scholarly journals Promotech: A general tool for bacterial promoter recognition

2021 ◽  
Author(s):  
Ruben Chevez-Guardado ◽  
Lourdes Pena-Castillo
Keyword(s):  
Bacterial Species ◽  
Prediction Methods ◽  
Promoter Prediction ◽  
Computational Tools ◽  
Wide Range ◽  
Promoter Recognition ◽  
Precision Recall Curve ◽  
Genomic Regions ◽  
General Tool ◽  
Recall Curve

Promoters are genomic regions where the transcription machinery binds to initiate the transcription of specific genes. Computational tools for identifying bacterial promoters have been around for decades. However, most of these tools were designed to recognize promoters in one or few bacterial species. Here, we present Promotech, a machine-learning-based method for promoter recognition in a wide range of bacterial species. We compared Promotech's performance with the performance of five other promoter prediction methods. Promotech outperformed these other programs in terms of area under the precision-recall curve (AUPRC) or precision at the same level of recall. Promotech is available at https://github.com/BioinformaticsLabAtMUN/PromoTech.

scholarly journals Promotech: a general tool for bacterial promoter recognition

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruben Chevez-Guardado ◽  
Lourdes Peña-Castillo
Keyword(s):  
Bacterial Species ◽  
Prediction Methods ◽  
Promoter Prediction ◽  
Computational Tools ◽  
Wide Range ◽  
Promoter Recognition ◽  
Precision Recall Curve ◽  
Genomic Regions ◽  
General Tool ◽  
Recall Curve

AbstractPromoters are genomic regions where the transcription machinery binds to initiate the transcription of specific genes. Computational tools for identifying bacterial promoters have been around for decades. However, most of these tools were designed to recognize promoters in one or few bacterial species. Here, we present Promotech, a machine-learning-based method for promoter recognition in a wide range of bacterial species. We compare Promotech’s performance with the performance of five other promoter prediction methods. Promotech outperforms these other programs in terms of area under the precision-recall curve (AUPRC) or precision at the same level of recall. Promotech is available at https://github.com/BioinformaticsLabAtMUN/PromoTech.

scholarly journals Benchmark of computational methods for predicting microRNA-disease associations

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Zhou Huang ◽  
Leibo Liu ◽  
Yuanxu Gao ◽  
Jiangcheng Shi ◽  
Qinghua Cui ◽  
...  
Keyword(s):  
Performance Improvement ◽  
Disease Association ◽  
Prediction Methods ◽  
Similarity Matrix ◽  
Future Directions ◽  
Novel Mirna ◽  
Disease Associations ◽  
Precision Recall Curve ◽  
Single Predictor ◽  
Recall Curve

Abstract Background A series of miRNA-disease association prediction methods have been proposed to prioritize potential disease-associated miRNAs. Independent benchmarking of these methods is warranted to assess their effectiveness and robustness. Results Based on more than 8000 novel miRNA-disease associations from the latest HMDD v3.1 database, we perform systematic comparison among 36 readily available prediction methods. Their overall performances are evaluated with rigorous precision-recall curve analysis, where 13 methods show acceptable accuracy (AUPRC > 0.200) while the top two methods achieve a promising AUPRC over 0.300, and most of these methods are also highly ranked when considering only the causal miRNA-disease associations as the positive samples. The potential of performance improvement is demonstrated by combining different predictors or adopting a more updated miRNA similarity matrix, which would result in up to 16% and 46% of AUPRC augmentations compared to the best single predictor and the predictors using the previous similarity matrix, respectively. Our analysis suggests a common issue of the available methods, which is that the prediction results are severely biased toward well-annotated diseases with many associated miRNAs known and cannot further stratify the positive samples by discriminating the causal miRNA-disease associations from the general miRNA-disease associations. Conclusion Our benchmarking results not only provide a reference for biomedical researchers to choose appropriate miRNA-disease association predictors for their purpose, but also suggest the future directions for the development of more robust miRNA-disease association predictors.

scholarly journals A relationship between the incremental values of area under the ROC curve and of area under the precision-recall curve

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Qian M. Zhou ◽  
Lu Zhe ◽  
Russell J. Brooke ◽  
Melissa M. Hudson ◽  
Yan Yuan
Keyword(s):  
Prediction Accuracy ◽  
Risk Model ◽  
Event Rate ◽  
Numerical Study ◽  
Superior Performance ◽  
New Model ◽  
Wide Range ◽  
Precision Recall Curve ◽  
Dose Model ◽  
Recall Curve

Abstract Background Incremental value (IncV) evaluates the performance change between an existing risk model and a new model. Different IncV metrics do not always agree with each other. For example, compared with a prescribed-dose model, an ovarian-dose model for predicting acute ovarian failure has a slightly lower area under the receiver operating characteristic curve (AUC) but increases the area under the precision-recall curve (AP) by 48%. This phenomenon of disagreement is not uncommon, and can create confusion when assessing whether the added information improves the model prediction accuracy. Methods In this article, we examine the analytical connections and differences between the AUC IncV (ΔAUC) and AP IncV (ΔAP). We also compare the true values of these two IncV metrics in a numerical study. Additionally, as both are semi-proper scoring rules, we compare them with a strictly proper scoring rule: the IncV of the scaled Brier score (ΔsBrS) in the numerical study. Results We demonstrate that ΔAUC and ΔAP are both weighted averages of the changes (from the existing model to the new one) in separating the risk score distributions between events and non-events. However, ΔAP assigns heavier weights to the changes in higher-risk regions, whereas ΔAUC weights the changes equally. Due to this difference, the two IncV metrics can disagree, and the numerical study shows that their disagreement becomes more pronounced as the event rate decreases. In the numerical study, we also find that ΔAP has a wide range, from negative to positive, but the range of ΔAUC is much smaller. In addition, ΔAP and ΔsBrS are highly consistent, but ΔAUC is negatively correlated with ΔsBrS and ΔAP when the event rate is low. Conclusions ΔAUC treats the wins and losses of a new risk model equally across different risk regions. When neither the existing or new model is the true model, this equality could attenuate a superior performance of the new model for a sub-region. In contrast, ΔAP accentuates the change in the prediction accuracy for higher-risk regions.

scholarly journals Trends in Molecular Diagnosis and Diversity Studies for Phytosanitary Regulated Xanthomonas

2021 ◽  
Vol 9 (4) ◽  
pp. 862
Author(s):  
Vittoria Catara ◽  
Jaime Cubero ◽  
Joël F. Pothier ◽  
Eran Bosis ◽  
Claude Bragard ◽  
...  
Keyword(s):  
Molecular Diagnosis ◽  
Bacterial Species ◽  
Management Strategies ◽  
Diagnostic Methods ◽  
Plant Diseases ◽  
Wild Plants ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Wide Range ◽  
Diversity Studies

Bacteria in the genus Xanthomonas infect a wide range of crops and wild plants, with most species responsible for plant diseases that have a global economic and environmental impact on the seed, plant, and food trade. Infections by Xanthomonas spp. cause a wide variety of non-specific symptoms, making their identification difficult. The coexistence of phylogenetically close strains, but drastically different in their phenotype, poses an added challenge to diagnosis. Data on future climate change scenarios predict an increase in the severity of epidemics and a geographical expansion of pathogens, increasing pressure on plant health services. In this context, the effectiveness of integrated disease management strategies strongly depends on the availability of rapid, sensitive, and specific diagnostic methods. The accumulation of genomic information in recent years has facilitated the identification of new DNA markers, a cornerstone for the development of more sensitive and specific methods. Nevertheless, the challenges that the taxonomic complexity of this genus represents in terms of diagnosis together with the fact that within the same bacterial species, groups of strains may interact with distinct host species demonstrate that there is still a long way to go. In this review, we describe and discuss the current molecular-based methods for the diagnosis and detection of regulated Xanthomonas, taxonomic and diversity studies in Xanthomonas and genomic approaches for molecular diagnosis.

scholarly journals Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Hannes Petruschke ◽  
Christian Schori ◽  
Sebastian Canzler ◽  
Sarah Riesbeck ◽  
Anja Poehlein ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Intestinal Microbiota ◽  
De Novo ◽  
Bacterial Species ◽  
Intestinal Microbiome ◽  
Single Strain ◽  
Small Proteins ◽  
Human Intestinal Microbiota ◽  
Wide Range

Abstract Background The intestinal microbiota plays a crucial role in protecting the host from pathogenic microbes, modulating immunity and regulating metabolic processes. We studied the simplified human intestinal microbiota (SIHUMIx) consisting of eight bacterial species with a particular focus on the discovery of novel small proteins with less than 100 amino acids (= sProteins), some of which may contribute to shape the simplified human intestinal microbiota. Although sProteins carry out a wide range of important functions, they are still often missed in genome annotations, and little is known about their structure and function in individual microbes and especially in microbial communities. Results We created a multi-species integrated proteogenomics search database (iPtgxDB) to enable a comprehensive identification of novel sProteins. Six of the eight SIHUMIx species, for which no complete genomes were available, were sequenced and de novo assembled. Several proteomics approaches including two earlier optimized sProtein enrichment strategies were applied to specifically increase the chances for novel sProtein discovery. The search of tandem mass spectrometry (MS/MS) data against the multi-species iPtgxDB enabled the identification of 31 novel sProteins, of which the expression of 30 was supported by metatranscriptomics data. Using synthetic peptides, we were able to validate the expression of 25 novel sProteins. The comparison of sProtein expression in each single strain versus a multi-species community cultivation showed that six of these sProteins were only identified in the SIHUMIx community indicating a potentially important role of sProteins in the organization of microbial communities. Two of these novel sProteins have a potential antimicrobial function. Metabolic modelling revealed that a third sProtein is located in a genomic region encoding several enzymes relevant for the community metabolism within SIHUMIx. Conclusions We outline an integrated experimental and bioinformatics workflow for the discovery of novel sProteins in a simplified intestinal model system that can be generically applied to other microbial communities. The further analysis of novel sProteins uniquely expressed in the SIHUMIx multi-species community is expected to enable new insights into the role of sProteins on the functionality of bacterial communities such as those of the human intestinal tract.

scholarly journals SCAPP: an algorithm for improved plasmid assembly in metagenomes

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
David Pellow ◽  
Alvah Zorea ◽  
Maraike Probst ◽  
Ori Furman ◽  
Arik Segal ◽  
...  
Keyword(s):  
Bacterial Species ◽  
Bacterial Genome ◽  
Biological Knowledge ◽  
Assessment Procedure ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Human Gut ◽  
Double Stranded Dna ◽  
Wide Range ◽  
Python Package

Abstract Background Metagenomic sequencing has led to the identification and assembly of many new bacterial genome sequences. These bacteria often contain plasmids: usually small, circular double-stranded DNA molecules that may transfer across bacterial species and confer antibiotic resistance. These plasmids are generally less studied and understood than their bacterial hosts. Part of the reason for this is insufficient computational tools enabling the analysis of plasmids in metagenomic samples. Results We developed SCAPP (Sequence Contents-Aware Plasmid Peeler)—an algorithm and tool to assemble plasmid sequences from metagenomic sequencing. SCAPP builds on some key ideas from the Recycler algorithm while improving plasmid assemblies by integrating biological knowledge about plasmids. We compared the performance of SCAPP to Recycler and metaplasmidSPAdes on simulated metagenomes, real human gut microbiome samples, and a human gut plasmidome dataset that we generated. We also created plasmidome and metagenome data from the same cow rumen sample and used the parallel sequencing data to create a novel assessment procedure. Overall, SCAPP outperformed Recycler and metaplasmidSPAdes across this wide range of datasets. Conclusions SCAPP is an easy to use Python package that enables the assembly of full plasmid sequences from metagenomic samples. It outperformed existing metagenomic plasmid assemblers in most cases and assembled novel and clinically relevant plasmids in samples we generated such as a human gut plasmidome. SCAPP is open-source software available from: https://github.com/Shamir-Lab/SCAPP.

scholarly journals Genome-Wide Identification of Resveratrol Intrinsic Resistance Determinants in Staphylococcus aureus

Antibiotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 82
Author(s):  
Liping Liu ◽  
Hanne Ingmer ◽  
Martin Vestergaard
Keyword(s):  
Staphylococcus Aureus ◽  
Stress Response ◽  
Inhibitory Activity ◽  
Bacterial Species ◽  
Dna Integrity ◽  
Intrinsic Resistance ◽  
Potential Health ◽  
Cellular Effects ◽  
Development Of Resistance ◽  
Wide Range

Resveratrol has been extensively studied due to its potential health benefits in multiple diseases, for example, cancer, obesity and cardiovascular diseases. Besides these properties, resveratrol displays inhibitory activity against a wide range of bacterial species; however, the cellular effects of resveratrol in bacteria remain incompletely understood, especially in the human pathogen, Staphylococcus aureus. In this study, we aimed to identify intrinsic resistance genes that aid S. aureus in tolerating the activity of resveratrol. We screened the Nebraska Transposon Mutant Library, consisting of 1920 mutants with inactivation of non-essential genes in S. aureus JE2, for increased susceptibly to resveratrol. On agar plates containing 0.5× the minimum inhibitory concentration (MIC), 17 transposon mutants failed to grow. Of these, four mutants showed a two-fold reduction in MIC, being the clpP protease mutant and three mutants with deficiencies in the electron transport chain (menD, hemB, aroC). The remaining 13 mutants did not show a reduction in MIC, but were confirmed by spot-assays to have increased susceptibility to resveratrol. Several genes were associated with DNA damage repair (recJ, xerC and xseA). Treatment of S. aureus JE2 with sub-inhibitory concentrations of resveratrol did not affect the expression of recJ, xerC and xseA, but increased expression of the SOS–stress response genes lexA and recA, suggesting that resveratrol interferes with DNA integrity in S. aureus. Expression of error-prone DNA polymerases are part of the SOS–stress response and we could show that sub-inhibitory concentrations of resveratrol increased overall mutation frequency as measured by formation of rifampicin resistant mutants. Our data show that DNA repair systems are important determinants aiding S. aureus to overcome the inhibitory activity of resveratrol. Activation of the SOS response by resveratrol could potentially facilitate the development of resistance towards conventional antibiotics in S. aureus.

Effect of Silver Ions on the Structural and Antibacterial Properties of Bone Replacement Material

2013 ◽  
Vol 795 ◽  
pp. 692-696 ◽  
Author(s):  
Nida Iqbal ◽  
Mohammed Rafiq Abdul Kadir ◽  
Nasrul Humaimi Bin Mahmood ◽  
Micheal Moses ◽  
Mashitah Binti Mad Salim ◽  
...  
Keyword(s):  
Calcium Phosphates ◽  
Bacterial Species ◽  
Calcium Nitrate ◽  
Antibacterial Properties ◽  
Silver Ions ◽  
Antibacterial Activities ◽  
Silver Addition ◽  
Wide Range ◽  
Microbial Infections ◽  
Inorganic Mineral

Antibacterial materials based on calcium phosphates have wide range of biomedical applications in the prevention of microbial infections. The synthesis of inorganic mineral component of bone i.e. hydroxyapatite was done with the addition of silver (Ag) (5-15 wt %) as antibacterial agent. The wet precipitation synthesis was carried out using diammonium hydrogen phosphate and calcium nitrate as P and Ca precursors. The presence and effect of silver addition on the structure was studied using Fourier Transform-Infrared (FTIR) spectroscopy and Energy Dispersive X-ray (EDX) techniques. The antibacterial properties of all samples were evaluated using Disc Diffusion Technique (DDT) againstS. aureus,B. subtilis, P. aeruginosaandE. coli. Antibacterial activities of samples were found to vary depending on the bacterial species and Ag loading percentage. The antibacterial assay suggested that the addition of Ag ions within hydroxyapatite can be effectively provided the required level of antibacterial activity against bacteria.

scholarly journals Role of CxxC-finger protein 1 in establishing mouse oocyte epigenetic landscapes

2021 ◽  
Author(s):  
Qian-Qian Sha ◽  
Ye-Zhang Zhu ◽  
Yunlong Xiang ◽  
Jia-Li Yu ◽  
Xiao-Ying Fan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Histone H3 ◽  
Finger Protein ◽  
Maternal Genome ◽  
Wide Range ◽  
Transcriptional Changes ◽  
Nuclear Events ◽  
Genomic Regions ◽  
Cxxc Finger Protein 1

Abstract During oogenesis, oocytes gain competence and subsequently undergo meiotic maturation and prepare for embryonic development; trimethylated histone H3 on lysine-4 (H3K4me3) mediates a wide range of nuclear events during these processes. Oocyte-specific knockout of CxxC-finger protein 1 (CXXC1, also known as CFP1) impairs H3K4me3 accumulation and causes changes in chromatin configurations. This study investigated the changes in genomic H3K4me3 landscapes in oocytes with Cxxc1 knockout and the effects on other epigenetic factors such as the DNA methylation, H3K27me3, H2AK119ub1 and H3K36me3. H3K4me3 is overall decreased after knocking out Cxxc1, including both the promoter region and the gene body. CXXC1 and MLL2, which is another histone H3 methyltransferase, have nonoverlapping roles in mediating H3K4 trimethylation during oogenesis. Cxxc1 deletion caused a decrease in DNA methylation levels and affected H3K27me3 and H2AK119ub1 distributions, particularly at regions with high DNA methylation levels. The changes in epigenetic networks implicated by Cxxc1 deletion were correlated with the transcriptional changes in genes in the corresponding genomic regions. This study elucidates the epigenetic changes underlying the phenotypes and molecular defects in oocytes with deleted Cxxc1 and highlights the role of CXXC1 in orchestrating multiple factors that are involved in establishing the appropriate epigenetic states of maternal genome.

Elucidating Protein-protein Interactions Through Computational Approaches and Designing Small Molecule Inhibitors Against them for Various Diseases

2018 ◽  
Vol 18 (20) ◽  
pp. 1719-1736 ◽  
Author(s):  
Sharanya Sarkar ◽  
Khushboo Gulati ◽  
Manikyaprabhu Kairamkonda ◽  
Amit Mishra ◽  
Krishna Mohan Poluri
Keyword(s):  
Small Molecule ◽  
Protein Interactions ◽  
Small Molecule Inhibitors ◽  
Computational Techniques ◽  
Protein Protein Interactions ◽  
Computational Tools ◽  
Computational Approaches ◽  
Protein Protein Interaction ◽  
Wide Range ◽  
Therapeutic Measures

Background: To carry out wide range of cellular functionalities, proteins often associate with one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and computational approaches were applied on PPIs in order to determine the interacting partners, and also to understand how an abnormality in such interactions can become the principle cause of a disease. Objective: This review aims to elucidate the case studies where PPIs involved in various human diseases have been proven or validated with computational techniques, and also to elucidate how small molecule inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against certain diseases. Results: Computational techniques to predict PPIs are emerging rapidly in the modern day. They not only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting the PPIs. Some of them are already being tested in the clinical trials. Conclusion: This review delineated the classification of computational tools that are essential to investigate PPIs. Furthermore, the review shed light on how indispensable computational tools have become in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently against dreadful diseases in a shorter time span.

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