Advanced Complexity and Plasticity of Neural Activity in Reciprocally Connected Human Cerebral Organoids Macroscopic axonal connections in the human brain distribute information and neuronal activity across the brain. Although brain organoid technologies have recently provided novel avenues to investigate human brain function by replicating small neuronal networks of the brain in vitro, functionality of the macroscopic connections between distant regions has not been investigated with organoids. Here, we describe the neural activity of human cerebral organoids reciprocally connected by a bundle of axons. The connected organoids produced significantly more intense and complex oscillatory activity than conventional cerebral organoids. Optogenetic manipulations revealed that the connected organoids could respond to external stimuli and maintain the elevated frequency of neuronal activity for a short term, indicating that the connected organoids exhibit plasticity as a neuronal network. Our findings highlight functional importance of inter-regional connections and suggest that connected organoids can be used as a powerful tool for investigating the development and functions of macroscopic circuits in the human brain. can allow researchers to develop and test compounds to modulate activity of in vitro neuronal network models in unprecedented ways.
The Role of the Ventrolateral Anterior Temporal Lobes in Social Cognition A key challenge for neurobiological models of social cognition is to elucidate whether brain regions are specialised for that domain. In recent years, discussion surrounding the role of anterior temporal regions epitomises such debates; some argue the anterior temporal lobe (ATL) is part of a domain-specific network for social processing, while others claim it comprises a domain-general hub for semantic representation. In the present study, we used ATL-optimised fMRI to map the contribution of different ATL structures to a variety of paradigms frequently used to probe a crucial social ability, namely  theory of mind (ToM). Using multiple tasks enables a clearer attribution of activation to ToM as opposed to idiosyncratic features of stimuli. Further, we directly explored whether these same structures are also activated by a non-social task probing semantic representations. We revealed that common to all of the tasks was activation of a key ventrolateral ATL region that is often invisible to standard fMRI. This constitutes novel evidence in support of the view that the ventrolateral ATL contributes to social cognition via a domain-general role in semantic processing, and against claims of a specialised social function.
A Physiometric Investigation of Inflammatory Composites: Comparison of A Priori Aggregates, Empirically-identified Factors, and Individual Proteins Most research testing the association between inflammation and health outcomes (e.g., heart disease, diabetes, depression) has focused on individual proteins; however, some studies have used summed composites of inflammatory markers without first investigating dimensionality. Using two different samples (MIDUS-2: N = 1,255 adults, MIDUS-R: N = 863 adults), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor- (TNF-), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compared the resulting factor structure to a) an "a priori"/tau-equivalent factor structure in which all inflammatory proteins equally load onto a single dimension (comparable to the summed composites) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, and their associations with health outcomes. An exploratory factor analysis indicated a two-factor structure (Factor 1: CRP and fibrinogen; Factor 2: IL-8 and IL-10) in MIDUS-2 and was replicated in MIDUS-R. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit, but both strongly outperformed the "a priori"/tau-equivalent structure (which did not achieve acceptable model fit in any models). Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions. However, modeling individual proteins resulted in findings more robust to correction for multiple comparisons despite more conservative adjustments. Further, reliability for all latent variables was poor. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, individual inflammatory proteins or, potentially (if empirically supported and biologically-plausible) empirically-identified inflammatory factors should be used in accordance with theory. Inter-tissue convergence of gene expression during ageing suggests age-related loss of tissue and cellular identity Developmental trajectories of gene expression may reverse in their direction during ageing, a phenomenon previously linked to cellular identity loss. Our analysis of cerebral cortex, lung, liver and muscle transcriptomes of 16 mice, covering development and ageing intervals, revealed widespread but tissue-specific ageing-associated expression reversals. Cumulatively, these reversals create a unique phenomenon: mammalian tissue transcriptomes diverge from each other during postnatal development, but during ageing, they tend to converge towards similar expression levels, a process we term Divergence followed by Convergence, or DiCo. We found that DiCo was most prevalent among tissue-specific genes and associated with loss of tissue identity, which is confirmed using data from independent mouse and human datasets. Further, using publicly available single-cell transcriptome data, we showed that DiCo could be driven both by alterations in tissue cell type composition and also by cell-autonomous expression changes within particular cell types. The cell growth cycle: resource allocation and subcellular pattern formation in budding yeast. Metabolic oscillation percolate throughout cellular physiology. The transcriptome oscillates between gene cohorts encoding for biosynthesis and growth, and for catabolism and stress response. However, long protein half-lives dampen effects on protein abundance, and the function of periodic transcription remains elusive. To test three prevailing hypotheses, we performed RNA-seq analysis during a dynamic state of the system, just preceding a bifurcation of system dynamics to a longer period. A few enzymes with short protein half-live and high transcript abundance amplitude could play a direct role in metabolic dynamics (hypothesis H1), e.g., carbonic anhydrase, sulfate uptake and the glyoxylate cycle. Substantial changes in the relative duration of expression of the antagonistic cohorts precede the bifurcation, supporting the idea of a function in cellular resource allocation (H2). The pulse-width modulation model, a mathematical formulation of this idea, explains the dependence of the cycle period on the culture growth rate. This pulse-like model of cell growth provides a first theoretical framework, where the phenomenon is understood as a mechanism of cellular resource allocation and protein homeostasis. The universal temporal program of transcription encodes the spatial structure of the cell, and we further suggest a function in pattern formation of the growing cell (H3). STING activation promotes robust immune response and NK cell-mediated tumor regression in glioblastoma models Immunotherapy has had a tremendous impact on cancer treatment in the past decade, with hitherto unseen responses at advanced and metastatic stages of the disease. However, the aggressive brain tumor glioblastoma (GBM) is highly immunosuppressive and remains largely refractory to current immunotherapeutic approaches. The cGAS-STING cytoplasmic double stranded DNA (dsDNA) sensing pathway has emerged as a next-generation immunotherapy target with potent local immune stimulatory properties.

Here, we investigated the status of the STING pathway in GBM and the modulation of the brain tumor microenvironment (TME) with the STING agonist ADU-S100. Our data reveal the presence of STING in human GBM specimens, where it stains strongly in the tumor vasculature. We show that human GBM explants can respond to STING agonist treatment by secretion of inflammatory cytokines. In murine GBM models, we show a profound shift in the tumor immune landscape after STING agonist treatment, with massive infiltration of the tumor-bearing hemisphere with innate immune cells including inflammatory macrophages, neutrophils and NK populations. Treatment of established murine intracranial GL261 and CT-2A tumors by biodegradable ADU-S100-loaded intracranial implants demonstrated a significant increase in survival in both models and long-term survival with immune memory in GL261. Responses to treatment were abolished by NK cell depletion. This study reveals therapeutic potential and deep remodeling of the TME by STING activation in GBM and warrants the further examination of STING agonists alone or in combination with other immunotherapies such as cancer vaccines, CAR T cells, NK therapies or immune checkpoint blockade.

Significance statementModulation of the immune microenvironment is critical for immunosuppressive and therapy refractory tumors like glioblastoma. Activation of the STING pathway deeply remodels the brain tumor environment and attracts innate immune cells and natural killer cell populations, producing a robust antitumor effect with long-term immune memory. We further show that human glioblastoma tissue can respond to the therapy and lay the foundations for combined intracranial immunotherapies by using crosslinked biodegradable brain implants. How to achieve a higher selection plateau in forest tree breeding? Fostering Heterozygote x Homozygote relationships in Optimal Contribution Selection in the case study of Populus nigra In breeding, Optimal Contribution Selection (OCS) is one of the most effective strategies to balance short- and long-term genetic responses, by maximizing genetic gain and minimizing global coancestry. Considering genetic diversity in the selection dynamic - through coancestry - is undoubtedly the reason for the success of OCS, as it avoids initial loss of favorable alleles. Originally formulated with the pedigree relationship matrix, global coancestry can nowadays be assessed with one of the possible formulations of the realized genomic relationship matrix. Most formulations were optimized for genomic evaluation, but few for the management of coancestry. We introduce here an alternative formulation specifically developed for Genomic OCS (GOCS), intended to better control heterozygous loci, and thus better account for Mendelian sampling. We simulated a multi-generation breeding program with mate allocation and under GOCS for twenty generations, solved with quadratic programming. With the case study of Populus nigra, we have shown that, although the dynamic was mainly determined by the trade-off between genetic gain and genetic diversity, better formulations of the genomic relationship matrix, especially those fostering individuals carrying multiple heterozygous loci, can lead to better short-term genetic gain and a higher selection plateau. Impact of circadian time of dosing on cardiomyocyte-autonomous effects of glucocorticoids Mitochondrial capacity is critical to adapt the high energy demand of the heart to circadian oscillations and diseased states. Glucocorticoids regulate the circadian cycle of energy metabolism, but little is known about how circadian timing of exogenous glucocorticoid dosing directly regulates heart metabolism through cardiomyocyte-autonomous mechanisms. While chronic oncedaily intake of glucocorticoids promotes metabolic stress and heart failure, we recently discovered that intermittent once-weekly dosing of exogenous glucocorticoids promoted muscle metabolism in normal and obese skeletal muscle. However, the effects of glucocorticoid intermittence on heart metabolism and heart failure remain unknown. Here we investigated the extent to which circadian time of dosing regulates the effects of the glucocorticoid prednisone in heart metabolism and function in conditions of single pulse or chronic intermittent dosing. In WT mice, we found that prednisone improved cardiac content of NAD+ and ATP with light-phase dosing (ZT0), while the effects were blocked by dark-phase dosing (ZT12). The drug effects on mitochondrial function were cardiomyocyte-autonomous, as shown by inducible cardiomyocyte-restricted glucocorticoid receptor (GR) ablation, and depended on an intact cardiomyocyte clock, as shown by inducible cardiomyocyte-restricted ablation of Brain and Muscle ARNT-like 1 (BMAL1). Conjugating time-of-dosing with chronic intermittence, we found that once-weekly prednisone improved metabolism and function in heart after myocardial injury dependent on circadian time of intake, i.e. with lightphase but not dark-phase dosing. Our study identifies cardiac-autonomous mechanisms through which circadian-specific intermittent dosing reconverts glucocorticoid drugs to metabolic boosters for the heart. OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition Beta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as "temporal beta-diversity", and most approaches are simply an extension of spatial beta-diversity. The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the "individual-based beta-diversity" concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity. Here, individual-based beta-diversity indices are extended to multiple-unit cases. In addition, a novel type of random permutation criterion related to these multiple-unit indices for detecting patterns of individual persistence is introduced in the present study. To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama. Information regarding "individuals" is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the methods proposed here are expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using traditional individual-tracked forest monitoring data. Multi-omic analysis of the Arabidopsis clock activator mutant rve 4 6 8 reveals connections to carbohydrate metabolism and proteasome regulation Plants are able to sense changes in their light environments, such as the onset of day and night, as well as anticipate these changes in order to adapt and survive. Central to this ability is the plant circadian clock, a molecular circuit that precisely orchestrates plant cell processes over the course of a day. REVEILLE proteins (RVEs) are recently discovered members of the plant circadian circuitry that activate the evening complex and PRR genes to maintain regular circadian oscillation. The RVE 8 protein and its two homologs, RVE 4 and 6, have been shown to limit the length of the circadian period, with rve 4 6 8 triple-knockout plants possessing an elongated period along with increased leaf surface area, biomass, cell size and delayed flowering relative to wild-type Col-0 plants. Here, using a multi-omics approach consisting of phenomics, transcriptomics, proteomics, and metabolomics we draw novel connections between RVE8-like proteins and a number of core plant cell processes. In particular, we reveal that loss of RVE8-like proteins results in altered carbohydrate, organic acid and lipid metabolism, including a starch excess phenotype at dawn. We further demonstrate that rve 4 6 8 plants have lower levels of 20S proteasome subunits and possess significantly reduced proteasome activity, potentially explaining the increase in cell-size observed in RVE8-like mutants. Overall, this robust, multi-omic dataset, provides substantial new insights into the far reaching impact RVE8-like proteins have on the diel plant cell environment. Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent Betacoronavirus strains Comparative functional analysis of the dynamic interactions between various Betacoronavirus mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. Machine learning was used to identify functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Conserved dynamics regions of ACE2 involve both the N-terminal helices, as well as a region of more transient dynamics encompassing K353, Q325 and a novel motif AAQPFLL 386-92 that appears to coordinate their dynamic interactions with the viral RBD at N501. We also demonstrate that the functional evolution of Betacoronavirus zoonotic spillovers involving ACE2 interaction dynamics are likely pre-adapted from two precise and stable binding sites involving the viral bat progenitor strains interaction with CD26 at SAMLI 291-5 and SS 333-334. Our analyses further indicate that the human endemic strains hCoV-HKU1 and hCoV-OC43 have evolved more stable N-terminal helix interactions through enhancement of an interfacing loop region on the viral RBD, whereas the highly transmissible SARS-CoV-2 variants (B.1.1.7, B.1.351 and P.1) have evolved more stable viral binding via more focused interactions between the viral N501 and ACE2 K353 alone. Analysis of caspase-mediated suppression of the cGAS/STING pathway in Kaposi's sarcoma associated herpesvirus lytic infection reveals a dramatic cellular heterogeneity in type I interferon responses As a result of the ongoing virus-host arms race, viruses have evolved numerous immune subversion strategies, many of which are aimed at suppressing the production of type I interferons (IFNs)1. This focus on IFN evasion highlights the essential role of these cytokines in controlling viral infections. Apoptotic caspases have recently emerged as important regulators of type I IFN signaling in both non-infectious contexts and during viral infection2-5. Despite being widely considered anti-viral factors since they can trigger cell death, several apoptotic caspases promote viral replication by suppressing innate immune responses2-5. Indeed, we previously discovered that the AIDS-associated oncogenic gammaherpesvirus Kaposis sarcoma-associated herpesvirus (KSHV) exploits caspase-8 activity to suppress the antiviral type I IFN response and promote viral replication5. However, the mechanism of this novel viral immune evasion strategy is poorly understood, particularly how caspase-8 antagonizes IFN signaling during KSHV infection. Here we show that caspase activity inhibits the DNA sensor cGAS6 during KSHV lytic replication to block type I IFN induction. Furthermore, we use single-cell RNA-sequencing to reveal that the potent antiviral state conferred upon caspase inhibition is mediated by an exceptionally small percentage of IFN-{beta}-producing cells, thus uncovering further complexity of IFN regulation during viral infection. Collectively, these results provide insight into multiple levels of cellular type I IFN regulation that viruses co-opt for immune evasion. Unraveling these mechanisms can inform targeted therapeutic strategies for viral infections and reveal cellular mechanisms of regulating interferon signaling in the context of cancer and chronic inflammatory diseases. Mutations on RBD of SARS-CoV-2 Omicron variant result in stronger binding to human ACE2 receptor The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to more than 270 million infections and 5.3 million of deaths worldwide. Several major variants of SARS-CoV-2 have emerged and posed challenges in controlling the pandemic. The recently occurred Omicron variant raised serious concerns about reducing the efficacy of vaccines and neutralization antibodies due to its vast mutations. We have modelled the complex structure of the human ACE2 protein and the receptor binding domain (RBD) of Omicron Spike protein (S-protein), and conducted atomistic molecular dynamics simulations to study the binding interactions. The analysis shows that the Omicron RBD binds more strongly to the human ACE2 protein than the original strain. The mutations at the ACE2-RBD interface enhance the tight binding by increasing hydrogen bonding interaction and enlarging buried solvent accessible surface area. A novel nongenetic murine model of hyperglycemia and hyperlipidemia-associated aggravated atherosclerosis ObjectiveAtherosclerosis, the main pathology underlying cardiovascular diseases is accelerated in diabetic patients. Genetic mouse models require breeding efforts which are time-consuming and costly. Our aim was to establish a new nongenetic model of inducible metabolic risk factors that mimics hyperlipidemia, hyperglycemia, or both and allows the detection of phenotypic differences dependent on the metabolic stressor(s).

Methods and ResultsWild-type mice were injected with gain-of-function PCSK9D377Y (proprotein convertase subtilisin/kexin type 9) mutant adeno-associated viral particles (AAV) and streptozotocin and fed either a high-fat diet (HFD) for 12 or 20 weeks or a high-cholesterol/high-fat diet (Paigen diet, PD) for 8 weeks. To evaluate atherosclerosis, two different vascular sites (aortic sinus and the truncus of the brachiocephalic artery) were examined in the mice. Combined hyperlipidemic and hyperglycemic (HGHCi) mice fed a HFD or PD displayed characteristic features of aggravated atherosclerosis when compared to hyperlipidemia (HCi HFD or PD) mice alone. Atherosclerotic plaques of HGHCi HFD animals were larger, showed a less stable phenotype (measured by the increased necrotic core area, reduced fibrous cap thickness, and less -SMA-positive area) and had more inflammation (increased plasma IL-1{beta} level, aortic pro-inflammatory gene expression, and MOMA-2-positive cells in the BCA) after 20 weeks of HFD. Differences between the HGHCi and HCi HFD models were confirmed using RNA-seq analysis of aortic tissue, revealing that significantly more genes were dysregulated in mice with combined hyperlipidemia and hyperglycemia than in the hyperlipidemia-only group. The HGHCi-associated genes were related to pathways regulating inflammation (increased Cd68, iNos, and Tnfa expression) and extracellular matrix degradation (Adamts4 and Mmp14). When comparing HFD with PD, the PD aggravated atherosclerosis to a greater extent in mice and showed plaque formation after 8 weeks. Hyperlipidemic and hyperglycemic mice fed a PD (HGHCi PD) showed less collagen (Sirius red) and increased inflammation (CD68-positive cells) within aortic plaques than hyperlipidemic mice (HCi PD). HGHCi-PD mice represent a directly inducible hyperglycemic atherosclerosis model compared with HFD-fed mice, in which atherosclerosis is severe by 8 weeks.

ConclusionWe established a nongenetically inducible mouse model allowing comparative analyses of atherosclerosis in HCi and HGHCi conditions and its modification by diet, allowing analyses of multiple metabolic hits in mice. Glycolysis/gluconeogenesis specialization in microbes is driven by biochemical constraints of flux sensing Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic re-organization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa and Pseudomonas putida. We combined growth dynamics and dynamic changes of intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis and growth and uncovered fundamental limitations of the regulatory network: after nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.

Graphical synopsis O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

Standfirst textMicrobes face a series of fundamental trade-offs that limit their ability to optimize simultaneously for both glycolytic and gluconeogenic growth.

Bullet pointsO_LILag times between glycolysis and gluconeogenesis show asymmetry in many microbes: A long lag in one direction, but a short lag in the other.
C_LIO_LILong lag times are caused by an inability to sense fluxes after nutrient shifts.
C_LIO_LIWith existing regulation, lag time asymmetry can only be overcome by reducing either growth rate or increasing futile cycling in metabolism.
C_LI Sox8 remodels the cranial ectoderm to generate the ear The vertebrate inner ear arises from a pool of progenitors with the potential to contribute to all the sense organs and cranial ganglia in the head. Here we explore the molecular mechanisms that control ear specification from these precursors. Using a multi-omics approach combined with loss-of-function experiments we identify a core transcriptional circuit that imparts ear identity, along with the first genome-wide characterization of non-coding elements that integrate this information. This analysis places the transcription factor Sox8 at the top of the ear determination network. Introducing Sox8 into cranial ectoderm not only converts non-ear cells into ear progenitors, but also activates the cellular programs for ear morphogenesis and neurogenesis. Thus, Sox8 has the unique ability to remodel transcriptional networks in the cranial ectoderm towards ear identity. Quantitative analysis of gene expression on the inactive human X chromosome The human X chromosome exists in active (Xa) and inactive (Xi) states. To quantify Xi gene expression and explore its implications, we conducted RNA sequencing in two cell types from individuals with one Xa and zero to three Xis. Linear models fit the data well, indicating equal contributions from each Xi and quantifying significant Xi-driven expression changes for 124 of 406 expressed X-chromosome genes. As revealed by allele-specific expression analyses, these Xi-driven changes reflect both i) Xi transcription and ii) Xi modulation - both positive and negative - of Xa transcript levels. Incorporating population and evolutionary measures of constraint on expression levels, we identified 13 X-chromosome genes most likely to drive the phenotypic consequences of natural variation in Xi copy number. These analytics and the underlying datasets offer a foundation for understanding Turner, Klinefelter, and other sex chromosome aneuploidy syndromes, and sex-chromosome effects on health and disease in euploid males and females. Exploring the Interactome of Cytochrome P450 2E1 in Human Liver Microsomes with Chemical Crosslinking Mass Spectrometry Aiming to elucidate the grounds of system-wide effects of the alcohol-induced increase in the content of cytochrome P450 2E1 (CYP2E1) on drug metabolism, we explored the array of its protein-protein interactions (proteome) in human liver microsomes (HLM) with chemical crosslinking mass spectrometry (CXMS). Our strategy employs membrane incorporation of purified CYP2E1 modified with photoreactive crosslinkers benzophenone-4-maleimide (BPM) and 4-(N-succinimidylcarboxy)benzophenone (BPS). Exposure of bait-incorporated HLM samples to light was followed by isolating the His-tagged bait protein and its crosslinked aggregates on Ni-NTA agarose. Analyzing the individual bands of SDS-PAGE slabs of thereby isolated protein with the toolset of untargeted proteomics, we detected the crosslinked dimeric and trimeric complexes of CYP2E1 with other drug-metabolizing enzymes. Among the most extensively crosslinked partners of CYP2E1 are the cytochromes P450 2A6, 2C8, 3A4, 4A11, and 4F2. Of particular interest are the interactions of CYP2E1 with the latter two enzymes, which are involved in the synthesis and disposal of vasoactive and pro-inflammatory eicosanoids. We also detected the conjugates of CYP2E1 with UDP-glucuronosyltransferases (UGTs) 1A and 2B, fatty aldehyde dehydrogenase (ALDH3A2), epoxide hydrolase 1 (EPHX1), disulfide oxidase 1 (ERO1L), and ribophorin II (RPN2). These results demonstrate the exploratory power of the proposed CXMS strategy and corroborate the concept of tight functional integration in the human drug-metabolizing ensemble through protein-protein interactions of the constituting enzymes. Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. 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. SARS-CoV-2 RdRp uses NDPs as a substrate and is able to incorporate NHC into RNA from diphosphate form molnupiravir The coronavirus disease 2019 (COVID-19) has been ravaging throughout the world for more than two years and has severely impaired both human health and the economy. The causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) employs the viral RNA-dependent RNA polymerase (RdRp) complex for genome replication and transcription, making RdRp an appealing target for antiviral drug development. Here, we reveal that RdRp can recognize and utilize nucleoside diphosphates (NDPs) as a substrate to synthesize RNAs with an efficiency of about two thirds of using nucleoside triphosphates (NTPs) as a substrate. NDPs incorporation is also template-specific and has high fidelity. Moreover, RdRp can incorporate {beta}-d-N4-hydroxycytidine (NHC) into RNA while using diphosphate form molnupiravir (MDP) as a substrate. We also observed that MDP is a better substrate for RdRp than the triphosphate form molnupiravir (MTP). Co-infection of Candidatus Piscichlamydia trichopodus (order Chlamydiales) and Henneguya sp (Myxosporea, Myxobolidae) in snakeskin gourami Trichopodus pectoralis (Regan 1910) The present study describes a simultaneous infection of a novel Chlamydia-like organism (CLO) with a Myxozoa parasite, Henneguya sp. in snakeskin gourami Trichopodus pectoralis in Thailand. A new CLO is proposed "Candidatus Piscichlamydia trichopodus" (CPT) based on 16S rRNA phylogenetic analysis. Systemic intracellular CPT infection was confirmed by histological examination, in situ hybridization, PCR assay, and sequencing of 16S rRNA. This novel pathogen belongs to the order Chlamydiales but differs in certain aspects from other species. The histopathological changes associated with CPT infection were different from the typical pathological lesions of epitheliocystis caused by previously known CLO. Unlike other CLO, CPT localized in the connective tissue rather than in the epithelial cells and formed smaller clumps of intracellular bacteria that stained dark blue with hematoxylin. On the other hand, typical myxospores of the genus Henneguya with tails were observed in the gill sections. Infection with Henneguya sp. resulted in extensive destruction of the gill filaments, most likely leading to respiratory distress. Due to the frequency of co-infections and the unavailability of culture methods for CLO and Henneguya sp, it was difficult to determine which pathogens were directly responsible for the associated mortality. However, co-infections may increase the negative impact on the host and the severity of the disease. Given the commercial importance of the snakeskin gourami and its significant aquaculture potential, the findings of this study are important for further studies on disease prevention. An epigenomic shift in amygdala marks the transition to maternal behaviors in alloparenting virgin female mice In many species, adults care for young offspring that are not their own, a phenomenon called alloparenting. However, most nonparental adults must be sensitized by repeated or extended exposures to newborns before they will robustly display parental-like behaviors. To capture neurogenomic events underlying the transition to active parental caring behaviors, we analyzed brain gene expression and chromatin profiles of virgin female mice co-housed with mothers during pregnancy and after birth. After an initial display of antagonistic behaviors and a surge of defense-related gene expression, we observed a dramatic shift in the chromatin landscape specifically in amygdala of the pup-exposed virgin females, accompanied by a dampening of anxiety-related gene expression. This epigenetic shift coincided with hypothalamic expression of the oxytocin gene and the emergence of behaviors and gene expression patterns classically associated with maternal care. The results outline a neurogenomic program associated with dramatic behavioral changes and suggest molecular networks relevant to human postpartum mental health. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. 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.