bluuebunny/crossref_metadata_2025 huggingface dataset:
Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity
Authors: Williams RJ , Brintz Ben J. , Dos Santos Gabriel Ribeiro , Huang Angkana , Buddhari Darunee , Kaewhiran Surachai , Iamsirithaworn Sopon , Rothman Alan L. , Thomas Stephen , Farmer Aaron , Fernandez Stefan , Cummings Derek A T , Anderson Kathryn B , Salje Henrik , Leung Daniel T.
Published: August 2023

The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data. In cross validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric, significantly improved model performance.
Age-dependent effects of adiposity on asthma risk during childhood and adulthood: a lifecourse Mendelian randomization study
Authors: Urquijo Helena , Leyden Genevieve M , Davey Smith George , Richardson Tom G
Published: August 2023

Background

Separating the direct and long-term consequences of childhood lifestyle factors on asthma risk can be exceptionally challenging in epidemiology given that cases are typically diagnosed at various timepoints throughout the lifecourse.

Methods

In this study, we used human genetic data to evaluate the effects of childhood and adulthood adiposity on risk of pediatric (n=13,962 cases) and adult-onset asthma (n=26,582 cases) with a common set of controls (n=300,671) using a technique known as lifecourse Mendelian randomization.

Findings

We found that childhood adiposity increases risk of pediatric asthma (OR=1.20, 95% CI=1.03 to 1.37, P=0.03), whereas there was weak evidence that it has a long-term influence on adult-onset asthma (OR=1.05, 95% CI=0.93 to 1.17, P=0.39). Conversely, there was strong evidence that adulthood adiposity increases asthma risk in midlife using our lifecourse approach (OR=1.37, 95% CI=1.28 to 1.46, P=7×10−12).

Interpretation

These findings suggest that adiposity in childhood and adulthood are independent risk factors for asthma at each of their corresponding timepoints in the lifecourse. This inference would not be possible without the application of human genetic data, emphasizing the value of this approach in uncovering risk factors that begin to exert their influence on disease at early stages in life.

Funding

The Medical Research Council and the British Heart Foundation.
Metabolomics Identifies and Validates Serum Androstenedione as Novel Biomarker for Diagnosing Primary Angle Closure Glaucoma and Predicting the Visual Field Progression
Authors: Li Shengjie , Ren Jun , Qiu Yichao , Jiang Zhendong , Shao Mingxi , Li Yingzhu , Wu Jianing , Song Yunxiao , Sun Xinghuai , Gao Shunxiang , Cao Wenjun
Published: August 2023

Background

Primary angle closure glaucoma (PACG) is the leading cause of irreversible blindness in Asia, and no reliable, effective diagnostic, and predictive biomarkers are used in clinical routines. A growing body of evidence shows metabolic alterations in patients with glaucoma. we aimed to develop and validate potential metabolite biomarkers to diagnose and predict the visual field progression of PACG.

Methods

Here, we used a 5-phases (discovery phase, validation phase 1, validation phase 2, supplementary phase, and cohort phase) multicenter (EENT hospital, Shanghai Xuhui central hospital), cross-sectional, prospective cohort study design to perform widely-targeted metabolomics and chemiluminescence immunoassay to determine candidate biomarkers. Five machine learning (random forest, support vector machine, lasso, K-Nearest neighbor, and Gaussian NB) approaches were used to identify an optimal algorithm. The discrimination ability was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration was assessed by Hosmer-Lemeshow tests and calibration plots.

Results

Studied serum samples were collected from 616 participants, and 1464 metabolites were identified. Machine learning algorithm determines that androstenedione exhibited excellent discrimination and acceptable calibration in discriminating PACG across the discovery phase (discovery set 1, areas under the receiver operating characteristic curve [AUC] =1.0 [95%CI, 1.00-1.00]; discovery set, AUC=0.85 [95%CI, 0.80-0.90]) and validation phases (internal validation, AUC=0.86 [95%CI, 0.81-0.91]; external validation, AUC=0.87 [95%CI, 0.80-0.95]).

Androstenedione also exhibited a higher AUC (0.92-0.98) to discriminate the severity of PACG. In the supplemental phase, serum androstenedione levels were consistent with those in aqueous humor (r=0.82, P=0.038) and significantly (P=0.021) decreased after treatment. Further, cohort phase demonstrates that higher baseline androstenedione levels (hazard ratio=2.71 [95% CI: 1.199-6.104], P=0.017) were associated with faster visual field progression.

Conclusion

Our study identifies serum androstenedione as a potential biomarker for diagnosing PACG and indicating visual field progression.
Expansion of a frontostriatal salience network in individuals with depression
Authors: Lynch Charles J. , Elbau Immanuel , Ng Tommy , Ayaz Aliza , Zhu Shasha , Manfredi Nicola , Johnson Megan , Wolk Danielle , Power Jonathan D. , Gordon Evan M. , Kay Kendrick , Aloysi Amy , Moia Stefano , Caballero-Gaudes Cesar , Victoria Lindsay W. , Solomonov Nili , Goldwaser Eric , Zebley Benjamin , Grosenick Logan , Downar Jonathan , Vila-Rodriguez Fidel , Daskalakis Zafiris J. , Blumberger Daniel M. , Williams Nolan , Gunning Faith M. , Liston Conor
Published: August 2023

Hundreds of neuroimaging studies spanning two decades have revealed differences in brain structure and functional connectivity in depression, but with modest effect sizes, complicating efforts to derive mechanistic pathophysiologic insights or develop biomarkers.1Furthermore, although depression is a fundamentally episodic condition, few neuroimaging studies have taken a longitudinal approach, which is critical for understanding cause and effect and delineating mechanisms that drive mood state transitions over time. The emerging field of precision functional mapping using densely-sampled longitudinal neuroimaging data has revealed unexpected, functionally meaningful individual differences in brain network topology in healthy individuals,2–5but these approaches have never been applied to individuals with depression. Here, using precision functional mapping techniques and 11 datasets comprising n=187 repeatedly sampled individuals and >21,000 minutes of fMRI data, we show that the frontostriatal salience network is expanded two-fold in most individuals with depression. This effect was replicable in multiple samples, including large-scale, group-average data (N=1,231 subjects), and caused primarily by network border shifts affecting specific functional systems, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was unexpectedly stable over time, unaffected by changes in mood state, and detectable in children before the subsequent onset of depressive symptoms in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in specific frontostriatal circuits that tracked fluctuations in specific symptom domains and predicted future anhedonia symptoms before they emerged. Together, these findings identify a stable trait-like brain network topology that may confer risk for depression and mood-state dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.
YiNet: An Integrated Traditional Chinese and Western Medicine Platform for Viral Infectious Diseases
Authors: Dong Fei , Guo Jincheng , Liu Liu , Han Aiqing , Zhang Jian , He Zihao , Qu Xinchi , Lei Shuangshuang , Wang Zhaoxin , Zhou Liwei , Wang Yifan , He Haoyang , Bu Dechao , Zhao Yi , Gu Xiaohong
Published: August 2023

Viral infectious diseases (VIDs) impose a heavy burden on global public health. Traditional Chinese medicine (TCM) has previously and is currently contributing to the prevention and treatment of infectious diseases. Omics and information technology enable the precise identification of virus characteristics, virus‒host interactions and TCM mechanisms. In this study, we constructed the YiNet platform to better integrate the novel techniques and historical experience of TCM in infectious diseases. YiNet comprises three modules: knowledge base, database and toolkit. The YiNet knowledge base involves 43 VIDs, thereby systematically integrating the knowledge regarding viruses, host symptoms and TCM and Western medicine (commonly used chemical drugs, 6,899 herbs and 2,481 formulas). The YiNet database module includes multiple databases, comprising 57,340 genome sequences of 45,791 viral strains and 5,726 multi-omics datasets such as RNA-seq, ChIP-seq and ATAC-seq from different tissues and cell models. It also integrates 1,105 real-world TCM clinical cases. We adopted visual analysis tool to investigate pathogen–host–herb relationships. To explore pharmacological mechanisms for the core herbs, we added formula data mining and network pharmacology analysis pipelines and visualisation tools. YiNet can facilitate the mechanistic study of TCM and drug development for VIDs. The YiNet platform is publicly available athttp://yinet.gene.ac/.
Napping and circadian sleep-wake regulation during healthy aging
Authors: Deantoni Michele , Reyt Mathilde , Baillet Marion , Dourte Marine , De Haan Stella , Lesoinne Alexia , Vandewalle Gilles , Maquet Pierre , Berthomier Christian , Muto Vincenzo , Hammad Gregory , Schmidt Christina
Published: August 2023

Study objectives

Daytime napping is frequently reported among the older population and has attracted increasing attention due to its association with multiple health conditions. Here, we tested whether napping in the aged is associated with altered circadian regulation of sleep, sleepiness and vigilance performance.

Methods

Sixty healthy older individuals (mean age: 69y., 39 women) were recruited with respect to their napping habits (30 nappers, 30 non-nappers). All participants underwent an in-lab 40-h multiple nap protocol (10 cycles of 80 mins of sleep opportunity alternating with 160 mins of wakefulness), preceded and followed by a baseline and recovery sleep period. Saliva samples for melatonin assessment, sleepiness and vigilance performance were collected during wakefulness and electrophysiological data were recorded to derive sleep parameters during scheduled sleep opportunities.

Results

The circadian amplitude of melatonin secretion was reduced in nappers, compared to non-nappers. Furthermore, nappers were characterized by higher sleep efficiencies and REM sleep proportion during day-compared to night-time naps. The nap group also presented altered modulation in sleepiness and vigilance performance at specific circadian phases.

Discussion

Our data indicate that napping is associated with an altered circadian sleep-wake propensity rhythm and thereby contribute to the understanding of the biological correlates underlying napping and/or sleep-wake cycle fragmentation during healthy aging. Altered circadian sleep-wake promotion can lead to a less distinct allocation of sleep into night-time and/or a reduced wakefulness drive during the day, thereby potentially triggering the need to sleep at adverse circadian phase.

SIGNIFICANCE STATEMENT

While napping has raised increasing interest as a health risk factor in epidemiological studies, its underlying regulation processes in the aged remain largely elusive. Here we assessed whether napping in the older population is associated with physiological and behavioral changes in circadian sleep-wake characteristics. Our data indicate that, concomitant to a reduced circadian amplitude in melatonin secretion, healthy older nappers are characterized by reduced day-night differences in sleep efficiency and more particularly in REM sleep, compared to their non-napping counterparts. These results suggest altered circadian response as a cause or consequence of chronic napping in the aged and thereby contribute to the understanding of nap regulation during healthy aging.
Modulation of Recovery from Neonatal Hyperoxic Lung Injury by Sex as a Biological Variable
Authors: Cantu Abiud , Gutierrez Manuel Cantu , Dong Xiaoyu , Leek Connor , Anguera Montserrat , Lingappan Krithika
Published: August 2023

Recovery from lung injury during the neonatal period requires the orchestration of many biological pathways. The modulation of such pathways can drive the developing lung towards proper repair or persistent maldevelopment that can lead to a disease phenotype. Sex as a biological variable can regulate these pathways differently in the male and female lung exposed to neonatal hyperoxia. In this study, we assessed the contribution of cellular diversity in the male and female neonatal lung following injury. Our objective was to investigate sex and cell-type specific transcriptional changes that drive repair or persistent injury in the neonatal lung and delineate the alterations in the immune-endothelial cell communication networks using single cell RNA sequencing (sc-RNAseq) in a murine model of hyperoxic injury. We generated transcriptional profiles of >55,000 cells isolated from the lungs of postnatal day 1 (PND 1) and postnatal day 21 (PND 21) neonatal male and female C57BL/6 mice exposed to 95% FiO2between PND 1-5 (saccular stage of lung development). We show the presence of sex-based differences in the transcriptional states of lung endothelial and immune cells at PND 1 and PND 21. Furthermore, we demonstrate that biological sex significantly influences the response to injury, with a greater number of differentially expressed genes showing sex-specific patterns than those shared between male and female lungs. Pseudotime trajectory analysis highlighted genes needed for lung development that were altered by hyperoxia. Finally, we show intercellular communication between endothelial and immune cells at saccular and alveolar stages of lung development with sex-based biases in the crosstalk and identify novel ligand-receptor pairs. Our findings provide valuable insights into the cell diversity, transcriptional state, developmental trajectory, and cell-cell communication underlying neonatal lung injury, with implications for understanding lung development and possible therapeutic interventions while highlighting the crucial role of sex as a biological variable.
Dabrafenib alters MDSC differentiation and function by activation of GCN2
Authors: Ciudad M. Teresa , Quevedo Rene , Lamorte Sara , Jin Robbie , Nzirorera Nadine , Koritzinsky Marianne , McGaha Tracy L.
Published: August 2023

The effect of targeted therapeutics on anti-cancer immune responses is poorly understood. The BRAF inhibitor dabrafenib has been reported to activate the integrated stress response (ISR) kinase GCN2, and the therapeutic effect has been partially attributed to GCN2 activation. Since ISR signaling is a key component of myeloid-derived suppressor cell (MDSC) development and function, we measured the effect of dabrafenib on MDSC differentiation and suppressive activity. Our data showed that dabrafenib attenuated MDSC ability to suppress T cell activity, which was associated with a GCN2-dependent block of the transition from monocytic progenitor to polymorphonuclear (PMN)-MDSCs and proliferative arrest resulting in PMN-MDSC loss. Transcriptional profiling revealed that dabrafenib-driven GCN2 activation altered metabolic features in MDSCs enhancing oxidative respiration, and attenuated transcriptional programs required for PMN development. Moreover, we observed a broad downregulation of transcriptional networks associated with PMN developmental pathways, and increased activity of transcriptional regulons driven byAtf5,Mafg, andZbtb7a. This transcriptional program alteration underlies the basis for PMN-MDSC developmental arrest, skewing immature MDSC development towards monocytic lineage cells.In vivo, we observed a pronounced reduction in PMN-MDSCs in dabrafenib-treated tumor-bearing mice suggesting that dabrafenib impacts MDSC populations systemically and locally, in the tumor immune infiltrate. Thus, our data reveals transcriptional networks that govern MDSC developmental programs, and the impact of GCN2 stress signaling on the innate immune landscape in tumors, providing novel insight into potentially beneficial off target effects of dabrafenib.
Vitamin D deficiency induces erectile dysfunction: role of superoxide
Authors: Olivencia Miguel A. , Climent Belen , Barreira Bianca , Morales-Cano Daniel , Sánchez Ana , Fernández Argentina , García-Gómez Borja , Romero-Otero Javier , Rodríguez Claudia , Moreno Laura , Prieto Dolores , Larriba María Jesús , Cogolludo Angel , Angulo Javier , Perez-Vizcaino Francisco
Published: August 2023

Epidemiological studies suggest a relationship between vitamin D deficiency and erectile dysfunction (ED) but its causal relationship and the mechanism involved are unclear. Here we demonstrate that isolated corpora cavernosa (CC) from human donors with low vitamin D levels show reduced NO-dependent erectile function. This ED is also reproduced in vitamin D deficient rats and vitamin D receptor knockout micein vivoandex vivoand is associated with penile fibrosis. Vitamin D deficiency also blunts the response of CC to the phosphodiesterase 5 inhibitor sildenafil. CC from deficient rats show increased superoxide and their impaired erectile function is restored by superoxide scavengers. These results suggest that vitamin D deficiency induces ED via increased superoxide production.
Quantum machine learning for untangling the real-world problem of cancers classification based on gene expressions
Authors: Ghoabdi Mohadeseh Zarei , Afsaneh Elaheh
Published: August 2023

Quantum machine learning algorithms using the power of quantum computing provide fast- developing approaches for solving complicated problems and speeding-up calculations for big data. As such, they could effectively operate better than the classical algorithms. Herein, we demonstrate for the first time the classification of eleven cancers based on the gene expression values with 4495 samples using quantum machine learning. In addition, we compare the obtained quantum classification results with the classical outcomes. By implementing a dimensional reduction method, we introduce significant biomarkers for each cancer. In this research, we express that some of the identified gene biomarkers are consistent with DNA promotor methylation, and some other ones can be applied for the survival determination of patients.
Accessory genes define species-specific pathways to antibiotic resistance
Authors: Dillon L. , Dimonaco NJ. , Creevey CJ.
Published: August 2023

Background

The rise of antimicrobial resistance (AMR) is a growing concern globally and a deeper understanding of AMR gene carriage vs usage is vital for future responses to reduce the spread of AMR. Identification of AMR phenotype by laboratory-based assays are often hindered by difficulties in establishing cultures. This issue could be resolved by rapid computational assessment of an organism’s genome, however, AMR gene finder tools are not intended to infer AMR phenotype which is likely to be a product of multiple gene interactions.

Methods

To understand the importance of multi-gene interactions to the relationship between AMR genotype and AMR phenotype, we applied machine learning approaches to 16,950 genomes from microbial isolates representing 28 different genera with 1.2 million corresponding laboratory-determined MICs for 23 different antibiotics. We then elucidated the genomic paths to phenotypic antimicrobial resistance with the aim of allowing for the development of rapid determination of AMR phenotype from genomes or even whole microbiomes.

Results

The application of machine learning models resulted in a >1.5-fold increase in average prediction accuracy of AMR phenotype across the 23 antibiotic models. Interpretation of these models revealed 528 distinct genomic pathways to phenotypic resistance, many of which were species-specific and involved genes which have not previously been associated with AMR phenotype. This is the first study to demonstrate the utility of machine learning models in the prediction of AMR phenotype for a wide range of clinically relevant organisms and antibiotics. This could be applied as a rapid and affordable alternative to culture-based techniques, estimating taxonomy in addition to AMR phenotype, and providing real-time monitoring of multi-drug resistant pathogens.

Availability and implementation

Contact

ldillon05@qub.ac.uk

View supplementary information at this link

https://osf.io/cj4bq/?view_only=c0ee87b7609543b688953089be4c376f

See Code Availability for scripts used.
Microcystin-RR is a biliary toxin selective for neonatal cholangiocytes
Authors: Gupta Kapish , Chen Dongning , Wells Rebecca G.
Published: August 2023

BACKGROUND AND AIMS

Biliary atresia is a fibrosing cholangiopathy affecting neonates that is thought to be caused by a prenatal environmental insult to the bile duct. Biliatresone, a plant toxin with an α-methylene ketone group, was previously implicated in toxin-induced biliary atresia in Australian livestock, but is found in a limited location and is highly unlikely to be a significant human toxin. We hypothesized that other molecules with α-methylene ketone groups, some with the potential for significant human exposure, might also be biliary toxins.

APPROACH AND RESULTS

We focused on the family of microcystins, cyclic peptide toxins from blue-green algae that have an α-methylene ketone group and are found worldwide, particularly during harmful algal blooms. We found that microcystin-RR, but not 6 other microcystins, caused damage to cell spheroids made using cholangiocytes isolated from 2-3-day-old mice, but not from adult mice. We also found that microcystin- RR caused occlusion of extrahepatic bile duct explants from 2-day-old mice, but not 18-day-old mice. Microcystin-RR caused elevated reactive oxygen species in neonatal cholangiocytes, and treatment with N-acetyl cysteine partially prevented microcystin-RR- induced lumen closure, suggesting a role for redox homeostasis in its mechanism of action.

CONCLUSIONS

This study highlights the potential for environmental toxins to cause neonatal biliary disease and identifies microcystin-RR acting via increased redox stress as a possible neonatal bile duct toxin.
Brain Specific Estrogen Ameliorates Cognitive Effects of Surgical Menopause in Mice
Authors: Salinero Abigail E. , Abi-Ghanem Charly , Venkataganesh Harini , Sura Avi , Smith Rachel M. , Thrasher Christina A. , Kelly Richard D. , Hatcher Katherine M. , NyBlom Vanessa , Shamlian Victoria , Kyaw Nyi-Rein , Belanger Kasey M. , Gannon Olivia J. , Stephens Shannon B.Z. , Zuloaga Damian G. , Zuloaga Kristen L.
Published: August 2023

Menopause is a major endocrinological shift that leads to an increased vulnerability to the risk factors for cognitive impairment and dementia. This is thought to be due to the loss of circulating estrogens, which exert many potent neuroprotective effects in the brain. Systemic replacement of estrogen post-menopause has many limitations, including increased risk for estrogen-sensitive cancers. A more promising therapeutic approach therefore might be to deliver estrogen only to the brain thus limiting adverse peripheral side effects. We examined whether we could enhance cognitive performance by delivering estrogen exclusively to the brain in post-menopausal mice. We modeled surgical menopause via bilateral ovariectomy (OVX). We treated mice with the pro-drug 10β,17β-dihydroxyestra-1,4-dien-3-one (DHED), which can be administered systemically but is converted to 17β-estradiol only in the brain. Young (2.5-month) and middle-aged (11-month-old) female C57BL/6J mice received ovariectomy and a subcutaneous implant containing vehicle (cholesterol) or DHED. At 3.5 months old (young group) and 14.5 months old (middle-aged group), mice underwent behavior testing to assess memory. DHED did not significantly alter metabolic status in middle-aged, post-menopausal mice. In both young and middle-aged mice, the brain-specific estrogen DHED improved spatial memory. Additional testing in middle-aged mice also showed that DHED improved working and recognition memory. These promising results lay the foundation for future studies aimed at determining if this intervention is as efficacious in models of dementia that have comorbid risk factors.
Sclerotome-derived vascular smooth muscle progenitors contribute to the haematopoietic stem cell specification niche
Authors: Kelley Clair M. , Glenn Nicole O. , Gays Dafne , Santoro Massimo M. , Clements Wilson K.
Published: August 2023

Haematopoietic stem cells (HSCs) are the self-renewing progenitors that continuously populate the haemato-immune cell lineages throughout life, and constitute the therapeutic component of bone marrow transplants. A major biomedical goal has been to understand the native specification of HSCs during embryonic development as a means to informin vitrodirected differentiation of pluripotent stem cells. Across vertebrate phyla, HSCs derive from haemogenic endothelium in the ventral floor of the primitive dorsal aorta (DA), also known as the descending aorta in mammals. Competent HSC-fated cells in the endothelium likely receive instructive signaling from neighbouring cells that constitute a “specification niche.” We previously showed that experimental manipulations leading to defects in the most ventral compartment of the somite, the sclerotome, are correlated with HSC defects, raising the possibility that sclerotome patterning is required for HSC specification. Here we show that in zebrafish, specific sclerotome-derived cells contact the DA immediately prior to the emergence of HSCs. These cells subsequently give rise to vascular smooth muscle cells (VSMCs). When sclerotome patterning is disrupted, VSMCs are diminished, and HSC specification fails. We conclude that sclerotome-derived VSMC progenitors contribute to the embryonic HSC specification niche, most likely by providing unknown HSC inductive signals.
Spontaneous and double-strand break repair-associated quasipalindrome and frameshift mutagenesis in budding yeast: role of mismatch repair
Authors: Sugawara Neal , Towne Mason J. , Lovett Susan T. , Haber James E.
Published: August 2023

Although gene conversion (GC) inSaccharomyces cerevisiaeis the most error-free way to repair double-strand breaks (DSBs), the mutation rate during homologous recombination is 1000 times greater than during replication. Many mutations involve dissociating a partially-copied strand from its repair template and re-aligning with the same or another template, leading to -1 frameshifts in homonucleotide runs, quasipalindrome (QP)-associated mutations and microhomology-mediated interchromosomal template switches. We studied GC induced by HO endonuclease cleavage atMATα, repaired by anHMR::Kl-URA3donor. We inserted intoHMR::Kl-URA3an 18-bp inverted repeat where one arm had a 4-bp insertion. Most GCs yieldmat::Kl-ura3::QP+4(Ura-) outcomes, but template-switching produces Ura+colonies, losing the 4-bp insertion. If the QP arm without the insertion is first encountered by repair DNA polymerase and is then (mis)used as a template, the palindrome is perfected. When the QP+4 arm is encountered first, Ura+derivatives only occur after second-end capture and second-strand synthesis. QP+4 mutations are suppressed by mismatch repair (MMR) proteins Msh2, Msh3, and Mlh1, but not Msh6. Deleting Rdh54 significantly reduces QP mutations only when events creating Ura+occur in the context of a D-loop but not during second-strand synthesis. A similar bias is found with a proofreading-defective DNA polymerase mutation (pol3-01). DSB-induced mutations differed in several genetic requirements from spontaneous events. We also created a +1 frameshift in the donor, expanding a run of 4 Cs to 5 Cs. Again, Ura3+recombinants markedly increased by disabling MMR, suggesting that MMR acts during GC but favors the unbroken, template strand.
Structure-based self-supervised learning enables ultrafast prediction of stability changes upon mutation at the protein universe scale
Authors: Sun Jinyuan , Zhu Tong , Cui Yinglu , Wu Bian
Published: August 2023

Predicting free energy changes (ΔΔG) is of paramount significance in advancing our comprehension of protein evolution and holds profound implications for protein engineering and pharmaceutical development. Traditional methods, however, often suffer from limitations such as sluggish computational speed or heavy reliance on biased training datasets. These challenges are magnified when aiming for accurate ΔΔG prediction across the vast universe of protein sequences. In this study, we present Pythia, a self-supervised graph neural network tailored for zero-shot ΔΔG predictions. In comparative benchmarks with other self-supervised pre-training models and force field-based methods, Pythia outshines its contenders with superior correlations while operating with the fewest parameters, and exhibits a remarkable acceleration in computational speed, up to 105-fold. The efficacy of Pythia is corroborated through its application in predicting thermostable mutations of limonene epoxide hydrolase (LEH) with significant higher experimental success rates. This efficiency propels the exploration of 26 million high-quality protein structures. Such a grand-scale application signifies a leap forward in our capacity to traverse the protein sequence space and potentially enrich our insights into the intricacies of protein genotype-phenotype relationships. We provided a web app athttps://pythia.wulab.xyzfor users to conveniently execute predictions. Keywords: self-supervised learning, protein mutation prediction, protein thermostability
Expression patterns of m6A RNA methylation regulators under apoptotic conditions in various human cancer cell lines
Authors: Akçaöz-Alasar Azime , Sağlam Buket , Vatansever Ipek Erdogan , Akgül Bünyamin
Published: August 2023

The emerging evidence suggests that epitranscriptomics changes play a crucial role in the pathogenesis of cancer. However, expression patterns of m6A RNA modifiers under apoptotic conditions are unknown. We measured the transcript abundance of m6A RNA modifiers under cisplatin- and tumor necrosis factor alpha (TNF-α)-induced apoptotic conditions. In general, the abundance of m6A modifiers is increased upon cisplatin treatment whereas TNF-α treatment has led to a reduction in their expression. Specifically, cisplatin-induced apoptosis, but not TNF-α mediated apoptosis, lowered the abundance of METTL14 and FTO transcripts. Additionally, cisplatin treatment plummeted the abundance of IGF2BP2 and IGF2BP3 readers following cisplatin treatment. These results suggest that differential response of cancer cells to apoptotic inducers could be partially due to m6A RNA modifiers.
Exploiting Epigenetic Targets to Overcome Taxane Resistance in Prostate Cancer
Authors: Cevatemre Buse , Bulut Ipek , Dedeoglu Beyza , Isiklar Arda , Syed Hamzah , Yedier Bayram Ozlem , Bagci-Onder Tugba , Acilan Ayhan Ceyda
Published: August 2023

The development of taxane resistance remains a major challenge for castration resistant prostate cancer (CR-PCa), despite the effectiveness of taxanes in prolonging patient survival. To uncover novel targets, we performed an epigenetic drug screen on taxane (docetaxel and cabazitaxel) resistant CR-PCa cells. We identified BRPF reader proteins, along with several epigenetic groups (CBP/p300, Menin-MLL, PRMT5 and SIRT1) that act as targets effectively reversing the resistance mediated by ABCB1. Targeting BRPFs specifically resulted in the resensitization of resistant cells, while no such effect was observed on the sensitive compartment. These cells were successfully arrested at the G2/M phase of cell cycle and underwent apoptosis upon BRPF inhibition, confirming the restoration of taxane susceptibility. Pharmacological inhibition of BRPFs reduced ABCB1 activity, indicating that BRPFs may be involved in an efflux-related mechanism. Indeed, ChIP-qPCR analysis confirmed binding of BRPF1 to the ABCB1 promoter suggesting direct regulation of the ABCB1 gene at the transcriptional level. RNA-seq analysis revealed that BRPF1 knockdown affects the genes enriched in mTORC1 and UPR signaling pathways, revealing potential mechanisms underlying its functional impact, which is further supported by the enhancement of taxane response through the combined inhibition of ABCB1 and mTOR pathways, providing evidence for the involvement of multiple BRPF1-regulated pathways. Beyond clinical attributes (Gleason score, tumor stage, therapy outcome, recurrence), metastatic PCa databases further supported the significance of BRPF1 in taxane resistance, as evidenced by its upregulation in taxane-exposed PCa patients.
Application of a Novel Numerical Simulation to Biochemical Reaction systems
Authors: Sato Takashi
Published: August 2023

Motivation

Omics data and single-cell analyses have recently produced many biological informatics. These require simple, fast, and flexible numerical/analytical methods such as ordinary differential equations. However, formulating these equations and their computational processescanbe expensive and imprecise for simulating reactions involving genes and a small number of molecular systems. Therefore, developing a straightforward simulation method is necessary.

Results

We developed a natural number simulation (NNS) method using binomial probability-based stochastic algorithms. Hence, this paper simulated one-gene systems for feedback and feed-forward reactions, allosteric biochemical reactions, and SIR-type population dynamics. Furthermore, NNS can calculate any biological reaction systems written using stoichiometric formula. Thus, NNS provides a comfortable simulation tool for the scientific and engineering fields; algorithms and applications are detailed using Python.

Availability and implementation

Calculation results and the program are available as supplementary information in binomial_v15.zip inhttps://binomial-simulation.com/en/python-program/.

Contact

sato@zeon.co.jp

Supplementary Information

Supplementary data are available in this pdf file.

Graphical Abstract
weIMPUTE: A User-Friendly Web-Based Genotype Imputation Platform
Authors: Tang You , Li Mingliang , Li Zhuo , Li Qi , Hu Xiaodong , Yu Jun , Lin Jian , Bi Chunguang , Yu Helong , Huang Meng
Published: August 2023

Genotype imputation is a critical preprocessing step in genome-wide association studies (GWAS), enhancing statistical power for detecting associated single nucleotide polymorphisms (SNPs) by increasing marker size. In response to the needs of researchers seeking user-friendly graphical tools for imputation without requiring informatics or computer expertise, we have developed weIMPUTE, a web-based imputation graphical user interface (GUI). Unlike existing genotype imputation software, weIMPUTE supports multiple imputation software, including SHAPEIT, Eagle, Minimac4, Beagle, and IMPUTE2, while encompassing the entire workflow, from quality control to data format conversion. This comprehensive platform enables both novices and experienced users to readily perform imputation tasks. For reference genotype data owners, weIMPUTE can be installed on a server or workstation, facilitating web-based imputation services without data sharing. weIMPUTE represents a versatile imputation solution for researchers across various fields, offering the flexibility to create personalized imputation servers on different operating systems.
Cross-talk quantification in molecular networks with application to pathway-pathway and cell-cell interactions
Authors: Chiodi A , Pelucchi P , Mosca E
Published: August 2023

Motivations

Disease phenotypes are interpreted as the consequence of interactions among molecular processes affected by a series of molecular alterations. Current omics approaches underline the importance of such interactions, focusing on molecular mechanisms, by using manually curated pathways or gene sets. As there are no clear boundaries between gene sets, cross-talks between them are relevant to investigate disease phenotypes.

Here we present Ulisse, a method to (1) quantify cross-talks between gene sets, with application to pathways and intercellular cross-talks; (2) investigate the role of the genes involved in cross-talks, via functional relevance analysis, in terms of regulated processes/cell types. As a proof-of-concept, we studied pathway and cell-cell cross-talks in normal and tumoral breast samples, and compared the obtained results with other available tools: PathNet for pathway cross-talk, ICELLNET and SingleCellSignalR for intercellular cross-talk.

Results

Cross-talk analysis allowed to identify dysregulated interactions between tumor progression key mechanisms, while intercellular cross-talks describe well-known interactions of the tumor with the microenvironment. Through functional relevance analysis, Ulisse was able to pinpoint well known key players of the tumor, as well as potential therapeutic targets. The comparison of Ulisse to other packages highlighted the good performance of our package. In conclusion, Ulisse proved to be a valuable tool to study cross-talks, and provide a newly implemented approach to analyse involved genes.

Availability and implementation

Ulisse is an R package and available athttps://github.com/emosca-cnr/Ulisse

Contact

ettore.mosca@itb.cnr.it

Supplementary information

Link to supplementary tables + reference to on-line supplementary material
Age-specific walking speed during locomotor adaptation leads to more generalization across contexts
Authors: Mariscal Dulce M. , Sombric Carly J. , Torres-Oviedo Gelsy
Published: August 2023

Previous work has shown that compared with young adults, older adults generalize their walking patterns more across environments that impose different motor demands (i.e., split-belt treadmill vs. overground). However, in this previous study, all participants walked at a speed that was more comfortable for older adults than young participants, which leads to the question of whether young adults would generalize more their walking patterns than older adults when exposed to faster speeds that are more comfortable for them. To address this question, we examined the interaction between healthy aging and walking speed on the generalization of a pattern learned on a split-belt treadmill (i.e., legs moving at different speeds) to overground. We hypothesized that walking speed during split-belt walking regulates the generalization of walking patterns in an age-specific manner. To this end, groups of young (<30 y/o) and older (65+ y/o) adults adapted their gait on a split-belt treadmill at either slower or faster walking speeds. We assessed the generalization of movements between the groups by quantifying their aftereffects during overground walking, where larger overground aftereffects represent more generalization, and zero aftereffects represent no generalization. We found an interaction between age and walking speed in the generalization of walking patterns. More specifically, older adults generalized more when adapted at slower speeds, whereas younger adults did so when adapted at faster speeds. These results suggest that comfortable walking speeds lead to more generalization of newly acquired motor patterns beyond the training contexts.
Frequent, infinitesimal bottlenecks maximize the rate of microbial adaptation
Authors: Delaney Oscar , Letten Andrew , Engelstädter Jan
Published: August 2023

Serial passaging is a fundamental technique in experimental evolution. The choice of bottleneck severity and frequency poses a dilemma: longer growth periods allow beneficial mutants to arise and grow over more generations, but simultaneously necessitate more severe bottlenecks with a higher risk of those same mutations being lost. Short growth periods require less severe bottlenecks, but come at the cost of less time between transfers for beneficial mutations to establish. The standard laboratory protocol of 24-hour growth cycles with severe bottlenecking has logistical advantages for the experimenter but limited theoretical justification. Here we demonstrate that contrary to standard practice, the rate of adaptive evolution is maximized when bottlenecks are frequent and small, indeed infinitesimally so in the limit of continuous culture. This result derives from revising key assumptions underpinning previous theoretical work, including changing the metric of optimization to incorporate experiment runtime, and using a full binomial distribution for bottlenecking, rather than a Poisson approximation. We also show that adding resource constraints and clonal interference to the model leaves the qualitative results unchanged. Implementing these findings will require liquid-handling robots to perform frequent bottlenecks, or chemostats for continuous culture. Further innovation in and adoption of these technologies has the potential to accelerate the rate of discovery in experimental evolution.
Using Attenuated Total Reflection (ATR) to Investigate the Temperature Dependent Dielectric Properties of Tympanic Membrane, Ear Canal, and Muscle tissues
Authors: Shams Reza , Vilagosh Zoltan , Sly David
Published: August 2023

The attenuated total reflection (ATR) setup, equipped with a diamond crystal and operating in a mixed reflection/transmission mode, demonstrated a superior and efficient capacity for investigating temperature-related interactions of biological materials at the THz-far infrared beamline at the Australian Synchrotron. This methodology was employed explicitly to investigate the temperature-driven variations in reflectance of biological tissues, such as the tympanic membrane, skeletal muscle, and brain samples, in addition to the interaction of water with THz radiation. Uniquely, the technique detected a characteristic ‘crossover flare’ feature in the spectral scan, a trait inherent to water and water-based compounds. It also identified a ‘quiet zone’ feature, a region exhibiting no temperature-dependent reflectance variation at higher frequencies. Remarkably, this approach required minimum sample preparation and was non-destructive, enabling the investigation of a range of tissue temperatures to ascertain the influence of temperature on the reflection and absorption dynamics of THz radiation.
Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis
Authors: Li Yingjie , Wang Cankun , Ma Anjun , Rani Abdul Qawee , Luo Mingjue , Li Jenny , Liu Xuefeng , Ma Qin
Published: August 2023

Human Papillomaviruses (HPVs) are associated with around 5-10% of human cancer, notably nearly 99% of cervical cancer. The mechanisms HPV interacts with stratified epithelium (differentiated layers) during the viral life cycle, and oncogenesis remain unclear. In this study, we used single-cell transcriptome analysis to study viral gene and host cell differentiation-associated heterogeneity of HPV-positive cervical cancer tissue. We examined the HPV16 genes - E1, E6, and E7, and found they expressed differently across nine epithelial clusters. We found that three epithelial clusters had the highest proportion of HPV-positive cells (33.6%, 37.5%, and 32.4%, respectively), while two exhibited the lowest proportions (7.21% and 5.63%, respectively). Notably, the cluster with the most HPV-positive cells deviated significantly from normal epithelial layer markers, exhibiting functional heterogeneity and altered epithelial structuring, indicating that significant molecular heterogeneity existed in cancer tissues and that these cells exhibited unique/different gene signatures compared with normal epithelial cells. These HPV-positive cells, compared to HPV-negative, showed different gene expressions related to the extracellular matrix, cell adhesion, proliferation, and apoptosis. Further, the viral oncogenes E6 and E7 appeared to modify epithelial function via distinct pathways, thus contributing to cervical cancer progression. We investigated the HPV and host transcripts from a novel viewpoint focusing on layer heterogeneity. Our results indicated varied HPV expression across epithelial clusters and epithelial heterogeneity associated with viral oncogenes, contributing biological insights to this critical field of study.
Machine learning of cellular metabolic rewiring
Authors: Xavier Joao B.
Published: August 2023

Metabolic rewiring allows cells to adapt their metabolism in response to evolving environmental conditions. Traditional metabolomics techniques, whether targeted or untargeted, often struggle to interpret these adaptive shifts. Here, we introduceMetaboLiteLearner, a machine learning framework that harnesses the detailed fragmentation patterns from electron ionization (EI) collected in scan mode during gas chromatography/mass spectrometry (GC/MS) to predict abundance changes in metabolically adapted cells. When tested on breast cancer cells with different preferences to metastasize to specific organs,MetaboLiteLearnerpredicted the impact of metabolic rewiring on metabolites withheld from the training dataset using only the EI spectra, without metabolite identification or pre-existing knowledge of metabolic networks. The model learned captures shared and unique metabolomic shifts between brain- and lung-homing metastatic lineages, suggesting potential organ-tailored cellular adaptations. Integrating machine learning and metabolomics paves the way for new insights into complex cellular adaptations.

Significance

Metabolic rewiring—the cellular adaptation to shifts in environment and nutrients—plays key roles in many contexts, including cancer metastasis. Traditional metabolomics often falls short of capturing the nuances of these metabolic shifts. This work introducesMetaboLiteLearner, a machine learning approach that harnesses the rich fragmentation patterns from electron ionization collected in scan mode during gas chromatography/mass spectrometry, paving the way for new insights into metabolic adaptations. Demonstrating its robustness on a breast cancer model, we highlightMetaboLiteLearner’s potential to reshape our understanding of metabolic rewiring, with implications in diagnostics, therapeutics, and basic cell biology.