Hierarchical Bayesian Integrated Model for Estimating Migratory Bird Harvest in Canada The Canadian Wildlife Service (CWS) requires reliable estimates of the harvest of migratory game birds, including waterfowl, to effectively manage populations of these hunted species. The National Harvest Survey is an annual survey of hunters who purchase Canadas mandatory migratory game bird hunting permit, integrating information from a survey of hunting activity with information from a separate survey of species composition in the harvest. We use these survey data to estimate the number of birds harvested for each species, as well as hunting activity metrics such as the number of active hunters and days spent hunting. The analytical methods used to generate these estimates have not changed since the survey was first designed in the early 1970s. Here we describe a new hierarchical Bayesian integrated model, which replaces the series of ratio estimators that comprised the old model. We are now using this new model to generate estimates for migratory bird harvests as of the 2019-2020 hunting season, and to generate updated estimates for all earlier years. The hierarchical Bayesian model uses over-dispersed Poisson distributions to model mean hunter activity and harvest (zero inflated Poisson and zero truncated Poisson, respectively). It also includes multinomial distributions to model some key components including, variation in total harvest across periods of the hunting season, the species composition of the harvest within each of those periods, and the age and sex composition in the harvests of a given species. We estimated the parameters of the Poisson and the multinomial distributions for each year as random effects using first-difference time-series. This time-series component allows the model to share information across years and reduces the sensitivity of the estimates to annual sampling noise. The new model estimates are generally very similar to those from the old model, particularly for the species that occur most commonly in the harvest, and so the results do not suggest any major changes to harvest management decisions and regulations. However, estimates for all species from the new model are more precise and less susceptible to annual sampling error, particularly for species that occur less commonly in the harvest (e.g., sea ducks and other species of conservation concern). This new model, with its hierarchical Bayesian framework, will also facilitate future improvements and elaborations, allowing the incorporation of prior information from the rich literature and knowledge in game bird management and biology.
Scaling effects of temperature on parasitism from individuals to host-parasite systems Parasitism is expected to change in a warmer future, but whether warming leads to substantial increases in parasitism remains unclear. Understanding how warming effects on parasitism in individual hosts (e.g., parasite load) translate to effects on population-level parasitism (e.g., prevalence, R0) remains a major knowledge gap. We analyzed the temperature dependence of parasitism at both host and population levels in thirteen empirical vector-borne host-parasite systems and found a strong, significant positive correlation between the thermal optima of individual- and population-level parasitism. We also found a significant, positive correlation in eleven environmentally-transmitted parasite systems, though several of these systems exhibited thermal optima >5{o}C apart between individual and population levels. Similarly, parasitism thermal optima were close to host performance thermal optima in vector-borne systems but not in environmentally-transmitted systems. We then adapted and simulated simple models for both transmission modes and found a similar pattern to the empirical systems: thermal optima in vector-borne systems were more strongly correlated across scales compared to environmentally-transmitted systems. Generally, our results suggest that information on the temperature-dependence, and specifically the thermal optimum, at either the individual- or population-level should provide a useful--though not quantitatively exact--baseline for predicting temperature dependence at the other level, especially in vector-borne parasite systems. Environmentally-transmitted parasitism may operate by a different set of rules, in which temperature-dependence is decoupled in some systems, requiring the need for trait-based studies of temperature-dependence at individual and population levels.
Engineered bacteria detect tumor DNA Advances in bacterial engineering have catalysed the development of living cell diagnostics and therapeutics1-3, including microbes that respond to diseases such as gut inflammation4, intestinal bleeding5, pathogens6 and hypoxic tumors7. Bacteria can easily access the entire gastrointestinal tract via oral administration8, and they can produce outputs that can be noninvasively measured in stool4 or urine7. Cellular memory, such as bistable switches4,9,10 or genomic rearrangement11, has been used to allow bacteria to store information over time. However, living biosensors have not yet been engineered to detect specific DNA sequences or mutations from outside the cell. Here, we engineer naturally competent Acinetobacter baylyi to detect donor DNA from the genomes of colorectal cancer (CRC) cells and organoids. We characterize the functionality of the biosensors in vitro with co-culture assays and then validate in vivo with sensor bacteria delivered orally or rectally into mice injected with orthotopic donor CRC organoids. We observe horizontal gene transfer from the tumor to the sensor bacteria in vivo, allowing their detection in stool. The sensor bacteria achieved 100% discrimination between mice with and without CRC using both delivery methods. Our findings establish a framework for biosensing applications that require the detection of mutations or organisms within environments that are difficult to sample. In addition, the platform can be readily expanded to include in situ production and delivery of therapeutic payloads at the detection site. A Novel Proposal for an Index for Regional Cerebral Perfusion Pressure - A Theoretical Approach Using Fluid Dynamics Cerebral blood flow (CBF) / cerebral blood volume (CBV) ratio derived by [15O] H2O/ CO2 and CO positron emission tomography (PET) examination has been used empirically as an index for cerebral perfusion pressure (CPP). However, this equation lacks a theoretical basis and furthermore, has not been confirmed to be proportionate to CPP, as direct measurement of local CPP is not practical.

We have developed a new index for CPP using the Poiseuille equation based on a simple model. Our model suggests that CBF/CBV2 is proportionate to CPP and that it is mathematically a more accurate index than CBF/CBV. 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. Sarcoplasmic reticulum calcium handling in young DBA/2J vs C57BL/10 mdx models of Duchenne muscular dystrophy The DBA/2J (D2) mdx mouse has emerged as a more severe model of Duchenne muscular dystrophy when compared to the traditional C57BL/10 (C57) mdx mouse. Here, we questioned whether sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) function would differ in muscles from young D2 and C57 mdx mice. In gastrocnemius muscles, both D2- and C57 mdx mice exhibited signs of impaired Ca2+ uptake, however, this was more severe in D2 mdx mice. Maximal SERCA activity was lowered only in D2 mdx gastrocnemius muscles and not C57 mdx muscles. Furthermore, in the left ventricle and diaphragm, Ca2+ uptake was impaired in C57 mdx muscles with lowered rates of Ca2+ uptake compared with C57 WT mice, whereas in muscles from D2 mdx mice, rates of Ca2+ uptake were unattainable due to the severe impairments in their ability to transport Ca2+. Overall, our study demonstrates that SERCA function is drastically impaired in young D2 mdx mice. Substrate dynamics contribute to enzymatic specificity in human and bacterial methionine adenosyltransferases Protein conformational change can facilitate the binding of non-cognate substrates and underlie promiscuous activities. However, the contribution of substrate conformational dynamics to this process is comparatively poorly understood. Here we analyse human (hMAT2A) and Escherichia coli (eMAT) methionine adenosyltransferases that have identical active sites but different substrate specificity. In the promiscuous hMAT2A, non-cognate substrates bind in a stable conformation to allow catalysis. In contrast, non-cognate substrates rarely sample stable productive binding modes in eMAT owing to altered mobility in the enzyme active site. Different cellular concentrations of substrate likely drove the evolutionary divergence of substrate specificity in these orthologs. The observation of catalytic promiscuity in hMAT2A led to the detection of a new human metabolite, methyl thioguanosine, that is produced at elevated level in a cancer cell line. This work establishes that identical active sites can result in different substrate specificity owing to the effects of substrate and enzyme dynamics. Protein Complex Structure Prediction Powered by Multiple Sequence Alignments of Interologs from Multiple Taxonomic Ranks and AlphaFold2 AlphaFold2 is expected to be able to predict protein complex structures as long as a multiple sequence alignment (MSA) of the interologs of the target protein-protein interaction (PPI) can be provided. However, preparing the MSA of protein-protein interologs is a non-trivial task due to the existence of paralogs. In this study, a simplified phylogeny-based approach was applied to generate the MSA of interologs, which was then used as the input to AlphaFold2 for protein complex structure prediction. Extensively benchmarked this protocol on non-redundant PPI dataset including 107 bacterial PPIs and 442 eukaryotic PPIs, we show complex structures of 79.5% of the bacterial PPIs and 49.8% of the eukaryotic PPIs can be successfully predicted. Considering PPIs may not be conserved in species with long evolutionary distances, we further restricted interologs in the MSA to different taxonomic ranks of the species of the target PPI in protein complex structure prediction. We found the success rates can be increased to 87.9% for the bacterial PPIs and 56.3% for the eukaryotic PPIs if interologs in the MSA are restricted to a specific taxonomic rank of the species of each target PPI. Finally, we show the optimal taxonomic ranks for protein complex structure prediction can be selected with the application of the recalculated predicted TM-scores of the output models. An End-to-End Deep Learning Speech Coding and Denoising Strategy for Cochlear Implants Cochlear implant (CI) users struggle to understand speech in noisy conditions. To address this problem, we propose a deep learning speech denoising sound coding strategy that estimates the CI electric stimulation patterns out of the raw audio data captured by the micro-phone, performing end-to-end CI processing. To estimate the relative denoising performance differences between various approaches, we compared this technique to a classic Wiener filter and to a convTasNet. Speech enhancement performance was assessed by means of signal-to-noise-ratio improvement and the short-time objective speech intelligibility measure. Additionally, 5 CI users were evaluated for speech intelligibility in noise to assess the potential benefits of each algorithm. Our results show that the proposed method is capable of replacing a CI sound coding strategy while preserving its general use for every listener and performing speech enhancement in noisy environments, without sacrificing algorithmic latency. Immune complex solubility and size govern individual Fc-gamma receptor responses: Novel biomarkers for autoimmune diseases Fc-gamma receptor (Fc{gamma}R) activation by soluble IgG immune complexes (sICs) represents a major mechanism of inflammation in certain autoimmune diseases such as systemic lupus erythematosus (SLE). A robust and scalable test system allowing for the detection and quantification of sIC bioactivity is missing. Previously described Fc{gamma}R interaction assays are limited to certain Fc{gamma}Rs, lack scalability and flexibility, are not indicative of receptor activation or lack sensitivity towards sIC size. We developed a comprehensive reporter cell panel detecting individual activation of Fc{gamma}Rs from humans and the mouse. The reporter cell lines were integrated into an assay format that provides flexible read-outs enabling the quantification of sIC reactivity via ELISA or a fast detection using flow cytometry. This identified Fc{gamma}RIIA(H) and Fc{gamma}RIIIA as the most sIC-sensitive Fc{gamma}Rs in our test system. Applying the assay we demonstrate that sICs versus immobilized ICs are fundamentally different Fc{gamma}R-ligands with regard to Fc{gamma}R preference and signal strength. Reaching a detection limit in the very low nanomolar range, the assay proved also to be sensitive to sIC stoichiometry and size enabling for the first time a complete reproduction of the Heidelberger-Kendall precipitation curve in terms of immune receptor activation. Analyzing sera from SLE patients and mouse models of lupus and arthritis proved that sIC-dependent Fc{gamma}R activation has predictive capabilities regarding severity of SLE disease. The new methodology provides a sensitive, scalable and comprehensive tool to evaluate the size, amount and bioactivity of sICs in all settings.

One Sentence SummaryIn this study we established a comprehensive Fc{gamma}R reporter cell assay enabling the detection and quantification of soluble immune complexes generated in experimental and clinical settings. A Positive Correlation between Bacterial GC Content and Growth Temperature BackgroundGC pairs are generally more stable than AT pairs; GC-rich genomes were proposed to be more adapted to high temperatures than AT-rich genomes. Previous studies consistently showed positive correlations between growth temperature and the GC contents of structural RNA genes. However, for the whole genome sequences and the silent sites of the codons in protein-coding genes, the relationship between GC content and growth temperature is in a long-lasting debate.

ResultsWith a dataset much larger than previous studies (681 bacteria and 155 archaea with completely assembled genomes), our phylogenetic comparative analyses showed positive correlations between optimal growth temperature (Topt) and GC content both in bacterial and archaeal structural RNA genes and in bacterial whole genome sequences, chromosomal sequences, plasmid sequences, core genes, and accessory genes. However, in the 155 archaea, we did not observe a significant positive correlation of Topt with whole-genome GC content (GCw) or GC content at four-fold degenerate sites. We randomly drew 155 samples from the 681 bacteria for 1000 rounds. In most cases (> 95%), the positive correlations between Topt and genomic GC contents became statistically nonsignificant (P > 0.05). This result suggested that the small sample sizes might account for the lack of positive correlations between growth temperature and genomic GC content in the 155 archaea and the bacterial samples of previous studies. Comparing the GC content among four categories (psychrophiles/psychrotrophiles, mesophiles, thermophiles, and hyperthermophiles) also revealed a positive correlation between GCw and growth temperature in bacteria. By including the GCw of incompletely assembled genomes, we expanded the sample size of archaea to 303. Positive correlations between GCw and Topt appear especially after excluding the halophilic archaea whose GC contents might be are strongly shaped by intense UV radiation.

ConclusionsThis study explains the previous contradictory observations and ends a long debate. Prokaryotes growing in high temperatures have higher GC contents. Thermal adaptation is one possible explanation for the positive association. Meanwhile, we propose that the elevated efficiency of DNA repair in response to heat mutagenesis might have the by-product of increasing GC content like that happens in intracellular symbionts and marine bacterioplankton. Rapid evolution of seed dormancy during sunflower de-domestication Hybridization between crops and their wild relatives may promote the evolution of de-domesticated (feral) weeds. Wild sunflower (Helianthus annuus L.) is typically found in ruderal environments, but crop-wild hybridization may facilitate the evolution of weedy populations. Using one crop-specific mitochondrial marker (CMS-PET1) and 14 nuclear SSR markers, we studied the origin and genetic diversity of a recently discovered weedy population of sunflower (named BRW). Then, using a resurrection approach, we tested for rapid evolution of weedy traits (seed dormancy, herbicide resistance, and competitive ability) by sampling weedy and wild populations 10 years apart (2007 and 2017). All the weedy plants present the CMS-PET1 cytotype, confirming their feral origin. At the nuclear markers, BRW showed higher genetic diversity than the cultivated lines and low differentiation with one wild population, suggesting that wild hybridization increased their genetic diversity. We found support for rapid evolution towards higher seed dormancy, but not for higher competitive ability or herbicide resistance. Our results highlight the importance of seed dormancy during the earliest stages of adaptation and show that crop-wild hybrids can evolve quickly in agricultural environments. ConVarT: a search engine for orthologous variants and functional inference of human genetic variants The availability of genetic variants, together with phenotypic annotations from model organisms, facilitates comparing these variants with equivalent variants in humans. However, existing databases and search tools do not make it easy to scan for equivalent variants, namely "matching variants" (MatchVars) between humans and other organisms. Therefore, we developed an integrated search engine called ConVarT (http://www.convart.org/) for matching variants between humans, mice, and C. elegans. ConVarT incorporates annotations (including phenotypic and pathogenic) into variants, and these previously unexploited phenotypic MatchVars from mice and C. elegans can give clues about the functional consequence of human genetic variants. Our analysis shows that many phenotypic variants in different genes from mice and C. elegans, so far, have no counterparts in humans, and thus, can be useful resources when evaluating a relationship between a new human mutation and a disease. Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty BackgroundMultiple sequence alignments (MSAs) represent the fundamental unit of data inputted to most comparative sequence analyses. In phylogenetic analyses in particular, errors in MSA construction have the potential to induce further errors in downstream analyses such as phylogenetic reconstruction itself, ancestral state reconstruction, and divergence time estimation. In addition to providing phylogenetic methods with an MSA to analyze, researchers must also specify a suitable evolutionary model for the given analysis. Most commonly, researchers apply relative model selection to select a model from candidate set and then provide both the MSA and the selected model as input to subsequent analyses. While the influence of MSA errors has been explored for most stages of phylogenetics pipelines, the potential effects of MSA uncertainty on the relative model selection procedure itself have not been explored.

ResultsWe assessed the consistency of relative model selection when presented with multiple perturbed versions of a given MSA. We find that while relative model selection is mostly robust to MSA uncertainty, in a substantial proportion of circumstances, relative model selection identifies distinct best-fitting models from different MSAs created from the same set of sequences. We find that this issue is more pervasive for nucleotide data compared to amino-acid data. However, we also find that it is challenging to predict whether relative model selection will be robust or sensitive to uncertainty in a given MSA.

ConclusionsWe find that that MSA uncertainty can affect virtually all steps of phylogenetic analysis pipelines to a greater extent than has previously been recognized, including relative model selection. 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. Serotonin signals through postsynaptic Gαq, Trio RhoGEF, and diacylglycerol to promote C. elegans egg-laying circuit activity and behavior Activated Gq signals through Phospholipase-C{beta} (PLC{beta}) and Trio, a Rho GTPase exchange factor (RhoGEF), but how these distinct effector pathways promote cellular responses to neurotransmitters like serotonin remains poorly understood. We used the egg-laying behavior circuit of C. elegans to determine whether PLC{beta} and Trio mediate serotonin and Gq signaling through independent or related biochemical pathways. Our genetic rescue experiments suggest that PLC{beta} functions in neurons while Trio RhoGEF functions in both neurons and the postsynaptic vulval muscles. While Gq, PLC{beta}, and Trio RhoGEF mutants all fail to lay eggs in response to serotonin, optogenetic stimulation of the serotonin-releasing HSN neurons restores egg laying only in PLC{beta} mutants. PLC{beta} mutants showed vulval muscle Ca2+ transients while strong Gq and Trio RhoGEF mutants had little or no vulval muscle Ca2+ activity. Treatment with phorbol 12-myristate 13-acetate (PMA) that mimics 1,2-diacylglycerol (DAG), a product of PIP2 hydrolysis, rescued egg-laying circuit activity and behavior defects of Gq signaling mutants, suggesting both Phospholipase-C and Rho signaling promote synaptic transmission and egg laying via modulation of DAG levels. DAG activates effectors including UNC-13, however we find that phorbol esters, but not serotonin, stimulate egg laying in unc-13 and PLC{beta} mutants. These results support a model where serotonin signaling through Gq, PLC{beta}, and UNC-13 promote neurotransmitter release, and that serotonin also signals through Gq, Trio RhoGEF, and an unidentified, PMA-responsive effector to promote postsynaptic muscle excitability. Thus, the same neuromodulator serotonin can signal in distinct cells and effector pathways to coordinate activation of a motor behavior circuit. A computational modeling approach for predicting multicell patterns based on signaling-induced differential adhesion Differential adhesion within cell populations enables the emergence of unique patterns in heterogeneous multicellular systems. This process has been previously explored using synthetically engineered heterogenous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models may be leveraged to more systematically explore the key parameters that drive the emergence of different patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. The model was used to predict how varying initial cell seedings, cadherin induction probabilities, or homotypic adhesion strengths between cells impact spheroid patterning, and unsupervised machine learning techniques were used to map system parameters to unique spheroid patterns. The model was then deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern. Programmed knockout mutation of liver fluke granulin, Ov-grn-1, impedes malignant transformation during chronic opisthorchiasis Infection with the food-borne liver fluke Opisthorchis viverrini is the principal risk factor for cholangiocarcinoma in the Mekong Basin countries of Thailand, Lao PDR, Vietnam, Myanmar and Cambodia. Using a novel model of CCA, involving infection with gene-edited liver flukes in the hamster during concurrent exposure to a nitrosamine, we explored the role of the fluke granulin-like growth factor Ov-GRN-1 in malignancy. We produced programmed gene knockout flukes ({Delta}Ov-grn-1) by delivery of a CRISPR/Cas9/gRNA system by electroporation. Genome sequencing confirmed Cas9-catalyzed mutations in the targeted genes, which was accompanied by rapid depletion of transcripts and the cognate proteins. Whereas Ov-grn-1 gene-edited parasites colonized the biliary tract and developed into adult flukes, less hepatobiliary tract disease manifested during chronic infection with{Delta} Ov-grn-1 worms in comparison to hamsters infected with control parasites. Specifically, immunohistochemical analysis of thin sections of livers revealed markedly less periductal fibrosis surrounding the flukes and less liver fibrosis globally during infection with{Delta} Ov-grn-1 genotype worms, minimal biliary epithelial cell proliferation, and markedly fewer mutations of TP53 in biliary epithelial cells. Moreover, fewer hamsters developed high-grade cholangiocarcinoma when infected with the{Delta} Ov-grn-1 flukes compared to controls. The clinically-relevant, pathophysiological phenotype of the hepatobiliary tract confirmed a role for this secreted growth factor in malignancy and morbidity during opisthorchiasis. Conformist social learning inoculates against adverse risk aversion Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majoritys behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This  collective behavioural rescue, emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences. The activity and functions of soil microbial communities in the Finnish sub-Arctic vary across vegetation types Increased microbial activity in high-latitude soils due to climate change might lead to higher greenhouse gas (GHG) emissions. However, mechanisms of microbial GHG production and consumption in tundra soils are not thoroughly understood. We analyzed 116 soil metatranscriptomes from 73 sites in the Finnish sub-Arctic to investigate how the diversity and functional potential of bacterial and archaeal communities vary across vegetation types and soil layers. Soils differed in physicochemical conditions, with meadow soils being characterized by higher pH and low soil organic matter (SOM) and carbon/nitrogen ratio whereas dwarf shrub-dominated ecosystems with high SOM and low pH. Actinobacteria, Acidobacteria, Alphaproteobacteria, and Planctomycetes predominated all communities but there were significant differences on genus level between vegetation types, as plant polymer degrading groups were more active in shrub-dominated soils compared to meadows. Given that climate change scenarios predict expansion in dwarf shrubs at high latitudes, our results indicate that the rate of carbon turnover in tundra soils may increase in the future. Additionally, transcripts of methanotrophs were detected in the mineral layer of all soils, potentially moderating methane fluxes from deeper layers. In all, this study provides new insights into possible shifts in tundra microbial diversity and activity with climate change. Morphology of immatures of the thelytokous ant, Monomorium triviale Wheeler (Formicidae: Myrmicinae: Solenopsidini) with descriptions of the extraordinary last-instar queen larvae The ant genus Monomorium is one of the most species-rich but taxonomically problematic groups in the hyperdiverse subfamily Myrmicinae. An East Asian species, M. triviale Wheeler, produces both reproductive queens and sterile workers via obligate thelytokous parthenogenesis. Here, we describe the immature forms of M. triviale based on light and scanning electron microscopy observations, with a note on the striking caste dimorphism in the last larval instar. The last-instar queen larvae were easily recognized by their large size, "aphaenogastroid" body shape, and rows of doorknob-like tubercles on the lateral and dorsal body surface. This type of queen-specific structure has not been found in ants in general, let alone congeneric species found in Japan. In stark contrast to the queen larvae, worker larvae showed a "pheidoloid" body shape and a body surface similar to other ants. The worker larvae were estimated to have three instars, consistent with previously described congeners. The pupae of both castes had no cocoon, a characteristic commonly described in other Myrmicinae species. In total, the developmental period from egg to adult worker averaged 59 days under 25{degrees}C. We discuss possible functions of the tubercles of queen larvae based on previous studies. Myoparr-associated and -independent multiple roles of heterogeneous nuclear ribonucleoprotein K during skeletal muscle cell differentiation RNA-binding proteins (RBPs) regulate cell physiology via the formation of ribonucleic-protein complexes with coding and non-coding RNAs. RBPs have multiple functions in the same cells; however, the precise mechanism through which their pleiotropic functions are determined remains unknown. In this study, we revealed the multiple inhibitory functions of heterogeneous nuclear ribonucleoprotein K (hnRNPK) for myogenic differentiation. We first identified hnRNPK as a lncRNA Myoparr binding protein. Gain- and loss-of-function experiments showed that hnRNPK repressed the expression of myogenin at the transcriptional level. The hnRNPK-binding region of Myoparr was required to repress myogenin expression. Moreover, hnRNPK repressed the expression of a set of genes coding for aminoacyl-tRNA synthetases in a Myoparr-independent manner. Mechanistically, hnRNPK regulated the eIF2/Atf4 pathway, one branch of the intrinsic pathways of the endoplasmic reticulum sensors, in differentiating myoblasts. Thus, our findings demonstrate that hnRNPK plays lncRNA-associated and - independent multiple roles during myogenic differentiation, indicating that the analysis of lncRNA-binding proteins will be useful for elucidating both the physiological functions of lncRNAs and the multiple functions of RBPs. Loss of histone methyltransferase SETD1B in oogenesis results in the redistribution of genomic histone 3 lysine 4 trimethylation Histone 3 lysine 4 trimethylation (H3K4me3) is an epigenetic mark found at gene promoters and CpG islands. H3K4me3 is essential for mammalian development, yet mechanisms underlying its genomic targeting are poorly understood. H3K4me3 methyltransferases SETD1B and MLL2 are essential for oogenesis. We investigated changes in H3K4me3 in Setd1b conditional knockout (cKO) oocytes using ultra-low input ChIP-seq, with comparisons to DNA methylation and gene expression analyses. H3K4me3 was redistributed in Setd1b cKO oocytes showing losses at active gene promoters associated with downregulated gene expression. Remarkably, many regions also gained H3K4me3, in particular those that were DNA hypomethylated, transcriptionally inactive and CpG-rich, which are hallmarks of MLL2 targets. Consequently, loss of SETD1B disrupts the balance between MLL2 and de novo DNA methyltransferases in determining the epigenetic landscape during oogenesis. Our work reveals two distinct, complementary mechanisms of genomic targeting of H3K4me3 in oogenesis, with SETD1B linked to gene expression and MLL2 to CpG content.

Graphical AbstractIn oogenesis, SETD1B and CXXC1 target H3K4me3 to actively transcribed gene promoters, while MLL2 targets transcriptionally inactive regions based on underlying CpG composition (upper panel). When SETD1B is ablated, H3K4me3 is lost at a subset of active promoters, resulting in downregulation of transcription (lower panel). Loss of SETD1B alters the activity of MLL2, permitting MLL2 to deposit H3K4me3 at CpG-rich regions, many of which should otherwise be DNA methylated. Thus, it is evident that MLL2 and de novo DNMTs compete for genomic occupancy late in oogenesis, and loss of SETD1B disrupts the balance of these mechanisms.

O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY Ultrahigh-Throughput Ambient MS: Direct Analysis at 22 Samples per Second by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) mass spectrometry is an ambient-direct sampling method being developed for high-throughput, label-free, biochemical screening of large-scale compound libraries. Here, we report the development of an ultrahigh-throughput continuous motion IR-MALDESI sampling approach capable of acquiring data at rates up to 22.7 samples per second in a 384-well microtiter plate. At top speed, less than 1% analyte carryover is observed from well-to-well and signal intensity relative standard deviations (RSD) of 11.5% and 20.9% for 3 M 1-hydroxymidazolam and 12 M dextrorphan, respectively, are achieved. The ability to perform parallel kinetics studies on 384 samples with ~30s time resolution using an isocitrate dehydrogenase 1 (IDH1) enzyme assay is shown. Finally, we demonstrate the repeatability and throughput of our approach by measuring 115,200 samples from 300 microtiter plate reads consecutively over 5.54 hours with RSDs under 8.14% for each freshly introduced plate. Taken together, these results demonstrate the use of IR-MALDESI at sample acquisition rates that surpass other currently reported direct sampling mass spectrometry approaches used for high throughput compound screening.

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org.highwire.dtl.DTLVardef@5f916corg.highwire.dtl.DTLVardef@4473b4org.highwire.dtl.DTLVardef@82e8forg.highwire.dtl.DTLVardef@128b57b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Reduction of protein disulfide isomerase results in open conformations and stimulates dynamic exchange between structural ensembles Protein disulfide isomerase (PDI) is a ubiquitous redox-regulated enzyme that interacts with hundreds of client proteins intracellularly and extracellularly. It comprises two redox-sensitive domains, each hosting the conserved catalytic motif CxxC, two redox-insensitive protein-binding domains, and three linkers. Snapshots of oxidized and reduced PDI have been obtained by X-ray crystallography. Yet, how PDIs structure dynamically changes in response to the redox microenvironment and ligand binding remain unknown. Here, we used multiparameter confocal single-molecule Forster resonance energy transfer (smFRET) and multiple FRET pairs to track the movements of the two catalytic domains with high temporal resolution. Our studies document that, at equilibrium, PDI visits three structurally distinct conformational ensembles, two "open" (O1 and O2) and one "closed" (C). We show that the redox environment dictates the time spent in each ensemble and the rate at which they exchange. While oxidized PDI samples O1, O2 and C more evenly and in a slower fashion, reduced PDI predominantly populates O1 and O2, and exchanges between them more rapidly, on the sub-millisecond timescale. These findings were not expected based on crystallographic data. Using mutational analyses, we further demonstrate that the two active sites are structurally nonequivalent and that ligands targeting the active sites of reduced PDI shift the equilibrium towards closed conformations of the enzyme. This work introduces a new structural framework that challenges current views of PDI dynamics, helps rationalize the multifaced role of PDI in biology and may assist drug development. Newly developed ad hoc molecular assays show how eDNA can witness and anticipate the monk seal recolonization of central Mediterranean The monk seal Monachus monachus is the most endangered pinniped worldwide and the only one found in the Mediterranean, where its distribution and abundance have suffered a drastic decline in the last few decades. Data on its status are scattered due to both its rarity and evasiveness, and records are biased towards occasional, mostly coastal, encounters. Nowadays molecular techniques allow us to detect and quantify minute amounts of DNA traces released in the environment (eDNA) by any organism. We present three qPCR-assays targeting the monk seal mitogenome. The assays were soundly tested on an extensive and diversified sample set (n=73), including positive controls from Madeira breeding population collected during the peak of abundance, and two opportunistic Mediterranean eDNA-sample collections (offshore/coastal) from on-going projects. Monk seal DNA was detected in 47.2% and 66.7% of the samples collected in the Tyrrhenian from a ferry platform (2018-2019) and in the Pelagie archipelago -Strait of Sicily- (2020) respectively, anticipating (up to 2 year) visual observations occurred subsequently in proximity of the sampled areas. In the Tyrrhenian, detection occurrence increased between 2018 and 2019. Monk seal DNA recoveries were commoner in night-time ferry-samples, suggesting nocturnal predatory activity in pelagic waters. The proposed technique provides a non-invasive and yet highly-sensitive tool for defining the monk seal actual distribution and home range, its recovery rate and pinpoint coastal/offshore localities where prioritizing conservation, research, citizen science and education initiatives.