Vitamin D status affects proteomic profile of HDL-associated proteins and inflammatory mediators in dyslipidemia.

Vitamin D deficiency and dyslipidemia have substantial implications for human health globally. Vitamin D is essential for bone metabolism and immune modulation, and its insufficiency is linked to various chronic inflammatory conditions. Dyslipidemia, characterized by low levels of high-density lipoprotein (HDL) and elevated levels of low-density lipoprotein (LDL) and triglycerides, is also prevalent. Previous research has shown a connection between vitamin D deficiency and low HDL, but the precise mechanism by which vitamin D influences HDL production and its anti-inflammatory properties remains unclear. This study aimed to investigate the proteomic profiles of individuals with and without vitamin D deficiency and dyslipidemia, specifically focusing on the effects of vitamin D on HDL production, its anti-inflammatory potential, and the molecular pathways associated with vitamin D deficiency and dyslipidemia, particularly inflammation and cancer pathways. By analyzing the proteomic profiles of 274 participants from the Qatar Biobank database, we identified 1301 proteins. Our findings indicated a decrease in HDL-associated apolipoproteins (ApoM and ApoD) in individuals with both dyslipidemia and vitamin D deficiency. Conversely, participants with these conditions exhibited increased expression of acute-phase proteins (SAA1 and SOD1), which are associated with inflammation. Pathway enrichment analysis revealed heightened inflammatory activity in individuals with vitamin D deficiency and dyslipidemia, with notable enrichments in pathways such as MAPK, JAK-STAT, Ras signaling, cytokine-cytokine receptor interaction, AGE-RAGE, ErbB signaling, and cancer pathways. Overall, cases of vitamin D deficiency showed enrichment in inflammation pathways, while individuals with both vitamin D deficiency and dyslipidemia demonstrated enhanced activation of cancer and inflammation pathways.

Genomic Alterations, Gene Expression Profiles and Functional Enrichment of Normal-Karyotype Acute Myeloid Leukaemia Based on Targeted Next-Generation Sequencing.

Characterising genomic variants is paramount in understanding the pathogenesis and heterogeneity of normal-karyotype acute myeloid leukaemia (AML-NK). In this study, clinically significant genomic biomarkers were ascertained using targeted DNA sequencing and RNA sequencing on eight AML-NK patients' samples collected at disease presentation and after complete remission. In silico and Sanger sequencing validations were performed to validate variants of interest, and they were followed by the performance of functional and pathway enrichment analyses for overrepresentation analysis of genes with somatic variants. Somatic variants involving 26 genes were identified and classified as follows: 18/42 (42.9%) as pathogenic, 4/42 (9.5%) as likely pathogenic, 4/42 (9.5%) as variants of unknown significance, 7/42 (16.7%) as likely benign and 9/42 (21.4%) as benign. Nine novel somatic variants were discovered, of which three were likely pathogenic, in the CEBPA gene with significant association with its upregulation. Transcription misregulation in cancer tops the affected pathways involving upstream genes (CEBPA and RUNX1) that were deregulated in most patients during disease presentation and were closely related to the most enriched molecular function gene ontology category, DNA-binding transcription activator activity RNA polymerase II-specific (GO:0001228). In summary, this study elucidated putative variants and their gene expression profiles along with functional and pathway enrichment in AML-NK patients.

Comparing the Biology of Young versus Old Age Estrogen-Receptor-Positive Breast Cancer through Gene and Protein Expression Analyses.

Background: Breast cancer developed at a young age (≤45 years) is hypothesized to have unique biology; however, findings in this field are controversial. Methods: We compared the whole transcriptomic profile of young vs. old-age breast cancer using DNA microarray. RNA was extracted from 13 fresh estrogen receptor (ER)-positive primary breast cancer tissues of untreated patients (7 = young age ≤45 years and 6 = old age ≥55 years). In silico validation for the differentially expressed genes (DEGs) by young-age patients was conducted using The Cancer Genome Atlas (TCGA) database. Next, we analyzed the protein expression encoded by two of the significantly down-regulated genes by young-age patients, Glycine N-acyltransferase-like 1 (GLYATL-1) and Ran-binding protein 3 like (RANBP3L), using immunohistochemical analysis in an independent cohort of 56 and 74 ER-positive pre-therapeutic primary breast cancer tissues, respectively. Results: 12 genes were significantly differentially expressed by young-age breast cancers (fold change >2 or <2- with FDR p-value < 0.05). TCGA data confirmed the differential expression of six genes. Protein expression analysis of GLYATL-1 and RANBP3L did not show heterogeneous expression between young and old-age breast cancer tissues. Loss of expression of GLYATL-1 was significantly (p-value 0.005) associated with positive lymph node status. Higher expression of RANBP3L was significantly associated with breast cancers with lower histopathological grades (p-value 0.038). Conclusions: At the transcriptomic level, breast cancer developed in young and old age patients seems homogenous. The variation in the transcriptomic profiles can be attributed to the other clinicopathological characteristics rather than the age of the patient.

DES-Amyloidoses "Amyloidoses through the looking-glass": A knowledgebase developed for exploring and linking information related to human amyloid-related diseases.

More than 30 types of amyloids are linked to close to 50 diseases in humans, the most prominent being Alzheimer's disease (AD). AD is brain-related local amyloidosis, while another amyloidosis, such as AA amyloidosis, tends to be more systemic. Therefore, we need to know more about the biological entities' influencing these amyloidosis processes. However, there is currently no support system developed specifically to handle this extraordinarily complex and demanding task. To acquire a systematic view of amyloidosis and how this may be relevant to the brain and other organs, we needed a means to explore "amyloid network systems" that may underly processes that leads to an amyloid-related disease. In this regard, we developed the DES-Amyloidoses knowledgebase (KB) to obtain fast and relevant information regarding the biological network related to amyloid proteins/peptides and amyloid-related diseases. This KB contains information obtained through text and data mining of available scientific literature and other public repositories. The information compiled into the DES-Amyloidoses system based on 19 topic-specific dictionaries resulted in 796,409 associations between terms from these dictionaries. Users can explore this information through various options, including enriched concepts, enriched pairs, and semantic similarity. We show the usefulness of the KB using an example focused on inflammasome-amyloid associations. To our knowledge, this is the only KB dedicated to human amyloid-related diseases derived primarily through literature text mining and complemented by data mining that provides a novel way of exploring information relevant to amyloidoses.

Qatar genome: Insights on genomics from the Middle East.

Despite recent biomedical breakthroughs and large genomic studies growing momentum, the Middle Eastern population, home to over 400 million people, is underrepresented in the human genome variation databases. Here we describe insights from Phase 1 of the Qatar Genome Program with whole genome sequenced 6047 individuals from Qatar. We identified more than 88 million variants of which 24 million are novel and 23 million are singletons. Consistent with the high consanguinity and founder effects in the region, we found that several rare deleterious variants were more common in the Qatari population while others seem to provide protection against diseases and have shaped the genetic architecture of adaptive phenotypes. These results highlight the value of our data as a resource to advance genetic studies in the Arab and neighboring Middle Eastern populations and will significantly boost the current efforts to improve our understanding of global patterns of human variations, human history, and genetic contributions to health and diseases in diverse populations.

Genetic predisposition to cancer across people of different ancestries in Qatar: a population-based, cohort study.

BACKGROUND: Disparities in the genetic risk of cancer among various ancestry groups and populations remain poorly defined. This challenge is even more acute for Middle Eastern populations, where the paucity of genomic data could affect the clinical potential of cancer genetic risk profiling. We used data from the phase 1 cohort of the Qatar Genome Programme to investigate genetic variation in cancer-susceptibility genes in the Qatari population. METHODS: The Qatar Genome Programme generated high-coverage genome sequencing on DNA samples collected from 6142 native Qataris, stratified into six distinct ancestry groups: general Arab, Persian, Arabian Peninsula, Admixture Arab, African, and South Asian. In this population-based, cohort study, we evaluated the performance of polygenic risk scores for the most common cancers in Qatar (breast, prostate, and colorectal cancers). Polygenic risk scores were trained in The Cancer Genome Atlas (TCGA) dataset, and their distributions were subsequently applied to the six different genetic ancestry groups of the Qatari population. Rare deleterious variants within 1218 cancer susceptibility genes were analysed, and their clinical pathogenicity was assessed by ClinVar and the CharGer computational tools. FINDINGS: The cohort included in this study was recruited by the Qatar Biobank between Dec 11, 2012, and June 9, 2016. The initial dataset comprised 6218 cohort participants, and whole genome sequencing quality control filtering led to a final dataset of 6142 samples. Polygenic risk score analyses of the most common cancers in Qatar showed significant differences between the six ancestry groups (p<0·0001). Qataris with Arabian Peninsula ancestry showed the lowest polygenic risk score mean for colorectal cancer (-0·41), and those of African ancestry showed the highest average for prostate cancer (0·85). Cancer-gene rare variant analysis identified 76 Qataris (1·2% of 6142 individuals in the Qatar Genome Programme cohort) carrying ClinVar pathogenic or likely pathogenic variants in clinically actionable cancer genes. Variant analysis using CharGer identified 195 individuals carriers (3·17% of the cohort). Breast cancer pathogenic variants were over-represented in Qataris of Persian origin (22 [56·4%] of 39 BRCA1/BRCA2 variant carriers) and completely absent in those of Arabian Peninsula origin. INTERPRETATION: We observed a high degree of heterogeneity for cancer predisposition genes and polygenic risk scores across ancestries in this population from Qatar. Stratification systems could be considered for the implementation of national cancer preventive medicine programmes. FUNDING: Qatar Foundation.

Thousands of Qatari genomes inform human migration history and improve imputation of Arab haplotypes.

Arab populations are largely understudied, notably their genetic structure and history. Here we present an in-depth analysis of 6,218 whole genomes from Qatar, revealing extensive diversity as well as genetic ancestries representing the main founding Arab genealogical lineages of Qahtanite (Peninsular Arabs) and Adnanite (General Arabs and West Eurasian Arabs). We find that Peninsular Arabs are the closest relatives of ancient hunter-gatherers and Neolithic farmers from the Levant, and that founder Arab populations experienced multiple splitting events 12-20 kya, consistent with the aridification of Arabia and farming in the Levant, giving rise to settler and nomadic communities. In terms of recent genetic flow, we show that these ancestries contributed significantly to European, South Asian as well as South American populations, likely as a result of Islamic expansion over the past 1400 years. Notably, we characterize a large cohort of men with the ChrY J1a2b haplogroup (n = 1,491), identifying 29 unique sub-haplogroups. Finally, we leverage genotype novelty to build a reference panel of 12,432 haplotypes, demonstrating improved genotype imputation for both rare and common alleles in Arabs and the wider Middle East.

Author Correction: Bioprospecting desert plant Bacillus endophytic strains for their potential to enhance plant stress tolerance.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Bioprospecting desert plant Bacillus endophytic strains for their potential to enhance plant stress tolerance.

Plant growth-promoting bacteria (PGPB) are known to increase plant tolerance to several abiotic stresses, specifically those from dry and salty environments. In this study, we examined the endophyte bacterial community of five plant species growing in the Thar desert of Pakistan. Among a total of 368 culturable isolates, 58 Bacillus strains were identified from which the 16 most divergent strains were characterized for salt and heat stress resilience as well as antimicrobial and plant growth-promoting (PGP) activities. When the 16 Bacillus strains were tested on the non-host plant Arabidopsis thaliana, B. cereus PK6-15, B. subtilis PK5-26 and B. circulans PK3-109 significantly enhanced plant growth under salt stress conditions, doubling fresh weight levels when compared to uninoculated plants. B. circulans PK3-15 and PK3-109 did not promote plant growth under normal conditions, but increased plant fresh weight by more than 50% when compared to uninoculated plants under salt stress conditions, suggesting that these salt tolerant Bacillus strains exhibit PGP traits only in the presence of salt. Our data indicate that the collection of 58 plant endophytic Bacillus strains represents an important genomic resource to decipher plant growth promotion at the molecular level.

The Genome Sequence of the Wild Tomato Solanum pimpinellifolium Provides Insights Into Salinity Tolerance.

Solanum pimpinellifolium, a wild relative of cultivated tomato, offers a wealth of breeding potential for desirable traits such as tolerance to abiotic and biotic stresses. Here, we report the genome assembly and annotation of S. pimpinellifolium 'LA0480.' Moreover, we present phenotypic data from one field experiment that demonstrate a greater salinity tolerance for fruit- and yield-related traits in S. pimpinellifolium compared with cultivated tomato. The 'LA0480' genome assembly size (811 Mb) and the number of annotated genes (25,970) are within the range observed for other sequenced tomato species. We developed and utilized the Dragon Eukaryotic Analyses Platform (DEAP) to functionally annotate the 'LA0480' protein-coding genes. Additionally, we used DEAP to compare protein function between S. pimpinellifolium and cultivated tomato. Our data suggest enrichment in genes involved in biotic and abiotic stress responses. To understand the genomic basis for these differences in S. pimpinellifolium and S. lycopersicum, we analyzed 15 genes that have previously been shown to mediate salinity tolerance in plants. We show that S. pimpinellifolium has a higher copy number of the inositol-3-phosphate synthase and phosphatase genes, which are both key enzymes in the production of inositol and its derivatives. Moreover, our analysis indicates that changes occurring in the inositol phosphate pathway may contribute to the observed higher salinity tolerance in 'LA0480.' Altogether, our work provides essential resources to understand and unlock the genetic and breeding potential of S. pimpinellifolium, and to discover the genomic basis underlying its environmental robustness.

DES-Mutation: System for Exploring Links of Mutations and Diseases.

During cellular division DNA replicates and this process is the basis for passing genetic information to the next generation. However, the DNA copy process sometimes produces a copy that is not perfect, that is, one with mutations. The collection of all such mutations in the DNA copy of an organism makes it unique and determines the organism's phenotype. However, mutations are often the cause of diseases. Thus, it is useful to have the capability to explore links between mutations and disease. We approached this problem by analyzing a vast amount of published information linking mutations to disease states. Based on such information, we developed the DES-Mutation knowledgebase which allows for exploration of not only mutation-disease links, but also links between mutations and concepts from 27 topic-specific dictionaries such as human genes/proteins, toxins, pathogens, etc. This allows for a more detailed insight into mutation-disease links and context. On a sample of 600 mutation-disease associations predicted and curated, our system achieves precision of 72.83%. To demonstrate the utility of DES-Mutation, we provide case studies related to known or potentially novel information involving disease mutations. To our knowledge, this is the first mutation-disease knowledgebase dedicated to the exploration of this topic through text-mining and data-mining of different mutation types and their associations with terms from multiple thematic dictionaries.

In silico exploration of Red Sea Bacillus genomes for natural product biosynthetic gene clusters.

BACKGROUND: The increasing spectrum of multidrug-resistant bacteria is a major global public health concern, necessitating discovery of novel antimicrobial agents. Here, members of the genus Bacillus are investigated as a potentially attractive source of novel antibiotics due to their broad spectrum of antimicrobial activities. We specifically focus on a computational analysis of the distinctive biosynthetic potential of Bacillus paralicheniformis strains isolated from the Red Sea, an ecosystem exposed to adverse, highly saline and hot conditions. RESULTS: We report the complete circular and annotated genomes of two Red Sea strains, B. paralicheniformis Bac48 isolated from mangrove mud and B. paralicheniformis Bac84 isolated from microbial mat collected from Rabigh Harbor Lagoon in Saudi Arabia. Comparing the genomes of B. paralicheniformis Bac48 and B. paralicheniformis Bac84 with nine publicly available complete genomes of B. licheniformis and three genomes of B. paralicheniformis, revealed that all of the B. paralicheniformis strains in this study are more enriched in nonribosomal peptides (NRPs). We further report the first computationally identified trans-acyltransferase (trans-AT) nonribosomal peptide synthetase/polyketide synthase (PKS/ NRPS) cluster in strains of this species. CONCLUSIONS: B. paralicheniformis species have more genes associated with biosynthesis of antimicrobial bioactive compounds than other previously characterized species of B. licheniformis, which suggests that these species are better potential sources for novel antibiotics. Moreover, the genome of the Red Sea strain B. paralicheniformis Bac48 is more enriched in modular PKS genes compared to B. licheniformis strains and other B. paralicheniformis strains. This may be linked to adaptations that strains surviving in the Red Sea underwent to survive in the relatively hot and saline ecosystems.

Comparative genomic analysis of ten clinical Streptococcus pneumoniae collected from a Malaysian hospital reveal 31 new unique drug-resistant SNPs using whole genome sequencing.

BACKGROUND: Streptococcus pneumoniae or pneumococcus is a leading cause of morbidity and mortality worldwide, specifically in relation to community-acquired pneumonia. Due to the overuse of antibiotics, S. pneumoniae has developed a high degree of resistance to a wide range of antibacterial drugs. METHODS: In this study, whole genome sequencing (WGS) was performed for 10 clinical strains of S. pneumoniae with different levels of sensitivity to standard antibiotics. The main objective was to investigate genetic changes associated with antibiotic resistance in S. pneumoniae. RESULTS: Our results showed that resistant isolates contain a higher number of non-synonymous single nucleotide polymorphisms (SNPs) as compared to susceptible isolates. We were able to identify SNPs that alter a single amino acid in many genes involved in virulence and capsular polysaccharide synthesis. In addition, 90 SNPs were only presented in the resistant isolates, and 31 SNPs were unique and had not been previously reported, suggesting that these unique SNPs could play a key role in altering the level of resistance to different antibiotics. CONCLUSION: Whole genome sequencing is a powerful tool for comparing the full genome of multiple isolates, especially those closely related, and for analysing the variations found within antibiotic resistance genes that lead to differences in antibiotic sensitivity. We were able to identify specific mutations within virulence genes related to resistant isolates. These findings could provide insights into understanding the role of single nucleotide mutants in conferring drug resistance.

Next generation sequencing reveals the antibiotic resistant variants in the genome of Pseudomonas aeruginosa.

Rapid progress in next generation sequencing and allied computational tools have aided in identification of single nucleotide variants in genomes of several organisms. In the present study, we have investigated single nucleotide polymorphism (SNP) in ten multi-antibiotic resistant Pseudomonas aeruginosa clinical isolates. All the draft genomes were submitted to Rapid Annotations using Subsystems Technology (RAST) web server and the predicted protein sequences were used for comparison. Non-synonymous single nucleotide polymorphism (nsSNP) found in the clinical isolates compared to the reference genome (PAO1), and the comparison of nsSNPs between antibiotic resistant and susceptible clinical isolates revealed insights into the genome variation. These nsSNPs identified in the multi-drug resistant clinical isolates were found to be altering a single amino acid in several antibiotic resistant genes. We found mutations in genes encoding efflux pump systems, cell wall, DNA replication and genes involved in repair mechanism. In addition, nucleotide deletions in the genome and mutations leading to generation of stop codons were also observed in the antibiotic resistant clinical isolates. Next generation sequencing is a powerful tool to compare the whole genomes and analyse the single base pair variations found within the antibiotic resistant genes. We identified specific mutations within antibiotic resistant genes compared to the susceptible strain of the same bacterial species and these findings may provide insights to understand the role of single nucleotide variants in antibiotic resistance.

DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species.

Tomato is the most economically important horticultural crop used as a model to study plant biology and particularly fruit development. Knowledge obtained from tomato research initiated improvements in tomato and, being transferrable to other such economically important crops, has led to a surge of tomato-related research and published literature. We developed DES-TOMATO knowledgebase (KB) for exploration of information related to tomato. Information exploration is enabled through terms from 26 dictionaries and combination of these terms. To illustrate the utility of DES-TOMATO, we provide several examples how one can efficiently use this KB to retrieve known or potentially novel information. DES-TOMATO is free for academic and nonprofit users and can be accessed at http://cbrc.kaust.edu.sa/des_tomato/, using any of the mainstream web browsers, including Firefox, Safari and Chrome.

Identification of Putative Transmembrane Proteins Involved in Salinity Tolerance in Chenopodium quinoa by Integrating Physiological Data, RNAseq, and SNP Analyses.

Chenopodium quinoa (quinoa) is an emerging crop that produces nutritious grains with the potential to contribute to global food security. Quinoa can also grow on marginal lands, such as soils affected by high salinity. To identify candidate salt tolerance genes in the recently sequenced quinoa genome, we used a multifaceted approach integrating RNAseq analyses with comparative genomics and topology prediction. We identified 219 candidate genes by selecting those that were differentially expressed in response to salinity, were specific to or overrepresented in quinoa relative to other Amaranthaceae species, and had more than one predicted transmembrane domain. To determine whether these genes might underlie variation in salinity tolerance in quinoa and its close relatives, we compared the response to salinity stress in a panel of 21 Chenopodium accessions (14 C. quinoa, 5 C. berlandieri, and 2 C. hircinum). We found large variation in salinity tolerance, with one C. hircinum displaying the highest salinity tolerance. Using genome re-sequencing data from these accessions, we investigated single nucleotide polymorphisms and copy number variation (CNV) in the 219 candidate genes in accessions of contrasting salinity tolerance, and identified 15 genes that could contribute to the differences in salinity tolerance of these Chenopodium accessions.

Semantic prioritization of novel causative genomic variants.

Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.

Genome wide profiling in oral squamous cell carcinoma identifies a four genetic marker signature of prognostic significance.

BACKGROUND: Cancers of the oral cavity are primarily oral squamous cell carcinomas (OSCCs). Many of the OSCCs present at late stages with an exceptionally poor prognosis. A probable limitation in management of patients with OSCC lies in the insufficient knowledge pertaining to the linkage between copy number alterations in OSCC and oral tumourigenesis thereby resulting in an inability to deliver targeted therapy. OBJECTIVES: The current study aimed to identify copy number alterations (CNAs) in OSCC using array comparative genomic hybridization (array CGH) and to correlate the CNAs with clinico-pathologic parameters and clinical outcomes. MATERIALS AND METHODS: Using array CGH, genome-wide profiling was performed on 75 OSCCs. Selected genes that were harboured in the frequently amplified and deleted regions were validated using quantitative polymerase chain reaction (qPCR). Thereafter, pathway and network functional analysis were carried out using Ingenuity Pathway Analysis (IPA) software. RESULTS: Multiple chromosomal regions including 3q, 5p, 7p, 8q, 9p, 10p, 11q were frequently amplified, while 3p and 8p chromosomal regions were frequently deleted. These findings were in confirmation with our previous study using ultra-dense array CGH. In addition, amplification of 8q, 11q, 7p and 9p and deletion of 8p chromosomal regions showed a significant correlation with clinico-pathologic parameters such as the size of the tumour, metastatic lymph nodes and pathological staging. Co-amplification of 7p, 8q, 9p and 11q regions that harbored amplified genes namely CCND1, EGFR, TPM2 and LRP12 respectively, when combined, continues to be an independent prognostic factor in OSCC. CONCLUSION: Amplification of 3q, 5p, 7p, 8q, 9p, 10p, 11q and deletion of 3p and 8p chromosomal regions were recurrent among OSCC patients. Co-alteration of 7p, 8q, 9p and 11q was found to be associated with clinico-pathologic parameters and poor survival. These regions contain genes that play critical roles in tumourigenesis pathways.

bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli.

Motivation: The computational search for promoters in prokaryotes remains an attractive problem in bioinformatics. Despite the attention it has received for many years, the problem has not been addressed satisfactorily. In any bacterial genome, the transcription start site is chosen mostly by the sigma (σ) factor proteins, which control the gene activation. The majority of published bacterial promoter prediction tools target σ 70 promoters in Escherichia coli . Moreover, no σ-specific classification of promoters is available for prokaryotes other than for E. coli . Results: Here, we introduce bTSSfinder, a novel tool that predicts putative promoters for five classes of σ factors in Cyanobacteria (σ A , σ C , σ H , σ G and σ F ) and for five classes of sigma factors in E. coli (σ 70 , σ 38 , σ 32 , σ 28 and σ 24 ). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC = 0.86, F 1 -score = 0.93) compared to the next best tool with MCC = 0.59, F 1 -score = 0.79) and covers multiple classes of promoters. Availability and Implementation: bTSSfinder is available standalone and online at http://www.cbrc.kaust.edu.sa/btssfinder . Contacts: ilham.shahmuradov@kaust.edu.sa or vladimir.bajic@kaust.edu.sa. Supplementary information: Supplementary data are available at Bioinformatics online.

Metagenomics as a preliminary screen for antimicrobial bioprospecting.

Since the composition of soil directs the diversity of the contained microbiome and its potential to produce bioactive compounds, many studies has been focused on sediment types with unique features characteristic of extreme environments. However, not much is known about the potential of microbiomes that inhabit the highly saline and hot Red Sea lagoons. This case study explores mangrove mud and the microbial mat of sediments collected from the Rabigh harbor lagoon and Al Kharrar lagoon for antimicrobial bioprospecting. Rabigh harbor lagoon appears the better location, and the best sediment type for this purpose is mangrove mud. On the other hand, Al Kharrar lagoon displayed increased anaerobic hydrocarbon degradation and an abundance of bacterial DNA associated with antibiotic resistance. Moreover, our findings show an identical shift in phyla associated with historic hydrocarbon contamination exposure reported in previous studies (that is, enrichment of Gamma- and Delta-proteobacteria), but we also report that bacterial DNA sequences associated with antibiotic synthesis enzymes are derived from Gamma-, Delta- and Alpha-proteobacteria. This suggests that selection pressure associated with hydrocarbon contamination tend to enrich the bacterial classes DNA associated with antibiotic synthesis enzymes. Although Actinobacteria tends to be the common target for research when it comes to antimicrobial bioprospecting, our study suggests that Firmicutes (Bacilli and Clostridia), Bacteroidetes, Cyanobacteria, and Proteobacteria should be antimicrobial bioprospecting targets as well. To the best of our knowledge, this is the first metagenomic study that analyzed the microbiomes in Red Sea lagoons for antimicrobial bioprospecting.