Paternal aging affects developmental convergence of vocal behavior in individual mice: machine learning-driven analyses of individuality Infant crying is an innate communicative behavior that is frequently impaired in certain neurodevelopmental disorders (NDDs). Since advanced paternal age is a reported risk factor for NDDs in offspring, we evaluated the impact of a fathers age on early vocal development in C57BL/6J mice. We recorded and applied a unique combination of computational analyses to ultrasonic vocalizations (USVs) emitted by mouse pups sired by young and aged fathers. Our data showed that advanced paternal age reduced the number and duration of USVs, and altered the syllable composition in pups. Moreover, pups born to young fathers showed convergent vocal characteristics with a rich repertoire during postnatal development, while those born to aged fathers exhibited more divergent vocal patterns with limited repertoire. Principal component analysis in conjunction with clustering analysis demonstrated that pups from aged fathers deviated from typical trajectories of vocal development, which were considered as atypical individuals. Thus, our study indicates that advanced paternal age has a significant effect on offsprings early vocal development. It is suggested that the trajectories of vocal development could be a useful marker of the NDD-like phenotype associated with the advanced paternal age. In addition, our comprehensive computational analysis described here is an effective approach to characterize the altered individual diversity relevant to neurodevelopmental disorders.

One Sentence SummaryAdvanced paternal age affects vocal development in early postnatal mice, with more pups showing atypical developmental trajectories.
GWAS-associated variants, non-genetic factors, and transient transcriptome in Multiple Sclerosis etiopathogenesis: a colocalization analysis A clinically actionable understanding of multiple sclerosis (MS) etiology goes through GWAS interpretation, prompting research on new gene regulatory models. We previously suggested a stochastic etiologic model where small-scale random perturbations could reach a threshold for MS development. The recently described mapping of the transient transcriptome (TT), including intergenic and intronic RNAs, seems appropriate to verify this model through a rigorous colocalization analysis. We show that genomic regions coding for the TT were significantly enriched for MS-associated GWAS variants and DNA binding sites for molecular transducers mediating putative, non-genetic, etiopathogenetic factors for MS (e.g., vitamin D deficiency, Epstein Barr virus latent infection, B cell dysfunction). These results suggest a model whereby TT-coding regions are hotspots of convergence between genetic ad non-genetic factors of risk/protection for MS, and plausibly for other complex disorders. Our colocalization analysis also provides a freely available data resource (www.mscoloc.com) for future research on MS transcriptional regulation.
Protein-protein interactions on membrane surfaces analysed using pull-downs with supported bilayers on silica beads Discovery-based proteomics workflows that identify novel interactors rely on immunoprecipitations or pull-downs with genetically-tagged bait proteins immobilized on appropriate matrices. But strategies to analyse protein interactions on a diffusible membrane surface combined with the practical ease of pull-downs remain unavailable. Such strategies are important to analyse protein complexes that mature in composition and stability because of diffusion-based encounter between participant proteins. Here, we describe a generic pull-down strategy to analyse such complexes using chelating lipid-containing supported bilayers formed on silica beads. These templates can display desired His-tagged bait proteins on a diffusible membrane surface. Using clathrin-mediated endocytosis as a paradigm, we find that the clathrin-binding adaptor protein epsin1 displayed as bait on these templates pulls down significantly higher amounts of clathrin from brain lysates than when immobilized on conventional matrices. Together, our results establish the potential of such templates as superior matrices for analysing protein-protein interactions and resultant complexes formed on membrane surfaces. High-level carbapenem tolerance requires antibiotic-induced outer membrane modifications. Antibiotic tolerance is an understudied potential contributor to antibiotic treatment failure and the emergence of multidrug-resistant bacteria. The molecular mechanisms governing tolerance remain poorly understood. A prominent type of {beta}-lactam tolerance relies on the formation of cell wall-deficient spheroplasts, which maintain structural integrity via their outer membrane (OM), an asymmetric lipid bilayer consisting of phospholipids on the inner leaflet and a lipid-linked polysaccharide (lipopolysaccharide, LPS) enriched in the outer monolayer on the cell surface. How a membrane structure like LPS, with its reliance on mere electrostatic interactions to maintain stability, is capable of countering internal turgor pressure is unknown. Here, we have uncovered a novel role for the PhoPQ two-component system in tolerance to the {beta}-lactam antibiotic meropenem in Enterobacterales. We found that PhoPQ is induced by meropenem treatment and promotes an increase in 4-amino-4-deoxy-L-aminoarabinose [L-Ara4N] modification of lipid A, the membrane anchor of LPS. L-Ara4N modifications enhance structural integrity, and consequently tolerance to meropenem, in several Enterobacterales species. Importantly, mutational inactivation of the negative PhoPQ regulatory element mgrB (commonly selected for during clinical therapy with the last-resort antibiotic colistin, an antimicrobial peptide [AMP]) results in dramatically enhanced tolerance, suggesting that AMPs can collaterally select for meropenem tolerance via stable overactivation of PhoPQ. Lastly, we identify histidine kinase inhibitors (including an FDA-approved drug) that inhibit PhoPQ-dependent LPS modifications and consequently potentiate meropenem to enhance killing of tolerant cells. In summary, our results suggest that PhoPQ-mediated LPS modifications play a significant role in stabilizing the OM, promoting survival when the primary integrity maintenance structure, the cell wall, is removed.

SignificanceTreating an infection with an antibiotic often fails, resulting in a tremendous public health burden. One understudied likely reason for treatment failure is the development of "antibiotic tolerance", the ability of bacteria to survive normally lethal exposure to an antibiotic. Here, we describe a molecular mechanism promoting tolerance. A bacterial stress sensor (PhoPQ) is activated in response to antibiotic (meropenem) treatment and consequently strengthens a bacterial protective "shell" to enhance survival. We also identify inhibitors of this mechanism, opening the door to developing compounds that help antibiotics work better against tolerant bacteria. Response of soil and vegetation in a warm-temperate Pine forest to intensive biomass harvests, phosphorus fertilisation, and wood ash application. Background and AimsConcerns about climate change and carbon economy have prompted the promotion of alternative energy sources, including forest-based bioenergy. An evaluation of the environmental consequences of intensive harvests (stumps and roots, and also branches and foliage) for energy wood supply, and use of wood-ash recycling as a compensatory practice, helps in the evaluation of the use of forest biomass for energy production.

MethodsWe made use of records from a split-plot experimental site crossing four different intensities of biomass harvesting (Stem-Only Harvest [SOH], Aboveground Additional Harvest [AAH], Belowground Additional Harvest [BAH], and Whole-Tree Harvest [WTH]) and three compensation methods (control [C], wood ash application [A] and phosphorus fertilisation [P]) to evaluate, in the 11-years-old stand (maritime pine: Pinus pinaster) that followed the biomass exports of the former stand, their effects on nutrient budgets, tree growth, soil fertility, chemical properties and soil carbon. This site is located in a forest on a poor soil, under a warm temperate climate (SW France).

Key resultsDespite their low additional biomass exports (+10% for AAH to +34% for WTH), the non-conventional harvest practices exported much higher quantities of nutrients than the conventional SOH technique (for example +145% for N and K in WTH). Consequently, these treatments had negative effects on the soil nutritive status. Additional biomass harvests impacted the soil organic matter content, with negative effects on P-organic, soil cation exchange capacity, exchangeable Ca, and most extractible nutrients. However, data suggested that tree growth and foliage nutrient content had not yet been significantly impacted by harvest treatments, whereas tree nutritional status was improved by P-fertiliser or wood ash. As expected, we observed a positive effect of wood ash application on soil pH and nutrient content but, like additional harvests, wood ash application decreased the pool of soil organic carbon (~10% of the initial stock with ~7% of N-total losses).

ConclusionsOverall, this factorial experiment showed that exporting more forest biomass due to the additional harvesting of tree canopies, stumps and roots had negative consequences on the ecosystem biogeochemistry. Additional harvests have aggravated the poverty of the already oligotrophic soil, and decreased the soil organic carbon content. Importantly, applying nutrients as fertiliser or wood ash did not compensate for all the negative impacts of biomass exports and the method of wood ash recycling in forests could even decrease the soil organic carbon. Creatine transporter deficient rat model show motor dysfunction, cerebellar alterations and muscle creatine deficiency without muscle atrophy Creatine (Cr) is a nitrogenous organic acid and plays roles as fast phosphate energy buffer to replenish ATP, osmolyte, antioxidant, neuromodulator, and as a compound with anabolic and ergogenic properties in muscle. Cr is taken from the diet or endogenously synthetized by the enzymes AGAT and GAMT, and specifically taken up by the transporter SLC6A8. Loss-of-function mutations in the genes encoding for the enzymes or the transporter cause Cerebral Creatine Deficiency Syndromes (CCDS). CCDS are characterized by brain Cr deficiency, intellectual disability with severe speech delay, behavioral troubles, epilepsy and motor dysfunction. Among CCDS, the X-linked Cr transporter deficiency (CTD) is the most prevalent with no efficient treatment so far. Different animal models of CTD show reduced brain Cr levels, cognitive deficiencies and together they cover other traits similar to those of patients. However, motor function was poorly explored in CTD models and some controversies in the phenotype exist in comparison with CTD patients. Our recently described Slc6a8Y389C knock-in (KI) rat model of CTD showed mild impaired motor function, morphological alterations in cerebellum, reduced muscular mass, Cr deficiency and increased guanidinoacetate content in muscle, although no consistent signs of muscle atrophy. Our results indicate that such motor dysfunction co-occurred with both nervous and muscle dysfunction, suggesting that muscle strength and performance as well as neuronal connectivity might be affected by this Cr deficiency in muscle and brain. Modulations in motor unit discharge are related to changes in fascicle length during isometric contractions The integration of electromyography (EMG) and ultrasound imaging has provided important information about the mechanisms of muscle activation and contraction. Unfortunately, EMG does not allow an accurate assessment of the interplay between the neural drive received by muscles, changes in fascicle length (FL) and the force/torque produced. We aimed to assess the relationship between modulations in tibialis anterior (TA) motor unit (MU) firing rate, FL and dorsiflexion torque (DT) using ultrasound-transparent high-density EMG electrodes. EMG and ultrasound images were recorded simultaneously from TA, using a 32-electrode silicon matrix, while performing isometric dorsiflexion, at diverse ankle joint positions (0{degrees} and 30{degrees} plantar flexion) and torques (20% and 40% of maximum). EMG signals were decomposed into individual MUs and changes in FL were assessed with a fascicle-tracking algorithm. MU firings were converted into a cumulative spike train (CST) that was cross-correlated with DT (CST-DT) and FL (CST-FL). High cross-correlations were found for CST-FL, 0.60 (range: 0.31-0.85) and CST-DT 0.71 (range: 0.31-0.88). Cross-correlation lags revealed that the delay between CST-FL (~75ms) was significantly smaller than CST-DT (~150ms, p<0.001). These delays affected the interpretation of MU recruitment/de-recruitment thresholds, with FL showing similar lengths for both recruitment and de-recruitment. This study is the first to demonstrate that changes in TA FL are closely related to both modulations in MU firing frequency and DT. These relationships allow assessment of the interplay between neural drive, muscle contraction and resultant torque, thereby providing a better understanding of the mechanisms responsible for the generation of muscle force.

NEW AND NOTEWORTHYBy employing ultrasound-transparent high-density surface EMG electrodes, we show that modulations in tibialis anterior motor unit discharge rate were closely related to both changes in its fascicle length and resultant torque. These relationships allowed quantifying delays between neural drive and muscle shortening as well as muscle shortening and torque during submaximal isometric contractions, providing an accurate estimation of the time required to generate muscle force and subsequent production of torque via the tendon. A nontoxic tetrodotoxin analog, 5,6,11-trideoxytetrodotoxin, as an olfactory chemoattractant for the grass puffer Toxic puffers contain the potent neurotoxin, tetrodotoxin (TTX). Although TTX is considered to serve as a defense substance, previous behavioral studies have demonstrated that TTX acts as an attractive pheromone for some toxic puffers. To elucidate the physiological mechanism of putative pheromonal action of TTX, we examined whether grass puffers Takifugu alboplumbeus can detect TTX. Electroolfactogram (EOG) results suggest that the olfactory epithelium (OE) of grass puffers responded to a type of TTX analog (5,6,11-trideoxyTTX), although it did not respond to TTX. We also examined the attractive action of 5,6,11-trideoxyTTX on grass puffers by recording their swimming behavior under dark conditions. Grass puffers preferred to stay on the side of the aquarium where 5,6,11-trideoxyTTX was administered, and their swimming speed decreased. Additionally, odorant-induced labeling of olfactory sensory neurons by immunohistochemistry against neural activity marker (phosphorylated extracellular signal regulated kinase; pERK) revealed that labeled olfactory sensory neurons were localized in the region surrounding "islets" where there was considered as nonsensory epithelium. 5,6,11-trideoxyTTX has been known to accumulate in grass puffers, but its toxicity is much lower (almost nontoxic) than TTX. Our results suggest that toxic puffers may positively use this unknown function TTX analog as an olfactory chemoattractant. Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. HOW CONCERNING IS A SARS-COV-2 VARIANT OF CONCERN? COMPUTATIONAL PREDICTIONS AND THE VARIANTS LABELING SYSTEM We herein report a study to evaluate the use of computational prediction of SARS-CoV-2 genetic variations in improving the current variants labeling system. First, we reviewed the basis of the system developed by the World Health Organization (WHO) for the labeling of SARS-CoV-2 genetic variants and the adaptations made to it by the United States Center of Diseases Control (CDC). We observed that the labeling system is based upon the virus major attributes. However, we found that the labeling criteria of the SARS-CoV-2 variants derived from these attributes are not accurately defined and are used differently by the two health management agencies. Consequently, discrepancies exist between the labels given by WHO and CDC to same variants. Our observations suggest that giving the VOC label to a new variant is premature and might not be appropriate. Therefore, we carried out a comparative computational study to predict the effects of the mutations on the virus structure and functions of five VOCs. By linking these data to the criteria used by WHO and the CDC for variant labeling, we ascertained that comparative computational predictions of the impact of genetic variations are a better ground for rapid and more accurate labelling of SARS-CoV-2 variants. We propose to label all emergent variants VUM or VBM and to carry out computational predictive studies and thorough variants comparison, upon which more appropriate and informative labels can be attributed. Furthermore, harmonization of the variants labeling system would be globally beneficial to communicate about and fight COVID-19 pandemic. Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: the Multi-Targeting Drug DREAM Challenge A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact,  dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop  cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. Tetrazoles as PPARγ ligands: A Structural and Computational Investigation. Diabetes is an important chronic disease affecting about 10% of the adult population in the US and over 420 million people worldwide, resulting in 1.6 million deaths every year, according to the World Health Organization. The most common type of the disease, type 2 diabetes, can be pharmacologically managed using oral hypoglycemic agents or thiazolidinediones (TZDs), such as pioglitazone, which act by activating the Peroxisome Proliferated-Activated Receptor {gamma}. Despite their beneficial effects in diabetes treatment, TZDs like rosiglitazone and troglitazone were withdrawn due to safety reasons, creating a void in the pharmacological options for the treatment of this important disease. Here, we explored a structure-based approach in the screening for new chemical probes for a deeper investigation of the effects of PPAR{gamma} activation. A class of tetrazole compounds was identified and the compounds named T1, T2 and T3 were purchased and evaluated for their ability to interact with the PPAR{gamma} ligand binding domain (LBD). The compounds were binders with micromolar range affinity, as determined by their IC50 values. A Monte Carlo simulation of the compound T2 revealed that the tetrazole ring makes favorable interaction with the polar arm of the receptor binding pocket. Finally, the crystal structure of the PPAR{gamma}-LBD-T2 complex was solved at 2.3 [A], confirming the binding mode for this compound. The structure also revealed that, when the helix H12 is mispositioned, an alternative binding conformation is observed for the ligand suggesting an H12-dependent binding conformation for the tetrazole compound. CRSP: Comparative RNA-seq pipeline for species lacking both a reference genome and annotated transcriptome RNA sequencing (RNA-seq) has been a widely used high-throughput method to characterize transcriptomic dynamics spatiotemporally. However, typical RNA-seq data analysis pipelines depend on either a sequenced genome or annotated reference transcripts. This restriction makes the use of RNA-seq for species lacking both of sequenced genomes and reference transcripts challenging. To solve this problem, we developed CRSP, an RNA-seq pipeline integrating a comparative species strategy but not depending on a specific sequenced genome or reference transcripts. Benchmarking suggests the CRSP tool can achieve high accuracy to quantify gene expression levels.

AvailabilityCRSP and documents are available at: https://github.com/pjiang1105/CRSP. 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. RASopathy Mutations Demonstrate the Critical Function of the Cysteine-rich Domain in Maintaining BRAF in an Autoinhibited State to Prevent Aberrant Signaling The RAF kinases are essential effectors of the RAS-GTPases, and germline mutations in BRAF or CRAF are disease drivers in the RASopathy developmental syndromes, with mutations in the cysteine-rich domain (CRD) often observed in BRAF but not CRAF. Although the CRD is known for roles in phosphatidylserine (PS) binding, the RAS-RAF interaction, and RAF autoinhibition, the interplay of these activities and their impact on BRAF function in normal and disease states is unclear. Here, we analyze a panel of BRAF-CRD RASopathy mutations and show that they all increase the biological activity of BRAF by relieving autoinhibition and/or enhancing PS/membrane binding. Strikingly, we find that relief of autoinhibition is the predominant factor determining the severity of the mutations. Comparison of the BRAF and CRAF CRDs further indicates that the BRAF-CRD is a stronger mediator of both autoinhibition and PS binding, and we identify residues contributing to these differences. Moreover, given the increased catalytic activity of BRAF versus CRAF, our studies reveal a more critical role for the CRD and autoinhibition in BRAF regulation and demonstrate that CRD-mediated autoinhibition is required to prevent aberrant BRAF signaling, a finding consistent with the high frequency of mutations that disrupt this function in the RASopathies. The important choice of reference environment in microevolutionary climate response predictions It is well documented that individuals of wild populations can adjust to climate change by means of phenotypic plasticity, but few reports on adaptation by means of genetically based microevolution caused by selection. Disentanglement of these separate effects requires that the reference environment (the environmental zero-point) is defined, and this should not be done arbitrarily. The problem is that an error in the reference environment may lead to large errors in predicted microevolution. Together with parameter values and initial mean trait values, the reference environment can be estimated from environmental, phenotypic and fitness data. A prediction error method for this purpose is described, with the feasibility shown by simulations. As shown in a toy example, an estimated reference environment may have large errors, especially for small populations. This may still be a better choice than use of an initial environmental value in a recorded time series, or the mean value, which is often used. Another alternative may be to use the mean value of a past and stationary stochastic environment, which the population is judged to have been fully adapted to, in the sense that the expected geometric mean fitness was at a global maximum. Exceptions are cases with constant phenotypic plasticity, where the microevolutionary changes per generation follow directly from phenotypic and environmental data, independent of the chosen reference environment. 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. Immune complex solubility and size govern Fc-gamma receptor responses: A scalable cell-based reporter system 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. Developing High-Affinity Decoy Receptor Optimized for Multiple Myeloma and Diffuse Large B Cell Lymphoma Treatment Recent T Cell therapies have been effective in the treatment of hematological cancers. However, immunotoxicity and treatment relapse pose significant clinical challenges. Here, we revealed distinctive requirement for neutralizing TNF receptor ligands APRIL and BAFF in MM and DLBCL. Furthermore, we investigated the use of BCMA decoy receptor (sBCMA-Fc) as a therapeutic inhibitor of ARPIL and BAFF. While wild-type sBCMA-Fc successfully blocked APRIL signaling with picomolar binding affinity, inhibiting tumor growth in MM models, it lacked efficacy in inhibiting DLBCL progression due to its weak binding for BAFF. To expand the therapeutic utility of sBCMA-Fc, using a protein engineering approach, we generated an affinity enhanced mutant sBCMA-Fc fusion molecule (sBCMA-Fc V3) with 4-folds and 500-folds enhancement in binding to APRIL and BAFF respectively. The sBCMA-Fc V3 clone significantly enhanced antitumor activity against both MM and DLBCL. Importantly, sBCMA-Fc V3 was proven to be a viable clinical candidate by showing adequate toxicity profile and on-target mechanism of action in nonhuman primates.

SUMMARYThis study demonstrates the dichotomous function of APRIL and BAFF in MM and DLBCL, that can be safely targeted by an engineered fusion protein designed to trap APRIL and BAFF with ultra-high binding affinity. METHYLOME DYNAMICS UPON PROTEASOME INHIBITION BY THE PSEUDOMONAS VIRULENCE FACTOR SYRINGOLIN A DNA methylation is an important epigenetic mark required for proper gene expression and silencing of transposable elements. DNA methylation patterns can be modified by environmental factors such as pathogen infection, where modification of DNA methylation can be associated with plant resistance. To counter the plant defense pathways, pathogens produce effectors molecule, several of which act as proteasome inhibitors. Here we investigated the effect of proteasome inhibition by the bacterial virulence factor Syringolin A on genome-wide DNA methylation. We show that Syringolin A treatment results in an increase of DNA methylation at centromeric and pericentromeric regions of Arabidopsis chromosomes. We identify several CHH DMRs that are enriched in the proximity of transcriptional start sites. Syringolin A treatment does not result in significant changes in small RNA composition. However, significant changes in genome transcriptional activity can be observed, including a strong upregulation of resistance genes that are located on chromosomal arms. We hypothesize that DNA methylation changes could be linked to the upregulation of some atypical members of the de novo DNA methylation pathway: AGO3, AGO9 and DRM1. Our data suggests that modification of genome-wide DNA methylation resulting from an inhibition of the proteasome by bacterial effectors could be part of a epi-genomic arms race against pathogens. Polycomb suppresses a female gene regulatory network to ensure testicular differentiation Gonadal sex determination is controlled by the support cells of testes and ovaries. In testes, the epigenetic mechanism that maintains cellular memory to suppress female sexual differentiation remains unknown. Here, we show that Polycomb suppresses a female gene regulatory network in Sertoli cells, the specific support cells for postnatal testes. Through genetic ablation, we removed Polycomb repressive complex 1 (PRC1) from embryonic Sertoli cells after sex determination. PRC1-depleted postnatal Sertoli cells exhibited defective proliferation and cell death, leading to the degeneration of adult testes. In adult Sertoli cells, PRC1 suppressed the specific, critical genes required for granulosa cells, the support cells of ovaries, thereby inactivating the female gene regulatory network. The underlying chromatin of female genes was coated with Polycomb-mediated repressive modifications: PRC1-mediated H2AK119ub and PRC2-mediated H3K27me3. Taken together, we identify a critical mechanism centered on Polycomb that maintains the male fate in adult testes. Cis-Regulatory Hubs: a new 3D Model of Complex Disease Genetics with an Application to Schizophrenia The 3-dimensional (3D) conformation of the chromatin creates complex networks of noncoding regulatory regions (distal elements) and promoters impacting gene regulation. Despite the importance of the role of noncoding regions in complex diseases, little is known about their interplay within regulatory hubs and implication in multigenic diseases like schizophrenia. Here we show that cis-regulatory hubs (CRHs) in neurons highlight functional interactions between distal elements and promoters, providing a model to explain epigenetic mechanisms involved in complex diseases. CRHs represent a new 3D model, where distal elements interact to create a complex network of active genes. In a disease context, CRHs highlighted strong enrichments in schizophrenia-associated genes, schizophrenia-associated SNPs and schizophrenia heritability compared to equivalent structures. Finally, CRHs exhibit larger proportions of genes differentially expressed in schizophrenia compared to promoter-distal element pairs or TADs. CRHs thus capture causal regulatory processes improving the understanding of complex disease etiology such as schizophrenia. These multiple lines of genetic and statistical evidence support CRHs as 3D models to study dysregulation of gene expression in complex diseases more generally.

Summary BlurbGenes and their regulatory elements are organized within 3D networks in neurons which model functional structures and explain schizophrenia genetic etiology. Material-mediated histogenesis using mechano-chemically microstructured cell niches Stem-cell derived tissue models are commonly cultured under globally-delivered stimuli that trigger histogenesis via self-organizing activity. However, the culture of such tissue models is prone to stochastic behavior, limiting the reproducibility of cellular composition and resulting in non-physiological architectures. To overcome these shortcomings, we developed a method for printing cell niche microenvironments with microstructured cues that mediate local histogenic processes, including mechanosensing and differentiation of selected cell types. Microstructured cues include independently tunable mechano-chemical properties, with conjugated peptides, proteins, and morphogens across a range of Youngs moduli. By rationally designing niches, we mediate the structure of tissues derived from stem-cell-progenitor sources, including a bone-fat assembly from stromal mesenchyme, and embryonic tissues derived from hiPSC. We show that microstructured cues can recapitulate mechano-chemical signals resembling early embryonic histogenesis. This outcome includes a role for niche mechanics in human embryonic organization, where soft niche mechanics bias markers of mesendodermal differentiation and epithelial-to-mesenchymal-transition (EMT), as well as a demonstration of a material-mediated morphogen signaling centers able to induce foci of mesenchymal and EMT differentiation. Thus, microstructured materials can mediate local histogenic processes to enhance the structure and composition of tissue models. Entorhinal cortex epigenome-wide association study highlights four novel loci showing differential methylation in Alzheimer's disease BackgroundStudies on DNA methylation (DNAm) in Alzheimers disease (AD) have recently highlighted several genomic loci showing association with disease onset and progression.

MethodsHere, we conducted an epigenome-wide association study (EWAS) using DNAm profiles in entorhinal cortex (EC) from 149 AD patients and control brains and combined these with two previously published EC datasets by meta-analysis (total n=337).

ResultsWe identified 12 cytosine-phosphate-guanine (CpG) sites showing epigenome-wide significant association with either case-control status or Braaks tau-staging. Four of these CpGs, located in proximity to CNFN/LIPE, TENT5A, PALD1/PRF1, and DIRAS1, represent novel findings. Integrating DNAm levels with RNA sequencing-based mRNA expression data generated in the same individuals showed significant DNAm-mRNA correlations for 6 of the 12 significant CpGs. Lastly, by calculating rates of epigenetic age acceleration using two recently proposed "epigenetic clock" estimators we found a significant association with accelerated epigenetic aging in AD patients vs. controls.

ConclusionIn summary, our study represents the hitherto most comprehensive EWAS in AD using EC and highlights several novel differentially methylated loci with potential effects on gene expression. A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactions AO_SCPLOWBSTRACTC_SCPLOWDrug combinations are a promising strategy to counter antibiotic resistance. However, current experimental and computational approaches do not account for the entire complexity involved in combination therapy design, such as the effect of pathogen metabolic heterogeneity, changes in the growth environment, drug treatment order and time interval. To address these limitations, we present a comprehensive approach that uses genome-scale metabolic modeling and machine learning to guide combination therapy design. Our mechanistic approach (a) accommodates diverse data types, (b) accounts for time- and order-specific interactions, and (c) accurately predicts drug interactions in various growth conditions and their robustness to pathogen metabolic heterogeneity. Our approach achieved high accuracy (AUC = 0.83 for synergy, AUC = 0.98 for antagonism) in predicting drug interactions for E. coli cultured in 57 metabolic conditions based on experimental validation. The entropy in bacterial metabolic response was predictive of combination therapy outcomes across time scales and growth conditions. Simulation of metabolic heterogeneity using population-FBA identified two sub-populations of E. coli cells defined by regulation of cis- to trans-isomerization of unsaturated fatty acids with distinct effects on drug interactions. Analysis of the vast landscape of condition-specific drug interactions revealed a set of 24 robustly synergistic drug combinations with potential for clinical use.

SO_SCPLOWIGNIFICANCEC_SCPLOWWorldwide, 700,000 people die each year from drug-resistant infections. Drug combinations have great potential to reduce the spread of drug-resistant bacteria. However, their potency is impacted by both the pathogen growth environment and the heterogeneity in pathogen metabolism. The metabolic heterogeneity in a pathogen population allows them to survive antibiotic treatment. Here we present a flexible machine-learning framework that utilizes diverse data types to effectively search through the large design space of both sequential and simultaneous combination therapies across hundreds of simulated growth conditions and pathogen metabolic states. Our approach can serve as a useful guide for the selection of robustly synergistic drug combinations. Interactions and information: Exploring task allocation in ant colonies using network analysis In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their groups. Ant colonies display high levels of organisational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g., physiology), or at the group level (e.g., the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published dataset (Mersch et al., 2013) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individuals task - foraging, cleaning or nursing - and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of Effective Information. Our results show that interaction history was tied to task allocation: ants who switched to a task are more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we showed that colony cohesion was stable even as ant-level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows.

HighlightsO_LIWe analysed the interaction networks of six Camponotus fellah colonies
C_LIO_LIWe tested how centrality and information flow were tied to task switching
C_LIO_LINode-level network metrics and the information theoretic measure of Effective Information explained differences among functional groups
C_LIO_LIInteractions were correlated with task switching, but the strength of the correlation differed across functional groups
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