27632 supplementation improves viability after cryopreservation. Long-term SSC cultures expanded in xeno-free, defined culture conditions shared identical protein expression profiles for well-known SSC markers, while gene expression analyses revealed a significant improvement in quiescent SSC and pan-germ markers. This xeno-free, defined formulation allows for standardized SSC culture free of animal pathogens.


title: Exogenous extracellular matrix proteins decrease cardiac fibroblast activation in stiffening microenvironment through CAPG

abstract: Controlling fibrosis is an essential part of regenerating the post-ischemic heart. In the post-ischemic heart, fibroblasts differentiate to myofibroblasts that produce collagen-rich matrix to physically stabilize the infarct area. Infarct models in adult mice result in permanent scarring unlike newborn animals which fully regenerate. Decellularized extracellular matrix (dECM) hydrogels derived from early-aged hearts have been shown to be a transplantable therapy that preserves heart function and stimulates cardiomyocyte proliferation and vascularization. In this study, we investigate the anti-fibrotic effects of injectable dECM hydrogels in a cardiac explant model in the context of age-associated tissue compliance. Treatments with adult and fetal dECM hydrogels were tested for molecular effects on cardiac fibroblast activation and fibrosis. Altered sensitivity of fibroblasts to the mechanosignaling of the remodeling microenvironment was evaluated by manipulating the native extracellular matrix in explants and also with elastomeric substrates in the presence of dECM hydrogels. The injectable fetal dECM hydrogel treatment decreases fibroblast activation and contractility and lowers the stiffness-mediated increases in fibroblast activation observed in stiffened explants. The anti-fibrotic effect of dECM hydrogel is most observable at highest stiffness. Experiments with primary cells on elastomeric substrates with dECM treatment support this phenomenon. Transcriptome analysis indicated that dECM hydrogels affect cytoskeleton related signaling including Macrophage capping protein (CAPG) and Leupaxin (LPXN). CAPG was down-regulated by the fetal dECM hydrogel. LPXN expression was decreased by stiffening the explants; however, this effect was reversed by dECM hydrogel treatment. Pharmacological disruption of cytoskeleton polymerization lowered fibroblast activation and CAPG levels. Knocking down CAPG expression with siRNA inhibited fibroblast activation and collagen deposition. Collectively, fibroblast activation is dependent on cooperative action of extracellular molecular signals and mechanosignaling by cytoskeletal integrity.


title: Differentiation of Peritubular Myoid-Like Cells from Human Induced Pluripotent Stem Cells

abstract: Spermatogenesis is a complex process requiring intricate cellular interactions between multiple cell types to produce viable sperm. Peritubular myoid cells (PTMs) are smooth muscle cells that line the seminiferous tubules and play a critical role in sperm production by providing mechanical support and molecular signaling factors. In vitro investigation of their contribution to spermatogenesis and their dysfunction in infertility is currently limited by the rare accessibility of human testicular tissue for research. Therefore, this study set forth to generate an alternative source of PTMs using human induced pluripotent stem cells (hiPSCs) - adult cells that have been reprogrammed into a pluripotent state, making them capable of indefinite expansion and the regeneration of any cell type in the body. PTMs and Leydig cells arise from a common progenitor, so we hypothesized that PTMs could be derived by modifying an existing differentiation protocol for Leydig cell differentiation from hiPSCs. These hiPSC-derived cells, or hPTMs, were characterized and compared to hiPSC-derived Leydig cells (hLCs) and human primary Sertoli cells as a negative control. Our findings show that the substitution of the molecular patterning factor Platelet-Derived Growth Factor Subunit B (PDGF-BB) for Platelet-Derived Growth Factor Subunit A (PDGF-AA) in a molecule-based differentiation protocol for deriving Leydig-like cells, is sufficient to derive peritubular myoid-like cells. This study describes a method for generating PTM-like cells from hiPSCs. These cells will allow for ongoing understanding of the cellular interactions required for normal spermatogenesis in an in vitro setting.


title: NeTOIF: A Network-based Approach for Time-Series Omics Data Imputation and Forecasting

abstract:
MotivationHigh-throughput studies of biological systems are rapidly generating a wealth of  omics-scale data. Many of these studies are time-series collecting proteomics and genomics data capturing dynamic observations. While time-series omics data are essential to unravel the mechanisms of various diseases, they often include missing (or incomplete) values resulting in data shortage. Data missing and shortage are especially problematic for downstream applications such as omics data integration and computational analyses that need complete and sufficient data representations. Data imputation and forecasting methods have been widely used to mitigate these issues. However, existing imputation and forecasting techniques typically address static omics data representing a single time point and perform forecasting on data with complete values. As a result, these techniques lack the ability to capture the time-ordered nature of data and cannot handle omics data containing missing values at multiple time points.

ResultsWe propose a network-based method for time-series omics data imputation and forecasting (NeTOIF) that handle omics data containing missing values at multiple time points. NeTOIF takes advantage of topological relationships (e.g., protein-protein and gene-gene interactions) among omics data samples and incorporates a graph convolutional network to first infer the missing values at different time points. Then, we combine these inferred values with the original omics data to perform time-series imputation and forecasting using a long short-term memory network. Evaluating NeTOIF with a proteomic and a genomic dataset demonstrated a distinct advantage of NeTOIF over existing data imputation and forecasting methods. The average mean square error of NeTOIF improved 11.3% for imputation and 6.4% for forcasting compared to the baseline methods.

Contactsmollah@wustl.edu


title: Epitope-Based Peptide prediction of vaccine against European bat lyssaviruses type 2 Glycoprotein G with Immunoinformatic Approach

abstract:
ObjectiveEuropean bat lyssaviruses (EBLV) type 2 is present in many European countries. Infection is usually seen in bats, the primary reservoirs of the viruses. Human deaths have been documented within few days following bat exposures. So, it is very useful to design an insilco peptide vaccine for European bat lyssaviruses type 2 virus using glycoprotein G as an immunogen to stimulate protective immune response

ResultsB cell tests were conducted for Bepipred with 15 conserved epitopes, Emini surface accessibility prediction with 7 conserved epitopes in the surface and Kolaskar and Tongaonkar antigenicity tested with three conserved epitopes being antigenic. 357 conserved epitopes were predicted to interact with different MHC-1 alleles with (IC50) [≤]500 while 282 conserved epitopes found to interact with MHC-II alleles with IC50[≤] 1000. Among all tested epitopes for world population coverage the epitope VFSYMELKV binding to MHC11 alleles was 97.94% and it found to bind 10 different alleles that indicate strong potential to formulate peptide vaccine for lyssaviruses type 2 virus. To the best of our knowledge this is the first study to propose peptide vaccine for European bat lyssavirus type 2.


title: LPMX: A pure rootless composable container system

abstract:
SummaryDelivering tools for genome analysis to users is often difficult given their complex dependencies and conflicts. Container virtualization systems such as Singularity isolate environments, helping developers avoid conflicts between tools. However, they lack composability, an easy way to integrate multiple tools in different containers or multiple tools both in a container and a host, which compromises the use of container systems in genome research. Another issue is that one may not be able to use a single container system of the same version at all sites they use, which discourages the use of container systems. To this end, we present a pure rootless composable container system, LPMX, that provides composability for letting developers easily integrate tools in different existing containers or on host, allowing researchers to compose existing containers. LPMX is pure rootless, so it does not require root privilege neither during installation nor at runtime, allowing researchers to use LPMX across sites without asking permissions from administrators. LPMX provides a pure userspace layered filesystem with at least an order of magnitude lower overhead for launching a new process than existing container systems. LPMX can import Docker and Singularity images.

Availability and ImplementationThe source code of LPMX is available at https://github.com/jasonyangshadow/lpmx under Apache 2.0 License.

Contactmkasa@k.u-tokyo.ac.jp

Supplementary informationSupplementary data are available at Bioinformaticsonline.


title: An accurate assignment test for extremely low-coverage whole-genome sequence data

abstract: Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. In ancient DNA research, such characters can provide further information on population continuity, evolution, climate change, species migration, or trade, depending on archaeological context. Yet, assignment tests often rely on moderate- to high-coverage sequence data, which can be difficult to obtain for many ancient specimens and in ecological studies, which often use sequencing techniques such as ddRAD to bypass the need for costly whole-genome sequencing. We have developed a novel approach that efficiently assigns biologically relevant information (such as population identity or structural variants) in extremely low-coverage sequence data. First, we generate databases from existing reference data using a subset of diagnostic Single Nucleotide Polymorphisms (SNPs) associated with a biological characteristic. Low coverage alignment files from ancient specimens are subsequently compared to these databases to ascertain allelic state yielding a joint probability for each association. To assess the efficacy of this approach, we assigned inversion haplotypes and population identity in several species including Heliconius butterflies, Atlantic herring, and Atlantic cod. We used both modern and ancient specimens, including the first whole-genome sequence data recovered from ancient herring bones. The method accurately assigns biological characteristics, including population membership, using extremely low-coverage (e.g. 0.0001x fold) based on genome-wide SNPs. This approach will therefore increase the number of ancient samples in ecological and bioarchaeological research for which relevant biological information can be obtained.


title: Risk of Bias Assessment in Preclinical Literature using Natural Language Processing

abstract:
ObjectiveWe sought to apply natural language processing to the task of automatic risk of bias assessment in preclinical literature, which could speed the process of systematic review, provide information to guide research improvement activity, and support translation from preclinical to clinical research.

Materials and MethodsWe use 7,840 full-text publications describing animal experiments with yes/no annotations for five risk of bias items. We implement a series of models including baselines (support vector machine, logistic regression, random forest), neural models (convolutional neural network, recurrent neural network with attention, hierarchical neural network) and models using BERT with two strategies (document chunk pooling and sentence extraction). We tune hyperparameters to obtain the highest F1 scores for each risk of bias item on the validation set and compare evaluation results on the test set to our previous regular expression approach.

ResultsThe F1 scores of best models on test set are 82.0% for random allocation, 81.6% for blinded assessment of outcome, 82.6% for conflict of interests, 91.4% for compliance with animal welfare regulations and 46.6% for reporting animals excluded from analysis. Our models significantly outperform regular expressions for four risk of bias items.

ConclusionFor random allocation, blinded assessment of outcome, conflict of interests and animal exclusions, neural models achieve good performance, and for animal welfare regulations, BERT model with sentence extraction strategy works better.


title: Revealing A-T and G-C Hoogsteen base pairs in stressed protein-bound duplex DNA

abstract: Watson-Crick base pairs (bps) are the fundamental unit of genetic information and the building blocks of the DNA double helix. However, A-T and G-C can also form alternative  Hoogsteen bps, expanding the functional complexity of DNA. We developed  Hoog-finder, which uses structural fingerprints to rapidly screen Hoogsteen bps, which may have been mismodeled as Watson-Crick in crystal structures of protein-DNA complexes. We uncovered seventeen Hoogsteen bps, seven of which were in complex with six proteins never before shown to bind Hoogsteen bps. The Hoogsteen bps occur near mismatches, nicks, and lesions and some appear to participate in recognition and damage repair. Our results suggest a potentially broad role for Hoogsteen bps in stressed regions of the genome and call for a community-wide effort to identify these bps in current and future crystal structures of DNA and its complexes.

category: biophysics


title: Behavioral effects of ethanol in the Red Swamp Crayfish(Procambarus clarkii)

abstract: Alcohol abuse and dependence remains one of the primary preventable sources of human mortality in the United States. Model laboratory species can be used to evaluate behavioral, neuropharmacological and other biological changes associated with alcohol exposure and to identify novel treatment modalities. This report describes methods for evaluating the behavioral effects of ethyl alcohol (ethanol; EtOH) in a crayfish model. Crayfish (Procambarus clarkii) were immersed in ethanol baths with concentrations ranging from 0.1 to 1.0 molar, and for durations of 10-30 minutes. Studies evaluated hemolymph alcohol concentration, locomotor behavior in an open field and anxiety-like behavior using a Light/Dark transfer approach. EtOH immersion produced dose dependent increases in hemolymph EtOH concentration (up to 249 mg/dL) and reductions in open field locomotor behavior that depended on EtOH concentration or exposure duration. Under baseline conditions, crayfish exhibit avoidance of the open parts of the locomotor arena and a preference for the covered portion, when available. Acute EtOH immersion decreased time spent in the covered portion of the Light/Dark arena, consistent with a decrease in anxiety-like behavior. EtOH immersion once per day for 5 days did not alter the acute locomotor behavioral response, however increased activity was observed 3 days after the repeated EtOH regimen. Overall, this study shows that this inexpensive, easily maintained species can be used for behavioral pharmacological experiments designed to assess the acute and repeated effects of EtOH.

category: pharmacology and toxicology


title: Behavioral effects of ethanol in the Red Swamp Crayfish (Procambarus clarkii)


title: Lack of Age-related Respiratory Changes in Daphnia

abstract: Aging is a multifaceted process of accumulation of damages and waste in cells and tissues; age-related changes in mitochondria and in respiratory metabolism have been in the focus of aging research for decades. Here we investigated age-related changes in respiration rates, lactate/pyruvate ratio, a commonly used proxy for NAD+/NADH balance, and mitochondrial membrane potential in 4 genotypes of an emerging model organism for aging research, a cyclic parthenogen Daphnia magna. We show that total body weight-adjusted respiration rate decreases with age, although this decrease is small in magnitude and not observed in anaesthetized animals, thus likely to be accounted for by decrease in locomotion and feeding activity. Lactate/pyruvate ratio and mitochondrial membrane potential ({Psi}mt) showed no age-related changes, with a possible exception of {Psi}mt measured in the optical lobe and in epipodites (excretory organs) in which {Psi}mt showed a maximum at middle age. We conclude that actuarial senescence in Daphnia is not caused by a decline in respiratory metabolism and discuss possible mechanisms of maintaining mitochondrial healthspan throughout the lifespan.

category: physiology


title: Deep vascular imaging in the eye with flow-enhanced ultrasound

abstract: The eyes retina is one of the most energy-demanding tissues in the body and thus requires high rates of oxygen delivery from a rich blood supply. The capillary lamina of the choroid lines the outer surface of the retina and is the dominating source of oxygen in most vertebrates, but this vascular bed is challenging to image with traditional optical techniques due to its position behind the highly light-absorbing retina. Here we describe a high-frequency ultrasound technique with flow-enhancement to image deep vascular beds (0.5 - 3 cm) of the eye with a high spatiotemporal resolution. This non-invasive method works well in species with nucleated red blood cells (non-mammalian and fetal animal models), and it generates non-invasive three-dimensional angiographies without the use of contrast agents that is independent of blood flow angles and with a higher sensitivity than Doppler based ultrasound imaging techniques.


title: DeepCME: A deep learning framework for solving the Chemical Master Equation

abstract:
Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogorovs forward equation is called the chemical master equation (CME), and it is a fundamental system of linear ordinary differential equations (ODEs) that describes the evolution of the probability distribution of the random state-vector representing the copy-numbers of all the reacting species. The size of this system is given by the number of states that are accessible by the chemical system, and for most examples of interest this number is either very large or infinite. Moreover, approximations that reduce the size of the system by retaining only a finite number of important chemical states (e.g. those with non-negligible probability) result in high-dimensional ODE systems, even when the number of reacting species is small. Consequently, accurate numerical solution of the CME is very challenging, despite the linear nature of the underlying ODEs. One often resorts to estimating the solutions via computationally intensive stochastic simulations.

The goal of the present paper is to develop a novel deep-learning approach for solving high-dimensional CMEs by reformulating the stochastic dynamics using Kolmogorovs backward equation. The proposed method leverages superior approximation properties of Deep Neural Networks (DNNs) and is algorithmically based on reinforcement learning. It only requires a moderate number of stochastic simulations (in comparison to typical simulation-based approaches) to train the "policy function". This allows not just the numerical approximation of the CME solution but also of its sensitivities to all the reaction network parameters (e.g. rate constants). We provide four examples to illustrate our methodology and provide several directions for future research.


title: Reporting amyloid beta levels via bioluminescence imaging with amyloid reservoirs inAlzheimer's disease models

abstract: Bioluminescence imaging has changed daily practice in preclinical research of cancers and other diseases in the last decades; however, it has been rarely applied in preclinical research of Alzheimers disease (AD). In this report, we demonstrated that bioluminescence imaging could be used to report the levels of amyloid beta (A{beta}) species in vivo. We hypothesized that AkaLumine, a newly discovered substrate for luciferase, could bind to A{beta} aggregates and plaques. We further speculated that the A{beta} species have the reservoir capacity to sequester and release AkaLumine to control the bioluminescence intensity, which could be used to report the levels of A{beta}s. Our hypotheses have been validated via in vitro solution tests, mimic studies with brain tissues and mice, two-photon imaging with AD mice, and in vivo bioluminescence imaging using transgenic AD mice that were virally transduced with aka Luciferase (AkaLuc), a new luciferase that generates bioluminescence in the near infrared window. As expected, compared to the control group, we observed that the A{beta} group showed lower bioluminescence intensity due to AkaLumine sequestering at early time points, while higher intensity due to AkaLumine releasing at later time points. Lastly, we demonstrated that this method could be used to monitor AD progression and therapeutic effectiveness of avagacestat, a well-studied gamma-secretase inhibitor. Importantly, a good correlation (R2 = 0.81) was established between in vivo bioluminescence signals and A{beta} burdens of the tested AD mice. We believe that our approach can be easily implemented into daily imaging experiments and has tremendous potential to change daily practice of preclinical AD research.


title: Enrichment analysis of GWAS data in autoimmunity delineates the multiple sclerosis-Epstein Barr virus association

abstract: We exploited genetic information to assess non-genetic influences in autoimmunity. We isolated gene modules whose products physically interact with environmental exposures related to autoimmunity, and analyzed their nominal statistical evidence of association with autoimmune and non-autoimmune diseases in genome-wide association studies (GWAS) data. Epstein Barr virus (EBV) and other Herpesviruses interactomes emerged as specifically associated with multiple sclerosis (MS), possibly under common regulatory mechanisms. Analyses of MS blood and brain transcriptomes, cytofluorimetric studies of endogenous EBV-infected lymphoblastoid lines, and lesion immunohistochemistry, confirmed a dysregulation of MS-associated EBV interactors, suggesting their contribution to CD40 signaling alterations in MS. These interactors resulted enriched in modules from inherited axonopathies-causing genes, supporting a link between EBV and neurodegeneration in MS, in accord with the observed transcriptomic dysregulations in MS brains. They were also enriched with top-ranked pharmaceutical targets prioritized on a genetic basis. This study delineates a disease-specific influence of herpesviruses on MS biology.


title: Statistical Power or More Precise Insights into Neuro-Temporal Dynamics? Assessing the Benefits of Rapid Temporal Sampling in fMRI

abstract: Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4 to 6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.


title: Adaptable and Automated Rodent Behavior Maze System

abstract:
Mazes are a fundamental and widespread tool in behavior and systems neuroscience research in rodents. However, their form and inflexibility often restrict potential experimental paradigms that involve multiple or adaptive maze designs. Unique layouts often cost substantial engineering and time investments from trainee scientists. To alleviate these issues, we have developed an automated modular maze system that is flexible and scalable. This system will allow for experiments with multiple track configurations in rapid succession. Additionally, the flexibility can expedite prototyping of behaviors. Finally, the standardized componentry enhances experimental reproducibility and repeatability. This maze system presents advantages over current maze options and can facilitate novel behavior and systems neuroscience research.

HighlightsO_LIModular maze system enables same-day behavior recordings from multiple flexibly-configured maze environments.
C_LIO_LIHigh degree of experimental reproducibility and repeatability.
C_LIO_LIAutomated lick-detection, liquid reward delivery, and movable barriers.
C_LIO_LIElectronics interface with SpikeGadgets hardware for plug-and-play automated control.
C_LIO_LIFlexibility enables rapid experimental piloting.
C_LI


title: Equivalent noise characterization of human lightness constancy

abstract: A goal of visual perception is to provide stable representations of task-relevant scene properties (e.g. object reflectance) despite variation in task-irrelevant scene properties (e.g. illumination, reflectance of other nearby objects). To study such stability in the context of the perceptual representation of lightness, we introduce a threshold-based psychophysical paradigm. We measure how thresholds for discriminating the achromatic reflectance of a target object (task-relevant property) in rendered naturalistic scenes are impacted by variation in the reflectance functions of background objects (task-irrelevant property), using a two-alternative forced-choice paradigm in which the reflectance of the background objects is randomized across the two intervals of each trial. We control the amount of background reflectance variation by manipulating a statistical model of naturally-occurring surface reflectances. For low background object reflectance variation, discrimination thresholds were nearly constant, indicating that observers internal noise determines threshold in this regime. As background object reflectance variation increases, its effects start to dominate performance. A model based on signal detection theory allows us to express the effects of task-irrelevant variation in terms of the equivalent noise, that is relative to the intrinsic precision of the task-relevant perceptual representation. The results indicate that although naturally-occurring background object reflectance variation does intrude on the perceptual representation of target object lightness, the effect is modest - within a factor of two of the equivalent noise level set by internal noise.


title: The influence of stimulus and behavioral histories on predictive control of smooth pursuit eye movements

abstract: The pursuit system has the ability to perform predictive control of eye movements. Even when the target motion is unpredictable due to velocity or direction changes, preceding changes in eye velocity are generated based on weighted averaging of past stimulus timing. However, it is still uncertain whether behavioral history influences the control of predictive pursuit. Thus, we attempted to clarify the influences of stimulus and behavioral histories on predictive pursuit to randomized target velocity. We used alternating-ramp stimuli, where the rightward velocity was fixed while the leftward velocity was either fixed (predictable) or randomized (unpredictable). Predictive eye deceleration was observed regardless of whether the target velocity was predictable or not. In particular, the predictable condition showed that the predictive pursuit responses corresponded to future target velocity. The linear mixed-effects model showed that both stimulus and behavioral histories of the previous two or three trials had influences on the predictive pursuit responses to the unpredictable target velocity. Our results suggest that the predictive pursuit system allows to track randomized target motion using the information from previous several trials, and the information of sensory input (stimulus) and motor output (behavior) in the past time sequences have partially different influences on predictive pursuit.


title: Aging-related cerebral microvascular changes visualized using Ultrasound Localization Microscopy in the living mouse

abstract: Aging-related cognitive decline is an emerging health crisis; however, no established unifying mechanism has been identified for the cognitive impairments seen in an aging population. A vascular hypothesis of cognitive decline has been proposed but is difficult to test given the contradictory radiologic needs of high-fidelity microvascular imaging resolution and a broad and deep brain imaging field of view. Super-resolution ultrasound localization microscopy (ULM) offers a potential solution by exploiting circulating microbubbles to achieve a vascular resolution approaching the capillary scale without sacrificing imaging depth. In this report, we apply ULM imaging to a mouse model of aging and quantify differences in cerebral vascularity, blood velocity, and vessel tortuosity across several brain regions. We found significant decreases in blood velocity, and significant increases in vascular tortuosity, across all brain regions in the aged cohort, and significant decreases in blood volume in the cortex. These data provide the first-ever measurements of subcortical microvascular dynamics in vivo and reveal that aging has a major impact on these measurements.


title: Confusions regarding stochastic fluctuations and accumulators in spontaneous movements

abstract: Experiments on choice-predictive brain signals have played an important role in the debate on free will. In a seminal study, Benjamin Libet and colleagues found that a negative-going EEG signal, the readiness potential (RP), can be observed over motor-related brain regions already a few hundred ms before a participant makes a conscious decision to move. If the onset of the readiness potential is taken as an indicator of the "brains decision to move" this could mean that this decision to move is made early, by unconscious brain activity, rather than later, at the time when the subject believes to be deciding. However, an alternative interpretation has recently been discussed, the stochastic decision model (SDM), that takes its inspiration from models of perceptual decision making. It suggests that the RP originates from an accumulation of stochastic internal fluctuations. In this view the decision happens only at a much later stage when an accumulated noise signal reaches a threshold. Here we address a number of confusions regarding both the evidence for the stochastic decision model as well as its interpretation. We will show: (a) that the evidence for the role of stochastic fluctuations is highly indirect; (b) that there is little direct support for the SDM from animal studies; (c) that deterministic (non-random) processes can explain the data in a similar way; (d) that the relative components of the model have been mischaracterized leading to an over-emphasis on the role of random fluctuations and an under-emphasis of deterministic aspects of the model; (e) that there is confusion regarding the role of "urgency" and "evidence" in the SDM and its link to perceptual decision making; (f) that the question whether the decision happens early or late depends on the nature of the noise fluctuations, specifically, whether they reflect "absolute" or "epistemic" randomness; (g) finally, that the model does not explain the temporal relationship between conscious decision and neural decision. Our aim is not to rehabilitate the role of RPs in the free will debate. Rather we aim to address some confusions and premature conclusions regarding the evidence for accumulators playing a role in these preparatory brain processes.


title: Postnatal lymph node expansion of stromal progenitors towards reticular and CD34+ stromal cell subsets is determined by distinct transcriptional programs

abstract:
Gut-draining mesenteric lymph nodes (mLN) provide the framework and microenvironment to shape intestinal adaptive immune responses. We previously delineated transcriptional signatures in LN stromal cells (SC), pointing to tissue-specific variability in composition and immuno-modulatory function of SCs.

Here, we dissect the tissue-specific epigenomic DNA accessibility and CpG methylation landscape of LN non-endothelial SCs and identify a microbiota-independent core epigenomic signature of LN SCs. By combined analysis of transcription factor (TF) binding sites together with the gene expression profiles of non-endothelial SCs, we delineated TFs poising skin-draining peripheral LN (pLN) SCs for pro-inflammatory responses. Furthermore, using scRNA-seq, we dissected the developmental trajectory of mLN SCs derived from postnatal to aged mice, identifying two distinct putative progenitors, namely CD34+ SC and fibroblastic reticular stromal cell (FRC) progenitors, which both feed the rapid postnatal LN expansion. Finally, we identified Irf3 as a key differentiation TF inferred from the epigenomic signature of mLN SCs that is dynamically expressed along the differentiation trajectories of FRCs, and validated Irf3 as a regulator of Cxcl9+ FRC differentiation.

Together, our data constitute a comprehensive transcriptional and epigenomic map of mLN development and dissect location-specific, microbiota-independent properties of mLN non-endothelial SCs. As such, our findings represent a valuable resource to identify core transcriptional regulators that impinge on the developing mLN early in life, thereby shaping long-lasting intestinal adaptive immune responses.

category: immunology


title: CD36: Hemin interaction axis to control immune responses and cytokine secretion from macrophages involving Lyn kinase.

abstract: The intensity and duration of TNF- production are mutually correlated with the level of CD36 expression level. The macrophages exposed to hemin exhibits modulation of non-opsonic phagocytosis of aged RBCs and ability to kill bacteria. Immuno-fluorescence study indicates translocation and sequestration of CD36 within the intracellular storage in the hemin treated macrophages. It in-tern dysregulate the global cytokine secretion from macrophages. CD36 has suitable hemin biophoric environment involving R292, D372 and Q382 to bind and the mutation in biophore residues (R292A, D372A or Q382A) significantly reduced the affinity. Ectopic expression of CD36 in MG63 cells showed several folds increment in cytokines TNF-, MCP-1, RANTES and CCL1 in response to hemin stimulation but no significant amount of cytokines released with mutants (R292A, D372A or Q382A), highlights the relevance of CD36-hemin interaction for immune-dysfunction. Hemin is driving down-stream signalling involving CD36 and subsequent recruitment of adaptor proteins to the cytosolic domain of CD36. Immuno-precipitation of membrane bound CD36 and detection of adaptor proteins indicate change in level of Lyn proteins with CD36 fractions after hemin stimulation to macrophages. The Lyn targeted siRNA restored the phagocytic activity, reduced the secretion of pro-inflammatory cytokine levels clearly suggests the Src family protein Lyn is crucial for CD36-hemin mediated immune dysregulation and cytokine secretion. In summary, hemin-CD36-Lyn cytokine signalling axis could be a contribution factor to severe malaria pathology and prognosis.


title: Selective pharmaceutical inhibition of PARP14 mitigates allergen-induced IgE and mucus overproduction in a mouse model of pulmonary allergic response

abstract: The type 2 cytokines IL-4 and IL-13, which share use of an IL-4 receptor alpha chain and its nuclear induction of the transcription factor STAT6, are crucial in elicitation and maintenance of allergic conditions that include asthma. Prior work has shown a physical and functional association of STAT6 with PARP14, an ADP-ribosyl monotransferase. Moreover, elimination of all PARP14 expression by gene targeting led to altered recall antibody responses and attenuation of ovalbumin-specific allergic lung inflammation with no apparent health issues for mice lacking this protein. However, an unanswered question is whether or not inhibition of the catalytic function has any biological consequence since PARP14 has multiple functional domains apart from the portion that catalyzes ADP-ribosylation. As reported separately, iterative structural analyses and medicinal chemistry fostered the generation of a compound, RBN2759, that is highly selective in its inhibition of PARP14 with negligible impact on other members of the PARP gene family. We show here that administration of this compound to mice previously sensitized to the allergen Alternaria alternata achieved biochemically active levels and altered physiological responses to the antigen. These results show for the first time that in vivo administration of a specific inhibitor of the ADP-ribosyltransferase activity encoded by PARP14 is sufficient to alter biological responses. Specifically, the orally absorbable pharmaceutical compound decreased allergen-induced mucus, blunted the induced increases in circulating IgE, and prevented suppression of IgG2a. We conclude that the catalytic activity can contribute to pathogenesis in allergic processes and propose that other biological endpoints that depend on ADP-ribosylation by PARP14 can be targeted using selective inhibition.


title: The zinc transporter ZnuABC is critical for the virulence of Chromobacterium violaceum and contributes to diverse zinc-dependent physiological processes

abstract: Chromobacterium violaceum is a ubiquitous environmental bacterium that causes sporadic life-threatening infections in humans. How C. violaceum acquires zinc to colonize environmental and host niches is unknown. In this work, we demonstrated that C. violaceum employs the zinc uptake system ZnuABC to overcome zinc limitation in the host, ensuring the zinc supply for several physiological demands. Our data indicated that the C. violaceum ZnuABC transporter is encoded in a zur-CV_RS15045-CV_RS15040-znuCBA operon. This operon was repressed by the zinc uptake regulator Zur and derepressed in the presence of the host protein calprotectin (CP) and the synthetic metal chelator EDTA. A {Delta}znuCBA mutant strain showed impaired growth under these zinc-chelated conditions. Moreover, the deletion of znuCBA provoked a reduction in violacein production, swimming motility, biofilm formation, and bacterial competition. Remarkably, the {Delta}znuCBA mutant strain was highly attenuated for virulence in an in vivo mouse infection model and showed a low capacity to colonize the liver, grow in the presence of CP, and resist neutrophil killing. Overall, our findings demonstrate that ZnuABC is essential for C. violaceum virulence, contributing to subvert the zinc-based host nutritional immunity.


title: Inverse Lansing effect: maternal age and provisioning affecting daughters' longevity and male offspring production

abstract: Maternal age effects on life history of offspring has been demonstrated in a variety of organisms, more often than not offspring of older mothers having lower life expectancy (Lansing effect). However, there is no consensus on how general this phenomenon is and what are the genetic and epigenetic mechanisms behind it. We tested the predictions of Lansing effect in several Daphnia magna clones in and observed a significant genotype-by-maternal age interaction, indicating clone-specific magnitude and direction of the effect of maternal age on daughters longevity. We then repeated this experiment with more detailed life-history and offspring provisioning data focusing on 2 clones with contrasting life-histories. One of these clones demonstrating the inverse Lansing effect, with daughters of older mothers living longer than those of young mothers. Individuals from a single-generation maternal age reversal treatment showed intermediate lifespan. We also report genotype-specific, ambidirectional, and largely fecundity-independent effects of maternal age on daughters propensity to produce male offspring, with daughters of older mothers showing higher male production than daughters of younger mothers in the least male-producing clone and vise versa. We tested whether both effects can be explained by either lipid provisioning of embryos by mothers of different age, or by properties of mitochondria transmitted by mothers of different age to their offspring, using rhodamine-123 assay of mitochondrial membrane potential as a measure of mitochondria quality. We show that once lipid provisioning is accounted for, the effects of maternal age on lifespan and male production disappear and that the effect of lipid provisioning itself is clone-dependent, confirming that maternal provisioning sets daughters life history parameters. In the clone showing the inverse Lansing effect we demonstrated that, contrary to the predictions, neonates produced by older mothers were characterized by higher mitochondrial membrane potential in neural tissues than their counterparts born to younger mothers. We conclude that, in at least some genotypes, a reverse Lansing effect is possible, and hypothesize that it may be a result of lower lipid provisioning creating calorically restricted environment during embryonic development.

category: developmental biology


title: Siderophores drive invasion dynamics in bacterial communities through their dual role as public good versus public bad

abstract: Microbial invasions can compromise ecosystem services and spur dysbiosis and disease in hosts. Nevertheless, the mechanisms determining invasion outcomes often remain unclear. Here, we examine the role of iron-scavenging siderophores in driving invasions of Pseudomonas aeruginosa into resident communities of environmental pseudomonads. Siderophores can be "public goods" by delivering iron to individuals possessing matching receptors; but they can also be "public bads" by withholding iron from competitors lacking these receptors. Accordingly, siderophores should either promote or impede invasion, depending on their dual effects on invader and resident growth. Using supernatant feeding and invasion assays, we show that invasion success indeed decreased when the invader was inhibited (public bad) rather than stimulated (public good) by the residents siderophores. Conversely, invasion success often increased when the invader could use its siderophore to inhibit the residents. Our findings identify siderophores as a major driver of invasion dynamics in bacterial communities.


title: Identifying charismatic bird species and traits with community science observations

abstract: AO_SCPLOWBSTRACTC_SCPLOWIdentifying which species are perceived as charismatic can improve the impact and efficiency of conservation outreach, as charismatic species receive more conservation funding and have their conservation needs prioritized (9; 17; 13). Sociological experiments studying animal charisma have relied on stated preferences to find correlations between hypothetical "willingness to pay" or "empathy" for a species conservation and species size, color, and aesthetic appeal (51; 13; 16). Recognizing the increasing availability of digital records of public engagement with animals that reveal preferences, an emerging field of "culturomics" uses Google search results, Wikipedia article activities, and other digital modes of engagement to identify charismatic species and traits (46; 31; 10; 41). In this study, we take advantage of community science efforts as another form of digital data that can reveal observer preferences. We apply a multi-stage analysis to ask whether opportunistic birders contributing to iNaturalist engage more with larger, more colorful, and rarer birds relative to a baseline, from eBird contributors, approximating unbiased detection. We find that body mass, color contrast, and range size all predict over-representation in the opportunistic dataset. We also find evidence that, across 473 modeled species, 52 species are significantly overreported and 158 are significantly underreported, indicating a wide variety of species-specific effects. Understanding which birds are charismatic can aid conservationists in creating impactful outreach materials and engaging new naturalists. The quantified differences between two prominent community science efforts may also be of use for researchers leveraging the data from one or both of them to answer scientific questions of interest.


title: DNA transposon expansion is associated with genome size increase in mudminnows

abstract:
Genome sizes of eukaryotic organisms vary substantially, with whole genome duplications (WGD) and transposable element expansion acting as main drivers for rapid genome size increase. The two North American mudminnows, Umbra limi and U. pygmaea, feature genomes about twice the size of their sister lineage Esocidae (e.g., pikes and pickerels). However, it is unknown whether all Umbra species share this genome expansion and which causal mechanisms drive this expansion. Using flow cytometry, we find that the genome of the European mudminnow is expanded similarly to both North American species, ranging between 4.5-5.4 pg per diploid nucleus. Observed blocks of interstitially located telomeric repeats in Umbra limi suggest frequent Robertsonian rearrangements in its history. Comparative analyses of transcriptome and genome assemblies show that the genome expansion in Umbra is driven by extensive DNA transposon expansion without WGD. Furthermore, we find a substantial ongoing expansion of repeat sequences in the Alaska blackfish Dallia pectoralis, the closest relative to the family Umbridae, which might mark the beginning of a similar genome expansion. Our study suggests that the genome expansion in mudminnows, driven mainly by transposon expansion, but not WGD, occurred before the separation into the American and European lineage.

Significance StatementNorth American mudminnows feature genomes about twice the size of their sister lineage Esocidae (e.g., pikes and pickerels). However, neither the mechanism underlaying this genome expansion, nor whether this feature is shared amongst all mudminnows is currently known. Using cytogenetic analyses, we find that the genome of the European mudminnow also expanded and that extensive chromosome fusion events have occurred in some Umbra species. Furthermore, comparative genomics based on de-novo assembled transcriptomes and genome assemblies, which have recently become available, indicates that DNA transposon activity is responsible for this expansion.

category: evolutionary biology


title: A single amino acid in RTEL1 determines telomere length in mice

abstract: Maintaining optimal telomere length throughout life limits cancer and enables healthy aging. Yet, it is unclear how the telomere length set point is determined. Telomeres in the house mouse, Mus musculus, are 2-4 times longer than human telomeres, limiting the use of the mouse as a model for telomere research. By introducing a single amino acid variation found in M. spretus into the helicase RTEL1 of M. musculus, we shortened its telomere length set point 2-3 times, implicating this variation in the dramatic difference in telomere length between the two mouse species. While the engineered mice are fertile and healthy, hepatocytes with short telomeres displayed reduced proliferation capacity. This  telomouse is a unique model for studying the implications of short telomeres in aging and cancer.


title: Interrogation of the Dynamic Properties of Higher-Order Heterochromatin Using CRISPR/dCas9

abstract: Eukaryotic chromosomes feature large regions of compact, repressed heterochromatin hallmarked by Heterochromatin Protein 1 (HP1). HP1 proteins play multi-faceted roles in shaping heterochromatin, and in cells, HP1 tethering to individual gene promoters leads to epigenetic modifications and silencing. However, emergent properties of HP1 at supranucleosomal scales remain difficult to study in cells due to lack of appropriate tools. Here, we develop CRISPR-Engineered Chromatin Organization (EChO), combining live cell CRISPR imaging with inducible large-scale recruitment of chromatin proteins to native genomic targets. We demonstrate that human HP1 tiling across kilobase-scale genomic DNA forms novel contacts with natural heterochromatin, integrates two distantly targeted regions, and reversibly changes chromatin from a diffuse to compact state. The compact state exhibits delayed disassembly kinetics and represses transcription across over 600 kilobases. These findings support a polymer model of HP1-mediated chromatin regulation and highlight the utility of CRISPR-EChO in studying supranucleosomal chromatin organization in living cells.


title: Spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissues at genome scale and cellular level

abstract: Cellular function in tissue is dependent upon the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping, but it remains elusive to capture spatial epigenetic information of tissue at cellular level and genome scale. Here we report on spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissue section via next-generation sequencing by combining in situ Tn5 transposition chemistry and microfluidic deterministic barcoding. Spatial chromatin accessibility profiling of mouse embryos delineated tissue region-specific epigenetic landscapes and identified gene regulators implicated in the central nerve system development. Mapping the accessible genome in human tonsil tissue with 20m pixel size revealed spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology takes spatial biology to a new realm by enabling spatially resolved epigenomics to improve our understanding of cell identity, state, and fate decision in relation to epigenetic underpinnings in development and disease.


title: Structure and mechanism of the RNA dependent RNase Cas13a from Rhodobacter capsulatus

abstract: Cas13a are single-molecule effectors of the Class II, Type VI family of CRISPR-Cas systems that are part of the bacterial and archaeal defense systems. These RNA-guided and RNA-activated RNA endonucleases are characterized by their ability to cleave target RNAs complementary to the crRNA-spacer sequence, as well as bystander RNAs in a sequence-unspecific manner. Due to cleavage of cellular transcripts they induce dormancy in the host cell and thus protect the bacterial population by aborting the infectious cycle of RNA-phages. Here we report the structural and functional characterization of a Cas13a enzyme from the photo-auxotrophic purple bacteria Rhodobacter capsulatus. The X-ray crystal structure of the RcCas13a-crRNA complex reveals its distinct crRNA recognition mode as well as the enzyme in its contracted, pre-activation conformation. Using site-directed mutagenesis in combination with mass spectrometry, we identified key-residues responsible for pre-crRNA processing by RcCas13a in its distinct catalytic site, and elucidated the acid-base mediated cleavage reaction mechanism. In addition, RcCas13a cleaves target-RNA as well as bystander-RNAs in Escherichia coli which requires its catalytic active HEPN (higher eukaryotes and prokaryotes nucleotide binding) domain nuclease activity. Our data provide further insights into the molecular mechanisms and function of this intriguing family of RNA-dependent RNA endonucleases that are already employed as efficient tools for RNA detection and regulation of gene expression.

category: biochemistry


title: Cyclic Microchip Assay for Measurement of Hundreds of Functional Proteins in Single Neurons

abstract: Proteins are responsible for nearly all cell functions throughout cellular life. To date, the molecular functions of hundreds of proteins have been studied as they are critical to cellular processes. Those proteins are varied dramatically at different statuses and differential stages of the cells even in the same tissue. The existing single-cell tools can only analyze dozens of proteins and thus have not been able to fully characterize a cell yet. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology that affords the comprehensive functional proteome profiling of single cells. It permits multiple, separate rounds of multiplex assays of the same single cells on a microchip where each round detects 40-50 proteins. A decoding process is followed to assign protein identities and quantify protein detection signals. We demonstrate the technology on a neuron cell line by detecting 182 proteins that includes surface makers, neuron function proteins, neurodegeneration markers, signaling pathway proteins and transcription factors. Further study on 5XFAD mouse, an Alzheimers Disease (AD) model, cells validate the utility of our technology which reveals the deep heterogeneity of brain cells. Through comparison with control mouse cells, the differentially expressed proteins in the AD mouse model have been detected. The single-cell CycMIST technology can potentially analyze the entire functional proteome spectrum, and thus it may offer new insights into cell machinery and advance many fields including systems biology, drug discovery, molecular diagnostics, and clinical studies.


title: Number of Synergies Impacts Sensitivity of Gait to Weakness and Contracture

abstract: Muscle activity during gait can be described by a small set of synergies, weighted groups of muscles, that are often theorized to reflect underlying neural control. For people with neurologic injuries, like in cerebral palsy or stroke, even fewer (e.g., < 5) synergies are required to explain muscle activity during gait. This reduction in synergies is thought to reflect simplified control strategies and is associated with impairment severity and treatment outcomes. Individuals with neurologic injuries also develop secondary musculoskeletal impairments, like weakness or contracture, that can also impact gait. The combined impacts of simplified control and musculoskeletal impairments on gait remains unclear. In this study, we use a musculoskeletal model constrained to synergies to simulate unimpaired gait. We vary the number of synergies (3-5), while simulating muscle weakness and contracture to examine how altered control impacts sensitivity to muscle weakness and contracture. Our results highlight that reducing the number of synergies increases sensitivity to weakness and contracture. For example, simulations using five-synergy control tolerated 40% and 51% more knee extensor weakness than those using four- and three-synergy control, respectively. Furthermore, the model became increasingly sensitive to contracture and proximal muscle weakness, such as hamstring and hip flexor weakness, when constrained to four- and three-synergy control. However, the models sensitivity to weakness of the plantarflexors and smaller bi-articular muscles was not affected by the number of synergies. These findings provide insight into the interactions between altered control and musculoskeletal impairments, emphasizing the importance of incorporating both in future simulation studies.


title: Estimating body segment parameters from three-dimensional human body scans

abstract: Body segment parameters are inputs for a range of applications. The estimation of body segment parameters that are participant-specific is desirable as it requires fewer prior assumptions and can reduce outcome measurement errors. Commonly used methods for estimating participant-specific body segment parameters are either expensive and out of reach (medical imaging), have many underlying assumptions (geometrical modelling) or are based on a specific subset of a population (regression models). Our objective was to develop a participant-specific 3D scanning and body segmentation method that estimates body segment parameters without any assumptions about the geometry of the body, ethnic background, and gender, is low-cost, fast, and can be readily available. Using a Microsoft Kinect camera, we developed a 3D surface scanning protocol that estimated participant-specific body segment parameters. To evaluate our system, we performed repeated 3D scans of 21 healthy participants (10 male, 11 female). We used open-source software to segment each body scan into 16 segments (head, torso, abdomen, pelvis, left and right hand, forearm, upper arm, foot, shank and thigh) and wrote custom software to estimate each segments mass, mass moment of inertia in the three principal orthogonal axes relevant to the center of the segment, longitudinal length, and center of mass. We compared our body segment parameter estimates to those obtained using two comparison methods and found that our system was consistent in estimating total body volume between repeated scans (male p=0.1194, female p = 0.2240), estimated total body mass without significant differences when compared to our comparison method and a medical scale (male p=0.8529, female p = 0.6339), and generated consistent and comparable estimates across all of the body segment parameters of interest. The work here outlines an inexpensive 3D surface scanning approach for estimating a range of participant-specific body segment parameters.


title: Microfluidic bioprinting for the in vitro generation of novel biomimetic human testicular tissues

abstract: Advances in cancer treatments have greatly improved pediatric cancer survival rates, leading to quality of life considerations and in particular fertility restoration. Accordingly, pre-pubertal patients have the option to cryopreserve testicular tissue for experimental restorative therapies, including in vitro spermatogenesis, wherein testicular tissue is engineered in vitro and spermatozoa are collected for in vitro fertilization (IVF). Current in vitro systems have been unable to reliably support the generation of spermatozoa from human testicular tissues, likely due to the inability for the dissociated testicular cells to recreate the native architecture of testicular tissue found in vivo. Recent advances in 3-D bioprinting can place cells into geometries at fine resolutions comparable to microarchitectures found in native tissues, and therefore hold promise as a tool for the development of a biomimetic in vitro system for human spermatogenesis. This study assessed the utility of bioprinting technology to recreate the precise architecture of testicular tissue and corresponding spermatogenesis for the first time. We printed testicular cell-laden hollow microtubules at similar resolutions to seminiferous tubules, and compared the results to testicular organoids. We show that the human testicular cells retain their viability and functionality post-printing, and illustrate an intrinsic ability to reorganize into their native cytoarchitecture. This study provides a proof of concept for the use of 3-D bioprinting technology as a tool to create biomimetic human testicular tissues.


title: TSEBRA: Transcript Selector for BRAKER

abstract:
BackgroundBRAKER is a suite of automatic pipelines, BRAKER1 and BRAKER2, for the accurate annotation of protein-coding genes in eukaryotic genomes. Each pipeline trains statistical models of protein-coding genes based on provided evidence and, then predicts protein-coding genes in genomic sequences using both the extrinsic evidence and statistical models. For training and prediction, BRAKER1 and BRAKER2 incorporate complementary extrinsic evidence: BRAKER1 uses only RNA-seq data while BRAKER2 uses only a database of cross-species proteins. The BRAKER suite has so far not been able to reliably exceed the accuracy of BRAKER1 and BRAKER2 when incorporating both types of evidence simultaneously. Currently, for a novel genome project where both RNA-seq and protein data are available, the best option is to run both pipelines independently, and to pick one, likely better output. Therefore, one or another type of the extrinsic evidence would remain unexploited.

ResultsWe present TSEBRA, a software that selects gene predictions (transcripts) from the sets generated by BRAKER1 and BRAKER2. TSEBRA uses a set of rules to compare scores of overlapping transcripts based on their support by RNA-seq and homologous protein evidence. We show in computational experiments on genomes of 11 species that TSEBRA achieves higher accuracy than either BRAKER1 or BRAKER2 running alone and that TSEBRA compares favorably with the combiner tool EVidenceModeler.

ConclusionTSEBRA is an easy-to-use and fast software tool. It can be used in concert with the BRAKER pipeline to generate a gene prediction set supported by both RNA-seq and homologous protein evidence.


title: drda: An R package for dose-response data analysis

abstract: Analysis of dose-response data is an important step in many scientific disciplines, including but not limited to pharmacology, toxicology, and epidemiology. The R package drda is designed to facilitate the analysis of dose-response data by implementing efficient and accurate functions with a familiar interface. With drda, it is possible to fit models by the method of least squares, perform goodness of fit tests, and conduct model selection. Compared to other similar packages, drda provides, in general, more accurate estimates in the least-squares sense. This result is achieved by a smart choice of the starting point in the optimization algorithm and by implementing the Newton method with a trust region with analytical gradients and Hessian matrices. In this article, drda is presented through the description of its methodological components and examples of its user-friendly functions. Performance is finally evaluated using a real, large-scale drug sensitivity screening dataset.


title: spicyR: Spatial analysis of in situ cytometry data in R

abstract:
MotivationHigh parameter histological techniques have allowed for the identification of a variety of distinct cell types within an image, providing a comprehensive overview of the tissue environment. This allows the complex cellular architecture and environment of diseased tissue to be explored. While spatial analysis techniques have revealed how cell-cell interactions are important within the disease pathology, there remains a gap in exploring changes in these interactions within the disease process. Specifically, there are currently no established methods for performing inference on cell localisation changes across images, hindering an understanding of how cellular environments change with a disease pathology.

ResultsWe have developed the spicyR R package to perform inference on changes in the spatial localisation of cell types across groups of images. Application to simulated data demonstrates a high sensitivity and specificity. We demonstrate the utility of spicyR by applying it to a type 1 diabetes imaging mass cytometry dataset, revealing changes in cellular associations that were relevant to the disease progression. Ultimately, spicyR allows changes in cellular environments to be explored under different pathologies or disease states.

Availability and ImplementationR package freely available at http://bioconductor.org/packages/release/bioc/html/spicyR.html and shiny app implementation at http://shiny.maths.usyd.edu.au/spicyR/

Contactellis.patrick@sydney.edu.au

Supplementary informationCode for reproducing key figures available at https://github.com/nickcee/spicyRPaper.


title: OrtSuite - from genomes to prediction of microbial interactions within targeted ecosystem processes

abstract: The high complexity found in microbial communities makes the identification of microbial interactions challenging. To address this challenge, we present OrtSuite, a flexible workflow to predict putative microbial interactions based on genomic content of microbial communities and targeted to specific ecosystem processes. The pipeline is composed of three user-friendly bash commands. OrtSuite combines ortholog clustering with genome annotation strategies limited to user-defined sets of functions allowing for hypothesis-driven data analysis such as assessing microbial interactions in specific ecosystems. OrtSuite matched, on average, 96 % of experimentally verified KEGG orthologs involved in benzoate degradation in a known group of benzoate degraders. Identification of putative synergistic species interactions was evaluated using the sequenced genomes of an independent study which had previously proposed potential species interactions in benzoate degradation. OrtSuite is an easy to use workflow that allows for rapid functional annotation based on a user curated database and can easily be extended to ecosystem processes where connections between genes and reactions are known. OrtSuite is an open-source software available at https://github.com/mdsufz/OrtSuite.


title: Comparative Analysis of Sorghum EMS Mutants and Natural Populations

abstract: To build a large-scale genomic resource for functional validation of sorghum genes through EMS-mutagenized BTx623 seeds, we deep sequenced (30-60X) an additional 445 phenotyped EMS mutant lines. 4.2 million EMS mutations are called with nearly 36,800 mutations that could have a disruptive effect on functions of over 15,500 genes. Combining variants carried by both the natural population and previous EMS efforts, over 69% of sorghum coding genes (23644) are now presented with one or more mutations that are, or are predicted to be, disruptive to their functions. Our results show that the EMS population carries more significant mutations but less in each sample than the natural population, which makes it more powerful in elucidating sorghum gene functions on a large scale and requiring less work in validation of candidate causal genes. We have made the data available through two ways, one is the integration with the BSAseq workflow that supports retrieving independent EMS samples carrying the same genes with significant mutation for complementary testing, and the other is a web application for directly querying genes with significant mutations on SciApps.org.


title: Precise annotation of Drosophila mitochondrial genomes leads to insights into AT-rich regions

abstract: In the present study, we performed precise annotation of Drosophila melanogaster, D. simulans, D. grimshawi, Bactrocera oleae mitochondrial (mt) genomes by pan RNA-seq analysis. Our new annotations corrected or modified some of the previous annotations and two important findings were reported for the first time, including the discovery of the conserved polyA(+) and polyA(-) motifs in the control regions (CRs) of insect mt genomes and the adding of CCAs to the 3 ends of two antisense tRNAs in D. melanogaster mt genome. Using PacBio cDNA-seq data from D. simulans, we precisely annotated the Transcription Initiation Sites (TISs) of the mt Heavy and Light strands in Drosophila mt genomes and reported that the polyA(+) and polyA(-) motifs in the CRs are associated with TISs. The discovery of the conserved polyA(+) and polyA(-) motifs provides insights into many polyA and polyT sequences in CRs of insect mt genomes, leading to reveal the mt transcription and its regulation in invertebrates. In addition, we provided a high-quality, well-curated and precisely annotated D. simulans mt genome (GenBank: MN611461), which should be included into the NCBI RefSeq database to replace the current reference genome NC_005781.


title: Dice-XMBD: Deep learning-based cell segmentation for imaging mass cytometry

abstract: Highly multiplexed imaging technology is a powerful tool to facilitate understanding cells composition and interaction in tumor microenvironment at subcellular resolution, which is crucial for both basic research and clinical applications. Imaging mass cytometry (IMC), a multiplex imaging method recently introduced, can measure up to 40 markers simultaneously in one tissue section by using a high-resolution laser with a mass cytometer. However, due to its high resolution and large number of channels, how to process and interpret the image data from IMC remains a key challenge for its further applications. Accurate and reliable single cell segmentation is the first and a critical step to process IMC image data. Unfortunately, existing segmentation pipelines either produce inaccurate cell segmentation results, or require manual annotation which is very time-consuming. Here, we developed Dice-XMBD, a Deep learnIng-based Cell sEgmentation algorithm for tissue multiplexed imaging data. In comparison with other state-of-the-art cell segmentation methods currently used in IMC, Dice-XMBD generates more accurate single cell masks efficiently on IMC images produced with different nuclear, membrane and cytoplasm markers. All codes and datasets are available at https://github.com/xmuyulab/Dice-XMBD.


title: Correlation in Domain Fluctuations Navigates Target Search of a Viral Peptide along RNA

abstract: Biological macromolecules often exhibit correlation in fluctuations involving distinct domains. This study decodes their functional implications in RNA-protein recognition and target-specific binding. The target search of a peptide along RNA in viral TAR-Tat complex is closely monitored using atomistic simulations, steered molecular dynamics simulations, free energy calculations, and a machine-learning-based clustering technique. An anti-correlated domain fluctuation is identified between the tetraloop and the bulge region in the apo form of TAR RNA that sets a hierarchy in the domain-specific fluctuations at each binding event and that directs succeeding binding footsteps. Thus, at each binding footstep, the dynamic partner selects an RNA location for binding where it senses higher fluctuation, which is conventionally reduced upon binding. This event stimulates an alternate domain-fluctuation which then dictates sequential binding footstep/s and thus, the search progresses. Our cross-correlation maps show that the fluctuations relay from one domain to another specific domain till the anti-correlation between that inter-domain fluctuations sustains. Artificial attenuation of that hierarchical domain fluctuation inhibits specific RNA binding. The binding is completed with the arrival of a few long-lived water molecules that mediate slightly distant RNA-protein sites and finally stabilizes the overall complex. The study underscores the functional importance of naturally designed fluctuating RNA motifs (bulge, tetraloop) and their interplay in dictating the directionality of the search in a highly dynamic environment.


title: Combining Multi-Dimensional Molecular Fingerprints to Predict hERG Cardiotoxicity of Compounds

abstract: At present, drug toxicity has become a critical problem with heavy medical and economic burdens. acLQTS (acquired Long QT Syndrome) is acquired cardiac ion channel disease caused by drugs blocking the hERG channel. Therefore, it is necessary to avoid cardiotoxicity in the drug design and computer models have been widely used to fix this plight. In this study, we present a molecular fingerprint based on the molecular dynamic simulation and uses it combined with other molecular fingerprints (multi-dimensional molecular fingerprints) to predict hERG cardiotoxicity of compounds. 203 compounds with hERG inhibitory activity (pIC50) were retrieved from a previous study and predicting models were established using four machine learning algorithms based on the single and multi-dimensional molecular fingerprints. Results showed that MDFP has the potential to be an alternative to traditional molecular fingerprints and the combination of MDFP and traditional molecular fingerprints can achieve higher prediction accuracy. Meanwhile, the accuracy of the best model, which was generated by consensus of four algorithms with multi-dimensional molecular fingerprints, was 0.694 (RMSE) in the test dataset. Besides, the number of hydrogen bonds from MDFP has been determined as a critical factor in the predicting models, followed by rgyr and sasa. Our findings provide a new sight of MDFP and multi-dimensional molecular fingerprints in building models of hERG cardiotoxicity prediction.


title: Patterns of gene expression in pollen of cotton (Gossypium hirsutum) indicate down-regulation as a feature of thermotolerance

abstract: Reproductive performance in plants is impaired as maximum temperatures consistently approach 40{degrees}C. However, the timing of heatwaves critically affects their impact. We studied the molecular responses of cotton male reproductive stages, to investigate the vulnerability of maturing pollen to high temperature. Tetrads, uninucleate and binucleate microspores, and mature pollen were subjected to SWATH-MS and RNA-seq analyses after exposure to 38/28{degrees}C (day/night) for 5 days. The results indicated that molecular signatures were down-regulated over developmental stages in response to heat. This was more evident in leaves where three-quarters of differentially changed proteins were decreased in abundance. Functional analysis showed that translation of genes increased in tetrads after exposure to heat; however, the reverse pattern was observed in mature pollen and leaves. Proteins involved in transport were highly abundant in tetrads, whereas in later stages of development and leaves, heat suppressed cell-to-cell communication. Moreover, a large number of heat shock proteins (HSPs) were identified in heat-affected tetrads, but these proteins were less abundant in mature pollen and leaves. We speculate that the sensitivity of tetrad cells to heat is related to increased activity of translation involved in non-essential pathways. Molecular signatures during pollen development after heatwaves provide markers for future genetic improvement.

category: plant biology


title: What is the main driver of unsustainable natural resource use in the Comoro Islands?

abstract: The Comoros archipelago is a biodiversity hotspot by virtue of its high level of endemism. However, it suffers one of the highest rates of forest loss worldwide, mainly due to strong anthropogenic pressures. As Comorian populations depend on forest resources for subsistence, establishing relevant conservation strategies for their sustainable management requires the consideration of multiple stakeholders perspectives toward biodiversity and habitat conservation. To better understand the relationships between humans and nature; how comorian people use natural resource and the relevance of a protected area for long-term biodiversity conservation, we used Q-methodology to assess local people s perceptions regarding biodiversity and conservation actions. Three discourses are identified during analysis: "Pro-environment discourse", "Keeping things as usual" and "Social and environmental concerns". According to the results, employed respondents, were favorable to long-term forest and biodiversity conservation. In contrast, unemployed respondents were in favor of more immediate benefits while unemployed but educated respondents were in favor to both long-term forest conservation and immediate benefits from forests. This suggests that the lack of livelihoods for rural people is the main factor leading them to overharvest natural resources. These results suggest that biodiversity conservation of the Comoros archipelagos may benefit for plan aiming at (1) developing tourism and maintaining sustainable production of crops and livestock that could allow enhancing the livelihoods and well-being of all social groups, (2) developing projects such as local markets that could allow villagers to sell their agricultural production, (3) setting up awareness campaign for tree-planting and reforestation. Reforestation could allow re-establishing natural plants and make large trees available for long-term purposes.

category: scientific communication and education