Bioinformatics Tools Research Articles

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

Integrative Analysis of the DUF668 Gene Family in Nicotiana tabacum to Excavate Their Potential Roles in Abiotic Stress Responses

The domain of the unknown function (DUF) gene families assumes pivotal roles in plant metabolic and stress responses. However, our comprehension of the tobacco DUF668 (NtDUF668) gene family and its specific reactions to heavy metal, drought, and salt stresses remain circumscribed. In the current investigation, a comprehensive genome-wide analysis of the NtDUF668 gene family was undertaken utilizing bioinformatics tools. The results unveiled a total of 20 members in the NtDUF668 gene family, denominated NtDUF668-01 to NtDUF668-20. Phylogenetic analyses indicated a closer genetic relationship of DUF668 genes between Nicotiana tabacum and Ipomoea batatas. The examination of gene structure and conservative motifs revealed a bifurcation into two major Clades, aligning with previous studies on DUF668 gene families from various plant species, emphasizing its highly conserved evolutionary mechanism across plants. The exploration of promoter regions of NtDUF668 genes revealed a plethora of cis-acting elements associated with abiotic and biotic stresses, light signaling, and phytohormones. Gene duplication events and selection pressure analysis disclosed the segmental duplication and strong purifying selection pressure during the evolution of NtDUF668 genes. Syntenic analysis indicated a relatively conserved evolutionary mechanism of DUF668 gene families within dicotyledons. Tissue-specific expression analysis suggested that NtDUF668 family members are potentially involved in root development, floral organ formation, and abscission. The expression patterns and qRT–PCR analysis of NtDUF668 genes implied the potentially functional involvements of NtDUF668s in response to multiple abiotic stresses. Furthermore, the stress-triggered member NtDUF668-08 exhibited specific nuclear localization. In conclusion, this genome-wide analysis illuminates the composition, phylogenetic relationships, and potential roles of the NtDUF668 gene family in abiotic stress responses. The identified candidate genes, particularly NtDUF668-08, warrant further research for functional investigation.

Short Fragmented Peptides from Pardachirus Marmoratus Exhibit Stronger Anticancer Activities in In Silico Residue Replacement and Analyses.

Cancer is a worldwide issue. It has been observed that conventional therapies face many problems, such as side effects and drug resistance. Recent research reportedly used marine-derived products to treat various diseases and explored their potential in treating cancers. This study aims to discover short-length anticancer peptides derived from pardaxin 6 through an in silico approach. Fragmented peptides ranging from 5 to 15 amino acids were derived from the pardaxin 6 parental peptide. These peptides were further replaced with one residue and, along with the original fragmented peptides, were predicted for their SVM scores and physicochemical properties. The top 5 derivative peptides were further examined for their toxicity, hemolytic probability, peptide structures, docking models, and energy scores using various web servers. The trend of in silico analysis outputs across 5 to 15 amino acid fragments was further analyzed. Results showed that when the amino acids were increased, SVM scores of the original fragmented peptides were also increased. Designed peptides had increased SVM scores, which was aligned with previous studies where the single residue replacement transformed the non-anticancer peptide into an anticancer agent. Moreover, in vitro studies validated that the designed peptides retained or enhanced anticancer effects against different cancer cell lines. Interestingly, a decreasing trend was observed in those fragmented derivative peptides. Single residue replacement in fragmented pardaxin 6 was found to produce stronger anticancer agents through in silico predictions. Through bioinformatics tools, fragmented peptides improved the efficiency of marine-derived drugs with higher efficacy and lower hemolytic effects in treating cancers.

Determination of IL-6 Gene Promoter Polymorphism in Patients with Hepatitis C and Its Impact on RNA Secondary Structure.

Background and Objectives: A polymorphism in the promoter region of the IL-6 gene would influence the level of IL-6 expression in patients with HCV, resulting in a pro-inflammatory response. Few studies have shown the association between -174G>C (rs1800795) and -1363G>T (rs2069827) polymorphisms and HCV infection, and their results have been contradictory. There are no data published in our population to study such an IL-6 stimulus against HCV infection and its impact on RNA secondary structure. Therefore, we isolated human subjects from the province of Punjab, Pakistan. The objective was to screen for IL-6 gene promoter polymorphisms -174G/C and -1363G/T and those correlated with serum concentrations of IL-6 in patients with HCV and compared with a control. Materials and Methods: In conventional PCR, measurement of serum IL-6 by CLIA and statistical analysis were performed to observe the genotype association studies. By integrating bioinformatics and computational tools, our study aimed to provide a comprehensive understanding of how variations in the promoter region of IL-6 may have functional implications on gene expression. Results: The -174G>C and -1363G>T genotypes in the promoter region of patients with HCV were in strong allelic association (Δ = 0.97, p < 0.001). Interestingly, the bioinformatics analysis was well aligned with our experimental data. Conclusions: Based on the data, it can be inferred that IL-6 gene promoter polymorphisms are important in the dysregulation of IL-6 levels in patients with HCV.

LncRNA-miRNA-mRNA network in kidney transcriptome of Labeo rohita under hypersaline environment

The present study describes the kidney transcriptome of Labeo rohita, a freshwater fish, exposed to gradually increased salinity concentrations (2, 4, 6 and 8ppt). A total of 10.25 Gbps data was generated, and a suite of bioinformatics tools, including FEELnc, CPC2 and BLASTn were employed for identification of long non-coding RNAs (lncRNAs) and micro RNAs (miRNAs). Our analysis revealed a total of 170, 118, 99, and 269 differentially expressed lncRNA and 120, 118, 99, and 124 differentially expressed miRNAs in 2, 4, 6 and 8 ppt treatment groups respectively. Two competing endogenous RNA (ceRNA) networks were constructed i.e. A* ceRNA network with up-regulated lncRNAs and mRNAs, down-regulated miRNAs; and B* ceRNA network vice versa. 2ppt group had 131 and 83 lncRNA-miRNA-mRNA pairs in A* and B* networks, respectively. 4ppt group featured 163 pairs in A* network and 191 in B* network, while the 6ppt had 103 and 105 pairs. 8ppt group included 192 and 174 pairs. These networks illuminate the intricate RNA interactions in freshwater fish to varying salinity conditions.

Whole-exome sequencing identifies ADGB as a novel causative gene for male infertility in humans: from motility to fertilization.

In male mice, adgb-knockout has been reported to cause male infertility with spermatogenesis defects involving flagella and acrosome. However, this remains unclear for humans. Sequencing studies were conducted in a research hospital on samples from three unrelated infertile men with severe asthenoteratozoospermia from Han Chinese families. Data were collected through rigorous in silico analysis. Sanger sequencing were performed to identify pathogenic mutations. Sperm cells from patients were characterized using electron microscopy and used to verify the pathogenicity of the genetic factors through functional assays. Intracytoplasmic sperm injections (ICSI) assays were performed in ADGB-affected males. Herein, in a cohort of 105 Han Chinese men with idiopathic asthenoteratozoospermia, we reported the identification of bi-allelic deleterious variants of ADGB in three infertile men from unrelated families using whole-exome sequencing. We found one homozygous frameshift ADGB variant (NM_024694.4: c.2801_2802del:p.K934Rfs*33), one homozygous missense ADGB variant (NM_024694.4: c.C3167T:p.T1056I), and one compound heterozygous ADGB variant (NM_024694.4: c.C3167T:p.T1056I; c.C3197T:p.A1066V). These variants were rare in general population and were predicted to be damaging by multiple bioinformatics tools. Further, the spermatozoa from patients harboring ADGB variants showed multiple acrosome and flagellum malformations under light and electron microscopy. Functional assays revealed the structural defects associated with dysregulation of ADGB and multiple spermatogenesis proteins. Notably, the fertilization success via ICSI treatment in all three patients, as well as the normal expression of PLCζ but CaM deficiency in the spermatozoa, suggesting that ICSI other than in vitro fertilization (IVF) is an optimal treatment for ADGB-deficient patients. Our findings provide new information for the molecular diagnosis of asthenoteratozoospermia and valuable reference for personalized genetic counselling and clinical treatment for these patients. The underlying risk of IVF failure behind sperm defects was highlighted.

Bioinformatics characterization of variants of uncertain significance in pediatric sensorineural hearing loss.

Rapid advancements in Next Generation Sequencing (NGS) and bioinformatics tools have allowed physicians to obtain genetic testing results in a more rapid, cost-effective, and comprehensive manner than ever before. Around 50% of pediatric sensorineural hearing loss (SNHL) cases are due to a genetic etiology, thus physicians regularly utilize targeted sequencing panels that identify variants in genes related to SNHL. These panels allow for early detection of pathogenic variants which allows physicians to provide anticipatory guidance to families. Molecular testing does not always reveal a clear etiology due to the presence of multigenic variants with varying classifications, including the presence of Variants of Uncertain Significance (VUS). This study aims to perform a preliminary bioinformatics characterization of patients with variants associated with Type II Usher Syndrome in the presence of other multigenic variants. We also provide an interpretation algorithm for physicians reviewing molecular results with medical geneticists. Review of records for multigenic and/or VUS results identified several potential subjects of interest. For the purposes of this study, two ADGRV1 compound heterozygotes met inclusion criteria. Sequencing, data processing, and variant calling (the process by which variants are identified from sequence data) was performed at Invitae (San Francisco CA). The preliminary analysis followed the recommendations outlined by the American College of Medical Genetics and Association for Molecular Pathology (ACMG-AMP) in 2015 and 2019. The present study utilizes computational analysis, predictive data, and population data as well as clinical information from chart review and publicly available information in the ClinVar database. Two subjects were identified as compound heterozygotes for variants in the gene ADGRV1. Subject 1's variants were predicted as deleterious, while Subject 2's variants were predicted as non-deleterious. These results were based on known information of the variants from ClinVar, multiple lines of computational data, population databases, as well as the clinical presentation. Early molecular diagnosis through NGS is ideal, as families are then able to access a wide range of resources that will ultimately support the child as their condition progresses. We recommend that physicians build strong relationships with medical geneticists and carefully review their interpretation before making recommendations to families, particularly when addressing the VUS. Reclassification efforts of VUS are supported by studies like ours that provide evidence of pathogenic or benign effects of variants.

Systematic Review and Meta-Analysis of Congenital Toxoplasmosis Diagnosis: Advances and Challenges.

To understand how congenital toxoplasmosis (CT) diagnosis has evolved over the years, we performed a systematic review and meta-analysis to summarize the kind of analysis that has been employed for CT diagnosis. PubMed and Lilacs databases were used in order to access the kind of analysis that has been employed for CT diagnosis in several samples. Our search combined the following combining terms: "congenital toxoplasmosis" or "gestational toxoplasmosis" and "diagnosis" and "blood," "serum," "amniotic fluid," "placenta," or "colostrum." We extracted data on true positive, true negative, false positive, and false negative to generate pooled sensitivity, specificity, and diagnostic odds ratio (DOR). Random-effects models using MetaDTA were used for analysis. Sixty-five articles were included in the study aiming for comparisons (75.4%), diagnosis performance (52.3%), diagnosis improvement (32.3%), or to distinguish acute/chronic infection phases (36.9%). Amniotic fluid (AF) and placenta were used in 36.9% and 10.8% of articles, respectively, targeting parasites and/or T. gondii DNA. Blood was used in 86% of articles for enzymatic assays. Colostrum was used in one article to search for antibodies. In meta-analysis, PCR in AF showed the best performance for CT diagnosis based on the highest summary sensitivity (85.1%) and specificity (99.7%) added to lower magnitude heterogeneity. Most of the assays being researched to diagnose CT are basically the same traditional approaches available for clinical purposes. The range in diagnostic performance and the challenges imposed by CT diagnosis indicate the need to better explore pregnancy samples in search of new possibilities for diagnostic tools. Exploring immunological markers and using bioinformatics tools and T. gondii recombinant antigens should address the research needed for a new generation of diagnostic tools to face these challenges.

Identification of trans-genus biomarkers for early diagnosis of intestinal schistosomiasis and progression of gut pathology in a mouse model using metabolomics.

Schistosomiasis is one of the most devastating human diseases worldwide. The disease is caused by six species of Schistosoma blood fluke; five of which cause intestinal granulomatous inflammation and bleeding. The current diagnostic method is inaccurate and delayed, hence, biomarker identification using metabolomics has been applied. However, previous studies only investigated infection caused by one Schistosoma spp., leaving a gap in the use of biomarkers for other species. No study focused on understanding the progression of intestinal disease. Therefore, we aimed to identify early gut biomarkers of infection with three Schistosoma spp. and progression of intestinal pathology. We infected 3 groups of mice, 3 mice each, with Schistosoma mansoni, Schistosoma japonicum or Schistosoma mekongi and collected their feces before and 1, 2, 4 and 8 weeks after infection. Metabolites in feces were extracted and identified using mass spectrometer-based metabolomics. Metabolites were annotated and analyzed with XCMS bioinformatics tool and Metaboanalyst platform. From >36,000 features in all conditions, multivariate analysis found a distinct pattern at each time point for all species. Pathway analysis reported alteration of several lipid metabolism pathways as infection progressed. Disturbance of the glycosaminoglycan degradation pathway was found with the presence of parasite eggs, indicating involvement of this pathway in disease progression. Biomarkers were discovered using a combination of variable importance for projection score cut-off and receiver operating characteristic curve analysis. Five molecules met our criteria and were present in all three species: 25-hydroxyvitamin D2, 1α-hydroxy-2β-(3-hydroxypropoxy) vitamin D3, Ganoderic acid Md, unidentified feature with m/z 455.3483, and unidentified feature with m/z 456.3516. These molecules were proposed as trans-genus biomarkers of early schistosomiasis. Our findings provide evidence for disease progression in intestinal schistosomiasis and potential biomarkers, which could be beneficial for early detection of this disease.

In silico Analysis of Structure and Function of Hypothetical Proteins in Salmonella typhimurium (SL1344)

Salmonella typhimurium strain SL1344(S.typhi) is a non typhoidal bacteria which may cause infection in human gastrointestinal tract, may cause abdominal pain, fever, diarrhea, and inflammation some times which may lead to the human death. A comparative study of hypothetical outer membrane proteins of Salmonella typhimurium strain SL1344 (S.typhi) was performed using bioinformatic tools. Bioinformatics is a source to analyse whole genomic sequence of a vast number of uncharacterized genes. Online databases like UniProt, String, Pfam and other tools were used. Thirteen uncharacterized and hypothetical protein present in outer membrane of the bacteria S.typhi were retrieved from UniProt and its structure and function were studied. In this study the cellular function, pathway of enzyme interaction, antibiotic resistance were analyzed. The structure of the protein as well the function of these proteins provides better understanding to perform molecular docking and identification of small molecule inhibitors.

Insights into dietary phytochemicals targeting Parkinson's disease key genes and pathways: A network pharmacology approach

Parkinson's disease (PD) is a complex neurological disease associated with the degeneration of dopaminergic neurons. Oxidative stress is a key player in instigating apoptosis in dopaminergic neurons. To improve the survival of neurons many dietary phytochemicals have gathered significant attention recently. Thus, the present study implements a comprehensive network pharmacology approach to unravel the mechanisms of action of dietary phytochemicals that benefit disease management. A literature search was performed to identify ligands (i.e., comprising dietary phytochemicals and Food and Drug Administration pre-approved PD drugs) in the PubMed database. Targets associated with selected ligands were extracted from the search tool for interactions of chemicals (STITCH) database. Then, the construction of a gene-gene interaction (GGI) network, analysis of hub-gene, functional and pathway enrichment, associated transcription factors, miRNAs, ligand-target interaction network, docking were performed using various bioinformatics tools together with molecular dynamics (MD) simulations. The database search resulted in 69 ligands and 144 unique targets. GGI and subsequent topological measures indicate histone acetyltransferase p300 (EP300), mitogen-activated protein kinase 1 (MAPK1) or extracellular signal-regulated kinase (ERK)2, and CREB-binding protein (CREBBP) as hub genes. Neurodegeneration, MAPK signaling, apoptosis, and zinc binding are key pathways and gene ontology terms. hsa-miR-5692a and SCNA gene-associated transcription factors interact with all the 3 hub genes. Ligand-target interaction (LTI) network analysis suggest rasagiline and baicalein as candidate ligands targeting MAPK1. Rasagiline and baicalein form stable complexes with the Y205, K330, and V173 residues of MAPK1. Computational molecular insights suggest that baicalein and rasagiline are promising preclinical candidates for PD management.

Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine

BackgroundHigh tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests.ResultsFFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm.Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as “true TMB high.” Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10–3927] versus 8.2 mut/Mb [2.5–897], p < 0.001).ConclusionsWe herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.

Flu-CED: A comparative transcriptomics database of influenza virus-infected human and animal models.

The continuing emergence of influenza virus has highlighted the value of public databases and related bioinformatic analysis tools in investigating transcriptomic change caused by different influenza virus infections in human and animal models. We collected a large amount of transcriptome research data related to influenza virus-infected human and animal models in public databases (GEO and ArrayExpress), and extracted and integrated array and metadata. The gene expression matrix was generated through strictly quality control, balance, standardization, batch correction, and gene annotation. We then analyzed gene expression in different species, virus, cells/tissues or after antibody/vaccine treatment and imported sample metadata and gene expression datasets into the database. Overall, maintaining careful processing and quality control, we collected 8064 samples from 103 independent datasets, and constructed a comparative transcriptomics database of influenza virus named the Flu-CED database (Influenza comparative expression database, https://flu.com-med.org.cn/). Using integrated and processed transcriptomic data, we established a user-friendly website for realizing the integration, online retrieval, visualization, and exploration of gene expression of influenza virus infection in different species and the biological functions involved in differential genes. Flu-CED can quickly query single and multi-gene expression profiles, combining different experimental conditions for comparative transcriptome analysis, identifying differentially expressed genes (DEGs) between comparison groups, and conveniently finding DEGs. Flu-CED provides data resources and tools for analyzing gene expression in human and animal models infected with influenza virus that can deepen our understanding of the mechanisms underlying disease occurrence and development, and enable prediction of key genes or therapeutic targets that can be used for medical research.

PlasmidEC and gplas2: an optimized short-read approach to predict and reconstruct antibiotic resistance plasmids in Escherichia coli.

Accurate reconstruction of Escherichia coli antibiotic resistance gene (ARG) plasmids from Illumina sequencing data has proven to be a challenge with current bioinformatic tools. In this work, we present an improved method to reconstruct E. coli plasmids using short reads. We developed plasmidEC, an ensemble classifier that identifies plasmid-derived contigs by combining the output of three different binary classification tools. We showed that plasmidEC is especially suited to classify contigs derived from ARG plasmids with a high recall of 0.941. Additionally, we optimized gplas, a graph-based tool that bins plasmid-predicted contigs into distinct plasmid predictions. Gplas2 is more effective at recovering plasmids with large sequencing coverage variations and can be combined with the output of any binary classifier. The combination of plasmidEC with gplas2 showed a high completeness (median=0.818) and F1-Score (median=0.812) when reconstructing ARG plasmids and exceeded the binning capacity of the reference-based method MOB-suite. In the absence of long-read data, our method offers an excellent alternative to reconstruct ARG plasmids in E. coli.

Targets and Effects of Common Biocompounds of Hibiscus sabdariffa (Delphinidin-3-Sambubiosid, Quercetin, and Hibiscus Acid) in Different Pathways of Human Cells According to a Bioinformatic Assay.

The utilization of food as a therapeutic measure for various ailments has been a prevalent practice throughout history and across different cultures. This is exemplified in societies where substances like Hibiscus sabdariffa have been employed to manage health conditions like hypertension and elevated blood glucose levels. The inherent bioactive compounds found in this plant, namely, delphinidin-3-sambubioside (DS3), quercetin (QRC), and hibiscus acid (HA), have been linked to various health benefits. Despite receiving individual attention, the specific molecular targets for these compounds remain unclear. In this study, computational analysis was conducted using bioinformatics tools such as Swiss Target Prediction, ShinnyGo 0.77, KEGG, and Stringdb to identify the molecular targets, pathways, and hub genes. Supplementary results were obtained through a thorough literature search in PubMed. DS3 analysis revealed potential genetic alterations related to the metabolism of nitrogen and glucose, inflammation, angiogenesis, and cell proliferation, particularly impacting the PI3K-AKT signaling pathway. QRC analysis demonstrated interconnected targets spanning multiple pathways, with some overlap with DS3 analysis and a particular focus on pathways related to cancer. HA analysis revealed distinct targets, especially those associated with pathways related to the nervous system. These findings emphasize the necessity for focused research on the molecular effects of DS3, QRC, and HA, thereby providing valuable insights into potential therapeutic pathways.

Immunoinformatic Identification of Multiple Epitopes of gp120 Protein of HIV-1 to Enhance the Immune Response against HIV-1 Infection.

Acquired Immunodeficiency Syndrome is caused by the Human Immunodeficiency Virus (HIV), and a significant number of fatalities occur annually. There is a dire need to develop an effective vaccine against HIV-1. Understanding the structural proteins of viruses helps in designing a vaccine based on immunogenic peptides. In the current experiment, we identified gp120 epitopes using bioinformatic epitope prediction tools, molecular docking, and MD simulations. The Gb-1 peptide was considered an adjuvant. Consecutive sequences of GTG, GSG, GGTGG, and GGGGS linkers were used to bind the B cell, Cytotoxic T Lymphocytes (CTL), and Helper T Lymphocytes (HTL) epitopes. The final vaccine construct consisted of 315 amino acids and is expected to be a recombinant protein of approximately 35.49 kDa. Based on docking experiments, molecular dynamics simulations, and tertiary structure validation, the analysis of the modeled protein indicates that it possesses a stable structure and can interact with Toll-like receptors. The analysis demonstrates that the proposed vaccine can provoke an immunological response by activating T and B cells, as well as stimulating the release of IgA and IgG antibodies. This vaccine shows potential for HIV-1 prophylaxis. The in-silico design suggests that multiple-epitope constructs can be used as potentially effective immunogens for HIV-1 vaccine development.

Virtual screening and site-directed mutagenesis-derived aptamers for precise Salmonella typhimurium prediction: emphasizing OmpD targeting and G-quadruplex stability

The efficient detection of the foodborne pathogen Salmonella typhimurium has historically been hampered by the constraints of traditional methods, characterized by protracted culture periods and intricate DNA extraction processes for PCR. To address this, our research innovatively focuses on the crucial and relatively uncharted virulence factor, the Outer Membrane Protein D (OmpD) in Salmonella typhimurium. By harmoniously integrating the power of virtual screening and site-directed mutagenesis, we unveiled aptamers exhibiting marked specificity for OmpD. Among these, aptamer 7ZQS stands out with its heightened binding affinity. Capitalizing on this foundation, we further engineered a repertoire of mutant aptamers, wherein APT6 distinguished itself, reflecting unmatched stability and specificity. Our rigorous validation, underpinned by cutting-edge bioinformatics tools, amplifies the prowess of APT6 in discerning and binding OmpD across an array of Salmonella typhimurium strains. This study illuminates a transformative approach to the prompt and accurate detection of Salmonella typhimurium, potentially redefining boundaries in applied analytical chemistry and bolstering diagnostic precision across diverse research and clinical domains. Communicated by Ramaswamy H. Sarma

Whole genome analysis of Bacillus velezensis 160, biological control agent of corn head smut.

In this study, we performed sequencing and analysis of the complete genome of the strain initially identified as Bacillus subtilis 160 as part of its characterization. This bacterium has shown its ability to control corn head smut in the field, a disease caused by the basidiomycete fungus Sporisorium reilianum. Analyzing the complete genome sequence not only provides a more precise taxonomic identification but also sheds light on the genetic potential of this bacterium, especially regarding mechanisms that allow it to exert biological control. Employing molecular and bioinformatics tools in studying the genomes of agriculturally significant microorganisms offers insights into the development of biofungicides and bioinoculants. These innovations aim to enhance plant growth and pave the way for strategies that boost crop productivity.

Pharmacomicrobiomics: Immunosuppressive Drugs and Microbiome Interactions in Transplantation.

The human microbiome is associated with human health and disease. Exogenous compounds, including pharmaceutical products, are also known to be affected by the microbiome, and this discovery has led to the field of pharmacomicobiomics. The microbiome can also alter drug pharmacokinetics and pharmacodynamics, possibly resulting in side effects, toxicities, and unanticipated disease response. Microbiome-mediated effects are referred to as drug-microbiome interactions (DMI). Rapid advances in the field of pharmacomicrobiomics have been driven by the availability of efficient bacterial genome sequencing methods and new computational and bioinformatics tools. The success of fecal microbiota transplantation for recurrent Clostridioides difficile has fueled enthusiasm and research in the field. This review focuses on the pharmacomicrobiome in transplantation. Alterations in the microbiome in transplant recipients are well documented, largely because of prophylactic antibiotic use, and the potential for DMI is high. There is evidence that the gut microbiome may alter the pharmacokinetic disposition of tacrolimus and result in microbiome-specific tacrolimus metabolites. The gut microbiome also impacts the enterohepatic recirculation of mycophenolate, resulting in substantial changes in pharmacokinetic disposition and systemic exposure. The mechanisms of these DMI and the specific bacteria or communities of bacteria are under investigation. There are little or no human DMI data for cyclosporine A, corticosteroids, and sirolimus. The available evidence in transplantation is limited and driven by small studies of heterogeneous designs. Larger clinical studies are needed, but the potential for future clinical application of the pharmacomicrobiome in avoiding poor outcomes is high.

Unearthing a Cryptic Biosynthetic Gene Cluster for the Piperazic Acid-Bearing Depsipeptide Diperamycin in the Ant-Dweller Streptomyces sp. CS113.

Piperazic acid is a cyclic nonproteinogenic amino acid that contains a hydrazine N-N bond formed by a piperazate synthase (KtzT-like). This amino acid, found in bioactive natural products synthesized by non-ribosomal peptide synthetases (NRPSs), confers conformational constraint to peptides, an important feature for their biological activities. Genome mining of Streptomyces strains has been revealed as a strategy to identify biosynthetic gene clusters (BGCs) for potentially active compounds. Moreover, the isolation of new strains from underexplored habitats or associated with other organisms has allowed to uncover new BGCs for unknown compounds. The in-house "Carlos Sialer (CS)" strain collection consists of seventy-one Streptomyces strains isolated from the cuticle of leaf-cutting ants of the tribe Attini. Genomes from twelve of these strains have been sequenced and mined using bioinformatics tools, highlighting their potential to encode secondary metabolites. In this work, we have screened in silico those genomes, using KtzT as a hook to identify BGCs encoding piperazic acid-containing compounds. This resulted in uncovering the new BGC dpn in Streptomyces sp. CS113, which encodes the biosynthesis of the hybrid polyketide-depsipeptide diperamycin. Analysis of the diperamycin polyketide synthase (PKS) and NRPS reveals their functional similarity to those from the aurantimycin A biosynthetic pathway. Experimental proof linking the dpn BGC to its encoded compound was achieved by determining the growth conditions for the expression of the cluster and by inactivating the NRPS encoding gene dpnS2 and the piperazate synthase gene dpnZ. The identity of diperamycin was confirmed by High-Resolution Mass Spectrometry (HRMS) and Nuclear Magnetic Resonance (NMR) and by analysis of the domain composition of modules from the DpnP PKS and DpnS NRPS. The identification of the dpn BGC expands the number of BGCs that have been confirmed to encode the relatively scarcely represented BGCs for depsipeptides of the azinothricin family of compounds and will facilitate the generation of new-to-nature analogues by combinatorial biosynthesis.