Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutational signatures of complex genomic rearrangements in human cancer

Complex genomic rearrangements (CGRs) are common in cancer and are known to form via two aberrant cellular structures—micronuclei and chromatin bridge. However, which mechanism is more relevant to CGR formation in cancer cells and whether there are other undiscovered mechanisms remain open questions. Here, we analyze 2,014 CGRs from 2,428 whole-genome sequenced tumors and deconvolute six CGR signatures based on the topology of CGRs. Through rigorous benchmarking, we show that our CGR signatures are highly accurate and biologically meaningful. Three signatures can be attributed to known biological processes—micronuclei- and chromatin-bridge-induced chromothripsis and extrachromosomal DNA. More than half of the CGRs belong to the remaining three newly discovered signatures. A unique signature (we named “hourglass chromothripsis”) with highly localized breakpoints and small amount of DNA loss is abundant in prostate cancer. Through genetic association analysis, we find SPOP as a candidate gene causing hourglass chromothripsis and playing important role in maintaining genome integrity. Our study offers valuable insights into the formation of CGRs.
Microsphere molecularly imprinted solid-phase extraction for diazepam analysis using itaconic acid as a monomer in propanol

Abstract Diazepam (DZP) is a benzodiazepine drug used as an anti-drug and sedative. It is often misused to induce or create euphoria in combination with other drugs (high or fly sensation) or administered alone. So far, screening for DZP abuse with sensitive analytical methods is needed, as its small concentrations make it difficult to detect. Increased sensitivity of the analytical method can be obtained by using a preparation method that selectively separates the analyte from the sample matrix. Molecularly imprinted polymer (MIP) is one of the preparation solutions with good selectivity, specificity, and sensitivity. MIP was made from DZP as a template, itaconic acid, and ethylene glycol dimethacrylate in a composition of 1:4:20. MIP was made by precipitation polymerisation to obtain microsphere polymer type. MIP had a binding capacity value of 0.0557 mg/g and followed the Freundlich isotherm. Application of the microsphere MIP on spiked blood serum resulted in a recovery of 105.63 ± 1.0% for MIP compared to 21.28 ± 0.4% for non-imprinted polymer, with the imprinting factor value reaching 4.96. Hence, MIP DZP with itaconic acid as a functional monomer and propanol as a porogen, fabricated by the precipitation polymerisation method, is a promising sorbent for DZP extraction in biological fluids.
A Novel Non-Invasive Epithelial Ovarian Cancer Mouse Model Of Hyperthermic Intraperitoneal Chemotherapy (HIPEC)

Background Hyperthermic intraperitoneal chemotherapy (HIPEC) in combination with interval cytoreductive surgery increases the overall survival of epithelial ovarian cancer (EOC) patients with advanced disease. Despite its proven benefits, the mechanism by which HIPEC extends overall survival remains unknown and current strategies to optimize HIPEC are therefore limited. A major challenge is the lack of a robust and streamlined model to investigate the mechanisms underlying HIPEC efficacy. Objective To introduce a novel murine model that can be used to enhance our understanding of HIPEC therapy. Method ID8-luc, an EOC mouse cell line, is inoculated into immunocompetent C57BL/6J mice intraperitoneally. Once tumor is detected by In Vivo Imaging System (IVIS), cisplatin (5 mg/kg) is injected intraperitoneally and superficial hyperthermia of 40°C is applied to the animal’s abdomen and pelvis using an FDA-approved hyperthermia unit (BSD500) for 20 minutes. To validate the model, four treatment conditions were tested: cisplatin and hyperthermia, cisplatin and normothermia, vehicle and hyperthermia, and vehicle and normothermia. Tumor growth was assessed over the course of treatment using IVIS optical spectrum. Results Tumor growth in mice treated with hyperthermic cisplatin was significantly suppressed compared to mice treated with normothermic cisplatin (p < 0.05). No significant differences in tumor growth were observed in the hyperthermic vehicle and normothermic vehicle groups. Conclusions We developed an innovative noninvasive mouse model of HIPEC. Similar to patients with advanced ovarian cancer who are treated with HIPEC at the time of interval cytoreductive surgery, our model demonstrates that hyperthermia enhances the inhibitory effect of cisplatin on intraperitoneal tumor growth. Development of this murine model provides an opportunity to elucidate the mechanisms underlying HIPEC and offer an opportunity to test adjunct treatments in a pre-clinical setting to enhance the utility of HIPEC.
Intraneuronal chloride levels encode tiredness in cortex

Continuous periods of wakefulness are associated with reduced performance levels due to the build-up of sleep pressure in active regions of the brain. These effects manifest as use-dependent changes in cortical network activity and the mechanisms underlying these changes represent targets for overcoming the cognitive effects of tiredness. Here we reveal a central role for intraneuronal chloride levels, which increase in a use-dependent manner during waking, and reduce the strength of local synaptic inhibition in mouse cortex. Activity-dependent increases in chloride account for spatial and temporal features of sleep pressure, they underlie cortical network oscillations in the sleep-deprived state, and targeting chloride regulation in cortex can rescue performance levels when tired. These findings provide a missing link between sleep-wake history, synaptic transmission and cortical dynamics. One-Sentence Summary The effects of sleep pressure on cortical function are caused by use-dependent changes in chloride-mediated synaptic inhibition.
Engineering Gelation Kinetics in Living Silk Hydrogels by Differential Dynamic Microscopy Microrheology and Machine Learning

Microbes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing mechanical and biological properties in living hydrogels—for example gel time of the hydrogel formulation and viability of the embedded organisms—can be challenging. In this work, a pipeline is developed to automate characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embedded E. coli—formulated from within a 4D parameter space—are engineered to gel within a pre-selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision-making under uncertainty. The rate of learning is observed to vary between AI-assisted planning and human planning, with the fastest rate occurring during AI-assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5-15 minutes, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties—at least over a finite range—while maintaining biological activity.
Decoding explicit and implicit representations of health and taste attributes of foods in the human brain

Obesity has become a significant problem word-wide and is strongly linked to poor food choices. Even in healthy individuals, taste perceptions often drive dietary decisions more strongly than healthiness. This study tested whether health and taste representations can be directly decoded from brain activity, both when explicitly considered, and when implicitly processed for decision-making. We used multivariate support vector regression for event-related potentials (as measured by the electroencephalogram) occurring in the first second of food cue processing to predict ratings of tastiness and healthiness. In Experiment 1, 37 healthy participants viewed images of various foods and explicitly rated their tastiness and healthiness, whereas in Experiment 2, 89 healthy participants indicated their desire to consume snack foods, with no explicit instruction to consider tastiness or healthiness. In Experiment 1 both attributes could be decoded, with taste information being available earlier than health. In Experiment 2, both dimensions were also decodable, and their significant decoding preceded the decoding of decisions (i.e., desire to consume the food). However, in Experiment 2, health representations were decodable earlier than taste representations. These results suggest that health information is activated in the brain during the early stages of dietary decisions, which is promising for designing obesity interventions aimed at quickly activating health awareness.
Unraveling microbial interactions in the gut microbiome

The human gut comprises trillions of microorganisms that take part in several critical functions of the body. Within this structured habitat, the microbes synergise with one another mainly mediated through metabolic exchanges. In this study, we used 52 most commonly occurring microbial species in the gut and identified the interactions between them. Using our previously developed graph-based algorithm, MetQuest, we enumerate several biosynthetic pathways, mainly involved in amino acid biosynthesis and spanning across a pair of organisms. We compute the Metabolic Support Index (MSI), which captures the extent of support/interaction between a pair of microbes, based on the incremental change in metabolic capabilities achieved in a community vis-à-vis the individual organisms. Our results from these analyses are four-fold. Firstly, we show that dependencies between the gut microorganisms largely vary with respect to the environmental conditions. We observe that few phyla such as Firmicutes, Fusobacteria and Proteobacter showed significantly higher metabolic support on DMEM conditions compared to HF medium. Secondly, we infer a microbial association network based on the MSI values and found that the gut organisms are arranged in trophic-levels, with B. bifidum and R. torques acting as central nodes with the highest betweenness centrality. Thirdly, we find that species belonging to Lactobacillus genus, especially L. mucosae and L. reuteri show an enriched amino acid synthesising ability in the presence of many other gut organisms on a minimal glucose medium. Finally, through pathway analyses, we observe that metabolic exchanges are medium-dependent, and many of the metabolites are involved in energy metabolism, nucleotide, and vitamin biosynthesis. Overall, this study sheds light on the astonishing variety of underlying interactions between microorganisms in the gut. Author Summary Microorganisms are ubiquitous and exist in evolutionarily and metabolically diverse communities around us. In practically every ecosystem, microbes form complex dynamic assemblages—such as in the human gut, where they outnumber human cells. Community structure in these microbiomes is dictated by a complex web of interactions, where metabolic interactions are known to predominate. In this study, we employ computational tools to interrogate community metabolic networks and unravel the dependencies between microbes in the gut. We used 52 important and commonly occurring microbial species in the gut, as identified in previous studies. Through our analyses, we show that the dependencies between gut organisms vary in different environmental conditions. Further, we show that these organisms are arranged in multiple trophic levels, where a select few of them acting as central nodes. We also identify the metabolic interactions and demonstrate how synergistic interactions can enhance the amino acid biosynthesis in gut bacteria. These results, taken together, help us better understand the mechanism behind these interactions, which would pave the way for the rational design of pre- and pro-biotic formulations.
Biochar alters soil properties, microbial community diversity, and enzyme activities, while decreasing conifer performance

Biochars are porous charcoal-like materials that can enhance soil health and plant growth, but its use has not been adequately evaluated in woody cropping systems. We set up an experimental Christmas tree plantation on a Marlette series soil amended with two types of biochar and conducted two studies on the impacts of biochar on the agroecosystem over three years following establishment. The first study investigated the effects of biochar on plant performance, soil physicochemical properties and extracellular enzyme activities, while the second investigated the response of the root-associated fungal community. Both biochars stimulated five extracellular enzyme activities, with increases of between 67% and 446%. Structural equation modelling identified increases to dissolved organic carbon and soil moisture as potential mechanisms of biochar’s effects on enzyme activities. Tree growth and survival were negatively affected by biochar application, depending on the tree species and biochar applied, which may have been due to induced nitrogen limitation. High-throughput sequencing showed that biochar decreased the diversity of root-associated fungal communities, with the ectomycorrhizal species Wilcoxina mikolae reaching levels of hyper-dominance on balsam fir in response to one of the biochars. Further studies should investigate how biochar can be harnessed to remediate specific soil quality issues or restructure soil ecosystems in ways that improve crop performance.
3D matrix adhesion composition facilitates nuclear force coupling to drive invasive cell migration

Cell invasion and metastasis is a multi-step process, initialised through the acquisition of a migratory phenotype and the ability to move through differing and complex 3D extracellular environments. In this study we set out to identify the parameters required for invasive cell migration in 3D environments. Cells interact with the extracellular matrix via transmembrane-spanning integrin adhesion complexes, which are well characterised in cells plated on 2D surfaces, yet much less is known about them in cells embedded in 3D matrices. We establish a technique to determine the composition of cell matrix adhesion complexes of invasive breast cancer cells in 3D matrices and on 2D surfaces and we identify an interaction complex enriched in 3D adhesive sites required for 3D invasive migration. Depletion of β-PIX-Myosin18A (Myo18A) abolishes cancer cell invasion, without negatively affecting matrix degradation, Rho GTPase signalling, or protrusion formation in collagen matrices. Instead, in a mechanism only seen in cells moving through 3D matrix, β-PIX and Myo18A drive the polarised recruitment of non-muscle Myosin 2A (NM2A) to the tips of protrusions. This recruitment of NM2A is required for the creation of an NM2A-NM2B isoform gradient, which ranges from the protrusion to the nucleus. We observe a requirement for active force transmission to the nucleus during invasive migration that is needed to pull the nucleus forward. We postulate that the establishment of the NM2A-NM2B actomyosin gradient facilitates the coupling of cell-matrix interactions at the protrusive cell front with nuclear movement, enabling effective invasive migration and front-rear cell polarity.
Verification of SARS-CoV-2-encoded small RNAs and contribution to infection-associated lung inflammation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019 (COVID-19), the respiratory illness responsible for the COVID-19 pandemic. SARS-CoV-2 is a positive-stranded RNA virus belongs to Coronaviridae family. The viral genome of SARS-CoV-2 contains around 29.8 kilobase with a 5′-cap structure and 3′-poly-A tail, and shows 79.2% nucleotide identity with human SARS-CoV-1, which caused the 2002-2004 SARS outbreak. As the successor to SARS-CoV-1, SARS-CoV-2 now has circulated across the globe. There is a growing understanding of SARS-CoV-2 in virology, epidemiology, and clinical management strategies. In this study, we verified the existence of two 18-22 nt small viral RNAs (svRNAs) derived from the same precursor in human specimens infected with SARS-CoV-2, including nasopharyngeal swabs and formalin-fixed paraffin-embedded (FFPE) explanted lungs from lung transplantation of COVID-19 patients. We then simulated and confirmed the formation of these two SARS-CoV-2-Encoded small RNAs in human lung epithelial cells. And the potential pro-inflammatory effects of the splicing and maturation process of these two svRNAs in human lung epithelial cells were also explored. By screening cytokine storm genes and the characteristic expression profiling of COVID-19 in the explanted lung tissues and the svRNAs precursor transfected human lung epithelial cells, we found that the maturation of these two small viral RNAs contributed significantly to the infection associated lung inflammation, mainly via the activation of the CXCL8, CXCL11 and type I interferon signaling pathway. Taken together, we discovered two SARS-CoV-2-Encoded small RNAs and investigated the pro-inflammatory effects during their maturation in human lung epithelial cells, which might provide new insight into the pathogenesis and possible treatment options for COVID-19.
Decoding Angiotensin II Type 1 Receptor Allosteric Communication to Gq and β-arrestin

The allosteric communication between the agonist binding site and the G protein or β-arrestin coupling sites in G protein-coupled receptors (GPCRs) play an important role in determining ligand efficacy towards these two signaling pathways and hence the ligand bias. Knowledge of the amino acid residue networks involved in the allosteric communication will aid understanding GPCR signaling and the design of biased ligands. Angiotensin II type I receptor (AT1R) is an ideal model GPCR to study the molecular basis of ligand bias as it has multiple β-arrestin2 and Gq protein biased agonists as well as three-dimensional structures. Using Molecular Dynamics simulations, dynamic allostery analysis, and functional BRET assays, we identified a network of residues involved in allosteric communication from the angiotensin II binding site to the putative Gq coupling sites and another network to the β-arrestin2 coupling sites, with 6 residues common to both pathways located in TM3, TM5 and TM6. Our findings unveil unique and common allosteric communication residue hubs for Gq and β-arr2 coupling by AngII ligands and suggests that some of these residues can be targeted to design biased AT1R ligands. Finally, we show through analysis of the inter-residue distance distributions of the activation microswitches involved in class A GPCR activation for ten different agonists, that these microswitches behave like rheostats with different relative strengths of activation, which we speculate could modulate the relative efficacy of these agonists toward the two signaling pathways. Significance Statement Knowledge of the residues involved in allosteric communication from the ligand binding site to the G protein or β-arrestin (β-arr) coupling sites in GPCRs will aid in understanding their role in mediating ligand bias. Using a combination of molecular dynamics simulations and functional signaling assays we have identified a network of residues involved in allosteric communication from the Angiotensin II (Ang II) binding site to the Gq and β-arr2 coupling sites in the Ang II type I receptor (AT1R). The residues in the allosteric network for β-arr2 coupling are distributed across multiple structural regions of AT1R compared to Gq coupling. The residues in the two networks show conserved chemical properties across class A GPCRs, demonstrating the importance of allosteric communication in modulating ligand bias.
Complexities in the role of acetylation dynamics in modifying inducible gene activation parameters

High levels of histone acetylation are associated with the regulatory elements of active genes, suggesting a link between acetylation and gene activation. However, several studies have shown that histone acetylation dynamics rather than hyperacetylation per se are important determinants in gene activation, particularly at inducible genes. We revisited this model, in the context of EGF-inducible gene expression and found that rather than a simple unifying model, there are two broad classes of genes; one in which high lysine acetylation activity is required for efficient gene activation, and a second group where the opposite occurs and high acetylation activity is inhibitory. We examined the latter class in more detail using EGR2 as a model gene and found that lysine acetylation levels are critical for several activation parameters, including the timing of expression onset, and overall amplitudes of the transcriptional response. In contrast, DUSP1 responds in the canonical manner and its transcriptional activity is promoted by acetylation. Single cell approaches demonstrate heterogenous DUSP1 activation kinetics and that acetylation levels influence allele activation frequencies. Our data therefore point to a complex interplay between acetylation dynamics and target gene induction, which cannot simply be explained by a unified response to acetylation activity. Instead, acetylation level thresholds are an important determinant of transcriptional induction dynamics that are sensed in a gene-specific manner.
Molecular dynamics simulations of zfP 2 X 4 receptors 2

ABSTRACT The ATP activated P2X4 receptor plays a prominent role in pain perception and modulation and thus may constitute 6 an alternative therapeutic target for controlling pain. Given the biomedical relevance of P2X4 receptors, and poor understanding 7 of molecular mechanisms that describe its gating by ATP, fundamental understanding of functional mechanism of these channels 8 is warranted. Through classical all-atom molecular dynamics (MD) simulations we investigated the number of ATP molecules 9 required to open (activate) the receptor for it to conduct ions. Since crystal structures of human P2X4 are not yet available, the 10 crystal structures of highly-homologous zebrafish P2X4 (zfP2X4) structures were utilized for this study. It has been identified 11 that at least two ATP molecules are required to prevent the open state receptor collapsing back to a closed state. Additionally, 12 we have discovered two metal binding sites, one at the intersection of the three monomers in the ectodomain (MBS1) and the 13 second one near the ATP binding site (MBS2), both of which are occupied by the potassium ions. This observation draws its 14 comparison to the gulf coast P2X receptor that it possess the same two metal binding sites, however, MBS1 and MBS2 in this 15 receptor are occupied by zinc and magnesium, respectively. 16