Batch experiments demonstrating a two-stage bacterial process coupling methanotrophic and heterotrophic bacteria for 1-alkene production from methane Methane (CH4) is a sustainable carbon feedstock source for aerobic CH4-oxidizing bacteria (methanotrophs) to produce value-added chemicals. Under substrate-limited (e.g., CH4, oxygen and nitrogen) conditions, CH4 oxidation results in the production of various short-chain organic acids and platform chemicals. These CH4-derived products could be broadened by utilizing them as a feedstock for heterotrophic bacteria. As a proof of concept, a two-stage system for CH4 abatement and 1-alkene production was developed in this study. Types I and II methanotrophs, i.e., Methylobacter tundripaludum SV96 and Methylocystis rosea SV97, respectively, were investigated in batch tests under different CH4 and air supplementation schemes. CH4 oxidation under either microaerobic or aerobic conditions induced the production of formate, acetate, succinate, and malate in M. tundripaludum SV96, accounting for 4.8-7.0% of consumed CH4-carbon while M. rosea SV97 produced the same compounds except for malate, and with lower efficiency than M. tundripaludum SV96, accounting for 0.7-1.8% of consumed CH4-carbon For the first time, the organic acids-rich spent media of methanotrophs were successfully used for 1-alkene production using engineered Acinetobacter baylyi ADP1  tesA-undA cells. The highest yield of 1-undecene was obtained from spent medium of M. tundripaludum SV96 at 68.9 {+/-} 11.6 mol mol Csubstrate-1.
The Achilles' heel of coronaviruses: targeting the 5' Polyuridines tract of the antigenome to inhibit Mouse coronavirus-induced cell death The current coronavirus pandemic situation is worsened by the rapidly-spreading SARS-CoV-2 virus variants. Identification of viral targets that are indispensable for the virus can be targeted to inhibit mutation-based new escape variant development. The 5-polyU tract of the antigenome offers such a target. Host cells do not harbor 5-polyU tracts on any of their transcripts, making the tract an attractive, virus-specific target. Inhibiting the 5-polyU can limit the use of the tract as template to generate 3 polyA tails of +RNAs of coronaviruses. Here, a modified DNA oligo with 3 polyAs is used to target the 5-polyU tract in mouse coronavirus (MHV-A59). The oligo treatment in mouse 17CL-1 cells infected with MHV-A59 significantly prevented virus-induced cell deaths. This proof-of-concept result shows a unique mode of action against mouse coronavirus without affecting host cells, and can be used for the development of novel classes of drugs that inhibit coronavirus infection in host cells, specifically by the COVID-19-causing virus SARS-CoV-2. In addition, as the 5-polyU tract is immediately generated upon infection, the tag can also be targeted for reliable early detection of viral infection.
Meiotic DSB-independent role of protein phosphatase 4 in Hop1 assembly to promote meiotic chromosome axis formation in budding yeast Dynamic changes in chromosomal structure that occur during meiotic prophase play an important role in the progression of meiosis. Among these structures, meiosis-specific chromosomal axis-loop structures are important as a scaffold for integrated control between the meiotic recombination reaction and the associated checkpoint system to ensure accurate chromosome segregation. However, the molecular mechanism of the initial step of chromosome axis-loop construction is not well understood. Here, we showed that in budding yeast, protein phosphatase 4 (PP4) that primarily counteracts Mec1/Tel1 phosphorylation is required to promote the assembly of chromosomal axis components Hop1 and Red1 onto meiotic chromatin via interaction with Hop1. PP4, in contrast, did not affect Rec8 assembly. Notably, unlike the previously known function of PP4, this novel function of PP4 was independent of meiotic DSB-dependent Tel1/Mec1 kinase activities. The defect in Hop1/Red1 assembly in the absence of PP4 function was not suppressed by dysfunction of Pch2, which removes Hop1 protein from the chromosome axis. This suggests that PP4 is required for the initial step of chromatin loading of Hop1 rather than stabilization of Hop1 on axes. These results indicate that phosphorylation/dephosphorylation-mediated regulation of Hop1 recruitment onto chromatin occurs during chromosome axis construction before meiotic double-strand break formation. Interacting phenotypes and the coevolutionary process: Interspecific indirect genetic effects alter coevolutionary dynamics Coevolution occurs when species interact to influence one anothers fitness, resulting in reciprocal evolutionary change. In many coevolving lineages, trait expression in one species is modified by the genotypes and phenotypes of the other, forming feedback loops reminiscent of models of intraspecific social evolution. Here, we adapt the theory of within-species social evolution, characterized by indirect genetic effects and social selection imposed by interacting individuals, to the case of interspecific interactions. In a trait-based model, we derive general expressions for multivariate evolutionary change in two species and the expected between-species covariance in evolutionary change when selection varies across space. We show that reciprocal interspecific indirect genetic effects can dominate the coevolutionary process and drive patterns of correlated evolution beyond what is expected from direct selection alone. In extreme cases, interspecific indirect genetic effects can lead to coevolution when selection does not covary between species or even when one species lacks genetic variance. Moreover, our model indicates that interspecific indirect genetic effects may interact in complex ways with cross-species selection to determine the course of coevolution. Importantly, our model makes empirically testable predictions for how different forms of reciprocal interactions contribute to the coevolutionary process. Curation, inference, and assessment of a globally reconstructed gene regulatory network for Streptomyces coelicolor Streptomyces coelicolor A3(2) is a model microorganism for the study of Streptomycetes, antibiotic production, and secondary metabolism in general. Even though S. coelicolor has an outstanding variety of regulators among bacteria, little effort to globally study its transcription has been made. We manually curated 29 years of literature and databases to assemble a meta-curated experimentally-validated gene regulatory network (GRN) with 5386 genes and 9707 regulatory interactions ([~]41% of the total expected interactions). This provides the most extensive and up-to-date reconstruction available for the regulatory circuitry of this organism. Only [~]6% (534/9707) are supported by experiments confirming the binding of the transcription factor to the upstream region of the target gene, the so-called "strong" evidence. While for the remaining interactions there is no confirmation of direct binding. To tackle network incompleteness, we performed network inference using several methods (including two proposed here) for motif identification in DNA sequences and GRN inference from transcriptomics. Further, we contrasted the structural properties and functional architecture of the networks to assess the reliability of the predictions, finding the inference from DNA sequence data to be the most trustworthy approach. Finally, we show two applications of the inferred and the curated networks. The inference allowed us to propose novel transcription factors for the key Streptomyces antibiotic regulatory proteins (SARPs). The curated network allowed us to study the conservation of the system-level components between S. coelicolor and Corynebacterium glutamicum. There we identified the basal machinery as the common signature between the two organisms. The curated networks were deposited in Abasy Atlas (https://abasy.ccg.unam.mx/) while the inferences are available as Supplementary Material. Plucking a string or playing a G? Choice type impacts human reinforcement learning In reinforcement learning (RL) experiments, participants learn to make rewarding choices in response to different stimuli; RL models use outcomes to estimate stimulus-response values which change incrementally. RL models consider any response type indiscriminately, ranging from more concretely defined motor choices (e.g. pressing a key with the index finger), to more general choices that can be executed in a number of ways (e.g. getting dinner at the restaurant). But does the learning process vary as a function of the choice type? In Experiment 1, we show that it does: participants were slower and less accurate in learning correct choices of a general format compared to learning more concrete, motor actions. Using computational modeling, we show that two mechanisms contribute to this. First, there was evidence of irrelevant credit assignment: the values of motor actions interfered with the values of other choice dimensions, resulting in more incorrect choices when the correct response is not defined by a single motor action; second, information integration for relevant general choices was slower. In Experiment 2, we replicated and further extended the findings from Experiment 1, by showing that slowed learning was attributable to weaker working memory use, rather than slowed RL learning. In both experiments we ruled out the explanation that the difference in performance between two condition types was driven by difficulty/different levels of complexity. We conclude that defining a more abstract choice space used by multiple learning systems for credit assignment recruits executive resources, limiting how much such processes then contribute to fast learning. Glucose inhibits haemostasis and accelerates diet-induced hyperlipidaemia in zebrafish larvae Hyperglycaemia damages the microvasculature in part through the reduced recruitment of immune cells and interference with platelet signalling, leading to poor wound healing and accelerated lipid deposition in mammals. We investigated the utility of zebrafish larvae to model the effect of glucose on neutrophil and macrophage recruitment to a tail wound, wound-induced haemostasis, and chicken egg yolk feed challenge-induced hyperlipidaemia by supplementing larvae with exogenous glucose by immersion or injection. Neither method of glucose supplementation affected the recruitment of neutrophils and macrophages following tail transection. Glucose injection reduced thrombocyte retention and fibrin plug formation while only thrombocyte retention was reduced by glucose immersion following tail transection. We observed accelerated lipid accumulation in glucose-injected larvae challenged with high fat chicken egg yolk feeding. Our study identifies conserved and divergent effects of high glucose on inflammation, haemostasis, and hyperlipidaemia in zebrafish larvae compared to mammals. If Research is Not the Evidence, What is it? The Lack of Research Citations in Health Vlogs Doctor-influencers have the knowledge needed to understand scientific research, and they have the social media popularity to share it with large audiences. In this article, I explore the treatment of evidence in vlogs by Egyptian doctor-influencers: how they present it and what they use instead of it. I answer the following questions: 1) How do doctor-influencers present evidence on social media? 2) If evidence is not the research, then what is it? The data was collected through in-depth interviews with 12 Egyptian doctor-influencers from different specializations; two focus groups; and a critical discourse analysis of 48 of the influencers most popular and most engaging videos. I found that the doctor-influencers cited academic research only in the videos about medical controversies, new treatments, misinformation, or common medical mistakes. In most of their videos, the Egyptian doctor-influencers scarcely referred to medical research. This is because they believe that their audiences would not understand evidence due to their low educational attainment, weak research skills, and the language barrier (as most medical research is published in English rather than Arabic). These findings highlight the challenges of communicating science in societies with a low level of education. In these settings, communicators may need to move beyond mediating research studies on social media and instead focus on simplifying, translating, and connecting evidence-based information to the cultural context. Artificial seawater based long-term culture of colonial ascidians Tunicates are highly diverse marine invertebrate filter-feeders that are vertebrates closest relatives. These organisms, despite a drastically different body plan during their adulthood, have a tissue complexity related to that of vertebrates. Ascidians, which compose most of the Tunicata, are benthic sessile hermaphrodites that reproduce sexually through a motile tadpole larval stage. Over half of the known ascidians species are able to reproduce asexually by budding, typically leading to the formation of colonies where animals, called zooids, are interconnected through an external vascular system. In addition, colonial ascidians are established models for important biological processes including allorecognition, immunobiology, aging, angiogenesis and whole-body regeneration. However, the current paucity in breeding infrastructures limits the study of these animals to coastal regions.

To promote a wider scientific spreading and popularity of colonial ascidians, we have developed a flexible recirculating husbandry setup for their long-term in-lab culture. Our system is inspired both by the flow-through aquariums used by coastal ascidian labs, as well as by the recirculating in-lab systems used for zebrafish research. Our hybrid system thus combines colony breeding, water filtering and food culturing in a semi-automated system where specimens develop on hanging microscopy glass slides. Temperature, light/dark cycles, flow speed and feeding rates can be controlled independently in four different breeding environments to provide room for species-specific optimization as well as for running experiments. This setup is complemented with a quarantine for the acclimatization of wild isolates.

Herein we present our success in breeding Botrylloides diegensis, a species of colonial ascidians, for more than 3 years in recirculating artificial seawater over 600 km away from their natural habitat. We show that colonies adapt well to in-lab culturing provided that a suitable marine microbiome is present, and that a specific strain can be isolated, propagated and efficiently used for research over prolonged periods of time. The flexible and modular structure of our system can be scaled and adapted to the needs of specific species, such as Botryllus schlosseri, as well as of particular laboratory spaces. Overall, we show that Botrylloides diegensis can be proficiently bred in-land and suggest that our results can be extended to other species of colonial ascidians to promote research on these fascinating animals.

HighlightsO_LIFirst artificial seawater based recirculating aquaculture for colonial ascidians
C_LIO_LIOver 3 years of continuous breeding
C_LIO_LISemi-automated setup with minimized maintenance
C_LIO_LIGood biomass production for strain propagation
C_LIO_LI4 different culture conditions for optimized breeding for species of interest
C_LI 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. Quercetin handles cellular oxidant / antioxidant systems and mitigates immunosenescence hallmarks in human PBMCs: an in vitro study Immunosenescence, oxidative stress, and low vaccine efficacy are important symptoms of aging. The goal of our study was to see if quercetin had anti-aging and stimulating effects on PBMC immune cells in vitro. In the presence of concanavalin a, PBMCs were isolated from healthy elderly and young people and cultured in a complete RPMI-1640 medium supplemented with quercetin. Cell proliferation was assessed using the MTT colorimetric assay after a 48-hour incubation period. Spectrophophotometric assays were used to assess oxidative biomarkers (PC, MDA, and GSH). The ELISA method was used to determine the amount of IL-2 released. A Griess reagent was used to investigate iNOS activity. When compared to young control cells, aged PBMCs had lower proliferation potency, lower IL-2 and NO release, and higher MDA and PC levels. Importantly, quercetin-treated aged PBMCs have a high proliferative response comparable to young cells, restored iNOS activity, and increased levels of GSH antioxidant defences. In comparison to untreated aged PBMCs, treated PBMCs have lower lipo-oxidative damage but higher PC levels. Quercetin may be used as a promising dietary vaccinal adjuvant in the elderly, it has significant effects in reducing immunosenescence hallmarks, as well as mitigating the lipo-oxidative stress in PBMCs cells.

Practical abstractQuercetin is a common dietary polyphenol found in fruits and vegetables that is well known for its antioxidant activity in radical scavenging and anticancer properties characterized by immune system stimulation. In vitro, quercetin boosts immune responses in the elderly and reduces immunosenescence symptoms, according to our findings. As a result, this molecule could be a safe and promising vaccine adjuvant for boosting immunity and reducing aging complications in immune cells as well as reducing oxidative stress in PBMC cells. Early postnatal activation of the hypoxia pathway disrupts β-cell function Hypoxic insults in the perinatal period can lead to persistent hyperinsulinism and profound hypoglycemia in newborns. We studied the impact of the hypoxia-inducible factor 1A (HIF1A) pathway on postnatal {beta}-cell function. Rat pups were treated daily between postnatal day (P)7 to P10 with adaptaquin (AQ), an inhibitor of prolyl hydroxylases, which stabilizes HIF1A. AQ-treated pups were hypoglycemic and had higher plasma insulin concentrations. Their islets had a decreased glucose threshold for insulin secretion, indicative of a delay in {beta}-cell postnatal functional maturation. Histology analyses revealed that AQ-treated pups had increased pancreatic insulin-positive area but no changes in the number of islets or number of {beta}-cells per islet, suggesting larger average {beta}-cell size. AQ-treated rat pups had decreased expression of cell cycle genes and decreased numbers of proliferating {beta}-cells. In conclusion, pharmacologic activation of the HIF1A pathway in the early postnatal period leads to hyperinsulinism, due to the persistence of a low glucose threshold for insulin secretion, and to decreased early postnatal {beta}-cell proliferation, suggesting it can impact adult {beta}-cell mass and diabetes risk. 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. A rationalized definition of tumor suppressor microRNAsexcludes miR-34a While several microRNAs (miRNAs) have been proposed to act as tumor suppressors, a consensual definition of tumor suppressing miRNAs is still missing. Similarly to coding genes, we propose that tumor suppressor miRNAs must show evidence of genetic or epigenetic inactivation in cancers, and exhibit an anti-tumorigenic (e.g., anti-proliferative) activity under endogenous expression levels. Here we observe that this definition excludes the most extensively studied tumor suppressor candidate miRNA, miR-34a. In analyzable cancer types, miR-34a does not appear to be down-regulated in primary tumors relatively to normal adjacent tissues. Deletion of miR-34a is occasionally found in human cancers, but it does not seem to be driven by an anti-tumorigenic activity of the miRNA, since it is not observed upon smaller, miR-34a-specific alterations. Its anti-proliferative action was observed upon large, supra-physiological transfection of synthetic miR-34a in cultured cells, and our data indicates that endogenous miR-34a levels do not have such an effect. Our results therefore argue against a general tumor suppressive function for miR-34a, providing an explanation to the lack of efficiency of synthetic miR-34a administration against solid tumors. Geometric machine learning informed by ground truth: Recovery of conformational continuum from single-particle cryo-EM data of biomolecules This work is based on the manifold-embedding approach to study biological molecules exhibiting continuous conformational changes. Previous work established a method capable of reconstructing 3D movies and accompanying energetics of atomic-level structures from single-particle cryo-EM images of macromolecules displaying multiple conformational degrees of freedom. Here, we introduce an unsupervised geometric machine learning approach that is informed by detailed heuristic analysis of manifolds formed by simulated heterogeneous cryo-EM datasets generated from an atomic structure. These simulated data were generated with increasing complexity to account for multiple conformational motions, state occupancies and typical microscope parameters in a wide range of signal-to-noise ratios. Using these datasets as ground-truth, we provide detailed exposition of our findings using several conformational motions while exploring the available parameter space. Guided by these insights, we build a framework to leverage the high-dimensional geometric information obtained towards reconstituting a quasi-continuum of conformational states in the form of a free-energy landscape and respective 3D density maps for all states therein. As shown by a direct comparison of results, this framework offers substantial improvements relative to the previous work. Structurally and functionally distinct early antibody responses predict COVID-19 disease trajectory and mRNA vaccine response A damaging inflammatory response is strongly implicated in the pathogenesis of severe COVID-19 but mechanisms contributing to this response are unclear. In two prospective cohorts, early non-neutralizing, afucosylated, anti-SARS-CoV-2 IgG predicted progression from mild, to more severe COVID-19. In contrast to the antibody structures that predicted disease progression, antibodies that were elicited by mRNA SARS-CoV-2 vaccines were low in Fc afucosylation and enriched in sialylation, both modifications that reduce the inflammatory potential of IgG. To study the biology afucosylated IgG immune complexes, we developed an in vivo model which revealed that human IgG-Fc{gamma}R interactions can regulate inflammation in the lung. Afucosylated IgG immune complexes induced inflammatory cytokine production and robust infiltration of the lung by immune cells. By contrast, vaccine elicited IgG did not promote an inflammatory lung response. Here, we show that IgG-Fc{gamma}R interactions can regulate inflammation in the lung and define distinct lung activities associated with the IgG that predict severe COVID-19 and protection against SARS-CoV-2.

One Sentence SummaryDivergent early antibody responses predict COVID-19 disease trajectory and mRNA vaccine response and are functionally distinct in vivo. Protein Complex Structure Prediction Powered by Multiple Sequence Alignments of Interologs from Multiple Taxonomic Ranks and AlphaFold2 AlphaFold2 is expected to be able to predict protein complex structures as long as a multiple sequence alignment (MSA) of the interologs of the target protein-protein interaction (PPI) can be provided. However, preparing the MSA of protein-protein interologs is a non-trivial task due to the existence of paralogs. In this study, a simplified phylogeny-based approach was applied to generate the MSA of interologs, which was then used as the input to AlphaFold2 for protein complex structure prediction. Extensively benchmarked this protocol on non-redundant PPI dataset including 107 bacterial PPIs and 442 eukaryotic PPIs, we show complex structures of 79.5% of the bacterial PPIs and 49.8% of the eukaryotic PPIs can be successfully predicted. Considering PPIs may not be conserved in species with long evolutionary distances, we further restricted interologs in the MSA to different taxonomic ranks of the species of the target PPI in protein complex structure prediction. We found the success rates can be increased to 87.9% for the bacterial PPIs and 56.3% for the eukaryotic PPIs if interologs in the MSA are restricted to a specific taxonomic rank of the species of each target PPI. Finally, we show the optimal taxonomic ranks for protein complex structure prediction can be selected with the application of the recalculated predicted TM-scores of the output models. TAP: Targeting and analysis pipeline for optimization and verification of coil placement in transcranial magnetic stimulation ObjectiveTranscranial magnetic stimulation (TMS) can modulate brain function via an electric field (E-field) induced in a region of interest (ROI) in the brain. The ROI E-field can be computationally maximized and set to match a specific reference using individualized head models to find the optimal coil placement and stimulus intensity. However, the available software lacks many practical features for prospective planning of TMS interventions and retrospective evaluation of the experimental targeting accuracy.

ApproachThe TMS targeting and analysis pipeline (TAP) software uses an MRI/fMRI-derived brain target to optimize coil placement considering experimental parameters such as the subjects hair thickness and coil placement restrictions. The coil placement optimization is implemented in SimNIBS 3.2, for which an additional graphical user interface (TargetingNavigator) is provided to visualize and adjust procedural parameters. The coil optimization process also computes the E-field at the target, allowing the selection of the TMS device intensity setting to achieve a specific E-field strength. The optimized coil placement information is prepared for neuronavigation software, which supports targeting during the TMS procedure. The neuronavigation system can record the coil placement during the experiment, and these data can be processed in TAP to quantify the accuracy of the experimental TMS coil placement and induced E-field.

Main resultsTAP was demonstrated in a study consisting of three repetitive TMS sessions in five subjects. TMS was delivered by an experienced operator under neuronavigation with the computationally optimized coil placement. Analysis of the experimental accuracy from the recorded neuronavigation data indicated coil location and orientation deviations up to about 2 mm and 2{degrees}, respectively, resulting in an 8% median decrease in the target E-field magnitude compared to the optimal placement.

SignificanceTAP supports navigated TMS with a variety of features for rigorous and reproducible stimulation delivery, including planning and evaluation of coil placement and intensity selection for E-field-based dosing. 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. Source-sink connectivity: A novel interictal EEG marker for seizure localization Over 15 million epilepsy patients worldwide have drug-resistant epilepsy (DRE). Successful surgery is a standard of care treatment for DRE but can only be achieved through complete resection or disconnection of the epileptogenic zone (EZ), the brain region(s) where seizures originate. Surgical success rates vary between 20-80% because no clinically validated biological markers of the EZ exist. Localizing the EZ is a costly and time-consuming process beginning with non-invasive neuroimaging and often followed by days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity (e.g., low-voltage high frequency activity) on individual channels occurring immediately before seizures or spikes that occur on interictal iEEG (i.e., between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in EZ localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients.

Intracranial EEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aim to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the EZ. We hypothesize that when a patient is not clinically seizing, it is because the EZ is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighboring nodes ("sources") and the inhibited nodes themselves ("sinks"). Specifically, patient-specific dynamical network models (DNMs) were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics (SSMs). We validated the SSMs in a retrospective analysis of 65 patients by using the SSMs of the annotated EZ to predict surgical outcomes. The SSMs predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians predictions (surgical success rate of this dataset). In failed outcomes, we identified regions of the brain with high SSMs that were untreated. When compared to high frequency oscillations, the most commonly proposed interictal iEEG feature for EZ localization, SSMs outperformed in predictive power (by a factor of 1.2) suggesting SSMs may be an interictal iEEG fingerprint of the EZ. SMC protein RecN drives RecA filament translocation and remodelling for in vivo homology search While the molecular repertoire of the homologous recombination pathway is well-studied, the search mechanism that enables recombination between distant homologous regions is poorly understood. Earlier work suggests that the recombinase RecA, an essential component for homology search, forms an elongated filament, nucleating at the break site. How this RecA structure carries out long distance search remains unclear. Here, we follow the dynamics of RecA after induction of a single double-strand break on the Caulobacter chromosome. We find that the RecA-nucleoprotein filament, once formed, rapidly translocates in a directional manner in the cell, undergoing several pole-to-pole traversals, until homology search is complete. Concomitant with translocation, we observe dynamic remodelling of the filament. Importantly in vivo, the RecA filament alone is incapable of such long distance movement; both translocation and dynamic remodelling are contingent on action of SMC-like protein RecN, via its ATPase cycle. We provide a stochastic description of RecN-regulated changes in filament length during translocation via modulation of RecA assembly-disassembly. In summary, we have uncovered the three key elements of homology search driven by RecN: mobility of a finite segment of RecA, filament remodelling and ability to conduct multiple pole-to-pole traversals, which together point to a novel optimal search strategy. Embryo development in Carica papaya Linn. Papaya (Carica papaya Linn.) is a tropical plant whose draft genome has been sequenced. Papaya produces large fruits rich in vitamins A and C and is an important cash crop in developing countries. Nonetheless, little is known about how the female gametophyte develops, how it is fertilized and how it develops into a mature seed containing an embryo and an endosperm. The Papaya female gametophyte displays a Polygonum-type architecture consisting of two synergid cells, an egg cell, a central cell, and three antipodal cells. Reports are available of the presumed existence of varieties in which cross fertilization is bypassed and autonomous development of embryos occurs (e.g., apomixis). In this study, we analyzed the development of female gametophytes in a commercial Hawaiian parental line and in the presumed apomictic Costa Rican line L1. Samples were collected before and after anthesis to compare the overall structure, size and transcriptional patterns of several genes that may be involved in egg and endosperm cell fate and proliferation. These genes were the putative papaya homologs of ARGONAUTE9 (AGO9), MEDEA (MEA), RETINOBLASTOMA RELATED-1 (RBR1), and SLOW WALKER-1 (SWA1). Our results suggest that its feasibly to identify structural features of Polygonum-type development, and that in bagged female flowers of line L1 we might have observed autonomous development of embryo-like structures. Possible downregulation of papaya homologs for AGO9, MEA, RBR1 and SWA1 was observed in embryo sacs from line L1 before and after anthesis, which may suggest a link between suspected apomixis and transcriptional downregulation of genes for RNA-directed DNA methylation, histone remodelers, and rRNA processing. Most notably, the large size of the papaya embryo sac suggests that it could be a cytological alternative to Arabidopsis thaliana for study. Significant variation in embryo sac size was observed between the varieties under study, suggesting wide differences in the genetic regulation of anatomical features. A chromosome-level genome assembly of the European Beech (Fagus sylvatica) reveals anomalies for organelle DNA integration, repeat content and distribution of SNPs The European Beech is the dominant climax tree in most regions of Central Europe and valued for its ecological versatility and hardwood timber. Even though a draft genome has been published recently, higher resolution is required for studying aspects of genome architecture and recombination. Here we present a chromosome-level assembly of the more than 300 year-old reference individual, Bhaga, from the Kellerwald-Edersee National Park (Germany). Its nuclear genome of 541 Mb was resolved into 12 chromosomes varying in length between 28 Mb and 73 Mb. Multiple nuclear insertions of parts of the chloroplast genome were observed, with one region on chromosome 11 spanning more than 2 Mb of the genome in which fragments up to 54,784 bp long and covering the whole chloroplast genome were inserted randomly. Unlike in Arabidopsis thaliana, ribosomal cistrons are present in Fagus sylvatica only in four major regions, in line with FISH studies. On most assembled chromosomes, telomeric repeats were found at both ends, while centromeric repeats were found to be scattered throughout the genome apart from their main occurrence per chromosome. The genome- wide distribution of SNPs was evaluated using a second individual from Jamy Nature Reserve (Poland). SNPs, repeat elements and duplicated genes were unevenly distributed in the genomes, with one major anomaly on chromosome 4. The genome presented here adds to the available highly resolved plant genomes and we hope it will serve as a valuable basis for future research on genome architecture and for understanding the past and future of European Beech populations in a changing climate. Extent of Molecular Chaperone Association Might Determine Fates of Membraneless Organelles during Aging in C. elegans Proteome imbalance can lead to protein misfolding and aggregation which is associated with pathologies. Protein aggregation can also be an active, organized process and can be exploited by cells as a survival strategy. In adverse conditions, it is beneficial to deposit the proteins in a condensate rather degrading and resynthesizing. Membraneless organelles (MLOs) are biological condensates formed through liquid-liquid phase separation (LLPS), involving cellular components such as nucleic acids and proteins. LLPS is a regulated process, which when perturbed, can undergo a transition from a physiological liquid condensate to pathological solid-like protein aggregates.

To understand how the MLO-associated proteins (MLO-APs) behave during aging, we performed a comparative meta-analysis with age related proteome of C. elegans. We found that the MLO-APs are highly abundant throughout the lifespan. Interestingly, they are aggregating more in long-lived mutant worms compared to the age matched wildtype worms. GO term analysis revealed that the cell cycle and embryonic development are among the top enriched processes in addition to RNP components in insoluble proteome. Considering antagonistic pleotropic nature of these developmental genes and post mitotic status of C. elegans, we assume that these proteins phase transit during post development. As the organism ages, these MLO-APs either mature to become more insoluble or dissolve in uncontrolled manner. However, in the long-lived daf-2 mutant worms, the MLOs may attain protective states due to extended availability and association of molecular chaperones. A comparison between time-constrained counts and line transects as methods to estimate butterfly diversity and monitor populations in tropical habitats Long-term species monitoring programmes have revealed catastrophic insect population declines and disruption of biological communities that are contributing to biodiversity loss. Such discoveries have been possible because of standardised methods, such as line transects, of counting butterflies and other insects. However, line transects are not feasible in many tropical and mountainous habitats, so alternative methods must be explored. To tackle this issue, we devised time-constrained (30-min) counts and compared butterfly diversity as estimated through this method with that estimated through line transects in three tropical habitats in India (evergreen forest, dry deciduous forest and an urban woodland). We tested the efficacy of the two methods to sample species richness and abundance, as well as numbers of rare, endemic and specialist butterflies. We observed greater species richness, and more species of habitat specialists and endemics per sample in time-constrained counts in evergreen forest, but not in the other two habitats. Thus, time-constrained counts were more efficient at detecting species in the species-rich evergreen habitat. Apart from this difference, the two sampling methods captured similar levels of species richness and other measures of diversity. Our study thus shows that time-constrained counts is a suitable if not a superior alternative to line transects to conduct butterfly diversity surveys and population monitoring in complex tropical landscapes. Due to methodological flexibility and simplicity, this method may be particularly useful to study the impacts of climate change, habitat fragmentation and land use practices on butterfly conservation in populous and tech-ready tropical countries using citizen science frameworks. RadGenNets: Deep Learning-Based Radiogenomics Model For Gene Mutation Prediction In Lung Cancer AO_SCPLOWBSTRACTC_SCPLOWIn this paper, we present our methodology that can be used for predicting gene mutation in patients with non-small cell lung cancer (NSCLC). There are three major types of gene mutations that a NSCLC patients gene structure can change to: epidermal growth factor receptor (EGFR), Kirsten rat sarcoma virus (KRAS), and Anaplastic lymphoma kinase (ALK). We worked with the clinical and genomics data for each patient as well CT scans. We preprocessed all of the data and then built a novel pipeline to integrate both the image and tabular data. We built a novel pipeline that used a fusion of Convolutional Neural Networks and Dense Neural Networks. Also, using a search approach, we pick an ensemble of deep learning models to classify the separate gene mutations. These models include EfficientNets, SENet, and ResNeXt WSL, among others. Our model achieved a high area under curve (AUC) score of 94% in detecting gene mutation.