Self-learning algorithm for denoising and advancing the integration of scRNA-seq datasets improves the identification of resilient and susceptible retinal ganglion cell types The clustering of single cell RNA-sequencing (scRNA-seq) data enables the classification of cell types, and the development of integration algorithms has enabled the tracing of altered-from-baseline transcriptomes to their respective cell type origins. Here, we developed an algorithm that removes sources of noise from scRNA-seq datasets and improves the accuracy of their integration. We found that this improvement of integration is further increased by an algorithm we developed for auto-determination of optimal weight-assignment to anchors. As a proof-of-concept, we show that our algorithm determined the type-origin of the 17% of injured retinal ganglion cells (RGCs) that an existing integration algorithm could not identify. As we found that the majority of the originally unassigned cells belonged to only several out of 45 RGC types, a consequent change in the proportions of the surviving types resulted in a moderately different ranking of resiliency to injury. This updated standard for RGC type resilience ranking improved the understanding of RGC type biology and the ranking-dependent prediction of genes for therapeutic neuroprotective targeting. Additional bioinformatic analyses revealed single-gene cluster-markers for RGC types and contributed new insights into the global characteristics of RGC types and how axonal injury affects them, showing how the extent of variance between transcriptomes of RGC types increases differentially during maturation and after injury. We also show, for the first time, that specific global properties of the transcriptome can predict the resilience to injury of certain cell types. Furthermore, we developed a website for cluster-by-cluster comparison of gene expression between uninjured and injured RGC types. The publicly available R library package, CellTools, for denoising and improving the integration of scRNA-seq datasets, as well as for associating cell types with the global properties of the transcriptome, will assist scRNA-seq studies of developing, injured, or diseased cell types across biological fields.
DeLUCS: Deep Learning for (Unsupervised) Clustering of DNA Sequences We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of primary DNA sequences, and generates "mimic" sequence FCGRs to self-learn data patterns (genomic signatures) through the optimization of multiple neural networks. A majority voting scheme is then used to determine the final cluster assignment for each sequence. The clusters learned by DeLUCS match true taxonomic groups for large and diverse datasets, with accuracies ranging from 77% to 100%: 2,500 complete vertebrate mitochondrial genomes, at taxonomic levels from sub-phylum to genera; 3,200 randomly selected 400 kbp-long bacterial genome segments, into clusters corresponding to bacterial families; three viral genome and gene datasets, averaging 1,300 sequences each, into clusters corresponding to virus subtypes. DeLUCS significantly outperforms two classic clustering methods (K-means++ and Gaussian Mixture Models) for unlabelled data, by as much as 47%. DeLUCS is highly effective, it is able to cluster datasets of unlabelled primary DNA sequences totalling over 1 billion bp of data, and it bypasses common limitations to classification resulting from the lack of sequence homology, variation in sequence length, and the absence or instability of sequence annotations and taxonomic identifiers. Thus, DeLUCS offers fast and accurate DNA sequence clustering for previously intractable datasets.
Analysis of science journalism reveals gender and regional disparities in coverage Science journalism is a critical way in which the public can remain informed and benefit from new scientific findings. Such journalism also shapes the publics view of the current state of scientific findings and legitimizes experts. Those covering science can only cite and quote a limited number of sources. Sources may be identified by the journalists research or by recommendations by other scientists. In both cases, biases may influence who is identified and ultimately included as an expert. To analyze possible biases in science journalism, we analyzed 22,001 non-research articles published by Nature. We chose to analyze Nature non-research articles since its research articles provide a natural comparator. Our analysis considered two possible sources of disparity: gender and name origin. To explore these sources of disparity, we extracted cited authors names as well as extracted names of quoted speakers. While citations and quotations within a piece do not reflect the entire information-gathering process, they can provide insight into the demographics of visible sources. We then used the extracted names to predict gender and name origin of the cited authors and speakers.

In order to appropriately quantify the level of difference, we must identify a suitable reference set for comparison. We chose first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period as our comparator. In our analysis, we found a skew towards male quotation in Nature science journalism-related articles. However, quotation is trending toward equal representation at a faster rate than first and last authorship in academic publishing. Interestingly, we found that the gender disparity in Nature quotes was column-dependent, with the "Career Features" column reaching gender parity. Our name origin analysis found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin. This finding was observed both in extracted quotes and journal citations, but dampened in citations. NECAB2 participates in an endosomal pathway of mitochondrial stress response at striatal synapses Synaptic signaling depends on ATP generated by mitochondria. Due to extensive connectivity, the striatum is especially vulnerable to mitochondrial dysfunction and thus requires efficient mitochondrial quality control and repair. We found that global knockout of the neuronal calcium-binding protein 2 (NECAB2) in the mouse causes loss of striatal synapses and behavioral phenotypes related to striatal dysfunction such as reduced motivation and altered sensory gating. Striatal mitochondria from Necab2 knockout mice are more abundant and smaller. They are characterized by increased respiration and superoxide production resulting in oxidative stress. This accumulation of dysfunctional mitochondria is caused by a defective assembly of mitochondria with early endosomes in a pathway that involves the small GTPase Rab5 and its guanine nucleotide exchange factor Alsin/ALS2. NECAB2 therefore participates in an endosomal pathway of mitochondrial stress response and repair important for striatal function. Macroscopic control of synchronous electrical signaling with chemically-excited gene expression Excitable cells can convert electrical signals into chemical outputs to facilitate the active transport of information across larger distances. This electrical-to-chemical conversion requires a tightly regulated expression of ion channels. Alterations of ion channel expression provide landmarks of numerous pathological diseases, such as cardiac arrhythmia, epilepsy, or cancer. Although the activity of ion channels can be locally regulated by external light or chemical stimulus, it remains challenging to coordinate the expression of ion channels on extended spatial-temporal scales in a non-invasive manner. Here, we have engineered yeast S. cerevisiae to read and convert local chemical concentrations into a dynamic electrical field distributed across cell populations. The core mechanism encodes a chemically-excitable dual-feedback gene circuit that precisely tunes the expression domain of potassium channels, globally coordinating cyclic firing of the plasma membrane potential (PMP). We demonstrate that this mechanism leverages an engineered constitutively open bacterial potassium channel KcsA to directly couple chemical stimuli with ion flux through gene expression and it can interface with the host ion channels through the pulsatile production of toxins. Our study provides a robust synthetic transcriptional toolbox underlying the conversion of local chemical environments into spatiotemporally organized electrical impulses for various cellular engineering, synthetic biology, and potential therapeutic applications. LPS-TLR4 pathway exaggerates alcohol-induced acute-on-chronic liver failure via provoking NETs formation Backgrounds: Intrahepatic infiltration of neutrophils is a character of alcoholic acute-on-chronic liver failure (AACLF) and neutrophil extracellular traps (NETs) are an important strategy for neutrophils to fix and kill invading microorganisms. Intestinal bacteria and the gut-liver axis have been thought to play a key role in many liver diseases also including AACLF. However, whether NETs appear in AACLF and play a role in AACLF is still unsure. Methods: WT, NE KO, and TLR4 KO mice were used to build the AACLF model, and the intestinal bacteria were eliminated at the same time and LPS was given. Then the formation of NETs and AACLF related markers were detected. Results: The serum MPO-DNA and LPS concentration was increased in AACLF patients and a correlation was revealed between these two indexes. More intrahepatic NETs formed in AACLF mice by testing MPO-DNA, Cit H3, and NE. These markers decreased with gut detergent and restored markers with gut detergent plus LPS supplement. While NETs formation failed to change with gut microbiome or combine LPS supplement in TLR4 KO mice. As we tested AACLF related characters, liver injury, intrahepatic fat deposition, inflammation, and fibrosis alleviated with depletion of NE. These related marks were also attenuated with gut sterilization by antibiotics and recovered with combined treatment with antibiotics plus LPS. But the liver injury, intrahepatic fat, fibro deposition, and liver inflammation-related markers did show a significant difference in TLR4 KO mice when they received the same treatment. Conclusion: Intestinal-derived LPS promotes NETs formation in AACLF through the TLR4 pathway and further accelerates the AACLF process by NETs. A Physiometric Investigation of Inflammatory Composites: Comparison of A Priori Aggregates, Empirically-identified Factors, and Individual Proteins Most research testing the association between inflammation and health outcomes (e.g., heart disease, diabetes, depression) has focused on individual proteins; however, some studies have used summed composites of inflammatory markers without first investigating dimensionality. Using two different samples (MIDUS-2: N = 1,255 adults, MIDUS-R: N = 863 adults), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor- (TNF-), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compared the resulting factor structure to a) an "a priori"/tau-equivalent factor structure in which all inflammatory proteins equally load onto a single dimension (comparable to the summed composites) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, and their associations with health outcomes. An exploratory factor analysis indicated a two-factor structure (Factor 1: CRP and fibrinogen; Factor 2: IL-8 and IL-10) in MIDUS-2 and was replicated in MIDUS-R. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit, but both strongly outperformed the "a priori"/tau-equivalent structure (which did not achieve acceptable model fit in any models). Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions. However, modeling individual proteins resulted in findings more robust to correction for multiple comparisons despite more conservative adjustments. Further, reliability for all latent variables was poor. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, individual inflammatory proteins or, potentially (if empirically supported and biologically-plausible) empirically-identified inflammatory factors should be used in accordance with theory. Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs. Agrobacterium mediated transformation and deciphering SNPs in TaLr67 gene homeologs for gene editing in wheat. Diseases adversely affect grain yield of crop plants. Leaf rust is a major disease of wheat. As race-specific resistance breaks down, introduction of newer sources of resistance often from older accessions is necessary. Linkage drag from the donor accessions adversely impacts grain yield. As a result, CIMMYT breeding effort has shifted to using durable resistance, also referred to as race non-specific host resistance, which allows slow rusting but maintains grain yield. One of the key genes for durable resistance is Lr67 and the resistant form of this gene is absent in CIMMYT elite lines. Hence, we have initiated efforts to convert the susceptible copy of Lr67 into its resistant form directly in these elite lines using gene editing. This would eliminate backcrossing and thus save time as well as eliminate linkage drag that would accompany the resistant copy of the gene if it were to be introgressed from an older accession. As first steps, we have isolated and sequenced the genomic copies from each of the A, B, and D genome of the Lr67 gene from three elite lines and an experimental line. Identification of more than 50 single nucleotide polymorphisms (SNPs) in the open reading frames (ORF) among these lines would be useful in designing the guide RNA molecules with precision. Further, we have streamlined genetic transformation of these elite lines, a prerequisite step for gene editing. Integrated annotation and analysis of genomic features reveal new types of functional elements and large-scale epigenetic phenomena in the developing zebrafish Zebrafish, a popular model for embryonic development and for modelling human diseases, has so far lacked a systematic functional annotation programme akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created the first central repository to store and process zebrafish developmental functional genomic data. Our Data Coordination Center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and reanalysed published genomics data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements in development, including novel classes with distinct features dependent on their activity in time and space. We delineated the distinction between regulatory elements active during zygotic genome activation and those active during organogenesis, identifying new aspects of how they relate to each other. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predict functional relationships between them beyond sequence similarity, extending the utility of zebrafish developmental genomics to mammals. Cargo-mediated mechanisms reduce inter-motor mechanical interference, promote load-sharing and enhance processivity in teams of molecular motors In cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of cytoskeletal filaments. How motors that typically mechanically interfere with each other, work as teams is unclear. Here we explored the possibility that purely physical mechanisms may potentially enhance teamwork, both at the single motor and cargo level. To explore these mechanisms, we developed a 3D dynamical simulation of cargo transport along microtubules by teams of canonically non-cooperative kinesin-1 motors. We accounted for cargo membrane fluidity by explicitly simulating the Brownian dynamics of motors on the cargo surface and considered both the load and ATP dependence of single motor functioning. We showed explicitly, for the first time, that surface fluidity leads to the reduction of negative mechanical interference between kinesins, enhancing load sharing thereby decreasing single motor off-rates and increasing processivity. Remarkably, we also showed that, independent of fluidity, increasing numbers of bound motors pull the cargo closer to the microtubule, increasing the on-rates of individual unbound motors, resulting in a cooperative increase in bound motor numbers that depends on 3D cargo geometry. At the cargo level, surface fluidity makes more motors available for binding, though this effect is significant only at low ATP or high motor density. Interestingly, we find that the fluidity induced reduction in mechanical interference dominates over the increased availability of motors for typical physiological and in vitro conditions, this allowing us to reconcile different experimental results in different regimes. Finally, we show that these effects can altogether result in enhanced mechanical efficiency and tunable cargo run-lengths for teams of molecular motors over physiological ranges of fluidity with implications for new experimental validation efforts, transport in vivo, artificial cargo design and multi-motor-driven mechanical processes in general.

Author summaryIn cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of protein filaments. How do intrinsically non-cooperative motors function as teams within cells? In this paper, we show, using computer simulations, that the fluid surfaces of cellular cargo reduce the mechanical interference between motors allowing better load sharing and decreasing their detachment rates, thereby increasing the distance over which they can carry cargo. We additionally found that motors pull cargo closer to the filament increasing the attachment rates of other unbound motors. These effects act synergistically with an increased availability of motors due to fluidity to further increase travel distances. Our simulation model accounted for the dynamics of the motors on the cargo surface and their load and ATP dependent kinetics, allowing us to connect single motor properties to overall transport. Our work on understanding how teamwork arises in mechanically coupled motors sheds new light on cellular processes, reconciles existing observations, encourages new experimental validation efforts and can also suggest new ways of improving mechanical efficiency and transport of artificial cargo powered by motor teams. Plucking a string or playing a G? Choice type impacts human reinforcement learning In reinforcement learning (RL) experiments, participants learn to make rewarding choices in response to different stimuli; RL models use outcomes to estimate stimulus-response values which change incrementally. RL models consider any response type indiscriminately, ranging from more concretely defined motor choices (e.g. pressing a key with the index finger), to more general choices that can be executed in a number of ways (e.g. getting dinner at the restaurant). But does the learning process vary as a function of the choice type? In Experiment 1, we show that it does: participants were slower and less accurate in learning correct choices of a general format compared to learning more concrete, motor actions. Using computational modeling, we show that two mechanisms contribute to this. First, there was evidence of irrelevant credit assignment: the values of motor actions interfered with the values of other choice dimensions, resulting in more incorrect choices when the correct response is not defined by a single motor action; second, information integration for relevant general choices was slower. In Experiment 2, we replicated and further extended the findings from Experiment 1, by showing that slowed learning was attributable to weaker working memory use, rather than slowed RL learning. In both experiments we ruled out the explanation that the difference in performance between two condition types was driven by difficulty/different levels of complexity. We conclude that defining a more abstract choice space used by multiple learning systems for credit assignment recruits executive resources, limiting how much such processes then contribute to fast learning. An ALS-associated mutant KIF5A forms oligomers and aggregates and induces neuronal toxicity KIF5A is a kinesin superfamily motor protein that transports various cargos in neurons. Mutations in Kif5a cause familial amyotrophic lateral sclerosis (ALS). These ALS mutations are in the intron of Kif5a and induce mis-splicing of KIF5A mRNA, leading to splicing out of exon 27, which in human KIF5A encodes the cargo-binding tail domain of KIF5A. Therefore, it has been suggested that ALS is caused by loss of function of KIF5A. However, the precise mechanisms regarding how mutations in KIF5A cause ALS remain unclear. Here, we show that an ALS-associated mutant of KIF5A, KIF5A({Delta}exon27), is predisposed to form oligomers and aggregates in cultured mouse cell lines. Interestingly, purified KIF5A({Delta}exon27) oligomers showed more active movement on microtubules than wild type KIF5A in vitro. Purified KIF5A({Delta}exon27) was prone to form aggregates in vitro. Moreover, KIF5A({Delta}exon27)-expressing Caenorhabditis elegans neurons showed morphological defects. These data collectively suggest that ALS-associated mutations of KIF5A are toxic gain-of-function mutations rather than simple loss-of-function mutations. Hematopoietic differentiation is characterized by a transient peak of entropy at a single cell level. Hematopoietic differentiation has been metaphorically represented as linear trajectories with discrete steps from hematopoietic stem cells to mature cells. While the transcriptional state of cells at the beginning or at the end of these trajectories are well described from bulk analysis, what happens in the intermediate states has remained elusive until the use of single cell approaches. Applying Shannon entropy to measure cell-to-cell variability among cells at the same stage of differentiation, we observed a transient peak of gene expression variability in all the hematopoietic differentiation pathways. Strikingly, genes with the highest entropy variation in a given differentiation pathway matched genes known as pathway-specific, whereas genes with the highest expression variation were common to all pathways. Finally, we showed that the level of cell-to-cell variation is increased in the most immature compartment of hematopoiesis in myelodysplastic syndromes. These data suggest that differentiation could be better conceptualized as a dynamical stochastic process with a transient stage of cellular indetermination. Effects of substrate on shrimp growth, water quality and bacterial community in the biofloc system nursing Penaeus vannamei postlarvae This study aimed to investigate the effects of substrate on water quality, shrimp growth and bacterial community in the biofloc system with a salinity of 5{per thousand}. Two treatments, biofloc system with (sB) or without (nB) addition of elastic solid packing filler (nylon) as substrate, were set up. Penaeus vannamei postlarvae (PL, [~] stage 15) were stocked at a density of 4000 PL m-3 in each treatment with triplicates for a 28-days culture experiment, taking glucose as carbon source (C:N 15:1). Results showed that the survival rate (96.3{+/-}3.6%), FCR (0.76{+/-}0.06) and productivity (1.54{+/-}0.12 kg m-3) in sB treatment were significantly better than those in nB treatment (81.0{+/-}7.1%, 0.98{+/-}0.08 and 1.14{+/-}0.09 kg m-3, P<0.05). All water parameters were in the recommended ranges. Substrate showed significant effect on TAN, TSS, turbidity, biofloc volume, pH and carbonate alkalinity (P < 0.05). Actinobacteria (4.0-22.7%), Bacteroidetes (10.4-33.5%), Firmicutes (0.2-11.2%), Planctomycetes (4.0-14.9%) and Proteobacteria (29.4-59.0%) were the most dominant phyla for both treatments. However, the bacterial community in sB treatment showed to be significantly different from that in nB treatment (Jaccard distance 0.94{+/-}0.01, P=0.001). Substrate showed significant effects on Shannon, Heip, Pielou and Simpson index, as well as relative abundances of Actinobacteria, Bacteroidetes and Planctomycetes (P < 0.05). The results suggested that addition of substrate affected the shrimp growth, water quality and bacterial community in the biofloc system nursing P. vannamei PL with a 5{per thousand} salinity. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Behavioral effects of ethanol in the Red Swamp Crayfish (Procambarus clarkii) 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. Strong immobilization of C. elegans en masse on cultivation plates by thermoelectric cooling for high-throughput submicron-resolution microscopy Despite its profound impact on biology, most high-resolution in vivo microscopy approaches remain low throughput because current immobilization techniques require significant manual effort. We greatly accelerate imaging of the nematode Caenorhabditis elegans by implementing a simple cooling approach to easily immobilize entire populations directly on their cultivation plates. We optimize and characterize cooling immobilization. Counterintuitively, relatively warmer temperatures immobilize animals significantly more effectively than colder temperatures utilized in prior studies. This enhanced immobilization enables clear submicron-resolution fluorescence imaging, which is challenging to achieve with most current immobilization techniques. We demonstrate 64x magnification 3D imaging and timelapse recording of neurons in adults and embryos without motion blur. Compared to standard azide immobilization, cooling immobilization reduces the animal preparation and recovery time by >98%, significantly increasing experimental speed. By obviating individual animal manipulation, our approach could also empower automated imaging of large C. elegans populations within standard experimental setups and workflows. Effect of a low concentration in chloride, sodium and potassium on oocyte maturation, oocyte hydration, ovulation and egg quality in rainbow trout. Water salinity is an important environmental factor known to have detrimental effects on salmonid reproduction, mostly when migrating female broodfish are held in sea water. In contrast, data obtained in freshwater are scarce and the impact of low water salinity, and more specifically of low water concentrations in sodium, chloride and potassium, during reproduction in freshwater is currently unknown. For this reason, and because ion and water fluxes are critical for the final steps of the female gamete formation, including oocyte hydration and ovulation, the aim of the present study was to investigate the impact of low salinity water on final oocyte maturation, ovulation and, ultimately, on egg quality, using rainbow trout as a physiological model and relevant aquaculture species.

Fish from the same commercial strain were raised either in a site characterized by low concentrations of Na+, K+, and Cl- ions in the water or in a closely located control site exhibiting higher concentration in these elements. Egg quality and duration of final oocyte maturation were investigated using innovative phenotyping tools such as automatic assessment of egg viability using the VisEgg system and non-invasive echograph-based monitoring of final oocyte maturation duration, respectively. Oocyte hydration during final oocyte maturation and after ovulation was also investigated. Finally, molecular phenotyping was performed using real-time PCR-based monitoring of several key players of final oocyte maturation and ovulation associated with ion and water transport, inflammation, proteolytic activity, and coagulation. Oocyte hydration and gene expression data were analyzed in the light of the duration of final oocyte maturation.

Here we show that low water salinity (i.e., low water concentration in chloride, sodium and potassium) negatively influences final oocyte maturation, ovulation and, ultimately, egg quality. Low water salinity triggered delayed ovulation and lower oocyte viability. When investigating the impact of low water salinity on final oocyte maturation duration, individuals presenting the most severe phenotypes exhibited impaired oocyte hydration and abnormally reduced gene expression levels of several key players of the ovulatory process. While the under expression of water (i.e., aquaporins) and ion (i.e., solute carriers) transporters is consistent with impaired oocyte hydration, our observations also indicate that the overall ovulatory gene expression program is disrupted. Our results raise the question of the mechanisms underlying the negative influence of low salinity water on the dynamics of the preovulatory phase, on the control of the oocyte homeostasis, including hydration, and on the overall success of the maturation-ovulation process.

HighlightsO_LILow water salinity impairs final oocyte maturation and egg quality in rainbow trout
C_LIO_LILow water salinity induces delayed ovulation and impaired oocyte hydration
C_LIO_LILow water salinity induces a dysregulation of several key ovulatory genes
C_LIO_LIMonitoring of final oocyte maturation can be performed using ultrasound staging
C_LI The 55K SNP-Based Exploration of QTL for Spikelet Number Per Spike in a Tetraploid Wheat (Triticum turgidum L.) Population: Chinese Landrace Ailanmai X Wild Emmer The spikelet number per spike (SNS) is a primary factor determining wheat yield. Common wheat breeding reduces the genetic diversity among elite germplasm resources, leading to a detrimental effect on future wheat production. It is, therefore, necessary to explore new genetic resources for SNS to increase wheat yield. A tetraploid landrace  Ailanmai x wild emmer wheat recombinant inbred line (RIL) population was used to construct a genetic map using the wheat 55K single nucleotide polymorphism (SNP) array. The linkage map containing 1150 bin markers with a total genetic distance of 2411.8 cM was obtained. Based on phenotypic data from eight environments and best linear unbiased prediction (BLUP) values, five quantitative trait loci (QTL) for SNS were identified, explaining 6.71-29.40% of the phenotypic variation. Two of them, QSns.sau-AM-2B.3 and QSns.sau-AM-3B.2, were detected as the major and novel QTL. Their effects were further validated in two additional F2 populations using tightly linked Kompetitive Allele-Specific PCR (KASP) markers. Potential candidate genes within the physical intervals of corresponding QTL were predicted to participate in inflorescence development and spikelet formation. Genetic associations between SNS and other agronomic traits were also detected and analyzed. This study demonstrates the feasibility of wheat 55K SNP array developed for common wheat in genetic mapping of tetraploid population and shows the potential application of wheat related species in wheat improvement programs. Predicting the zoonotic capacity of mammals to transmit SARS-CoV-2 Back and forth transmission of SARS-CoV-2 between humans and animals may lead to wild reservoirs of virus that can endanger efforts toward long-term control of COVID-19 in people, and protecting vulnerable animal populations that are particularly susceptible to lethal disease. Predicting high risk host species is key to targeting field surveillance and lab experiments that validate host zoonotic potential. A major bottleneck to predicting animal hosts is the small number of species with available molecular information about the structure of ACE2, a key cellular receptor required for viral cell entry. We overcome this bottleneck by combining species ecological and biological traits with 3D modeling of virus and host cell protein interactions using machine learning methods. This approach enables predictions about the zoonotic capacity of SARS-CoV-2 for over 5,000 mammals -- an order of magnitude more species than previously possible. The high accuracy predictions achieved by this approach are strongly corroborated by in vivo empirical studies. We identify numerous common mammal species whose predicted zoonotic capacity and close proximity to humans may further enhance the risk of spillover and spillback transmission of SARS-CoV-2. Our results reveal high priority areas of geographic overlap between global COVID-19 hotspots and potential new mammal hosts of SARS-CoV-2. With molecular sequence data available for only a small fraction of potential host species, predictive modeling integrating data across multiple biological scales offers a conceptual advance that may expand our predictive capacity for zoonotic viruses with similarly unknown and potentially broad host ranges. Cytosolic EZH2-IMPDH2 complexes regulate melanoma progression via GTP The enhancer of zeste homolog 2 (EZH2) oncoprotein is a histone methyltransferase that functions canonically as a catalytic subunit of the polycomb repressive complex 2 (PRC2) to tri-methylate histone H3 at Lys 27 (H3K27me3). Although targeting EZH2 methyltransferase is a promising therapeutic strategy against cancer, methyltransferase-independent oncogenic functions of EZH2 are described. Moreover, pharmacological EZH2 methyltransferase inhibition was only variably effective in pre-clinical and clinical studies, suggesting that targeting EZH2 methyltransferase alone may be insufficient. Here, we demonstrate a non-canonical mechanism of EZH2s oncogenic activity characterized by interactions with inosine monophosphate dehydrogenase 2 (IMPDH2) and downstream promotion of guanosine-5-triphosphate (GTP) production. EZH2-IMPDH2 interactions identified by Liquid Chromatography-Mass Spectrometry (LC-MS) of EZH2 immunoprecipitates from melanoma cells were verified to occur between the N-terminal EED-binding domain of cytosolic EZH2 and the CBS domain of IMPDH2 in a methyltransfersase-independent manner. EZH2 silencing reduced cellular GTP, ribosome biogenesis, RhoA-mediated actomyosin contractility and melanoma cell proliferation and invasion by impeding the activity of IMPDH2. Guanosine, which replenishes GTP, reversed these effects and thereby promoted invasive and clonogenic cell states even in EZH2 silenced cells. IMPDH2 silencing antagonized the proliferative and invasive effects of EZH2, also in a guanosine-reversible manner. In human melanomas, high cytosolic EZH2 and IMPDH2 expression were associated with nucleolar enlargement, a marker of ribosome biogenesis. EZH2-IMPDH2 complexes were also observed in a range of cancers in which Sappanone A (SA), which inhibits EZH2-IMPDH2 interactions, was anti-tumorigenic, although notably non-toxic in normal cells. These findings illuminate a previously unrecognized, non-canonical, methyltransferase-independent, and GTP-dependent mechanism by which EZH2 regulates tumorigenicity in melanoma and other cancers, opening new avenues for development of anti-EZH2 therapeutics.

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org.highwire.dtl.DTLVardef@153dd35org.highwire.dtl.DTLVardef@dfeb43org.highwire.dtl.DTLVardef@ce8148org.highwire.dtl.DTLVardef@189d8da_HPS_FORMAT_FIGEXP  M_FIG Graphical Abstract C_FIG HighlightsO_LIEZH2 has non-canonical methyltransferase-independent and GTP-dependent tumorigenic and metastatic functions in melanoma.
C_LIO_LIThe N-terminal EED-binding domain of EZH2 interacts with the CBS domain of IMPDH2 in a polycomb repressive complex 2- (PRC2-) and methylation-independent manner.
C_LIO_LIEZH2 accumulates with IMPDH2 in the cytoplasm and increases IMPDH2s tetramerization-mediated activity independently of EZH2 methyltransferase.
C_LIO_LIEZH2 upregulates GTP synthesis by IMPDH2 activation and thereby activates ribosome biogenesis via rRNA synthesis and actomyosin contractility via RhoA GTPase.
C_LIO_LISappanone A (SA) inhibits IMPDH2-EZH2 interactions and is anti-proliferative across a range of cancers including melanoma, but not in normal cells.
C_LI Reconstitution of 3'-processing of mammalian pre-mRNA reveals a central role of RBBP6 The 3 ends of almost all eukaryotic mRNAs are generated in an essential two-step processing reaction, endonucleolytic cleavage of an extended precursor followed by the addition of a poly(A) tail. By reconstituting the reaction from overproduced and purified proteins, we provide a minimal list of fourteen polypeptides essential and two stimulatory for RNA processing. In a reaction depending on the polyadenylation signal AAUAAA, the reconstituted system cleaves pre-mRNA at a single preferred site corresponding to the one used in vivo. Among the proteins, Cleavage Factor I stimulates cleavage but is not essential, consistent with its prominent role in alternative polyadenylation. RBBP6 is required, structural data showing it to contact and presumably activate the endonuclease CPSF73 through its DWNN domain. The C-terminal domain of RNA polymerase II is dispensable. ATP, but not its hydrolysis, supports RNA cleavage by binding to the hClp1 subunit of cleavage factor II with submicromolar affinity. A Kozak-related non-coding deletion effectively increases B.1.1.7 transmissibility The high transmissibility acquisition of SARS-CoV-2 Variant of Concern (VOC) B.1.1.7 remains unclear and only mutations in coding regions have been examined. We analyzed 875,338 high-quality SARS-CoV-2 genomic sequences and the epidemiology metadata. The occurrence of a non-coding deletion (g.a28271-) in the B.1.1.7 background immediately causes the rapid spread of B.1.1.7. The number of B.1.1.7-like strains lacking the deletion is significantly less than that of B.1.1.7 strains (n = 259 vs 92,688, P-value< 4.9 x 10-324). The same highly significant statistics is observed in different countries, gender and age groups. However, the deletion alone does not cause such high viral transmissibility. The deletion and another mutation (g.gat28280cta) co-affect translational efficiency of the genes N and ORF9b by changing the core Kozak sites. The deletion interacts synergistically with S:p.P681H and S:p.T716I to increase viral transmissibility. Therefore, the Kozak-related non-coding deletion, also carried by the Delta VOC, is crucial for the high viral transmissibility of SARS-CoV-2. Recombination marks the evolutionary dynamics of a recently endogenized retrovirus All vertebrate genomes have been colonized by retroviruses along their evolutionary trajectory. While endogenous retroviruses (ERVs) can contribute important physiological functions to contemporary hosts, such benefits are attributed to long-term co-evolution of ERV and host because germline infections are rare and expansion is slow, because the host effectively silences them. The genomes of several outbred species including mule deer (Odocoileus hemionus) are currently being colonized by ERVs, which provides an opportunity to study ERV dynamics at a time when few are fixed. Because we have locus-specific data on the distribution of cervid endogenous retrovirus (CrERV) in populations of mule deer, in this study we determine the molecular evolutionary processes acting on CrERV at each locus in the context of phylogenetic origin, genome location, and population prevalence. A mule deer genome was de novo assembled from short and long insert mate pair reads and CrERV sequence generated at each locus. CrERV composition and diversity have recently measurably increased by horizontal acquisition of a new retrovirus lineage. This new lineage has further expanded CrERV burden and CrERV genomic diversity by activating and recombining with existing CrERV. Resulting inter-lineage recombinants endogenized and subsequently retrotransposed. CrERV loci are significantly closer to genes than expected if integration were random and gene proximity might explain the recent expansion by retrotransposition of one recombinant CrERV lineage. Thus, in mule deer, retroviral colonization is a dynamic period in the molecular evolution of CrERV that also provides a burst of genomic diversity to the host population. A protease-activatable luminescent biosensor andreporter cell line for authentic SARS-CoV-2 infection Efforts to define serological correlates of protection against COVID-19 have been hampered by the lack of a simple, scalable, standardised assay for SARS-CoV-2 infection and antibody neutralisation. Plaque assays remain the gold standard, but are impractical for high-throughput screening. In this study, we show that expression of viral proteases may be used to quantitate infected cells. Our assays exploit the cleavage of specific oligopeptide linkers, leading to the activation of cell-based optical biosensors. First, we characterise these biosensors using recombinant SARS-CoV-2 proteases. Next, we confirm their ability to detect viral protease expression during replication of authentic virus. Finally, we generate reporter cells stably expressing an optimised luciferase-based biosensor, enabling viral infection to be measured within 24 h in a 96- or 384-well plate format, including variants of concern. We have therefore developed a luminescent SARS-CoV-2 reporter cell line, and demonstrated its utility for the relative quantitation of infectious virus and titration of neutralising antibodies.

Author summaryTechniques for measuring infection with SARS-CoV-2 in the laboratory are laborious and time-consuming, and different laboratories use different approaches. There is therefore no generally agreed way to quantitate neutralising antibodies against SARS-CoV-2, which block infection with the virus and protect people from COVID-19. In this study, we describe a new way to measure SARS-CoV-2 infection, which is much simpler and faster than existing methods. It relies on the production of a specific protease enzyme by the virus, which is able to cleave and activate an engineered protein biosensor in infected cells. This biosensor emits light in the presence of viral infection, and the amount of light released is used as a readout for the amount of infectious SARS-CoV-2 present. The signal is very sensitive, so the number of infected cells required is very small, and the method can be scaled-up to test many samples at once. In particular, we demonstrate how it can be used to detect different variants of SARS-CoV-2, and quantitate neutralising antibodies against these viruses.