bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sparse Epistatic Regularization of Deep Neural Networks for Inferring Fitness Functions
Authors: Aghazadeh Amirali , Nisonoff Hunter , Ocal Orhan , Brookes David H. , Huang Yijie , Koyluoglu O. Ozan , Listgarten Jennifer , Ramchandran Kannan 
Published: November 2020

AbstractDespite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitness functions. Expressive models in machine learning (ML), such as deep neural networks (DNNs), can model the nonlinearities in rugged fitness functions, which manifest as high-order epistatic interactions among the mutational sites. However, in the absence of an inductive bias, DNNs overfit to the small number of labeled sequences available for training. Herein, we exploit the recent biological evidence that epistatic interactions in many fitness functions are sparse; this knowledge can be used as an inductive bias to regularize DNNs. We have developed a method for sparse epistatic regularization of DNNs, called theepistatic net(EN), which constrains the number of non-zero coefficients in the spectral representation of DNNs. For larger sequences, where finding the spectral transform becomes computationally intractable, we have developed a scalable extension of EN, which subsamples the combinatorial sequence space uniformly inducing a sparse-graph-code structure, and regularizes DNNs using the resulting greedy optimization method. Results on several biological landscapes, from bacterial to protein fitness functions, show that EN consistently improves the prediction accuracy of DNNs and enables them to outperform competing models which assume other forms of inductive biases. EN estimates all the higher-order epistatic interactions of DNNs trained on massive sequence spaces—a computational problem that takes years to solve without leveraging the epistatic sparsity in the fitness functions.
Overall patient’s survival of glioblastoma associated to molecular markers: a pan-proteomic prospective study
Authors: Drelich Lauranne , Duhamel Marie , Wisztorski Maxence , Aboulouard Soulaimane , Gimeno Jean-Pascal , Caux Pierre-Damien , Ogrinc Nina , Devos Patrick , Cardon Tristan , Weller Michael , Escande Fabienne , Zairi Fahed , Maurage Claude-Alain , Fournier Isabelle , Le Rhun Emilie , Salzet Michel 
Published: November 2020

SUMMARYMolecular heterogeneities are a key feature of glioblastoma (GBM) pathology impeding patient’s stratification and leading to high discrepancies between patients mean survivals. Here, we established a molecular classification of GBM tumors using a pan-proteomic analysis. Then, we identified, from our proteomic data, 2 clusters of biomarkers associated with good or bad patient survival from 46 IDH wild-type GBMs. Three molecular groups have been identified and associated with systemic biology analyses. Group A tumors exhibit neurogenesis characteristics and tumorigenesis. Group B shows a strong immune cell signature and express poor prognosis markers while group C tumors are characterized by an anti-viral signature and tumor growth proteins. 124 proteins were found statistically different based on patient’s survival times, of which 10 are issued from alternative AltORF or non-coding RNA. After statistical analysis, a panel of markers associated to higher survival (PPP1R12A, RPS14, HSPD1 and LASP1) and another panel associated to lower survival (ALCAM, ANXA11, MAOB, IP_652563 and IGHM) has been validated by immunofluorescence. Taken together, our data will guide GBM prognosis and help to improve the current GBM classification by stratifying the patients and may open new opportunities for therapeutic development.SignificanceGlioblastoma are very heterogeneous tumors with median survivals usually inferior to 20 months. We conducted a pan-proteomics analysis of glioblastoma (GBM) in order to stratify GBM based on the molecular contained. Forty-six GBM cases were classified into three groups where proteins are involved in specific pathwaysi.e.the first group has a neurogenesis signature and is associated with a better prognosis while the second group of patients has an immune profile with a bad prognosis. The third group is more associated to tumorigenesis. We correlated these results with the TCGA data. Finally, we have identified 28 new prognostic markers of GBM and from these 28, a panel of 4 higher and 5 lower survival markers were validated. With these 9 markers in hand, now pathologist can stratify GBM patients and can guide the therapeutic decision.HighlightsA novel stratification of glioblastoma based on mass spectrometry was established.Three groups with different molecular features and survival were identified.This new classification could improve prognostication and may help therapeutic options.8 prognosis markers for oncologist therapeutic decision have been validated.
RpoS Contributes to Successful Opportunistic Colonization by Human Enteric Pathogens during Plant Disease
Authors: Lovelace Amelia H. , Lee Sangwook , Downs Diana M. , Soufi Ziad , Bota Pedro , Preston Gail M. , Kvitko Brian H. 
Published: November 2020

AbstractWith an increase in foodborne illnesses associated with the consumption of fresh produce, it is important to understand the interactions between human bacterial enteric pathogens and plants. It was previously established that diseased plants can create a permissive environment for opportunistic endophytic colonization of enteric pathogens. However, the factors that contribute to the colonization of enteric pathogens during plant disease are largely unknown. Here, we show that both strain and plant host factors contribute to significantly increased populations of enteric pathogens when co-inoculated with the plant pathogen,P. syringaepv.tomato. The twoSalmonella entericastrains DM10000 and 14028S, differ in their ability to metabolize host-derived apoplastic carbohydrates dependent on the sigma factor RpoS. TherpoSgene is an important strain factor for endophytic colonization byS. entericaduring plant disease. Our results suggest thatrpoSplays a crucial role duringin plantacolonization, balancing nutrient metabolism and stress responses.ImportanceFoodborne illnesses caused by the bacterial human enteric pathogens,E. coliO157:H7 andS. enterica, often results in vomiting and diarrhea. If left untreated, this illness can cause dehydration and sometimes death of a patient. BothE. coliO157:H7 andS. entericahave caused repeated fresh produce-associated epidemics. Crop disease could promote the ability of plants to act as reservoirs for produce-borne outbreaks. Plant pathogens dampen plant immunity, which allows for a more permissive environment for human enteric pathogens to grow. These internalized enteric pathogen populations are especially dangerous since they cannot be removed by washing alone. Therefore, the need to understand the factors that contribute to the opportunistic colonization of human enteric pathogens during plant disease is apparent. Our research has identified host and strain factors that contribute to opportunistic colonization of diseased plants, which will inform the development of future management strategies to mitigate future outbreaks.
Bacterial community associated with the dry-rot fungusSerpula lacrymansis dominated by Firmicutes and Proteobacteria
Authors: Embacher Julia , Neuhauser Sigrid , Zeilinger Susanne , Kirchmair Martin 
Published: November 2020

AbstractThe dry-rot fungusSerpula lacrymanscauses enormous structural damage by decaying construction timber thereby resulting in tremendous financial loss. Dry-rot fungi decompose cellulose and hemicellulose and, if the wood remains wet, are often accompanied by a succession of bacteria and other fungi. Bacterial-fungal interactions have considerable impact on all interaction partners ranging from antagonistic to beneficial relationships. However, little is known about possible interaction partners ofS. lacrymans. Here we show thatS. lacrymanshas many co-existing, mainly Gram-positive bacteria. By investigating differences in the bacterial community associated with fruiting bodies, mycelia and rhizomorphs, we provide evidence of preferential colonization ofS. lacrymanstissues by certain bacterial phyla. Bacteria isolated from fruiting bodies and mycelia were dominated by Firmicutes, while bacteria isolated from rhizomorphs were dominated by Proteobacteria. Actinobacteria and Bacteroidetes were found in lower abundances.In situfluorescence hybridization (FISH) analysis revealed that bacteria were not present biofilm-like, but occurred as independent cells, sometimes also attached to fungal spores. In co-culture, single bacterial isolates caused growth inhibition ofS. lacrymansand vice versa. Additionally, certain bacteria induced pigment production in the fungus. Our results provide first insights for a better understanding of the holobiontS. lacrymansand give hints that bacteria are able to influence the behavior, e.g. growth and secondary metabolite production, ofS. lacrymansin culture.ImportanceSerpula lacrymansis a very effective dry-rot causing fungus, specialized in degradation of coniferous timber in houses. The initial colonization is favored by water damage, and after establishment, the fungus starts to destruct cellulose and hemicellulose. It is among the most feared wood-rotting fungi in the built environment as the remediation ofS. lacrymansdamaged buildings is expensive and tedious. After improper renovation, the possibility of a recolonization byS. lacrymansis likely. As bacteria influence fungal establishment on wood, the need to investigate the bacterial community associated withS. lacrymansis apparent. The significance of our research is in identifying and characterizing bacteria associated withS. lacrymans.This will allow the assessment of their influence on fungal life style, leading to a broader understanding of the properties that makeS. lacrymansso extraordinarily aggressive at decaying wood compared to other indoor wood destroyers.
Saccharomyces cerevisiaeRequiresCFF1to Produce 4-hydroxy-5-methylfuran-3(2H)-one, a Mimic of the Bacterial Quorum-Sensing Autoinducer AI-2
Authors: Valastyan Julie S. , Kraml Christina M. , Pelczer Istvan , Ferrante Thomas , Bassler Bonnie L. 
Published: November 2020

AbstractQuorum sensing is a process of cell-to-cell communication that bacteria use to orchestrate collective behaviors. Quorum sensing depends on the production, release, and detection of extracellular signal molecules called autoinducers (AIs) that accumulate with increasing cell density. While most AIs are species-specific, the AI called AI-2 is produced and detected by diverse bacterial species and it mediates inter-species communication. We recently reported that mammalian cells produce an AI-2 mimic that can be detected by bacteria through the AI-2 receptor, LuxP, potentially expanding the role of the AI-2 system to inter-domain communication. Here, we describe a second molecule capable of inter-domain signaling through LuxP, 4-hydroxy-5-methylfuran-3(2H)-one (MHF) that is produced by the yeastSaccharomyces cerevisiae. Screening theS. cerevisiaedeletion collection revealed Cff1p, a protein with no known role, to be required for MHF production. Cff1p is proposed to be an enzyme, possibly an epimerase or isomerase, and substitution at the putative catalytic residue eliminated MHF production inS. cerevisiae. Sequence analysis uncovered Cff1p homologs in many species, primarily bacterial and fungal, but also viral, archaeal, and higher eukaryotic. Cff1p homologs from organisms from all domains can complement aS. cerevisiae cff1Δmutant and restore MHF production. In all test cases, the identified catalytic residue is conserved and required for MHF to be produced. These findings increase the scope of possibilities for inter-domain interactions via AI-2 and AI-2 mimics, highlighting the breadth of molecules and organisms that could participate in quorum sensing.ImportanceQuorum sensing is a cell-to-cell communication process that bacteria use to monitor local population density. Quorum sensing relies on extracellular signal molecules called autoinducers (AIs). One AI, called AI-2, is broadly made by bacteria and used for inter-species communication. Here, we describe a eukaryotic AI-2 mimic, 5-methylfuran-3(2H)-one, (MHF), that is made by the yeastSaccharomyces cerevisiae, and we identify the Cff1p protein as essential for MHF production. Hundreds of viral, archaeal, bacterial, and eukaryotic organisms possess Cff1p homologs. This finding, combined with our results showing that homologs from all domains can replaceS. cerevisiaeCff1p, suggests that like AI-2, MHF is widely produced. Our results expand the breadth of organisms that may participate in quorum-sensing-mediated interactions.
Network mapping of root-microbe interactions inArabidopsis thaliana
Authors: He Xiaoqing , Zhang Qi , Jin Yi , Jiang Libo , Wu Rongling 
Published: November 2020

AbstractUnderstanding how plants interact with their colonizing microbiota to determine plant phenotypes is a fundamental question in modern plant science. Existing approaches for genome-wide association studies (GWAS) are based on the association analysis between host genes and the abundance of individual microbes, failing to characterize the genetic architecture of microbial interactions that are thought to a determinant of microbiota structure, organization, and function. Here, we implement a behavioral model to quantify various patterns of microbe-microbe interactions, i.e., mutualism, antagonism, aggression, and altruism, and map host genes that modulate microbial networks constituted by these interaction types. We reanalyze a root-microbiome data involving 179 accessions ofArabidopsis thalianaand find that the four networks differ structurally in the pattern of bacterial-fungal interactions and microbiome complexity. We identify several fungus and bacterial hubs that play a central role in mediating microbial community assembly surroundingA. thalianaroot systems. We detect 1142 significant host genetic variants throughout the plant genome and then implement Bayesian networks (BN) to reconstruct epistatic networks involving all significant SNPs and find 91 hub QTLs. Gene annotation shows that a number of the hub genes detected are biologically relevant, playing roles in plant growth and development, resilience against pathogens, root development, and improving resistance against abiotic stress conditions. The new model allows us to better understand the underlying mechanisms that govern the relationships between plants and their entire microbiota and harness soil microbes for plant production.
Genomic investigation of a dengue virus outbreak in Thiès, Senegal, in 2018
Authors: Gaye Amy , Ndiaye Tolla , Sy Mouhamad , Deme Awa B. , Thiaw Alphonse B. , Sene Aita , Ndiaye Cheikh , Diedhiou Younouss , Mbaye Amadou M. , Ndiaye Ibrahima , Tomkins-Tinch Christopher , Gomis Jules F. , Badiane Aida S. , MacInnis Bronwyn , Park Daniel J. , Ndiaye Mouhamadou , Sy Ngayo , Sabeti Pardis C. , Siddle Katherine J. , Ndiaye Daouda 
Published: November 2020

AbstractDengue virus is a major and rapidly growing public health concern in tropic and subtropic regions across the globe. In late 2018, Senegal experienced its largest dengue virus outbreak to date, covering several regions. However, little is known about the genetic diversity of dengue virus (DENV) in Senegal. Here we used molecular tools including metagenomic sequencing to identify 19 previously undetected dengue virus cases from the city of Thiès and assemble 17 complete virus genomes. DENV3 was the most frequent serotype; 11 sequences (65%) were DENV3, 4 sequences were DENV2 and 2 were DENV1. Sequences were closest to recent sequences from West Africa, suggesting ongoing local circulation of viral populations; however, detailed inference is limited by the scarcity of available genomic data. We did not find clear associations with reported clinical signs or symptoms, highlighting the importance of testing for diagnosing febrile diseases. Overall, these findings expand the known range of DENV in Senegal, and underscore the need for better genomic characterization of DENV in West Africa.
Systematic evaluation of transcriptomic disease risk and diagnostic biomarker overlap between COVID-19 and tuberculosis: a patient-level meta-analysis
Authors: Sheerin Dylan , Abhimanyu  , Wang Xutao , Johnson W Evan , Coussens Anna 
Published: November 2020

AbstractBackgroundThe novel coronavirus, SARS-CoV-2, has increased the burden on healthcare systems already strained by a high incidence of tuberculosis (TB) as co-infection and dual presentation are occurring in syndemic settings. We aimed to understand the interaction between these diseases by profiling COVID-19 gene expression signatures on RNA-sequencing data from TB-infected individuals.MethodsWe performed a systematic review and patient-level meta-analysis by querying PubMed and pre-print servers to derive eligible COVID-19 gene expression signatures from human whole blood (WB), PBMCs or BALF studies. A WB influenza dataset served as a control respiratory disease signature. Three large TB RNA-seq datasets, comprising multiple cohorts from the UK and Africa and consisting of TB patients across the disease spectrum, were chosen to profile these signatures. Putative “COVID-19 risk scores” were generated for each sample in the TB datasets using the TBSignatureProfiler package. Risk was stratified by time to TB diagnosis in progressors and contacts of pulmonary and extra-pulmonary TB. An integrative analysis between TB and COVID-19 single-cell RNA-seq data was performed and a population-level meta-analysis was conducted to identify shared gene ontologies between the diseases and their relative enrichment in COVID-19 disease severity states.Results35 COVID-19 gene signatures from nine eligible studies comprising 98 samples were profiled on TB RNA-seq data from 1181 samples from 853 individuals. 25 signatures had significantly higher COVID-19 risk in active TB (ATB) compared with latent TB infection (p <0·005), 13 of which were validated in two independent datasets.FCN1- andSPP1-expressing macrophages enriched in BALF during severe COVID-19 were identified in circulation during ATB. Shared perturbed ontologies included antigen presentation, epigenetic regulation, platelet activation, and ROS/RNS production were enriched with increasing COVID-19 severity. Finally, we demonstrate that the overlapping transcriptional responses may complicate development of blood-based diagnostic signatures of co-infection.InterpretationOur results identify shared dysregulation of immune responses in COVID-19 and TB as a dual risk posed by co-infection to COVID-19 severity and TB disease progression. These individuals should be followed up for TB in the months subsequent to SARS-CoV-2 diagnosis.
Diabetes and Mortality Among 1.6 Million Adult Patients Screened for SARS-CoV-2 in Mexico
Authors: Woolcott Orison O. , Castilla-Bancayán Juan P. 
Published: November 2020

ABSTRACTBackgroundWhether diabetes is associated with COVID-19-related mortality remains unclear.MethodsIn this retrospective case-series study we examined the risk of death associated with self-reported diabetes in symptomatic adult patients with laboratory-confirmed COVID-19 who were identified through the System of Epidemiological Surveillance of Viral Respiratory Disease in Mexico from January 1 through November 4, 2020. Survival time was right-censored at 28 days of follow-up.ResultsAmong 757,210 patients with COVID-19 included in the study, 120,476 (16%) had diabetes and 80,616 died. Patients with diabetes had a 49% higher relative risk of death than those without diabetes (Cox proportional-hazard ratio; 1.49 (95% confidence interval [CI], 1.47-1.52), adjusting for age, sex, smoking habit, obesity, hypertension, immunodeficiency, and cardiovascular, pulmonary, and chronic renal disease. The relative risk of death associated with diabetes decreased with age (P=0.004). The hazard ratios were 1.66 (1.58-1.74) in outpatients and 1.14 (1.12-1.16) in hospitalized patients. The 28-day survival for inpatients with and without diabetes was, respectively, 73.5% and 85.2% for patients 20-39 years of age; 66.6% and 75.9% for patients 40-49 years of age; 59.4% and 66.5% for patients 50-59 years of age; 50.1% and 54.6% for patients 60-69 years of age; 42.7% and 44.6% for patients 70-79 years of age; and 38.4% and 39.0% for patients 80 years of age or older. In patients without COVID-19 (878,840), the adjusted hazard ratio for mortality was 1.78 (1.73-1.84).ConclusionIn symptomatic adult patients with COVID-19 in Mexico, diabetes was associated with higher mortality. This association decreased with age.
Structural basis for the association of PLEKHA7 with membrane-embedded phosphatidylinositol lipids
Authors: Aleshin Alexander E. , Yao Yong , Iftikhar Amer , Bobkov Andrey A. , Yu Jinghua , Cadwell Gregory , Klein Michael G. , Dong Chuqiao , Bankston Laurie A. , Liddington Robert C. , Im Wonpil , Powis Garth , Marassi Francesca M. 
Published: November 2020

SummaryPLEKHA7 (pleckstrin homology domain containing family A member 7) plays key roles in intracellular signaling, cytoskeletal organization and cell adhesion, and is associated with multiple human cancers. The interactions of its pleckstrin homology (PH) domain with membrane phosphatidyl-inositol-phosphate (PIP) lipids, are critical for proper cellular localization and function, and their inhibition is an attractive target for anti-cancer therapy. While structural data can provide insights in this area, little is known about the way in which PLEKHA7 and other PH domains interact with membrane-embedded PIPs. Here we report atomic-resolution structures of the PLEHA7 PH domain and describe the molecular mechanism for its recognition of membrane-bound PIPs. Using X-ray crystallography, nuclear magnetic resonance (NMR), molecular dynamics (MD) simulations, and isothermal titration calorimetry (ITC), we show – in atomic-level detail – that the interaction of PLEKHA7 with PIPs is multivalent and induces PIP clustering. The PIP binding mechanism is distinct from a discrete one-to-one interaction. Our findings reveal a central role of the membrane assembly in mediating protein-PIP association and provide a roadmap for the design of PLEKHA7-PIP inhibitors.
Inactivation of SARS-CoV-2 on surfaces and in solution with Virusend (TX-10), a novel disinfectant
Authors: Anderson Enyia R. , Hughes Grant L. , Patterson Edward I. 
Published: November 2020

AbstractUntil an effective vaccine against SARS-CoV-2 is available on a widespread scale, the control of the COVID-19 pandemic is reliant upon effective pandemic control measures. The ability of SARS-CoV-2 to remain viable on surfaces and in aerosols, means indirect contact transmission can occur and so there is an opportunity to reduce transmission using effective disinfectants in public and communal spaces. Virusend (TX-10), a novel disinfectant, has been developed as a highly effective disinfectant against a range of microbial agents. Here we investigate the ability of Virusend (TX-10) to inactivation SARS-CoV-2. Using surface and solution inactivation assays, we show that Virusend (TX-10) is able to reduce SARS-CoV-2 viral titre by 4log10PFU/mL within 1 minute of contact. Ensuring disinfectants are highly effective against SARS-CoV-2 is important in eliminating environmental sources of the virus to control the COVID-19 pandemic.