Two microbiota subtypes identified in Irritable Bowel Syndrome with distinct responses to the low FODMAP diet ObjectiveReducing FODMAPs can be clinically beneficial in IBS but the mechanism is poorly understood. We aimed to detect microbial signatures that might predict response to the low FODMAP diet and assess whether microbiota compositional and functional shifts could provide insights into its mode of action.

DesignWe used metagenomics to determine high-resolution taxonomic and functional profiles of the stool microbiota from IBS cases and household controls (n=56 pairs) on their usual diet. Clinical response and microbiota changes were studied in 41 pairs after 4 weeks on a low FODMAP diet.

ResultsUnsupervised analysis of baseline IBS cases pre-diet identified two distinct microbiota profiles, which we refer to as IBSP (pathogenic-like) and IBSH (health-like) subtypes. IBSP microbiomes were enriched in Firmicutes and genes for amino acid and carbohydrate metabolism, but depleted in Bacteroidetes species. IBSH microbiomes were similar to controls. On the low FODMAP diet IBSH and control microbiota were unaffected, but the IBSP signature shifted towards a health-associated microbiome with an increase in Bacteroidetes (p=0.009), a decrease in Firmicutes species (p=0.004) and normalization of primary metabolic genes. The clinical response to the low FODMAP diet was greater in IBSP subjects compared to IBSH (p = 0.02).

Conclusion50% of IBS cases manifested a  pathogenic gut microbial signature. This shifted towards the healthy profile on the low FODMAP diet; and IBSP cases showed an enhanced clinical responsiveness to the dietary therapy. The effectiveness of FODMAP exclusion in IBSP may result from the alterations in gut microbiota and metabolites produced. Microbiota signatures could be useful as biomarkers to guide IBS treatment; and investigating IBSP species and metabolic pathways might yield insights regarding IBS pathogenic mechanisms.

O_TEXTBOXSignificance of this studyO_ST_ABSWhat is already known on this subject?C_ST_ABSO_LIIBS subjects often respond to a low FODMAP diet.
C_LIO_LIThe gut microbiota has been implicated in IBS.
C_LIO_LIThe microbiota in IBS subjects may change with diet.
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What are the new findings?O_LIWe were able to stratify patients with IBS according to their gut microbiota species and metabolic gene signatures.
C_LIO_LIWe identified a distinct gut microbiota subtype with an enhanced clinical response to a low FODMAP diet compared to other IBS subjects.
C_LI

How might it impact on clinical practice in the foreseeable future?O_LIThe potential development of a microbiota signature as a biomarker to manage IBS cases with a low FODMAP diet recommendation.
C_LIO_LIIf the bacteria represented in the IBSP subtype are shown to play a pathogenic role in IBS, perhaps through the metabolic activity this provides a target for new therapies and an intermediate phenotype by which to assess them.
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C_TEXTBOX
Antiviral activity of molnupiravir precursor NHC against SARS-CoV-2 Variants of Concern (VOCs) and its therapeutic window in a human lung cell model SynopsisO_ST_ABSBackgroundC_ST_ABSThe UK Medicines and Regulatory Healthcare Agency (MHRA) have recently licensed the anti-viral drug, molnupiravir, for use in patients with mild-moderate COVID-19 disease with one or more risk factors for serious illness. Treatment with anti-viral drugs is best initiated early to prevent progression to severe disease, although the therapeutic window for intervention has not yet been fully defined.

ObjectivesThis study aimed to determine the activity of the molnupiravir (NHC) to different SARS-CoV-2 Variants of Concern (VoCs), and to establish the therapeutic window in human lung cell model.

MethodsDose response assays were performed in parallel to determine the IC50 (the concentration of drug required to inhibit virus titre by 50%) of NHC against different variants. Human ACE-2 A549 cells were treated with NHC at different time points either before, during or after infection with SARS- CoV-2.

ResultsHere we demonstrate that {beta}-D-N4-hydroxycytidine (NHC), the active metabolite of molnupiravir, has equivalent activity against four variants of SARS-CoV-2 in a human lung cell line ranging 0.04-0.16{micro}M IC50. Furthermore, we demonstrate that in-vitro activity of the drug is reduced in cells exposed to drug 48 hours after infection.

ConclusionsOne of the main advantages of molnupiravir is that it can be administered orally, and thus given to patients in an out-patient setting. These results support giving the drug early on after diagnosis or even in prophylaxis for individuals with high risk of developing severe disease.
Competitive dynamics underlie cognitive improvements during sleep. We provide evidence that human sleep is a competitive arena where cognitive domains vie for limited resources. Using pharmacology and effective connectivity analysis, we demonstrate that long-term memory and working memory are served by distinct offline neural mechanisms that are mutually antagonistic. Specifically, we administered zolpidem to increase central sigma activity and demonstrated targeted suppression of autonomic vagal activity. With effective connectivity, we determined the central activity has greater causal influence over autonomic activity, and the magnitude of this influence during sleep produced a behavioral trade-off between offline long-term and working memory processing. These findings show the first evidence of a sleep switch mechanism that toggles between central sigma-dependent long-term memory and autonomic vagal-dependent working memory processing.

Significant StatementSleep facilitates both long-term episodic memory consolidation and short-term working memory functioning. However, the mechanism by which the sleeping brain performs both complex feats, and which sleep features are associated with these processes remain unclear. Using a pharmacological approach, we demonstrate that long-term and working memory are served by distinct offline neural mechanisms, and that these mechanisms are mutually antagonistic. We propose a Sleep Switch model in which the brain toggles between the two memory processes via a complex interaction at the synaptic, systems, and mechanistic level, with implications for research on cognitive disturbances observed in neurodegenerative disorders such as Alzheimers and Parkinsons disease, both of which involve the decline of sleep. Ex vivo anticoagulants affect human blood platelet biomechanics with implications for high-throughput functional mechanophenotyping. Inherited platelet disorders affecting the human platelet cytoskeleton result in increased bleeding risk. However, deciphering their impact on cytoskeleton-dependent intrinsic biomechanics of platelets remains challenging and represents an unmet need from a diagnostic and prognostic perspective. It is currently unclear whether ex vivo anticoagulants used for the collection of peripheral blood impact the mechanophenotype of cellular components of blood. Using unbiased, high-throughput functional mechanophenotyping of single human platelets by deformability cytometry, we found that ex vivo anticoagulants are a critical pre-analytical variable that differentially influences platelet deformation, their size and functional response to agonists by altering the cytoskeleton. We applied our findings to characterize the functional mechanophenotype of platelets from a patient with Myosin Heavy Chain 9 (MYH9) related macrothrombocytopenia. Our data suggest that platelets from MYH9 p.E1841K mutation in humans affecting platelet non-muscle myosin heavy chain IIa (NMMHC-IIA) are biomechanically less deformable in comparison to platelets from healthy individuals. β-glucan imprinting remodels macrophage function in response to environmental cues In vitro, exposure of human primary monocytes to the fungal {beta}-glucan enhances their pro-inflammatory responsiveness towards several pathogens. Yet, the role of environmental condition of this process remains unclear. Here we found that {beta}-glucan-induced innate immune memory counteract the anti-inflammatory status of the macrophages. In response to {beta}-glucan imprinting, M-CSF-(M2-like-) macrophages increase their pro-inflammatory responsiveness to secondary stimuli associated with decrease of the M-CSF differentiation hallmarks. In contrast, in GM-CSF-(M1-like-) environment, {beta}-glucan imprinting reduced the pro-inflammatory canonical feature of the macrophages, together with their terminal differentiation marks. Comparing M-CSF and GM-CSF environment, we observed that {beta}-glucan-imprinted macrophages present comparable functions in terms of cytokine responses, phagocytosis, oxidative burst, and angiogenesis. This effect is mediated through Dectin-1 and associated with altered expression of the master regulators of macrophage terminal differentiation, IRF5 and IRF3. {beta}-glucan-induced innate immune memory skews the commitment of the macrophages in complex environment towards similar and less terminally differentiated cells. Together, these observations suggest a potential therapeutic role for {beta}-glucan-induced modulation of innate memory in different pathological contexts. Species-specific developmental timing dictates expansion of the avian wing skeletal pattern A fundamental question in biology is how species-specific rates of embryonic development are controlled in differently sized species. To address this problem, we compared wing development in the quail and the larger chick. We reveal that pattern formation (humerus to digits) is faster in the quail wing as determined by the earlier activation of 5 Hox genes, termination of developmental organisers (Shh and Fgf8) and the laying down of the skeleton (Sox9). Using interspecies tissue grafts, we show that developmental timing can be reset during a critical window in which retinoic acid signalling is active. Accordingly, retinoic acid can switch developmental timing between the quail and chick, and also between the chick and the larger turkey. We show that the incremental growth rate is equivalent between all three species, suggesting that differences in the expansion of the skeletal pattern are governed primarily by the tempo of development. Our findings have implications for how development is timed both within and between different species. Protein scaffold-based multimerization of soluble ACE2 efficiently blocks SARS-CoV-2 infection in vitro and in vivo Soluble ACE2 (sACE2) decoy receptors are promising agents to inhibit SARS-CoV-2, as their efficiency is less likely to be affected by common escape mutations in viral proteins. However, their success may be limited by their relatively poor potency. To address this challenge, we developed a large decoy library of sACE2 fusion proteins, generated with several protease inhibitors or multimerization tags. Among these decoys, multimeric sACE2 consisting of SunTag or MoonTag systems, which were originally utilized for signal amplification or gene activation systems, were extremely effective in neutralizing SARS-CoV-2 in pseudoviral systems and in clinical isolates. These novel sACE2 fusion proteins exhibited greater than 100-fold SARS-CoV-2 neutralization efficiency, compared to monomeric sACE2. SunTag or MoonTag in combination with a more potent version of sACE2, which has multiple point mutations for greater binding (v1), achieved near complete neutralization at a sub-nanomolar range, comparable with clinical monoclonal antibodies. Pseudoviruses bearing mutant versions of Spike, alpha, beta, gamma or delta variants, were also neutralized efficiently with SunTag or MoonTag fused sACE2(v1). Finally, therapeutic treatment of sACE2(v1)-MoonTag provided protection against SARS-CoV-2 infection in an in vivo mouse model. Overall, we suggest that the superior activity of the sACE2-SunTag or sACE2-MoonTag fusions is due to the greater occupancy of the multimeric sACE2 receptors on Spike protein as compared to monomeric sACE2. Therefore, these highly potent multimeric sACE2 decoy receptors may offer a promising treatment approach against SARS-CoV-2 infections.

One Sentence SummaryMultimerization of sACE2 markedly enhanced the neutralization of SARS-CoV-2 by blocking multiple viral spike proteins simultaneously. 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. Mendelian Randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics Mendelian Randomization (MR) is a valuable tool for inferring causal relationships among a wide range of traits using summary statistics from genome-wide association studies (GWASs). Existing summary-level MR methods often rely on strong assumptions, resulting in many false positive findings. To relax MR assumptions, ongoing research has been primarily focused on accounting for confounding due to pleiotropy. Here we show that sample structure is another major confounding factor, including population stratification, cryptic relatedness, and sample overlap. We propose a unified MR approach, MR-APSS, which (i) accounts for pleiotropy and sample structure simultaneously by leveraging genome-wide information; and (ii) allows to include more genetic variants with moderate effects as instrument variables (IVs) to improve statistical power without inflating type I errors. We first evaluated MR-APSS using comprehensive simulations and negative controls, and then applied MR-APSS to study the causal relationships among a collection of diverse complex traits. The results suggest that MR-APSS can better identify plausible causal relationships with high reliability. In particular, MR-APSS can perform well for highly polygenic traits, where the IV strengths tend to be relatively weak and existing summary-level MR methods for causal inference are vulnerable to confounding effects. Risky choice: probability weighting explains Independence Axiom violations in monkeys Expected Utility Theory (EUT) provides axioms for maximizing utility in risky choice. The Independence Axiom (IA) is its most demanding axiom: preferences between two options should not change when altering both options equally by mixing them with a common gamble. We tested common consequence (CC) and common ratio (CR) violations of the IA over several months in thousands of stochastic choices using a large variety of binary option sets. Three monkeys showed consistently few outright Preference Reversals (8%) but substantial graded Preference Changes (46%) between the initial preferred gamble and the corresponding altered gamble. Linear Discriminant Analysis (LDA) indicated that gamble probabilities predicted most Preference Changes in CC (72%) and CR (88%) tests. The Akaike Information Criterion indicated that probability weighting within Cumulative Prospect Theory (CPT) explained choices better than models using Expected Value (EV) or EUT. Fitting by utility and probability weighting functions of CPT resulted in nonlinear and non-parallel indifference curves (IC) in the Marschak-Machina triangle and suggested IA non-compliance of models using EV or EUT. Indeed, CPT models predicted Preference Changes better than EV and EUT models. Indifference points in out-of-sample tests were closer to CPT-estimated ICs than EV and EUT ICs. Finally, while the few outright Preference Reversals may reflect the long experience of our monkeys, their more graded Preference Changes corresponded to those reported for humans. In benefitting from the wide testing possibilities in monkeys, our stringent axiomatic tests contribute critical information about risky decision-making and serve as basis for investigating neuronal decision mechanisms. Earliest photic zone niches probed by ancestral microbial rhodopsins For billions of years, life has continuously adapted to dynamic physical conditions near the Earths surface. Fossils and other preserved biosignatures in the paleontological record are the most direct evidence for reconstructing the broad historical contours of this adaptive interplay. However, biosignatures dating to Earths earliest history are exceedingly rare. Here, we combine phylogenetic inference of primordial rhodopsin proteins with modeled spectral features of the Precambrian Earth environment to reconstruct the paleobiological history of this essential family of photoactive transmembrane proteins. Our results suggest that ancestral microbial rhodopsins likely acted as light-driven proton pumps and were spectrally tuned toward the absorption of green light, which would have enabled their hosts to occupy depths in a water column or biofilm where UV wavelengths were attenuated. Subsequent diversification of rhodopsin functions and peak absorption frequencies was enabled by the expansion of surface ecological niches induced by the accumulation of atmospheric oxygen. Inferred ancestors retain distinct associations between extant functions and peak absorption frequencies. Our findings suggest that novel information encoded by biomolecules can be used as "paleosensors" for conditions of ancient, inhabited niches of host organisms not represented elsewhere in the paleontological record. The coupling of functional diversification and spectral tuning of this taxonomically diverse protein family underscores the utility of rhodopsins as universal testbeds for inferring remotely detectable biosignatures on inhabited planetary bodies. 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. Profiles of expressed mutations in single cells reveal subclonal expansion patterns and therapeutic impact of intratumor heterogeneity Advances in single-cell RNA sequencing (scRNAseq) technologies uncovered an unexpected complexity in tumors, underlining the relevance of intratumor heterogeneity to cancer progression and therapeutic resistance. Heterogeneity in the mutational composition of cancer cells is a result of distinct (sub)clonal expansions, each with a distinct metastatic potential and resistance to specific treatments. Unfortunately, due to their low read coverage per cell, scRNAseq datasets are too sparse and noisy to be used for detecting expressed mutations in single cells. Additionally, the large number of cells and mutations present in typical scRNAseq datasets are too large for available computational tools to, e.g., infer distinct subclones, lineages or trajectories in a tumor. Finally, there are no principled methods to assess distinct subclones inferred through single-cell sequencing data and the genomic alterations that seed and potentially cause them. Here we present Trisicell, a computational toolkit for scalable mutational intratumor heterogeneity inference and assessment from scRNAseq as well as single-cell genome or exome sequencing data. Trisicell allows reliable identification of distinct clonal lineages of a tumor, offering the ability to focus on the most important subclones and the genomic alterations that are associated with tumor proliferation. We comprehensively assessed Trisicell on a melanoma model by comparing distinct lineages and subclones it identifies on scRNAseq data, to those inferred using matching bulk whole exome (bWES) and transcriptome (bWTS) sequencing data from clonal sublines derived from single cells. Our results demonstrate that distinct lineages and subclones of a tumor can be reliably inferred and evaluated based on mutation calls from scRNAseq data through the use of Trisicell. Additionally, they reveal a strong correlation between aggressiveness and mutational composition, both across the inferred subclones, and among human melanomas. We also applied Trisicell to infer and evaluate distinct subclonal expansion patterns of the same mouse melanoma model after treatment with immune checkpoint blockade (ICB). After integratively analyzing our cell-specific mutation calls with their expression profiles, we observed that each subclone with a distinct set of novel somatic mutations is strongly associated with a specific developmental status. Moreover, each subclone had developed a unique ICB-resistance mechanism. These results demonstrate that Trisicell can robustly utilize scRNAseq data to delineate intratumor heterogeneity and help understand biological mechanisms underlying tumor progression and resistance to therapy. Lipid membranes modulate the activity of RNA through sequence-dependent interactions RNA is a ubiquitous biomolecule that can serve as both catalyst and information carrier. Understanding how RNA bioactivity is controlled is crucial for elucidating its physiological roles and potential applications in synthetic biology. Here we show that lipid membranes can act as RNA organization platforms, introducing a novel mechanism for ribo-regulation. The activity of R3C ribozyme can be modified by the presence of lipid membranes, with direct RNA-lipid interactions dependent on RNA nucleotide content, base pairing and length. In particular, the presence of guanine in short RNAs is crucial for RNA-lipid interactions, and G-quadruplex formation further promotes lipid binding. Lastly, by artificially modifying the R3C substrate sequence to enhance membrane binding we generated a lipid-sensitive ribozyme reaction with riboswitch-like behavior. These findings introduce RNA-lipid interactions as a tool for developing synthetic riboswitches and novel RNA-based lipid biosensors, and bear significant implications for RNA World scenarios for the origin of life. A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information. The first sheep graph-based pan-genome reveals the spectrum of structural variations and their effects on tail phenotypes Structural variations (SVs) are a major contributor to genetic diversity and phenotypic variations, but their prevalence and functions in domestic animals are largely unexplored. Here, we assembled 26 haplotype-resolved genome assemblies from 13 genetically diverse sheep using PacBio HiFi sequencing. We constructed a graph-based ovine pan-genome and discovered 142,422 biallelic insertions and deletions, 7,028 divergent alleles and 13,419 multiallelic variations. We then used a graph-based approach to genotype the biallelic SVs in 684 individuals from 45 domestic breeds and two wild species. Integration with RNA-seq data allows to identify candidate expression-associated SVs. We demonstrate a direct link of SVs and phenotypes by localizing the putative causative insertion in HOXB13 gene responsible for the long-tail trait and identifying multiple large SVs associated with the fat-tail. Beyond generating a benchmark resource for ovine structural variants, our study highlights that animal genetic research will greatly benefit from using a pan-genome graph rather than a single reference genome. 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. The multi-level phenotypic impact of synonymous substitutions: heterologous gene expression in human cells. Redundancy in the genetic code allows for differences in transcription and/or translation efficiency between sequences carrying synonymous polymorphisms, potentially leading to phenotypic changes. It is commonly admitted that the evolution codon usage bias ("CUB", the over-representation of certain codons in a genome, a gene or in positions along a gene) are driven by a combination of neutral and selective processes, but their relative contribution is a matter of debate, especially in mammals. Particularly, integrative studies quantifying the phenotypic impact of CUB at different molecular and cellular levels are lacking. Here we report a multiscale analysis of the effects of synonymous codon recoding during heterologous gene expression in human cells.

Six synonymous versions of the shble antibiotic resistance gene were generated, fused to a fluorescent reporter, and independently expressed in HEK293 cells. Multiscale phenotype was assessed by means of: i) mRNA-to-DNA and protein-to-mRNA ratios for each shble version; ii) cellular fluorescence, using flow cytometry, as a proxy for single-cell level expression; and iii) real-time cell proliferation in absence or presence of antibiotic, as a proxy for the cell fitness.

We show that differences in CUB strongly impact the molecular and the cellular phenotype: i) they result in large differences in mRNA and in protein levels, as well in mRNA-to-protein ratio; ii) they introduce splicing events not predicted by current algorithms; iii) they lead to reproducible phenotypic heterogeneity; iv) they lead to a trade-off between the benefit of antibiotic resistance and the burden of heterologous expression.

We interpret that CUB modulate mRNA availability and suitability for translation in human cells, leading to differences in protein levels and eventually eliciting phenotypic differences.

AUTHOR SUMMARYThe genetic code is redundant, with several codons encoding for the same amino acid. These synonymous codons are not used with equal frequencies. Instead, codon usage bias (CUB) varies between species, genes, and even positions along a gene. At each of these levels, CUB are shaped by the overall balance between mutational biases and selection forces. To shed light on the molecular mechanisms underlying molecular and organism phenotypes, integrative studies quantifying the phenotypic impact of CUB at different levels of biological integration are necessary. Here, we monitored the multiscale changes induced by six synonymous versions of an antibiotic resistance gene independently expressed in a human cell line. We show that: 1. both mRNA levels, protein levels, and their ratios are affected by CUB; 2. potential effects on mRNA (splicing and availability for translation) seem to constitute the main level of action; 3. cell fitness is severely impacted by a trade-off between the burden of heterologous expression and the benefits of antibiotic resistance. This integrative study provides new insights on translation regulation and the associated phenotypic impact in human cells, associated to CU. G protein-coupled estrogen receptor activation by Bisphenol-A disrupts protection from apoptosis conferred by estrogen receptors ERα and ERβ in pancreatic beta cells 17{beta}-estradiol protects pancreatic {beta}-cells from apoptosis via the estrogen receptors ER, ER{beta} and GPER. Conversely, the endocrine disruptor Bisphenol-A (BPA), which exerts multiple effects in this cell type via the same estrogen receptors, increased basal apoptosis. The molecular initiated events that trigger these opposite actions have yet to be identified. We demonstrated that combined genetic downregulation and pharmacological blockade of each estrogen receptor increased apoptosis to a different extent. The increase in apoptosis induced by BPA was diminished by the pharmacological blockade or the genetic silencing of GPER, and it was partially reproduced by the GPER agonist G1. BPA and G1-induced apoptosis were abolished upon pharmacological inhibition, silencing of ER and ER{beta}, or in dispersed islet cells from ER{beta} knockout (BERKO) mice. Yet, the ER and ER{beta} agonists, PPT and DPN, respectively, had no effect on beta cell viability. To exert their biological actions, ER and ER{beta} form homodimers and heterodimers. Molecular dynamic simulations together with proximity ligand assay and coimmunoprecipitation experiments indicated that the interaction of BPA with ER and ER{beta} as well as the GPER activation by G1 decreased ER{beta} heterodimers. We propose that ER{beta} heterodimers play an antiapoptotic role in beta cells and that BPA- and G1-induced decrease in ER{beta} heterodimers leads to beta cell apoptosis. Unveiling how different estrogenic chemicals affect the crosstalk among estrogen receptors should help to identify diabetogenic endocrine disruptors.

HighlightsO_LIPharmacological blockade and gene silencing of estrogen receptors ER, ER{beta} and GPER indicate that they are antiapoptotic in basal conditions.
C_LIO_LIGPER activation by G1 and BPA triggered apoptosis via a crosstalk with ER and ER{beta}.
C_LIO_LIBPA interaction with ER and ER{beta} as well as GPER activation decreased ER{beta} heterodimers, which was associated to increased apoptosis.
C_LIO_LIThis pathway represents a novel molecular initiating event underlying the pro-apoptotic effect of BPA
C_LIO_LIThe EndoC-{beta}H1 cell line may be a valid model of human {beta}-cells for identifying diabetogenic pollutants.
C_LI Cooperation of two opposite flagella allows high-speed swimming and active turning in zoospores Phytophthora species cause diseases in a large variety of plants and represent a serious agricultural threat, leading, every year, to multibillion dollar losses. Infection occurs when these biflagellated zoospores move across the soil at their characteristic high speed and reach the roots of a host plant. Despite the relevance of zoospore spreading in the epidemics of plant diseases, characteristics of individual swimming of zoospores have not been fully investigated. It remains unknown about the characteristics of two opposite beating flagella during translation and turning, and the roles of each flagellum on zoospore swimming. Here, combining experiments and modeling, we show how these two flagella contribute to generate thrust when beating together, and identify the mastigonemes-attached anterior flagellum as the main source of thrust. Furthermore, we find that turning involves a complex active process, in which the posterior flagellum temporarily stops, while the anterior flagellum keeps on beating and changes its pattern from sinusoidal waves to power and recovery strokes, similar to Chlamydomonass breaststroke, to reorient its body to a new direction. Our study is a fundamental step towards a better understanding of the spreading of plant pathogens motile forms, and shows that the motility pattern of these biflagellated zoospores represents a distinct eukaryotic version of the celebrated "run-and-tumble" motility class exhibited by peritrichous bacteria. An environmentally responsive transcriptional state modulates cell identities during root development Roots are fundamental organs for plant development and response to their environment: they anchor the plant to its growth substrate, uptake nutrients and water vital to plant growth, and can sense and respond to a variety of biotic and abiotic stresses. The architecture of root systems and their growth are known to be strongly affected by the environmental conditions found in the soil. However, the acquisition of cell identities at the root meristem is still mainly viewed as ontogenetically driven, where a small number of stem cells generate all the cell types through stereotyped divisions followed by differentiation, along a simple developmental trajectory. The extent to which environmental cues precisely shape and affect these developmental trajectories remains an open question. We used single-cell RNA-seq, combined with spatial mapping, to deeply explore the trajectories of cell states at the tip of Arabidopsis roots, known to contain multiple developing lineages. Surprisingly, we found that most lineage trajectories exhibit a stereotyped bifid topology with two developmental trajectories rather than one. The formation of one of the trajectories is driven by a strong and specific activation of genes involved in the responses to various environmental stimuli, that affects only of a subset of the cells in multiple cell types simultaneously, revealing another layer of patterning of cell identities in the root that is independent of cell ontogeny. We demonstrate the robustness of this environmentally responsive transcriptional state by showing that it is present in a mutant where cell type identities are greatly perturbed, as well as in different Arabidopsis ecotypes. We also show that the root can adapt the proportion of cells that acquire this particular state in response to environmental signals such as nutrient availability. The discovery of this cell state reveals new layers of cell identity that may underpin the adaptive potential of plant development. A non-canonical convergence of carbohydrate and glutamine metabolism is required after metabolic rewiring in a solid environment The fate of pyruvate, which is modulated by the activity of the mitochondrial pyruvate carrier (MPC), is a defining metabolic feature in many cancers. Diffuse large B-cell lymphomas (DLBCLs) are a genetically and metabolically heterogeneous cancer. Although MPC expression and activity differed between DLBCL subgroups, mitochondrial pyruvate was uniformly consumed by glutamate pyruvate transaminase 2 (GPT2) to support -ketoglutarate production as part of glutaminolysis. This led us to discover that glutamine exceeds pyruvate as a carbon source for the tricarboxylic acid (TCA) cycle in DLBCLs. Furthermore, we found that MPC inhibition unexpectedly leads to decreased glutaminolysis, which is contrary to previous observations in other cell types. We also discovered that MPC inhibition and depletion only decreased DLBCL proliferation in an extracellular matrix (ECM) environment and in vivo xenografts, but not in the typical DLBCL suspension environment. We also have found that the metabolic profile of DLBCL cells in ECM is markedly different from cells in suspension environment. Thus, we report that besides the canonical glutamate dehydrogenase (GDH)-mediated glutaminolysis, the non-canonical GPT2 mediated consumption and assimilation of glutamine and pyruvate in DLBCLs enables their proliferation in an extracellular environment-dependent manner.

HIGHLIGHTSO_LIGlutamine, but not glucose, is a major carbon source for the tricarboxylic acid cycle in diffuse large B-cell lymphomas.
C_LIO_LIMitochondrial pyruvate supports glutaminolysis in diffuse large B-cell lymphomas by supplying pyruvate for glutamate pyruvate transaminase 2-mediated  -ketoglutarate production.
C_LIO_LIMitochondrial pyruvate carrier inhibition leads to decreased glutaminolysis in diffuse large B-cell lymphomas.
C_LIO_LI -ketoglutarate production is important for diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment.
C_LIO_LIMitochondrial pyruvate carrier activity supports diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment and in mouse xenografts.
C_LI New Segmentation and Feature Extraction Algorithm for Classification of White Blood Cells in Peripheral Smear Images This article addresses a new method for the classification of white blood cells (WBCs) using image processing techniques and machine learning methods. The proposed method consists of three steps: detecting the nucleus and cytoplasm, extracting features, and classification. At first, a new algorithm is designed to segment the nucleus. For the cytoplasm to be detected, only a part of it located inside the convex hull of the nucleus is involved in the process. This attitude helps us overcome the difficulties of segmenting the cytoplasm. In the second phase, three shapes and four novel color features are devised and extracted. Finally, by using an SVM model, the WBCs are classified. The segmentation algorithm can detect the nucleus with a dice similarity coefficient of 0.9675. The proposed method can categorize WBCs in Raabin-WBC, LISC, and BCCD datasets with accuracies of 94.65 %, 92.21 %, and 94.20 %, respectively. It is worth mentioning that the hyperparameters of the classifier are fixed only with the Raabin-WBC dataset, and these parameters are not readjusted for LISC and BCCD datasets. The obtained results demonstrate that the proposed method is robust, fast, and accurate. Beneficial effects of novel strains of Aureobasidium pullulans produced 1,3-1,6 β-glucans on non-esterified fatty acid levels in diabetic KKAy mice Obesity, metabolic syndrome, associated lipotoxicity and its cascade of events contribute to the majority of the burden related to non-communicable diseases globally. Preventive lifestyle changes aside, several beneficial effects have been reported in type II diabetes mellitus and dyslipidaemia patients with biological response modifier glucans (BRMG) produced as an exopolysaccharide by Aureobasidium pullulans. In this study, we compared two strains (AFO-202 and N-163) that produce beta glucans in alleviating lipotoxicity. This study was performed in obese diabetic mice model of KK-Ay mice, in four groups with six subjects in each group - Group 1: sacrificed on Day 0 for baseline values; Group 2: control (drinking water); Group 3: AFO-202 beta glucan--200 mg/kg/day; Group 4: N-163 beta glucan--300 mg/kg/day. The animals in groups 2-4 had the test solutions administered by gavage once daily for 28 consecutive days. Biochemical analyses were conducted of blood glucose, triglycerides, total cholesterol, LDL cholesterol, HDL cholesterol and non-esterified fatty acids (NEFA). Group 4 (N-163) had the lowest NEFA levels, as compared to the other groups, and marginally decreased triglyceride levels. The groups had no significant differences in blood glucose, HbA1c, triglycerides, or LDL and HDL cholesterol. N-163 produced by A. pullulans decreased NEFA in a diabetic mice model in 28 days. These results, although modest, warrant further in-depth research into lipotoxicity and associated inflammatory cascades in both healthy and disease affected subjects to develop novel strategies for prevention and management. Citation needed? Wikipedia and the COVID-19 pandemic BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Spatially explicit ecological modeling improves empirical characterization of dispersal Dispersal is a key ecological process, but remains difficult to measure. By recording numbers of dispersed individuals at different distances from the source one can acquire a dispersal gradient. Although dispersal gradients contain information on dispersal, they are influenced by the spatial extent of the source. How can we separate the two contributions to extract knowledge on dispersal?

One could use a small, point-like source for which a dispersal gradient represents a dispersal kernel, which quantifies the probability of an individual dispersal event from a source to a destination point. However, the validity of this approximation cannot be established before conducting measurements.

We formulated a theory that incorporates the spatial extent of sources to estimate dispersal kernels from dispersal gradients. We re-analyzed published dispersal gradients for three major plant pathogens. We also demonstrated using simulations that this approach provides more accurate estimates of dispersal kernels across biologically plausible scenarios. We concluded that the three plant pathogens disperse over substantially shorter distances compared to conventional estimates. Using this method, a significant proportion of published dispersal gradients can be re-analyzed to improve our knowledge about spatial scales of dispersal. Thus, our results can boost progress in characterization of dispersal across taxa.