bluuebunny/crossref_metadata_2025 huggingface dataset:
Evidence of RNA polymerase III recruitment and transcription at protein-coding gene promoters
Authors: Rajendra K C , Cheng Ruiying , Zhou Sihang , Lizarazo Simon , Smith Duncan , Van Bortle Kevin
Published: June 2024

RNA polymerase (Pol) I, II, and III are most commonly described as having distinct roles in synthesizing ribosomal RNA (rRNA), messenger RNA (mRNA), and specific small noncoding (nc)RNAs, respectively. This delineation of transcriptional responsibilities is not definitive, however, as evidenced by instances of Pol II recruitment to genes conventionally transcribed by Pol III, including the co-transcription ofRPPH1- the catalytic RNA component of RNase P. A comprehensive understanding of the interplay between RNA polymerase complexes remains lacking, however, due to limited comparative analyses for all three enzymes. To address this gap, we applied a uniform framework for quantifying global Pol I, II, and III occupancies that integrates currently available human RNA polymerase ChIP-seq datasets. Occupancy maps are combined with a comprehensive multi-class promoter set that includes protein-coding genes, noncoding genes, and repetitive elements. While our genomic survey appropriately identifies recruitment of Pol I, II, and III to canonical target genes, we unexpectedly discover widespread recruitment of the Pol III machinery to promoters of specific protein-coding genes, supported by colocalization patterns observed for several Pol III-specific subunits. We show that Pol III-occupied Pol II promoters are enriched for small, nascent RNA reads terminating in a run of 4 Ts, a unique hallmark of Pol III transcription termination and evidence of active Pol III activity at these sites. Pol III disruption differentially modulates the expression of Pol III-occupied coding genes, which are functionally enriched for ribosomal proteins and genes broadly linked to unfavorable outcomes in cancer. Our map also identifies additional, currently unannotated genomic elements occupied by Pol III with clear signatures of nascent RNA species that are sensitive to disruption of La (SSB) - a Pol III-related RNA chaperone protein. These findings reshape our current understanding of the interplay between Pols II and III and identify potentially novel small ncRNAs with broad implications for gene regulatory paradigms and RNA biology.
EfficientDe NovoAssembly and Recovery of Microbial Genomes from Complex Metagenomes Using a Reduced Set ofk-mers
Authors: Qayyum Hajra , Ali Amjad , Rehman Kayani Masood Ur
Published: June 2024

In recent years, the analysis of metagenomic data to recover unculturable microbes has revolutionized microbial genomics by rapidly expanding the reference genome catalog. Central to this, are the computational approaches ofde novoassembly and genome binning that enable large-scale reference-independent recovery of microbial genomes from the metagenomic sequencing data. Despite the advancements in bioinformatics approaches to address the computational challenges inherent to these tasks, the limitation of computational resources continues to be a significant barrier to harvesting the full potential of these techniques. Consequently, there is a stressed need to devise strategies involving the fine-tuning of the employed parameters for the effective utilization of the available metagenomic tools. As most of the available metagenome assembly tools are based on thede Bruijngraph framework that relies on a parameterk, selecting an appropriate subset ofk-mers has become a common approach in bioinformatics for efficient computations. In this study, we propose a reduced set ofk-mers, optimized to strike a balance between computational efficiency and the quality of the high- and low-complexity metagenome assemblies. Utilizing this set ofk-mers with MEGAHIT reduces the metagenome assembly time by half compared to the default set, thus greatly reducing the associated computational cost. In addition, it also brings the promise to improve large-scale genome binning studies that adopt this set in the future as we observed an increase in the total number of the recovered genomes as well as obtained higher proportions of high- and medium-quality genomes recovered from the reducedk-mers-based metagenome assemblies.
Broken time reversal symmetry in visual motion detection
Authors: Wu Nathan , Zhou Baohua , Agrochao Margarida , Clark Damon A.
Published: June 2024

Our intuition suggests that when a movie is played in reverse, our perception of motion in the reversed movie will be perfectly inverted compared to the original. This intuition is also reflected in many classical theoretical and practical models of motion detection. However, here we demonstrate that this symmetry of motion perception upon time reversal is often broken in real visual systems. In this work, we designed a set of visual stimuli to investigate how stimulus symmetries affect time reversal symmetry breaking in the fruit flyDrosophila’s well-studied optomotor rotation behavior. We discovered a suite of new stimuli with a wide variety of different properties that can lead to broken time reversal symmetries in fly behavioral responses. We then trained neural network models to predict the velocity of scenes with both natural and artificial contrast distributions. Training with naturalistic contrast distributions yielded models that break time reversal symmetry, even when the training data was time reversal symmetric. We show analytically and numerically that the breaking of time reversal symmetry in the model responses can arise from contrast asymmetry in the training data, but can also arise from other features of the contrast distribution. Furthermore, shallower neural network models can exhibit stronger symmetry breaking than deeper ones, suggesting that less flexible neural networks promote some forms of time reversal symmetry breaking. Overall, these results reveal a surprising feature of biological motion detectors and suggest that it could arise from constrained optimization in natural environments.

Significance

In neuroscience, symmetries can tell us about the computations being performed by a circuit. In vision, for instance, one might expect that when a movie is played backward, one’s motion percepts should all be reversed. Exact perceptual reversal would indicate a time reversal symmetry, but surprisingly, real visual systems break this symmetry. In this research, we designed visual stimuli to probe different symmetries in motion detection and identify features that lead to symmetry breaking in motion percepts. We discovered that symmetry breaking in motion detection depends strongly on both the detector’s architecture and how it is optimized. Interestingly, we find analytically and in simulations that time reversal symmetries are broken in systems optimized to perform with natural inputs.
Cell morphological representations of genes enhance prediction of drug targets
Authors: Iyer Niveditha S. , Michael Daniel J. , Chi S-Y Gordon , Arevalo John , Chandrasekaran Srinivas Niranj , Carpenter Anne E. , Rajpurkar Pranav , Singh Shantanu
Published: June 2024

Identifying how a given chemical of interest exerts its impact on biological systems is a critical step in developing new medicines and chemical products. The mechanism of a query compound of interest can sometimes be identified when its image-based morphological profile matches a compound in a library of well-annotated compound profiles.

In this study, we demonstrate a significant improvement in classification performance by incorporating side information: gene representations. We generate these representations using the morphological profiles of cells where the level of a single gene’s expression has been artificially increased or decreased. The genes are selected as those encoding known protein targets of annotated compounds in the library. A transformer model is trained to classify gene-compound pairs, where each pair represents a potential interaction between a gene and a compound, as true or false. Subsequently, the model generates a ranked list of likely target genes for a previously unseen query compound. Although the strategy exhibits high performance only for compounds that target previously encountered genes – likely due to the limited size of our training dataset – the performance increase demonstrates a notable improvement over simply matching compound profiles directly to compound profiles or to gene profiles. Larger datasets may improve the prediction capabilities of this approach, enabling the prediction of gene targets for novel compounds, which can then be experimentally validated.
Patterns and drivers of diatom diversity and abundance in the global ocean
Authors: Pierella Karlusich Juan J. , Cosnier Karen , Zinger Lucie , Henry Nicolas , Nef Charlotte , Bernard Guillaume , Scalco Eleonora , Dvorak Etienne ,   Tara Oceans Coordinators, Jimenez Vieira Fabio Rocha , Delage Erwan , Chaffron Samuel , Ovchinnikov Sergey , Zingone Adriana , Bowler Chris
Published: June 2024

Diatoms constitute one of the most diverse and ecologically important phytoplankton groups, yet their large-scale diversity patterns and drivers of abundance are unclear due to limited observations. Here, we utilizeTaraOceans molecular and morphological data, spanning pole to pole, to describe marine diatom diversity, abundance, and environmental adaptation and acclimation strategies. The dominance of diatoms among phytoplankton in terms of relative abundance and diversity was confirmed, and the most prevalent genera wereChaetoceros,Thalassiosira,ActinocyclusandPseudo-nitzschia. We defined 25 distinct diatom communities with varying environmental preferences illustrative of different life strategies. The Arctic Ocean stands out as a diatom hotspot with 6 of the diatom communities being exclusive to it. Light harvesting and photoprotection were among the cellular functions in which natural diatom populations invested the bulk of their transcriptional efforts. This comprehensive study sheds light on marine diatom distributions, offering insights to assess impacts of global change and oceanic anthropogenic impacts.
The long-chain fatty acid-CoA ligase FadD1 monitorsPseudomonas aeruginosaquorum sensing as a receptor of cis-2-decenoic acid
Authors: Song Shihao , Liu Jingyun , Wang Bing , Si Yang , Han Hongguang , Sun Xiuyun , Wang Mingfang , Cui Binbin , Wu Guangliang , Huo Yongliang , Xu Liangxiong , Gao Beile , Yang Liang , Wang Xiaoxue , Zhang Lian-Hui , Deng Yinyue
Published: June 2024

Diffusible signal factor (DSF)-family quorum sensing (QS) signals are widely utilized by many bacterial pathogens to modulate various biological functions and virulence. Previous studies showed thatcis-2-decenoic acid (cis-DA) is involved in modulation of biofilm dispersion inPseudomonas aeruginosa, but its signaling mechanism remains vague. Here, we report thatcis-DA regulates the physiology and virulence ofP. aeruginosathrough the long-chain fatty acid-CoA ligase FadD1.Cis-DA specifically binds to FadD1 with high affinity and enhances the binding of FadD1 to the promoter DNA region oflasR. Further analysis showed that the FadD1 is a response regulator ofcis-DA with a DNA-binding leucine zipper motif to control the transcription of various target genes. Moreover, FadD1 exhibited catalytic activity oncis-2-dodecenoic acid (BDSF) ofBurkholderia cenocepaciaand enhanced the competitiveness ofP. aeruginosa. Together, our work presents a new DSF-type QS signaling system, which is highlighted by its receptor and response regulator evolved from a canonical enzyme of fatty acid metabolism.

Abstract Figure

Highlights

The long-chain fatty acid-CoA ligase FadD1 acts as a global transcriptional regulator inP. aeruginosa. FadD1 is a receptor of QS signalcis-DA and functions at the top of the QS hierarchy inP. aeruginosa. The homolog of FadD1 inP. fluorescenscould bind to the target gene promoter by responding tocis-DA.

In brief

Pseudomonas aeruginosais a human pathogen with antibiotic resistance and a wide range of dynamic defenses makes it an extremely challenging organism to treat in modern-day medicine. It employscis-2-decenoic acid (cis-DA) quorum sensing to regulate the physiology and pathogenesis. Songet al.demonstrate that the long-chain fatty acid-CoA ligase FadD1 controls the important biological functions and virulence inP. aeruginosaas a novel response regulator ofcis-DA signal.
Public Perceptions of Neurotechnologies Used to Target Mood, Memory, and Motor Symptoms
Authors: Furrer Rémy A. , Merner Amanda R. , Stevens Ian , Zuk Peter , Williamson Theresa , Shen Francis X. , Lázaro-Muñoz Gabriel
Published: June 2024

Background

Advances in the development of neurotechnologies have the potential to revolutionize treatment of brain-based conditions. However, a critical concern revolves around the willingness of the public to embrace these technologies, especially considering the tumultuous histories of certain neurosurgical interventions. Therefore, examining public attitudes is paramount to uncovering potential barriers to adoption ensuring ethically sound innovation.

Methods

In the present study, we investigate public attitudes towards the use of four neurotechnologies (within-subjects conditions): deep brain stimulation (DBS), transcranial magnetic stimulation (TMS), pills, and MRI-guided focused ultrasound (MRgFUS) as potential treatments to a person experiencing either mood, memory, or motor symptoms (between-subjects conditions). US-based participants (N=1052; stratified to be nationally representative based on sex, race, age) were asked about their perceptions of risk, benefit, invasiveness, acceptability, perceived change to the person, and personal interest in using these neurotechnologies for symptom alleviation.

Results

Descriptive results indicate variability between technologies that the U.S. public is willing to consider if experiencing severe mood, memory, or motor symptoms. The main effect of neurotechnology revealed DBS was viewed as the most invasive and risky treatment and was perceived to lead to the greatest change to who someone is as a person. DBS was also viewed as least likely to be personally used and least acceptable for use by others. When examining the main effects of symptomatology, we found that all forms of neuromodulation were perceived as significantly more beneficial, acceptable, and likely to be used by participants for motor symptoms, followed by memory symptoms, and lastly mood symptoms. Neuromodulation (averaging across neurotechnologies) was perceived as significantly riskier, more invasive, and leading to a greater change to person for mood versus motor symptoms; however, memory and motor symptoms were perceived similarly with respect to risk, invasiveness, and change to person.

Conclusion

These results suggest that the public views neuromodulatory approaches that require surgery (i.e., DBS and MRgFUS) as riskier, more invasive, and less acceptable than those that do not. Further, findings suggest individuals may be more reluctant to alter or treat psychological symptoms with neuromodulation compared to physical symptoms.
Identification of an ANCA-Associated Vasculitis Cohort Using Deep Learning and Electronic Health Records
Authors: Wang Liqin , Novoa-Laurentiev John , Cook Claire , Srivatsan Shruthi , Hua Yining , Yang Jie , Miloslavsky Eli , Choi Hyon K. , Zhou Li , Wallace Zachary S.
Published: June 2024

Background

ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep learning model analyzing electronic health records (EHR) can more accurately identify AAV cases.

Methods

We examined the Mass General Brigham (MGB) repository of clinical documentation from 12/1/1979 to 5/11/2021, using expert-curated keywords and ICD codes to identify a large cohort of potential AAV cases. Three labeled datasets (I, II, III) were created, each containing note sections. We trained and evaluated a range of machine learning and deep learning algorithms for note-level classification, using metrics like positive predictive value (PPV), sensitivity, F-score, area under the receiver operating characteristic curve (AUROC), and area under the precision and recall curve (AUPRC). The deep learning model was further evaluated for its ability to classify AAV cases at the patient-level, compared with rule-based algorithms in 2,000 randomly chosen samples.

Results

Datasets I, II, and III comprised 6,000, 3,008, and 7,500 note sections, respectively. Deep learning achieved the highest AUROC in all three datasets, with scores of 0.983, 0.991, and 0.991. The deep learning approach also had among the highest PPVs across the three datasets (0.941, 0.954, and 0.800, respectively). In a test cohort of 2,000 cases, the deep learning model achieved a PPV of 0.262 and an estimated sensitivity of 0.975. Compared to the best rule-based algorithm, the deep learning model identified six additional AAV cases, representing 13% of the total.

Conclusion

The deep learning model effectively classifies clinical note sections for AAV diagnosis. Its application to EHR notes can potentially uncover additional cases missed by traditional rule-based methods.

SIGNIFICANCE AND INNOVATIONS

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Traditional approaches to identifying AAV cases for research have relied on registries assembled through clinical care and/or on billing codes which may miss important subgroups.

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Unstructured data entered as free text by clinicians document a patient’s diagnosis, symptoms, manifestations, and other features of their condition which may be useful for identifying AAV cases

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We found that a deep learning approach can classify notes as being indicative of AAV and, when applied at the case level, identifies more cases with AAV than rule-based algorithms.
Incidence and Predictors of Recurrent Pericarditis in Systemic Lupus Erythematosus
Authors: Kim Yoo Jin , Lovell Jana , Diab Alaa , Magder Laurence S. , Goldman Daniel , Petri Michelle , Fava Andrea , Adamo Luigi
Published: June 2024

IMPORTANCE

Pericarditis is the most common cardiac manifestation of Systemic Lupus Erythematosus (SLE) and known to recur among patients. Yet, the prevalence and risk factors of recurrent pericarditis in SLE patients are unknown.

OBJECTIVE

Determine the frequency and risk factors for the recurrence of pericarditis in patients with SLE.

DESIGN

Retrospective analysis of a well-characterized, prospective cohort of SLE patients enrolled between 1988 and 2023.

SETTING

A single-center cohort study of a diverse group of SLE patients treated at a tertiary medical center.

PARTICIPANTS

Patients diagnosed with pericarditis (n=590) among those enrolled in the Hopkins Lupus Cohort (n=2931).

MAIN OUTCOME

Re-occurrence of pericarditis. The SELENA revision of the SLE Disease Activity Index (SLEDAI) was used to define pericarditis. Clinical information was examined for all follow-up encounters after the first episode of pericarditis. Pericarditis that occurred at least six weeks after the first recorded episode was defined as “Recurrent”.

RESULTS

Of 2931 patients within the cohort, 590 had a history of pericarditis. In 3.4% of patients, the diagnosis of pericarditis was confirmed via electrocardiogram (EKG) or dedicated imaging, with 100% concordance between clinical and data-based diagnoses. During a median follow-up of 7 years (IQR: 3 – 14), 20% (n=120) of patients experienced recurrent pericarditis (recurrence rate ≈ 0.05 per person-year of follow-up). Most patients (51%) experienced only one recurrence, whereas 49% had ≥2 recurrences. In multivariate analysis, predictors of recurrence included younger age (≥60 years vs. <40, RR 0.11 (0.04, 0.32),P<.001), treatment with prednisone (≥20 mg vs. 0, RR 1.99 (1.17, 3.40),P= 0.012), active SLE disease (SLEDAI ≥3 vs. 0, RR 1.55 (1.21, 2.00),P<.001), and time since initial episode (3-10 years vs. <1, RR 0.32 (0.20, 0.52),P<.001).

CONCLUSION AND RELEVANCE

Recurrence is more likely to occur within one year of the onset of pericarditis, and younger patients and those with uncontrolled disease are at greater risk of recurrence. As in the general population, oral prednisone therapy is associated with a higher chance of recurrence in SLE patients, with a dose-dependent effect. These findings set the basis for future studies to define optimal treatment for recurrent pericarditis in SLE patients and suggest that oral corticosteroids should be avoided when treating pericarditis.
Can we Predict Training Performance with Shooting Heart Rate in Archers? – A Machine Learning Approach
Authors: Guru Chandra Sekara , Mahajan Uma , Krishnan Anup , Datta Karuna , Sharma Deep
Published: June 2024

Purpose

Heart rate (HR) values during different phases of shooting can be used for performance analysis. Machine learning (ML) methods are used in predicting performance. We aimed to develop ML model to predict performance scores using shooting HR values and also to predict the importance of these parameters in an archer.

Methods

32 archers (15 elite & 17 non-elite) shot two sessions of 30 arrows each indoor wearing heartrate chest monitor and were videographed. When each arrow was shot, 11 HR values were identified at different shooting phases. Other parameters with 35 linear variables and second-degree polynomial HR values were used to build ML models in Python V3.11.4. Session 1 and 2 total scores were used to train and test respectively. Root Mean Squared Error (RMSE) was used to evaluate the model performance after fine-tuning.

Results

RMSE of all 12 ML models ranged from 6.262 – 9.612. The Cat Boost model with the lowest RMSE of 6.262 was used to predict the Session 2 score. SHapley Additive exPlanations (SHAP) values showed each variable’s importance in prediction.

Conclusions

Sports age, resting systolic blood pressure, previous competition score, right hand grip-strength, age, HR before 2sec of arrow release, waist-to-hip ratio, concentration disruption trait anxiety and HR after 5sec of release are top parameters to predict score.

Practical Applications

ML model with shooting HR provides a better prediction of archery score of an individual archer.
Seroprevalence of SARS-CoV-2 and risk factors for infection among children in Uganda: a serial cross-sectional study
Authors: Bagala Irene , Namuganga Jane Frances , Nayebare Patience , Cuu Gloria , Katairo Thomas , Nabende Isaiah , Gonahasa Samuel , Nassali Martha , Tukwasibwe Stephen , Dorsey Grant , Nankabirwa Joaniter , Kitaka Sabrina Bakeera , Kiguli Sarah , Greenhouse Bryan , Ssewanyana Isaac , Kamya Moses R , Briggs Jessica
Published: June 2024

Background

Understanding COVID-19’s impact on children is vital for public health policy, yet age-specific data is scarce, especially in Uganda. This study examines SARS-CoV-2 seroprevalence and risk factors among Ugandan children at two timepoints, along with COVID-19-related knowledge and practices in households, including adult vaccination status.

Methods

Baseline surveys were conducted in 12 communities from April to May 2021 (post-Alpha wave) and follow-up surveys in 32 communities from November 2021 to March 2022 (Omicron wave). Household questionnaires and blood samples were collected to test for malaria by microscopy and for SARS-CoV-2 using a Luminex assay. Seroprevalence was estimated at both the survey and community level. Mixed-effects logistic regression models assessed the association between individual and household factors and SARS-CoV-2 seropositivity in children, adjusting for household clustering.

Results

More households reported disruptions in daily life at baseline compared to follow-up, though economic impacts lingered. By the follow-up survey, 52.7% of adults had received at least one COVID-19 vaccine dose. Overall seroprevalence in children was higher at follow-up compared to baseline (71.6% versus 19.2%, p < 0.001). Seroprevalence in children ranged across communities from 6-37% at baseline and 50-90% at follow-up. At baseline, children from the poorest households were more likely to be infected. Increasing age remained the only consistent risk factor for SARS-CoV-2 seroconversion at both timepoints.

Conclusions

Results indicate that a larger number of children were infected by the Delta and Omicron waves of COVID-19 compared to the Alpha wave. This study is the largest seroprevalence survey in children in Uganda, providing evidence that most children were infected with SARS-CoV-2 before the vaccine was widely available to pediatric populations. Pediatric infections were vastly underreported by case counts, highlighting the importance of seroprevalence surveys in assessing disease burden when testing and reporting rates are limited and many cases are mild or asymptomatic.
Evaluating survey techniques in wastewater-based epidemiology for accurate COVID-19 incidence estimation
Authors: Murakami Michio , Ando Hiroki , Yamaguchi Ryo , Kitajima Masaaki
Published: June 2024

Wastewater-based epidemiology (WBE) requires high-quality survey methods to determine the incidence of infections in catchment areas. In this study, the wastewater survey methods necessary for comprehending the incidence of infection by WBE are clarified. This clarification is based on the correlation with the number of confirmed coronavirus disease 2019 (COVID-19) cases, considering factors such as handling non-detect data, calculation method for representative values, analytical sensitivity, analytical reproducibility, sampling frequency, and survey duration. Data collected from 15 samples per week for two and a half years using a highly accurate analysis method were regarded as gold standard data, and the correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater and confirmed COVID-19 cases was analyzed by Monte Carlo simulation under the hypothetical situation where the quality of the wastewater survey method was reduced. Regarding data handling, it was appropriate to replace non-detect data with estimates based on distribution, and to use geometric means to calculate representative values. For the analysis of SARS-CoV-2 RNA in samples, using a highly sensitive and reproducible method (non-detect rates of < 40%; ≤ 0.4 standard deviation) and surveying at least three samples, preferably five samples, per week were considered desirable. Furthermore, conducting the survey over a period of time that included at least 50 weeks was necessary. A WBE that meets these survey criteria is sufficient for the determination of the COVID-19 infection incidence in the catchment area. Furthermore, WBE can offer additional insights into infection rates in the catchment area, such as the estimated 48% decrease in confirmed COVID-19 cases visiting a clinic following a COVID-19 legal reclassification in Japan.
Sex-biased gene expression across tissues reveals unexpected differentiation in the gills of the threespine stickleback
Authors: Sylvestre Florent , Aubin-Horth Nadia , Bernatchez Louis
Published: June 2024

Sexual dimorphism can evolve through sex-specific regulation of the same gene set. However, sex chromosomes can also facilitate this by directly linking gene expression to sex. Moreover, differences in gene content between heteromorphic sex chromosomes contributes to sexual dimorphism. Understanding patterns of sex-biased gene expression across organisms is important for gaining insight about the evolution of sexual dimorphism and sex chromosomes. Moreover, studying gene expression in species with recently established sex chromosomes can help understand the evolutionary dynamics of gene loss and dosage compensation. The three-spined stickleback is known for its strong sexual dimorphism, especially during the reproductive period. Sex is determined by a young XY sex chromosome pair with a non-recombining region divided in three strata, which have started to degenerate. Using the high multiplexing capability of 3′ QuantSeq to sequence the sex-biased transcriptome of liver, gills and brain, we provide the first characterization of sex-specific transcriptomes from ∼80 stickleback (40 males and 40 females) collected from a natural population during the reproductive period. We find that the liver is extremely differentiated between sexes (36% of autosomal genes) and reflects ongoing reproduction, while the brain shows very low levels of differentiation (0.78%) with no functional enrichment. Finally, the gills exhibit high levels of differentiation (5%), suggesting that sex should be considered in physiological and ecotoxicological studies of gill responses in fishes. We also find that sex-biased gene expression in hemizygous genes is mainly driven by a lack of dosage compensation. However, sex-biased expression of genes that have conserved copies on both sex chromosomes is likely driven by the degeneration of Y allele expression and a down-regulation of male-beneficial mutations on the X chromosome.
Lipid-siRNA conjugate accesses a perivascular transport mechanism and achieves widespread and durable knockdown in the central nervous system
Authors: Sorets Alexander , Schwensen Katrina , Francini Nora , Kjar Andrew , Abdulrahman Adam , Shostak Alena , Katdare Ketaki , Schoch Kathleen , Cowell Rebecca , Park Joshua , Ligocki Alexander , Ford William , Ventura-Antunes Lissa , Hoogenboezem Ella , Prusky Alex , Castleberry Mark , Michell Danielle L , Miller Timothy , Vickers Kasey , Schrag Matthew , Duvall Craig , Lippmann Ethan
Published: June 2024

Short-interfering RNA (siRNA) has gained significant interest for treatment of neurological diseases by providing the capacity to achieve sustained inhibition of nearly any gene target. Yet, efficacious drug delivery throughout deep brain structures of the CNS remains a considerable hurdle for intrathecally administered therapeutics. We herein describe an albumin-binding lipid-siRNA conjugate that transports along meningeal and perivascular CSF pathways, leading to broad dispersion throughout the CNS parenchyma. We provide a detailed examination of the temporal kinetics of gene silencing, highlighting potent knockdown for up to five months from a single injection without detectable toxicity. Single-cell RNA sequencing further demonstrates gene silencing activity across diverse cell populations in the parenchyma and at brain borders, which may provide new avenues for neurological disease-modifying therapies.
Predicting the alternative conformation of a known protein structure based on the distance map of AlphaFold2
Authors: Li Jiaxuan , Zhu Zefeng , Song Chen
Published: June 2024

With AlphaFold2 (AF2) becoming the top structural prediction tool, multiple studies have found that AF2 often favors one conformation state over others in high-precision structure predictions. Meanwhile, it has also been demonstrated that the prediction of multi-state structures from a given protein sequence is possible by subsampling multiple sequence alignment (MSA). In this work, we reveal that AF2 predictions contain information on multi-state structures even with the deepest MSA: protein distance maps extracted from AF2 often exhibit multi-peak signals in the distance probability distributions for residue pairs. By fitting and separating these multi-peak distributions of residue pairs, one can extract distinct distance information of two states, which can be incorporated into Rosetta as restraint energy functions to model large and complex conformational changes. Twenty protein systems with different types of conformational changes were selected for validation in modeling their alternative conformations. With our protocol, we successfully predicted the alternative conformations of 19 systems and achieved a template-based modeling score (TM-score) above 0.90 for the best-sampled models in nine cases. This work further expands the usage of AlphaFold2 in studying multi-state proteins.
An expanded metabolic pathway for androgen production by host-associated bacteria
Authors: Wang Taojun , Ahmad Saeed , Cruz-Lebrón Angélica , Ernst Sarah E. , Caicedo Kelly Yovani Olivos , Jeong Yoon , Binion Briawna , Mbuvi Pauline , Dutta Debapriya , Fernandez-Materan Francelys V. , Breister Adam M. , Lee Jae Won , Kang Jason D. , Harris Spencer C. , Ikegawa Shigeo , Gaskins H. Rex , Erdman John W. , Yang Glen , Cann Isaac , Daniel Steven L. , Hylemon Phillip B. , Anantharaman Karthik , Bernardi Rafael C. , Alves João M.P. , Sfanos Karen S. , Irudayaraj Joseph , Ridlon Jason M.
Published: June 2024

A growing body of literature implicates host-associated microbiota in the modulation of circulating androgen levels in the host, which could have far-reaching implications for androgen-mediated diseases. However, the microbial genetic pathways involved in androgen production remain unknown. Here, we report the first host-associated microbial gene (desF) encoding an enzyme that catalyzes conversion of androstenedione to epitestosterone (epiT) in the gut bacterium,Clostridium scindens. Despite current dogma that epiT is a nuclear androgen-receptor (AR) antagonist, we demonstrate that epiT is a potent androgen, as assessed by its ability to promote prostate cancer cell growth and expression of prostate specific antigen (PSA). We then quantified thedesFgene in fecal samples collected from individuals with advanced prostate cancer (rising blood PSA) undergoing androgen deprivation therapy combined with abiraterone acetate and prednisone (AA/P). Strikingly, fecaldesFlevels were elevated in a subset of individuals progressing on AA/P versus samples taken during AA/P response (stable). Importantly, we observed that AA does not inhibit the bacterial desmolase enzyme that is analogous to the human drug target of AA. We then determined that bacterial isolates from urine or prostatectomy tissue are capable of androgen production. From these isolates we detected 17β-hydroxysteroid dehydrogenase (17β-HSDH) activity, which has not been previously reported in urinary tract bacteria, and discovered thedesGgene in urinary isolates encoding 17β-HSDH that catalyzed conversion of androstenedione to testosterone. Applying advanced artificial intelligence and molecular dynamics, we predict the structures and ligand binding to DesF and DesG. Using a novel bioengineered microencapsulation technique, we demonstrate that urinary androgen-producing bacterial strains can also promote prostate cancer cell growth through steroid metabolism. Taken together, our results are a significant advance for steroid microbiology in humans and suggest that these microbial biotransformations should be further studied in the context of androgen-mediated physiological processes and diseases.
Sex and stress interactions in fear synchrony of mouse dyads
Authors: Ito Wataru , Morozov Alexei
Published: June 2024

Socially coordinated threat responses support the survival of animal groups. Given their distinct social roles, males and females must differ in such coordination. Here, we report such differences during the synchronization of auditory-conditioned freezing in mouse dyads. To study the interaction of emotional states with social cues underlying synchronization, we modulated emotional states with prior stress or modified the social cues by pairing unfamiliar or opposite-sex mice. In same-sex dyads, males exhibited more robust synchrony than females. Stress disrupted male synchrony in a prefrontal cortex-dependent manner but enhanced it in females. Unfamiliarity moderately reduced synchrony in males but not in females. In dyads with opposite-sex partners, fear synchrony was resilient to both stress and unfamiliarity. Decomposing the synchronization process in the same-sex dyads revealed sex-specific behavioral strategies correlated with synchrony magnitude: following partners’ state transitions in males and retroacting synchrony-breaking actions in females. Those were altered by stress and unfamiliarity. The opposite-sex dyads exhibited no synchrony-correlated strategy. These findings reveal sex-specific adaptations of socio-emotional integration defining coordinated behavior and suggest that sex-recognition circuits confer resilience to stress and unfamiliarity in opposite-sex dyads.
Barley variety Quest exhibits broad-spectrum, moderate quantitative resistance against diverseXanthomonas translucenspathovar translucens
Authors: Heiden Nathaniel , Burns Everett , Butchacas Jules , Roman-Reyna Veronica , Mikhail Kelly , Jacobs Jonathan M.
Published: June 2024

Barley (Hordeum vulgaresubspp.vulgare) is the fourth most widely produced cereal today and is valuable for both animal and human consumption. Bacterial leaf streak (BLS) of barley is caused primarily byX. translucenspv. translucens (Xtt) and can lead to significant yield losses. There are currently no available control methods for BLS pathogens, but there are ongoing efforts to identify and characterize sources of resistance to Xtt in available barley germplasm. These screening projects require field trials which are time-consuming and challenged due to variables introduced by environmental and weather conditions, field conditions and other organisms that may be present. Reliable greenhouse phenotyping techniques are needed to accelerate screening of barley germplasm against more Xtt strains. In this study, we established a rapid greenhouse spray inoculation protocol for pathogen-plant phenotyping. This provides a framework for rapid germplasm screening before time-consuming and limited field nursery trials. Our method confirmed the moderate quantitative resistance phenotype discovered in field trials for the cultivars Quest and Tradition against the Xtt strain CIX95. One week old seedlings of the previously characterized resistant line PI329000 were not resistant relative to the susceptible check line MW14-5371-013. The cultivar Quest then demonstrated moderate quantitative resistance against a diverse panel of Xtt strains. Xtt subgroup did not influence BLS outcomes on tested barley lines. We found evidence to support the hypothesis that the virulence of modern strains is increasing, though this does not improve their ability to cause disease on Quest.
Cooperative dynamics of PARP-1 Zinc-finger domains in the detection of DNA single-strand breaks
Authors: Sarma Parvathy A. P. , Abbadie Corinne , Cleri Fabrizio
Published: June 2024

The DNA single-strand break (SSB) repair pathway is initiated by the multifunctional enzyme PARP-1, which recognizes the broken DNA ends by its two zinc-finger domains, Zn1 and Zn2. Despite a number of experiments performed with different DNA configurations and reduced fragments of PARP-1, many details of this interaction that is crucial to the correct initiation of the repair chain are still unclear. We performed Molecular Dynamics (MD) computer simulations of the interaction between the Zn1/Zn2 domains of PARP-1 and a DNA hairpin including a missing nucleotide to simulate the presence of an SSB, a construct used in recent experiments. The role of Zn1 and Zn2 interacting with the SSB ends is studied in detail, both independently and cooperatively. We also explored, PARP-1 operating as a dimer, with the two Zn-fingers coming from two separate copies of the enzyme. By an extensive set of all-atom molecular simulations employing state-of-the art force fields, assisted by empirical docking and free-energy calculations, we conclude that the particular conformation of the DNA hairpin can indeed spontaneously open up by thermal fluctuations, up to extremely kinked deformations. However, such extreme localized deformations are rarely observed in free, long DNA fragments. Protein side-loops make contact with the DNA hairpin grooves, and help Zn2 to penetrate deep in the SSB gap. In this way, Zn2 can interact with the nucleotides opposite to the missing base. OVerall, Zn1 plays a secondary role: the crucial factor for the interaction is the relative arrangement of the Zn1/Zn2 couple, and their mutual orientation with respect to the 3′and 5′SSB end terminals. This helps to obtain an early interacting configuration, which ultimately leads to molecular PARP-1-DNA structures similar to those observed experimentally. Such findings represent an important step toward defining the detailed function of PARP-1 in the early stages of SSB recognition.
pyRforest: A comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R
Authors: Kolisnik Tyler , Keshavarz-Rahaghi Faeze , Purcell Rachel V , Smith Adam N.H. , Silander Olin K
Published: June 2024

Random Forest models are widely used in genomic data analysis and can offer insights into complex biological mechanisms, particularly when features influence the target in interactive, non-linear, or non-additive ways. Currently, some of the most efficient Random Forest methods in terms of computational speed are implemented in Python. However, many biologists use R for genomic data analysis, as R offers a unified platform for performing additional statistical analysis and visualization. Here we present an R package, pyRforest, which integrates Python scikit-learn `RandomForestClassifier` algorithms into the R environment. pyRforest inherits the efficient memory management and parallelization of Python, and is optimized for classification tasks on large genomic datasets, such as those from RNA-seq. pyRforest offers several additional capabilities, including a novel rank-based permutation method for biomarker identification. This method can be used to estimate and visualize p-values for individual features, allowing the researcher to identify a subset of features for which there is robust statistical evidence of an effect. In addition, pyRforest includes methods for the calculation and visualization of SHapley ADditive Explanations (SHAP) values. Finally, pyRforest includes support for comprehensive downstream analysis for gene ontology and pathway enrichment. pyRforest thus improves the implementation and interpretability of Random Forest models for genomic data analysis by merging the strengths of Python with R. pyRforest can be downloaded at: https://www.github.com/tkolisnik/pyRforest with an associated vignette at https://github.com/tkolisnik/pyRforest/blob/main/vignettes/pyRforest-vignette.pdf.
Unveiling the PHR-centered regulatory network orchestrating the phosphate starvation signaling in Chinese fir (Cunninghamia lanceolata)
Authors: Xu Huiming , Deng Lichuan , Zhou Xu , Xing Yifan , Li Guolong , Chen Yu , Huang Yu , Ma Xiangqing , Liu Zhong-Jian , Li Ming , Ma Liuyin
Published: June 2024

Phosphorus (P) is an essential mineral element for plant growth and is absorbed and utilized in the form of inorganic phosphate (Pi). However, Pi deficiency largely restricts plant growth in forest ecosystems, while the molecular mechanism of Pi deficiency in woody plants remains unclear. Here, we show that PHOSPHATE STARVATION RESPONSE (PHRs) were central regulators of Pi starvation signaling in Chinese fir, a gymnosperm woody plant. Pi deficiency repressed the shoot growth by decreasing the net photosynthesis rate, reducing the size and number of needle leaves, suppressing the plant height, and reducing the biomass accumulation of shoots in Chinese fir seedlings. Thirteen Chinese fir PHRs (ClPHRs) were characterized, which evolved differently from model and angiosperm woody plants. ClPHRs did not respond to Pi deficiency at the transcriptional level, whereas three ClPHRs responded to Pi deficiency by increasing the nuclear/cytoplasmic protein abundance ratio. Four ClPHRs can restore Pi starvation signaling by activating transcription ofAtPHT1;1andAtPHT1;4in theatphr1mutant. Notably, ClPHR7, which is evolutionarily distinct from AtPHR1, was the only ClPHR that could respond to Pi deficiency and restore Pi starvation signals. ClPHR7 could also interact with SPX through protein-protein interaction analysis. Thus, the SPX-PHR regulatory module was also present in gymnosperm woody plants, but the exactly responsible proteins were evolutionarily different from those of model plants. In summary, our results revealed the function of the SPX-PHR regulatory module in Pi starvation signaling and provided genetic information for engineered woody plants with high Pi use efficiency.
The impact of Agri-Environment Schemes (AES) and red fox (Vulpes vulpes) on the density of European brown hare (Lepus europaeus) populations in Hungary
Authors: Ujhegyi Nikolett , Biró Zsolt , Bókony Veronika , Keller Norbert , Katona Krisztián , Heltai Miklós , Csányi Sándor , Szemethy László
Published: June 2024

Most Lepus species can easily adapt to new or changing environments. Until the 1960s, the brown hare estimated stock in Hungary went above 1,200,000 specimens. But also in Hungary and across Europe, hare densities have decreased in the past few decades. The primary cause of declining hare populations is habitat alteration in agricultural landscapes caused by the intensification of agricultural practices. Because the well-being and herd size of small game species, such as the hare, are strongly influenced by the ecological environment, following in their population characteristics can be used as an indicator of habitat quality, with the results being used not only in wildlife management, but also in nature conservation and agricultural greening programs. Our goal is to compare the size of the hare game management to the efficiency of the agricultural support system, vegetation types, and the quantity of red fox, all of which can have an impact on the hare’s density.

In a large-scale survey we found that the estimated hare density index decreased year after year. There were no more animals discovered in the "better areas" overall. According to the model, if the game management units contained a large proportion of AKG arable land, the expected hare density would rise. Similarly, if the region had a high proportion of AKG fields but a low or average fox harvest rate, the hare population would be unable to grow. Animal density decreased slightly, albeit in a trend, as the number of AKG lawns increased. Hare distribution has shrunk over time, especially in areas with a high percentage of suitable habitat. The hare harvest density remained constant year after year in VGEs with a higher proportion of AKG grassland. The fox’s declining rate had no effect on the increase in harvest density. Overall, it appears from a national spatial scale study that even in less good areas, the support could not improve the habitat because its effect did not depend on the proportion of good areas, i.e. even in the case of VGEs with a small proportion of good areas, it could not add much to the hare population density a lot of AKG. Cattle pasture comprised a significant portion of the AKG grasslands. Because the effect of intensively grazed regions on hares is clearly negative due to excessively short grass, the high standard deviation values observed in high proportion AKG grasslands may be explained by this.